wildlife management practices

Transcription

APPENDIX C
Tejon Ranch Wildlife Assessment and
Recommendations
Prepared for
Tejon Ranch Conservancy
Prepared by
Kyran Kunkel
Mountain Thinking Conservation Science Collaborative,
Gallatin Gateway, MT
JANUARY 7, 2013
COVER PHOTOS (from left to right)
© Tejon Ranch Company 2007
© T. Maloney 2011
Steve Thompson, USFWS 2013
TABLE OF CONTENTS
Chapter/Section
Page
Introduction and Background ............................................................................................................................................. 1
Feral Pig Management ............................................................................................................................................................2
Proposed Management Strategy .......................................................................................................................................... 3
Feral Pigs and California Condor Foraging ...................................................................................................................... 4
Enhanced Wildlife Monitoring, Analysis, and Communication ................................................................................. 4
Wildlife Management/Species Conservation Plans........................................................................................................ 4
Depredation Management and Predator Harvest ............................................................................................................6
Connectivity ............................................................................................................................................................................. 7
1.
American Badger (Taxidea taxus) ........................................................................................................................... 10
2.
Black Bear (Ursus americanus) ................................................................................................................................. 17
3.
Bobcat (Felis rufus) .................................................................................................................................................... 29
4.
California Condor (Gymnogyps californianus) .................................................................................................... 38
5.
Cougar (Puma concolor) ........................................................................................................................................... 46
6.
Coyote (Canis latrans) ............................................................................................................................................... 60
7.
Elk (Cervus elaphus) .................................................................................................................................................. 69
8.
Feral Pig (Sus scrofa).................................................................................................................................................. 82
9.
Gray Fox (Urocyon cinereoargenteus) ................................................................................................................. 103
10. Mule Deer (Odocoileus hemionus) ........................................................................................................................ 108
11.
Pronghorn (Antilocapra americana)...................................................................................................................... 127
12. Red Fox (Vulpes vulpes) .......................................................................................................................................... 138
13. Ringtail (Bassariscus astutus) ................................................................................................................................. 141
14. San Joaquin kit fox (Vulpes macrotis mutica) .................................................................................................... 147
15. Upland Birds ............................................................................................................................................................... 157
Ranch-wide Management Plan, Volume 2
Conservation Activities and Best Management Practices
Wildlife Assessments | i
Mountain Thinking Conservation Science Collaborative
January 2013
FIGURES
Figure 4-1 Foraging Zone of California Condor on Tejon Ranch ............................................................................... 40
Figure 6-1 Carnivores Killed Annually by Federal Predator Control Agents (1939–1997) .................................... 63
Figure 7-1 Association between Calf Recruitment (elk calves:100 cows [ECALF]) and Year
on Tejon Ranch, 1995–2011 ...............................................................................................................................74
Figure 10-1 Trend in Fawn: Doe Ratios on Tejon Ranch, 1980-2010. ......................................................................... 109
Figure 10-2 Relationship between Mule Deer Doe: Fawn Ratio and Precipitation on Tejon
Ranch. .................................................................................................................................................................. 109
Figure 10-3 Adaptive Harvest Management Plan Developed by Montana Department of Fish,
Wildlife, and Parks ........................................................................................................................................... 120
Figure 11-1 Total Pronghorn Counted on Tejon Ranch, 1995–2011. ........................................................................... 130
Figure 11-2 Correlation between Previous-Year Precipitation and Pronghorn Fawn Ratio on
Tejon Ranch, 1995–2011. ................................................................................................................................... 131
Figure 14-1 San Joaquin Kit Fox Populations in the Central Valley of California ................................................... 148
TABLES
Table 2-1
Decision Matrix for Monitoring the Black Bear Population ..................................................................... 21
Table 3-1
Average Seasonal Food Overlap among Carnivores ....................................................................................30
Table 7-1
Tejon Ranch Elk Composition Counts ......................................................................................................... 69
Table 10-1 Tejon Ranch Deer Harvest, 1997–2011 ...........................................................................................................110
Table 10-2 Tejon Ranch Deer Herd Composition, 1999–2012...................................................................................... 111
Table 11-1
Habitat Suitability Criteria for Pronghorn in Grassland and Grassland-Scrub
Communities...................................................................................................................................................... 128
Table 11-2 Pronghorn Composition Counts on Tejon Ranch, 2011 ............................................................................ 131
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Introduction and Background
Wildlife in the Tehachapi region has been managed and harvested since humans have been using the landscape.
Tejon Ranch was created from four Mexican land grants purchased by General Edward Fitzgerald Beale in the
1860s, and before 1950 hunting on the Ranch was a privately controlled, unstructured activity. The commercial
hunting operation on Tejon Ranch was first developed in the 1950s. The Tejon Ranch Company’s (TRC’s)
current wildlife management operation developed in the 1980s, with the enrollment of Tejon Ranch in the Private
Lands Wildlife Enhancement and Management Area (PLM) Program established by the California Department of
Fish and Game (renamed in 2012 as the California Department of Fish and Wildlife [CDFW] (Tejon Ranch
Company and Tejon Ranch Conservancy 2009). Tejon is the largest property enrolled in the PLM.
The intent of CDFW’s PLM Program is to protect and improve wildlife habitat by encouraging landholders to
manage their property for the benefit of fish and wildlife (California Department of Fish and Game 2008). The
program offers landholders incentives, including flexible hunting seasons, to utilize wildlife for recreational
purposes on their property. Landholders may collect fees for access to hunting opportunities and other forms of
recreation, such as fishing, wildlife viewing, and photography. In return for the opportunity to generate revenue
from recreational hunting, the landholder must prepare a wildlife management plan and complete specific
wildlife habitat improvements on the PLM property. The PLM Program is revised and subject to California Fish
and Game Commission approval every 5 years. TRC provides an education program for all hunters to ensure that
they are following the rules of Tejon Ranch as well as state and federal laws concerning wildlife harvest. In
particular, TRC has instituted strict controls on the use of lead ammunition on the Ranch. TRC has also
implemented numerous wildlife enhancement projects on the Ranch as part of the PLM Program, such as
enhancing cover and improving water distribution.
Regulations and policies regarding the management and use of the fish and wildlife of the State of California are
established by the California Fish and Game Commission, and CDFW is charged with implementing these
policies and regulations. Management regulations and intensity vary among classes of wildlife. Because of their
imperiled status, threatened and endangered species have more intensive management and associated regulations
than large game and waterfowl, which in turn are managed more closely than upland species and small game
because the latter are considered more resilient with regard to harvest. Management of nongame species varies
depending on their conservation status. These species range from nuisance species, for which harvest may be
allowed depending on the species, to sensitive species for which no harvest is allowed and for which management
effort is often expended to promote population status.
TRC’s wildlife management requirements are sometimes more restrictive than state regulations. For example,
TRC is not allowing harvest of American badgers on the Ranch beginning in 2013 and encourages selective
harvesting of legally harvestable mule deer to improve the condition of the herd as part of the Tejon Ranch
Quality Deer Management (QDM) program. In 2013, TRC is selling hunting access for deer, elk, turkey, upland
game birds, and wild pig. Once access to Tejon Ranch has been purchased by a hunter, other species legally
harvestable in California can be taken with appropriate tags or permits, unless specifically prohibited by TRC.
TRC makes no additional revenue from these species; fees for tags or permits are paid directly to CDFW.
In 2008, TRC and five environmental organizations (Audubon California, Endangered Habitats League, Natural
Resources Defense Council, Planning and Conservation League, and Sierra Club) executed the Tejon Ranch
Conservation and Land Use Agreement (Ranch-wide Agreement). This agreement places 90% of the 270,000acre ranch into conservation and created the Tejon Ranch Conservancy (Conservancy) to serve as steward of the
areas designated as Conserved Lands. As part of the Ranch-wide Agreement, the Conservancy was charged with
developing a Ranch-wide Management Plan (RWMP) by June 2013, which affords the Conservancy the
opportunity to enhance conservation values in the Conserved Lands while respecting TRC’s economic uses.
Because TRC retains the right to conduct ranching and livestock management within the Conserved Lands at
Tejon Ranch, this wildlife assessment has been developed to support the Conservancy’s RWMP by providing
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recommendations for enhancing adaptive management of wildlife populations. The Conservancy’s proposed
Conservation Activities and Best Management Practices for TRC’s Reserved Rights, including wildlife
management, are presented in Volume 2 of the RWMP.
To better understand the status of Tejon Ranch wildlife and TRC’s Wildlife Management Program, Mountain
Thinking Conservation Science Collaborative (hereafter called Mountain Thinking) has conducted ecological
literature reviews and summarized harvests on Tejon Ranch (as applicable) for 15 species or guilds of species:
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American badger (Taxidea taxus)
black bear (Ursus americanus)
bobcat (Felis rufus)
California condor (Gymnogyps californianus)
cougar (Puma concolor)
coyote (Canis latrans)
Rocky Mountain elk (Cervus elaphus nelsoni)
feral pig (Sus scrofa)
gray fox (Urocyon cinereoargenteus)
red fox (Vulpes vulpes)
San Joaquin kit fox(Vulpes macrotis mutica)
mule deer (Odocoileus hemionus)
pronghorn (Antilocapra americana)
ringtail (Bassariscus astutus)
upland game birds (e.g., California quail, mountain quail, and turkey)
Mountain Thinking considers these species to be the highest priority species on Tejon Ranch because of their
potential roles in driving ecosystem functions, serving as indicators of ecosystem condition, their sensitivity or
regulatory protections; or having relatively high harvest levels. The information developed in these assessments is
provided in the 15 species-specific chapters of this report. The following sections summarize wildlife
management issues and best practices that have emerged from these assessments.
FERAL PIG MANAGEMENT
Perhaps the greatest conservation challenge for Tejon Ranch is feral pig management. Feral pigs became
established on the Ranch in the 1990s and are now its most harvested species. Feral pigs cause significant
ecological damage wherever they occur (The Wildlife Society 2011), including potentially preying on species of
conservation concern and competing with game species, and they are increasingly considered a risk to the human
food supply by transmitting diseases to crops or livestock. However, despite the threats posed by feral pig
populations, feral pigs are managed as a big game species by CDFW, and no management plan has been identified
for pigs in California. California’s treatment of feral pigs as a game species may limit options for their control and
eradication. Furthermore, feral pig hunting is an important source of revenue for both TRC and the State of
California, which may provide an economic incentive to maintain populations for hunting. It is assumed that pig
carcasses and gut piles generated by hunters on Tejon Ranch provide a year-round source of food for California
condors, and it is currently unclear how feral pig management would affect condor recovery efforts.
Mountain Thinking agrees with the policies of The Wildlife Society (2011) regarding feral swine:
1.
Promote the maintenance of biological diversity and ecosystem integrity and oppose the modification
and degradation of natural systems by feral swine.
2. Encourage state and provincial agencies to eradicate feral swine wherever feasible.
3. Support feral swine damage management actions that are cost effective and demonstrate results.
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4. Encourage research by public and private agencies and organizations on methods to control, reduce, or
eliminate feral swine and their impacts.
Feral pigs have been successfully eradicated from a number of island systems (e.g., Santa Catalina, California;
Santa Cruz Island, California; Galapagos Islands, Ecuador; and Sarigan Island, Commonwealth of Northern
Mariana Islands). Pigs were also successfully eradicated from Pinnacles National Monument (now National
Park), occupying 26,606 acres in mainland California, but no other successful pig eradication efforts have been
identified in other parts of the state, certainly not over large landscapes such as at Tejon Ranch. Because pigs are
present on lands adjacent to Tejon Ranch and installing pig-proof fencing around the entire perimeter of the
Ranch is not considered practical, reducing the pig population on the Ranch is believed to be a more feasible
management strategy. However, the level of population reduction necessary to reduce ecological damage to a
tolerable level and how such a level of population reduction can be achieved are unknown.
P ROPOSED MANAGEMENT STRATEGY
Mountain Thinking recommends following the general concepts of Campbell and Long (2009) for feral pig
management. Approaching feral pig damage management in a step-wise fashion will increase the likelihood of
success (VerCauteren et al. 2005):
1.
Clearly identify the problem, including the types and timing of damage being caused and other biological,
ecological, or sociological issues relating to the conflict.
2. Obtain an understanding of the ecology, life history, and population dynamics of feral swine as they
relate to the damages.
3. Select and implement the most effective, cost-efficient, humane, and socially acceptable management
techniques, using information gained through steps 1 and 2, to reduce the damages.
4. Perform an assessment of the reduction in damage over time in relation to the reduction in pig
abundance, considering factors such as costs and impacts of management actions on feral swine and nontarget wildlife populations, to evaluate the effectiveness of the program.
Based on this information, Mountain Thinking Conservation Science Collaborative recommends that a feral pig
management strategy be developed for Tejon Ranch, consisting of the following tasks:
▪
Develop an understanding of the abundance of pigs in various habitats on the Ranch, the nature and
magnitude of ecological damage, and the relationship between abundance and damage. A sampling
methodology should be developed to test the power and efficiency of techniques for long-term
monitoring, including assessing environmental damage from pigs. Ultimately, a determination must be
made regarding what abundance/density of pigs should be targeted to reduce damage to an acceptable
level.
▪
Develop an age/stage-specific population model incorporating birth and survival rates, including
mortality from hunting. This will allow age/stage-specific harvest scenarios to be evaluated for their
ability to achieve population targets.
▪
Develop control strategies for specific habitats and geographic locations on the Ranch, including
exclusion and harvest. Policies and approaches to maximize harvest of feral pigs by TRC hunting clients
should be emphasized, but means of increasing harvest above the level feasible by hunters should be
identified if needed. Some resource types may lend themselves to excluding pigs with fencing.
▪
Implement control strategies and monitor population responses of feral pigs and associated damage.
An index of relative population abundance of pigs can be developed using the track survey technique of Engeman
and colleagues (2007). Population size/density estimates can be obtained through capture–recapture techniques
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using remotely triggered cameras or observations from line transects. These methods would be used to assess the
baseline population of pigs on the Ranch and to evaluate changes following exclusion or harvest. Also
recommended is the testing of hunting removal population estimators. The technique could apply an open
population model whereby monitoring continues long term and employs a hunting removal estimator using
program MARK (Williams et al. 2001). Monitoring of catch per unit effort trends, by recording days of hunter
effort and success, should also be implemented. Testing these methods will allow the Conservancy to determine
the most cost-efficient approach to address the management objectives for Tejon Ranch. Using more than one
monitoring method may improve the quality of the estimate.
F ERAL PIGS AND C ALIFORNIA CONDOR FORAGING
California condors are a flagship endangered species of national recognition, and TRC has a long history of
collaborating on recovery efforts. The Tehachapi Uplands Multiple Species Habitat Conservation Plan (Dudek
2012) indicates that gut piles and carcasses from hunting may be especially important year-round sources of food
for condors in the Tehachapi region. However, while condors do forage on pig carcasses, researchers have a poor
understanding of the overall importance of feral pigs to condors, and thus the implications of a feral pig
management program at Tejon Ranch to condors. Mountain Thinking recommends investigating wildlife and
condor use of carcasses at Tejon Ranch to determine the relative importance of feral pigs as a food source for
condors, and considering these findings when formulating management strategies for feral pigs.
ENHANCED WILDLIFE MONITORING, ANALYSIS, AND COMMUNICATION
Few rigorous monitoring schemes have been developed and consistently applied to any species on Tejon Ranch,
so the overall status and trend of most species is not clear. Better monitoring would allow for more holistic,
integrated, and enhanced management, including estimation of sustainable harvests for multiple species. Wildlife
monitoring at Tejon Ranch consists of either total counts or composition counts (i.e., composition of the herd
with respect to bucks, does, and fawns) of mule deer, Rocky Mountain elk, and pronghorn; total harvests of
species included in the PLM Program; and harvests of other wildlife species as reported by hunters. However,
these monitoring efforts have been inconsistent over the years, records have many data gaps, and little analysis of
non-PLM species has been conducted to inform management.
Mountain Thinking recommends enhancing wildlife monitoring at Tejon Ranch, improving record keeping and
analysis of monitoring data, and utilizing these data to inform wildlife management decision making. The Tejon
Ranch Operations Committee is the forum to evaluate and discuss information generated from adaptive
management and monitoring, to collaboratively develop management objectives, and to incorporate adaptive Best
Management Practices into TRC wildlife management operations and practices as appropriate. The Tejon Ranch
Operations Committee and Tejon Ranch adaptive management framework are discussed further in Volume 2 of
the RWMP.
TRC has been updating its wildlife monitoring and record-keeping procedures to improve their utility for
management purposes. TRC should require (and emphasize to hunters) accurate reporting of effort expended
and of all animals harvested within designated hunting areas on Tejon Ranch, and should regularly compile these
data and share them with the Conservancy. The Conservancy will be exploring potential monitoring approaches
for various wildlife species in 2013 and will work with TRC to incorporate these techniques into existing wildlife
monitoring efforts as appropriate. Monitoring results will be used to develop explicit goals, objectives, and
strategies as part of wildlife management planning (discussed further below).
WILDLIFE M ANAGEMENT /SPECIES CONSERVATION PLANS
Modern harvest management requires justification for take and a minimum level of valid monitoring to support
management decisions. For most wildlife species on Tejon Ranch, a lack of population information limits the
ability to effectively develop species management strategies or optimal harvest targets. Currently, TRC’s wildlife
management planning is conducted only for PLM species (i.e., mule deer, Rocky Mountain elk, black bear,
pronghorn, and wild turkey), and management objectives in the PLM Program have not always been explicit.
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Harvest management appears to be focused primarily on mule deer. Mountain Thinking recommends utilizing
enhanced monitoring data (as described above) to develop wildlife management plans that will support all
harvest levels and conservation efforts for key species at Tejon Ranch. Key species include the species most
commonly harvested by hunters (e.g., mule deer); those that play important ecological roles (e.g., predators, feral
pig); and those that are of particular conservation concern (e.g., pronghorn, San Joaquin kit fox, ringtail).
Comprehensive, data-driven wildlife management planning will provide significant benefits for wildlife
conservation and management at Tejon Ranch, including the following:
▪
synthesizing existing knowledge of species status and trends and potential threats or limiting factors to
inform short- and long-term management;
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providing long-term consistency and rigor to management decision-making processes;
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predictability for all parties;
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demonstrating rationales for decisions to collaborating agencies and organizations;
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creating a process to assess successes and costs and benefits of alternative management approaches, and
a process to adapt management in response to these results; and
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identifying optimal harvests.
Wildlife management planning should be data-driven and implemented adaptively. Williams (2011) describes the
value of adaptive management:
For many important problems, adaptive management holds great promise in reducing the
uncertainties that limit effective management of natural resources. Indeed, utilizing management
itself in an experimental context may in many instances be the only feasible way to gain the
understanding needed to improve management. In concept, adaptive management is neither
conceptually complex nor operationally intricate. However, it does require users to acknowledge
and account for uncertainty, and sustain an operating environment that allows for its reduction
through careful planning, evaluation, and learning. The up-front costs associated with these
activities are compensated by more informative and collaborative resource management over the
long term.
This is consistent with the adaptive management approach to the Conservancy’s stewardship efforts at Tejon
Ranch, which are discussed further in Volume 2 of the RWMP.
Establishing management objectives is an indispensable component of the adaptive management process.
Objectives play a crucial role in evaluating performance, identifying critical uncertainties, and adapting
management through time. It is especially important to have clear, measurable, and agreed-upon objectives at the
outset, to guide decision making and assess progress in achieving management success. Of particular importance
is integrating and developing consensus on TRC’s economic and species management objectives with the
Conservancy’s conservation objectives. Population objectives should include an assessment of available habitat
and its quality, what population range can be expected and supported on the Ranch, the ecological role of the
species, and the potential management tradeoffs among species populations via ecological interactions such as
predation and competition. Harvest levels should be established in light of population objectives.
Monitoring in adaptive management provides data for four key purposes:
1.
to determine resource status, in order to identify appropriate management actions;
2. to develop and refine conceptual and quantitative models of resource dynamics and to identify
uncertainties;
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3. to increase understanding of resource dynamics via the comparison of predictions against survey data;
and
4. to evaluate progress toward achieving management objectives.
Monitoring is much more efficient and effective to the extent that it focuses on these purposes. Enhancing
wildlife monitoring at Tejon Ranch will facilitate management planning by providing objective information on
resource status and trends and on the effects of ongoing management.
DEPREDATION MANAGEMENT AND P REDATOR HARVEST
Carnivores are well known to play important ecological roles, and killing carnivores is increasingly controversial
and fraught with ecological and ethical issues that need to be understood when managing these species (Hecht
and Nickerson 1999). The role of apex predators (i.e., those at the top of food webs, such as cougars and wolves)
in regulating ecosystem structure is well documented (e.g., Estes et al. 2001, Ripple and Beschta 2008, Berger et
al. 2008). However, even smaller bodied, mid-level predators (i.e., mesopredators, such as foxes, skunks, and
raccoons) can play significant roles in structuring food webs (Soule et al. 1988, Roemer et al. 2009). Controlling
predator populations has historically been conducted to increase populations of prey species that are desirable as
game or to reduce losses of livestock (Palomares et al. 1995). However, research on the efficacy of predator
control for these purposes is mixed. For example, Harrington and Conover (2007) found no increase in mule deer
or pronghorn fawn survival in response to coyote population control, while Phillips and White (2003)
demonstrated that coyote control could provide a long-term positive effect on pronghorn populations. In
addition, juvenile survival in populations of density-dependent predators, such as coyotes, can increase in
response to predator control efforts that reduce population size (Knowlton 1972), essentially mitigating the
effect of the control effort on population size. While harvest may not affect predator populations per se, it can
affect ecological interactions that may consequently reduce populations of game species not considered by the
predator control program (Mezquida et al. 2006) or otherwise affect conservation values (Henke and Bryant
1999, Roemer et al. 2009)
Predators are removed from Tejon Ranch through the use of depredation permits and legal hunter harvest, but
the numbers of predators removed are unknown and the long-term effects of this mortality on predator and prey
populations are not clear. Management of predators may be an acceptable or even a necessary management
strategy in some instances. Given the important role of predators and their uncertain status and trends on Tejon
Ranch, however, Mountain Thinking recommends that predator management by TRC and its lessees (i.e.,
depredation) and harvest by hunters be conducted only if supported by science-based justifications.
Mountain Thinking recommends that TRC and the Conservancy develop a rigorous and objective predator
management policy that would be implemented in the event of livestock depredation or as part of management
efforts where predators may be limiting populations of focal species. Such a predator management policy would
spell out appropriate monitoring of livestock and predators and identify ways to measure and respond to
depredation, including use of appropriate nonlethal approaches before approval of any lethal approaches. Lethal
control should be implemented only with TRC authorization, as provided by the predator management policy,
and TRC should authorize lethal methods only after the use of nonlethal methods is proven ineffective. Records
of all livestock killed by coyotes and other predators, and the circumstances associated with the kill, should be
maintained by TRC.
Although harvest of some predators is legal in California, Mountain Thinking recommends that TRC discourage
predator hunting on Tejon Ranch as part of promoting conservation values. Harvesting predators should be
authorized by TRC only if wildlife management plans for these species or prey species (e.g., pronghorn) justify
the need or can demonstrate no significant adverse effects to predator and prey populations. This will require
enhanced monitoring of wildlife, including predator species, to support better planning and adaptive
management decision making as described above.
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CONNECTIVITY
Landscape connectivity is one of Tejon Ranch’s principal conservation values (Penrod et al. 2003, White and
Penrod 2012), and the Tehachapi region has been empirically demonstrated to provide genetic connectivity for
wide-ranging species such as black bear (Brown et al. 2009) and mountain lion (Ernest et al. 2003). Connectivity
can be considered both between Tejon and adjacent areas and among habitats within Tejon Ranch itself.
Maintaining and enhancing connectivity is essential to maintaining the Ranch’s wildlife populations, including
its potential role as providing source populations to surrounding areas and allowing species to move and adapt to
changing climates.
Roads and highways, such as Interstate 5 and State Route 58, potentially act as movement barriers to various
wildlife species (Penrod et al. 2003, Dudek 2009). Wildlife passage structures or other means of enhancing
movement of wildlife across roads have been considered for the Tehachapi region (Penrod et al. 2003). However,
improving major highways to facilitate wildlife passage will require significant physical improvements to these
highways, something TRC and the Conservancy are unlikely to initiate in the near term. The Conservancy should
seek to partner with appropriate agencies (e.g., California Department of Transportation and California High
Speed Rail Authority) to install wildlife crossing structures or otherwise enhance wildlife connectivity (e.g.,
removing median barriers on State Route 58) as opportunities arise.
Maintaining and enhancing connectivity within Tejon Ranch is a high priority and can take many forms. For
example, low-elevation San Joaquin grasslands on Tejon Ranch likely provide connectivity functions for species
such as San Joaquin kit fox. Enhancing grassland habitats or providing escape dens may expand available highquality habitats for kit fox, thereby improving the connectivity functions of the grasslands. Pronghorn
movements can be restricted by inappropriate fencing, and replacing the lower strands on barbed-wire fences
with smooth wire can facilitate pronghorn movements. In addition, riparian habitats often serve as travel
corridors for wildlife, and enhancing riparian habitats can facilitate their use for various wildlife species,
particularly between lower and higher elevation areas on Tejon Ranch.
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wolves, coyotes, and pronghorn. Ecology 89(3):818–828.
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California: signatures of population structure, competitive release, and historical translocation. Journal of
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http://joomla.wildlife.org/documents/positionstatements/feral_swine_080211.pdf.
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VerCauteren, K. C., R. Dolbeer, and E. Gese. 2005. Identification and management of wildlife damage. Pages 740–
778 in C. Braun (ed.), Techniques for Wildlife Investigations and Management, sixth edition. The Wildlife Society,
Bethesda, MD.
White, M. D., and K. Penrod. 2012. The Tehachapi Connection: a case study of linkage, design conservation, and
restoration. Ecological Restoration 30:279–282.
Wilcove, D. S., D. Rothstein, J. Dubow, A. Phillips, and E. Losos. 1998. Quantifying threats to imperiled species in
the United States. BioScience 48:607–615.
Williams, B. K. 2011. Adaptive management of natural resources—framework and issues. Journal of Environmental
Management 92:1346–1353.
1.
January 2013
American Badger (Taxidea taxus )
STATUS AND DISTRIBUTION
The American badger (Taxidea taxus) was listed as a Species
of Special Concern in 1986 as part of an effort by California
Department of Fish and Game (CDFG, now the California
Department of Fish and Wildlife) to identify taxa in
California that lacked a listing status of Threatened,
Endangered, or Fully Protected, yet still seemed vulnerable
to extinction (Williams 1986). Badgers were classified as
“third priority”: species that do not appear to face
extinction soon, but populations are declining seriously or
are otherwise highly vulnerable to human developments
(Williams 1986). Badger populations were recognized to
have diminished in large parts of their range prior to the
1930s, although specific population data were admittedly
lacking.
American Badger (© B. Bouton 2013)
As a follow-up to the badger’s inclusion on the List of Concern, CDFG conducted a population distribution study
in 1987. Occurrence data for the 1987 study were gathered through surveys mailed to licensed trappers, animal
control officials, and agency personnel throughout the state. Of the 521 responses received, most contained
reports from the 1970s and 1980s. Historic data were then compiled from trapping reports summarized by
Grinnell et al. (1937). A qualitative comparison between the two survey periods suggested that badgers had
disappeared from parts of their historic range in California, particularly from the Central Valley and northern
coast (Quinn and Diamond 2008).
Formal statewide management for badgers in California falls primarily under furbearer trapping regulations and
the species’ status as a Species of Special Concern. According to the California Fish and Game Code, badgers may
be taken for their fur under a trapping permit between November 16 and the last day of February. There is not a
bag limit on animals captured during this season. Depredating badgers (those causing injury to property) may be
taken at any time in any manner except for steel-jawed leg hold traps, but taking of young in the den is
prohibited. As a California Species of Special Concern, badgers should be considered during the environmental
review and conservation planning process to “…achieve conservation and recovery of these animals before they
meet California Endangered Species Act criteria for listing as threatened or endangered” (Comrack et al. 2008).
H ABITAT SELECTION AND S UITABILITY
Quinn (2008) studied badgers on the U.S. Bureau of Land Management’s (BLM’s) Fort Ord Public Lands in
northern Monterey County, California (elevation 20-250 meters [m]). The Fort Ord Public Lands, part of a
former U.S. Army base that was closed in 1994, encompass approximately 60 square kilometers (km2) of
grassland, coastal sage scrub, maritime chaparral, and coastal oak woodland habitats. She found that badgers
selected home ranges in native grasslands and shrub habitat in sandy/loamy soil with a preference for
intermediate slopes over steep and no slope.
Badgers are generally associated with open grassland habitats with ground-dwelling prey, including ground
squirrels. Montane forest ecosystems are used by badgers in British Columbia, however (Apps et al. 2002). These
areas are often characterized as early successional forest stands “not sufficiently re-stocked” following logging
and/or wildfire disturbance.
Quinn and Diamond (2008) observed that, of the 45 native habitats in California not converted to humandominated uses, 12 have less than 10% area in the highest class of protection. Most of these habitats with a low
January 2013
protection status are the highest quality badger habitat, including annual grasslands, of which 86.5% are under
private ownership and thus minimally protected.
Because of their burrowing behavior, soil texture and composition can also be important factors in habitat
suitability. Badgers have been shown to prefer glaciofluvial and glaciolacustrine soils, as well as fine, sandy loams
at the landscape scale in Canada (Apps et al. 2002). On the central coast of California, preference was observed
for sands, loams, and sand/loam mixes; association with clays and eroded soils (badlands and Xerorthents) was
negative (Quinn and Diamond 2008). Within their home range, badgers may be more flexible in their soil
requirements.
According to the California Wildlife Habitat Relationship database of Habitat Suitability Indices (HSI) (Davis et
al. 1998), marginal to suitable habitat for badgers covers a significant portion of the state. At the local scale,
however, suitable habitat is more fragmented. According to the HSI maps, most of Tejon Ranch is highly suitable
for badger reproduction, cover, and/or feeding, with ratings in suitability classes 4 and 5 (ranges 1–5).
POPULATION DYNAMICS
Density
Quinn and Diamond (2008) estimated a minimum density of 0.25 animals per km2 on the Fort Ord Public Lands
based on radio telemetry and compared this to density of digging activity (new badger holes per km2 = 14.1).
Estimates on the Carrizo Plain (closest location to Tejon Ranch) are 3.1 holes per km2 compared to 14.1 holes per
km2 on Fort Ord (Quinn and Diamond 2008); based on these estimates, the population density is likely
significantly lower on the Carrizo Plain.
Quinn and Diamond (2008) extrapolated statewide badger populations by taking the average index of badger
activity in all the sites surveyed (4.4 holes per km2) because this was similar to the Fort Ord activity level of 3.1
holes per km2, they used the Fort Ord population density (0.25 animals per km2) to extrapolate a statewide
population size of 22,400 animals if all suitable habitat were occupied. However, as badger digging activity has
not been definitively shown to correlate with badger population density (Messick 1987), these numbers are
speculative.
Based on similar extrapolation and using the Carrizo Plain density estimate, Tejon Ranch would support 55
badgers if all suitable badger habitat were occupied. However, estimating overall badger abundance at Tejon
Ranch is difficult, given the lack of data on density by habitat and the range of habitats on the Ranch. Thus, it is
recommended that surveys be completed on Tejon Ranch for this species of concern.
Reproduction
Badger reproduction rates are relatively low. Messick and Hornocker (1981) report that an average of 57% of
females produce a litter in a given year; Minta (1990) reports 25% of females successfully raising litters to aboveground emergence. In British Columbia, out of 10 potential litter attempts in 2 years for four radiomarked female
badgers, only one animal produced litters: one in her third year and another in her fifth (Newhouse and Kinley
2000). In a California study, of three adult females monitored through two breeding seasons, only one produced
one litter of at least one, and probably two, kits.
Diet
Digging after burrowing mammals is the badger’s trademark hunting strategy. Badgers tend to target juveniles in
the burrow system (Murie 1992, Michener and Iwanuik 2001, Armitage 2004). The burrow system entrances are
most likely first located by scent (Lampe 1976). When hunting juveniles, badgers often block prey burrow
entrances, presumably to prevent escape of the prey, before digging in pursuit (Minta et al. 1992, Murie 1992,
Michener 2004).
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Quinn (2008) reported prey preference of California ground squirrel (Spermophilus beechyi), Townsend ground
squirrel (Spermophilus townsendii), meadow vole (Microtus californicus), Botta’s pocket gopher (Thomomys bottae), and
kangaroo rats (Dipodomys spp.). Grinnell et al. (1937) reported similar prey preferences and also noted that
kangaroo rats seemed to be the dominant prey item in the southern San Joaquin Valley.
Mortality
Badgers are very susceptible to road mortality because they have poor vision, are nocturnal, and tend to navigate
by olfactory cues (Minta 1993). Moreover, their low-slung stature renders them unable to cross highway medians.
In a British Columbia study, seven of 10 radiomarked individuals were killed crossing transportation corridors,
six by vehicles and one by a train, during the 4-year study (Hoodicoff 2003). Thirteen untagged badgers were also
killed in vehicle collisions within the study site during the same period. Likewise, Messick et al. (1981) reported
that 59% of 157 badger mortalities in an Idaho population resulted from vehicle collisions.
In a mortality study by Proulx and MacKenzie (2012), the portion of a study area with relatively low levels of
rodenticide poisoning (19.6% of the area) had 2.2 times more American badgers killed per km of road and 6.4
times more red foxes killed per km of road than did the portion of the study area with high levels of poisoning
(89.7% of the area).
Almost nothing is known of disease occurrence among badgers in California. In one report, the prevalence of
antibodies to canine distemper virus was 70% for the 10 animals tested (Quinn and Diamond 2008).
Spatial Dynamics
Research indicates that home range size varies throughout badger distribution areas and is correlated with prey
density, female availability, and habitat attributes (Messick and Hornocker 1981, Minta 1990). Badgers show
restricted movement patterns in winter, likely remaining near reliable patches of prey (Messick 1987). Badger
home ranges, as reported in the literature, vary from 1.6 to 65 km2 for females and from 2.4 to 541 km2 for males
(Quinn and Diamond 2008). Quinn (2008) reported home range sizes of 2 km2 for females and 12 km2 for males
on the Fort Ord Public Lands, but the very sandy and friable soil at Fort Ord may provide an explanation for
these relatively small home ranges.
T RENDS AND POPULATION PRESSURES
Habitat Fragmentation
In a comparison of carnivores in southern California, Crooks (2002) detected badgers only in the largest habitat
blocks assessed (11.9, 44.5, and 44.5 km2). He concluded that, unlike the generalist urban mesopredators, the
badger and other relatively specialized mustelids tend to be primarily carnivorous and somewhat restricted in
their habitat preferences. Such specializations likely contribute to their patchy distribution in coastal southern
California and increase their vulnerability to environmental disturbances.
Jager et al. (2006) simulated badger activities on landscapes in Oklahoma with different degrees of habitat loss
and fragmentation, including by oil spill, using a spatially explicit and individual-based population model. Both
habitat loss and fragmentation increased the incidence of habitat-related mortality and decreased the proportion
of eligible females that mated, which decreased final population sizes and the likelihood of persistence. Parameter
exploration suggested that steep, threshold-like responses to habitat loss occurred when animals’ territories
included high-risk habitat (i.e., fragmented by spills). Badger populations showed a steeper decline with
increasing habitat loss on landscapes fragmented by spills than on less fragmented landscapes. Habitat
fragmentation made it difficult for badgers to form high-quality territories and exposed individuals to higher risk
while seeking to establish a territory. Their simulations also suggest that an inability to find mates (an Allee
effect) becomes increasingly important for landscapes that support a sparse distribution of territories.
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Harvest
Compared to other furbearer species, the badger’s lower reproductive potential may make it particularly
susceptible to population declines under heavy levels of harvest (Minta and Marsh 1988). This has been observed
in northern latitudes, where Canadian provinces experienced population declines due to trapping (Drescher
1974, Long and Killingley 1983). Harvest in California declined from more than 200 animals per year in the late
1980s to fewer than 25 animals annually in the 2000s.
MONITORING TECHNIQUES AND S URVEY METHODS
Quinn (2008) compared survey methods on her study site on Fort Ord and reported that using transect surveys
for burrows was the most useful survey method, spot lighting and cameras did not detect badgers, and scent
stations had little success. Her transect survey design consisted of burrow searches conducted along 15 transects,
each 1 km long, placed throughout the home range areas of eight radiomarked animals. The beginning of a
transect was located randomly at one corner of the grid cell, and the transect was then walked on a random
bearing within the 90-degree angle facing into the grid cell. Number, location, and age of burrows encountered
along each transect were recorded. New badger sign was detected on 12 of the 15 transects, while old badger sign
was detected on all transects. If transects were considered to be independent, the survey resulted in an estimate
of 12–15 badgers being present in the area.
Quinn (2008) suggested that transect searching overestimated badger population density, however, as several
transects were likely visited by the same badger and thus should not be considered independent. Likewise,
badger numbers may be underestimated by transect searches using this design, as several transects crossed more
than one home range (home ranges of the badgers in her study were significantly overlapped). Thus, a detection
at one transect may be attributable to activity from more than one badger. Transect searching can indeed verify
badger presence, however, and was superior to all other methods in this regard.
Transect surveying is potentially less costly and less labor-intensive than other methods because no special
equipment is required and searches can be completed in a relatively short time (walking each 1-km transect takes
less than an hour). Although adequate training is required to identify badger burrows, this training may be far
less intensive than that required for installing camera stations or identifying animal tracks at scent stations. For
establishing presence/absence of badgers in a given area, sampling intensity can likely be scaled back from that
used in the Quinn 2008 study to cover more ground. For example, 1-km transects spaced 2 km apart would still
have resulted in six (by new activity) or eight (by old activity) detections. Moreover, because badger populations
at Fort Ord may be denser and home ranges smaller than those in other areas, transects could probably be spaced
even further apart in areas where sign is rarer.
Another potential method that could be tested on badgers is collecting scat (including the use of scat dogs) and
conducting DNA analysis for population estimation, similar to successful methods used for coyote (Canis latrans)
(Prugh et al. 2005). Hair for DNA analysis might be collected by placing releasable snares at den entrances,
similar to the technique of Dupue and Ben-David (2005) for river otters (Lutra canadensis).
O VERALL CONSERVATION RECOMMENDATIONS
Manage Conflicts with Livestock and Agriculture
Because of the badger’s digging activities, some horsemen and cattle ranchers fear that horses and cows will step
in burrows, resulting in a broken leg or thrown rider (Long and Killingley 1983). However, few cases of horse
injury have been report, and it has been found that cattle are much less prone to such accidents than anecdote
would suggest (Minta and Marsh 1988). Thus, in California and much of the West, badger presence around
livestock is not typically considered a significant problem and rarely requires the corrective action of removing
badgers. However, exceptions can be made where badger burrowing occurs in horse-riding arenas, jumping
courses, or in or alongside frequently used equestrian trails. Riders unfamiliar with the terrain should be warned
of the hazards of badger dens and holes so they can avoid those areas or at least avoid galloping through those
particular pastures (Minta and Marsh 1988).
January 2013
Quinn and Diamond (2008) suggested that relocation of badgers may be a better management option where
agricultural damage is severe. Further assessment of relocation methods would be needed; however, due to
badgers’ opportunistic foraging habits, loose territorial structure, and propensity to travel long distances on their
own, this option may prove a viable one. Relocation should always be avoided, however, during the spring and
early summer, when mothers and dependent kits may be separated.
TEJON R ESEARCH AND CONSERVATION R ECOMMENDATIONS
Given the special conservation status of badgers in California, the following recommendations are proposed for
badgers on Tejon Ranch.
Conduct Population Surveys
Estimating overall badger abundance on Tejon Ranch is difficult, given the lack of data on density by habitat and
the range of habitats on the Ranch. To address this lack, surveys should be conducted on Tejon Ranch. Testing
DNA surveys are recommended, using either scat collection or hair collection at burrows (possibly using dogs).
Also recommended is comparing and testing burrow transects to the population estimates to establish baselines
for population trend monitoring on Tejon Ranch in the most likely habitats. Such data would be useful to refine
population extrapolations statewide.
Avoid Recreational and Depredation Take
Given that no food benefit and little economic benefit results from harvest of badgers, and because of the very
low reproduction rate of the species, recreational take of badgers on Tejon Ranch should be not be allowed. No
take should be allowed for depredations; translocations should be used to resolve significant documented
conflicts. Further, given the lack of areas with badger habitats under protected status, the viability of the
population on Tejon Ranch should be assessed and recommendations should be made, based on that assessment,
for conservation of a viable population of badgers. This would be the first such assessment in the state.
Limit Rodenticide Use
Given the high rate of mortality caused by rodenticides to badgers, bobcats, and other predators, use of
rodenticides should be limited outside of human-occupied areas and use of no toxic rodenticides and integrated
pest management (see above).
Secure Linkage Zones and Develop Highway Crossing Structures
As proposed by the South Coast Wildlands Project (Penrod et al. 2003), linkage zones for badgers should be
secured and highway crossing structures developed. The South Coast Wildlands Project considers badgers as a
focal species in all of its habitat linkage designs and developed a linkage model connecting the Sierra Madres to
the Sierra Nevada through Tejon Ranch. Based on the least cost path modeling for nine species that they then
merged into a least cost union, Penrod et al. (2003) proposed three crossing sites and structures along Interstate
5. They also recommended three areas for first-class crossing structures along Highway 58. Implementing these
linkage zones and crossing structures may provide habitat connectivity and protect against increasing habitat
fragmentation for the species. One type of corridor design that has proven beneficial for badgers is to provide
fencing to guide badgers to culverts running under high use roads where there has been a high rate of badger
mortality. This type of corridor design has nearly doubled the size of European badger populations in some
regions (Bekker and Canters 1995).
January 2013
R EFERENCES
Apps, C. D., N. J. Newhouse, and T. A. Kinley. 2002. Habitat associations of American badgers in southeastern
British Columbia. Canadian Journal of Zoology 80: 1228-1239.
Armitage, K. B. 2004. Badger predation on yellow-bellied marmots. American Midland Naturalist 151: 378–387.
Bekker, H., and K. J. Canters. 1995. The continuing story of badgers and their tunnels. Pp. 344-353 in Proceedings of
the International Conference on Habitat Fragmentation, Infrastructure and the Role of Ecological Engineering. Maastricht
and the Hague, the Netherlands.
Comrack, L., B. Bolster, J. Gustafson, D. Steele, and E. Burkett. 2008. Species of Special Concern: A Brief Description of an
Important California Department of Fish and Game Designation. California Department of Fish and Game, Wildlife
Branch, Nongame Wildlife Program Report 2008-03, Sacramento, CA. 4pp.
Crooks, K. R. 2002. Relative sensitivities of mammalian carnivores to habitat fragmentation. Conservation Biology
16:488–502.
Davis, F. W., D. M. Stoms, A. D. Hollander, K. A. Thomas, P. A. Stine, D. Odion, M. I. M. I. Borchert, J. H. Thorne,
M. V. Gray, R. E. Walker, K. Warner, and J. Graae. 1998. California GAP Analysis Project Report. University of
California, Santa Barbara, Santa Barbara, CA. Unpublished report.
Drescher, H. E. 1974. On the status of the badger, Taxidea taxus, in Manitoba (Canada). Zool. Anz., Jena 192:222-238.
Dupue, J., and M. Ben-David. 2005. Hair sampling techniques for otters. Journal of Wildlife Management 71:671-682.
Grinnell, J., J. S. Dixon, and J. M. Linsdale. 1937. Fur-bearing Mammals of California, Vol. 2. University of California
Press, Berkeley, CA. 777 pp.
Hoodicoff, C. 2003. Ecology of the badger (Taxidea taxus jeffersonii) in the Thompson region of British Columbia:
Implications for conservation. M.S. Thesis. University-College of the Cariboo, Vancouver, British Columbia.
Jager, H. I., E. A. Carr, and R. A. Efroymson. 2006. Simulated effects of habitat loss and fragmentation on a
solitary mustelid predator. Ecological Modelling 191: 416-430.
Kinley, T, and N. Newhouse. 2008. Ecology and translocation-aided recovery of an endangered badger
population. Journal of Wildlife Management 72:113-122
Lampe, R. P. 1976. Aspects of the predatory strategy of the North American badger, Taxidea taxus. Ph.D.
dissertation. University of Minnesota, St. Paul, St. Paul, MN.
Long, C.A., and C.A. Killingley. 1983. The Badgers of the World. Charles C. Thomas Publishing, Springfield, IL.
Messick, J., and M. Hornocker. 1981. Ecology of the badger in southwestern Idaho. J Wildlife. Monograph 76.
Messick, J.P. 1987. North American Badger. Pp. 586-597 in M. Novak, J.A. Baker, M.E. Obbard, and B. Malloch
(eds.). Wild Furbearer Management and Conservation in North America. Ministry of Natural Resources, Toronto,
Ontario. 1150pp.
Michener, G. R. 2004. Hunting and tool use by North American badgers preying on Richardson’s ground
squirrels. Journal of Mammalogy 85:1019-1027.
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Michener, G. R., and A. N. Iwanuik. 2001. Killing technique of North American badgers preying on Richardson’s
ground squirrels. Canadian Journal of Zoology 79:2109-2113.
Minta, S. C. 1990. The badger Taxidea taxus (Carnivora: Mustelidae): spatial-temporal analysis, dimorphic
territorial polygyny, population characteristics, and human influences on ecology. Ph.D. dissertation.
University of California, Davis, Davis, CA.
Minta, S. 1993. Sexual differences in spatio-temporal interaction among badgers. Oecologia 96:402-409.
Minta, S., and M. Mangel. 1989. A simple population estimate based on simulation for capture–recapture and
capture-resight data. Ecology 70:1738–1751.
Minta, S. C., and R. E. Marsh. 1988. Badgers (Taxidea taxus) as occasional pests in agriculture. Proceedings of the
Vertebrate Pest Conference 13:199-208.
Minta, S. C., K. A. Minta, and D. F. Lott. 1992. Hunting associations between badgers (Taxidea taxus) and coyotes
(Canis latrans). Journal of Mammalogy 73:814–820.
Murie, J. O. 1992. Predation by badgers on Columbian ground squirrels. Journal of Mammalogy 73:385-394.
Newhouse, N., and T. Kinley. 2000. Update COSEWIC status report on the American badger Taxidea taxus in
Canada. Pp. 1–26 in COSEWIC Assessment and Status Report on the American Badger Taxidea taxus in Canada.
Committee on the Status of Endangered Wildlife in Canada, Ottawa, Ontario, Canada.
Penrod, K., C. Cabañero, C. Luke, P. Beier, W. Spencer, and E. Rubin. 2003. South Coast Missing Linkages: A
linkage design for the Tehachapi Connection. Unpublished report. South Coast Wildlands Project,
Monrovia, CA.
Proulx, G. 2010. Factors contributing to the outbreak of Richardson’s ground squirrel populations in the
Canadian prairies. Proceedings Vertebrate Pest Conference 24:213–217.
Proulx, G., and N. MacKenzie. 2012. Relative abundance of American badger (Taxidea taxus) and red fox (Vulpes
vulpes) in landscapes with high and low rodenticide poisoning levels. Integrative Zoology 7:41-47.
Prugh, L., C. Ritland, S. Arthur, and C. Krebs. 2005. Monitoring coyote population dynamics by genotyping
faeces. Molecular Ecology 14:1585-1596.
Quinn, J. H. 2008. The ecology of the American badger Taxidea taxus in California: Assessing conservation needs
on multiple scales. Ph.D. dissertation. University of California, Davis, Davis, CA.
Quinn, J.H, and T. M. Diamond. 2008. The status of the American badger in California. Report to California Department
of Fish and Game Resource Assessment Program.
Williams, D. F. 1986. Mammalian Species of Special Concern in California. California Department of Fish and Game,
Wildlife Management Administration Division Report 86-1. Sacramento, CA
January 2013
2. Black Bear ( Ursus americanus )
California Department of Fish and Wildlife (CDFW)
(formerly the California Department of Fish and Game
[CDFG]) estimates that the statewide population of black
bears (Ursus americanus) has increased steadily from 7,500
bears in 1982 to 25,000–30,000 black bears that are now
estimated to occupy 135,000 square kilometers (km2)
(CDFG 2011). (In this assessment, the general term “bear”
is used interchangeably with “black bear.”) Black bears are
being observed in areas where they were not seen 50 years
ago, such as along the Central Coast and Transverse
Ranges of southern California.
The Sierra Nevada black bear subpopulation encompasses
the Sierra Nevada Floristic Province and extends from
Plumas County south to Kern County (CDFG 2011). Forty
percent of the statewide black bear population inhabits
the Sierra Nevada. Bear populations are relatively less
dense in the Sierra Nevada than in other ecoregions of the
state, with between 0.5 and 1.0 bear per 2.6 km2 (1 square
mile) (Grenfell and Brody 1986, Koch 1983, Sitton 1982).
California black bear (USFWS 2005)
The western/southwestern bear subpopulation extends south and east from Santa Cruz County to San Diego
County. Prior to 1950, bears were not believed to inhabit the Central Coast or Transverse Ranges (Storer and
Tevis 1996, Grinnell et al. 1937); black bears were believed to be excluded from or limited in these regions by the
larger California grizzly bear (Ursus arctos californicus). In most of their range in North America, black bears and
grizzly bears overlap extensively, and black bears were probably present historically at low densities in the
Tehachapis. During this period, grizzly bears occupied most of California, aside from the southeast deserts. After
the California grizzly bear became extinct around the beginning of the twentieth century, black bears started to
occupy areas from which they were previously excluded, including Ventura and Santa Barbara Counties
(Grinnell et al. 1937). CDFW supplemented this natural range expansion by moving black bears into southern
California during the early 1930s. The current black bear population in the San Gabriel and San Bernardino
Mountains is believed to be at least partially descended from this supplemental introduced population.
Probably less than 10 percent of the statewide black bear population inhabits the central western/southwestern
California bioregion, and bears are restricted to the Central Coast and Transverse Ranges in this bioregion. Based
on studies of black bears in chaparral habitats in Arizona (LeCount 1982) and southern California (Stubblefield
1992, Novick et al. 1981, Moss 1972), bear density is probably less than 0.25 bear per 2.6ºkm2.
No research or population estimates have been made for bears on or near Tejon. Applying the density from the
Sierra Nevada (Grenfell and Brody 1986, Koch 1983, Sitton 1982), the population on Tejon Ranch would
extrapolate to 200–400 bears.
Bear hunts were initiated on Tejon Ranch in 1995. From 2001 to 2008, an average of two bears were killed
annually. No harvest information is available for 2009 or 2010. No tags were issued for bear hunts on the Ranch in
2011. The Tejon Ranch Private Lands Wildlife Enhancement and Management Area (PLM) Program authorizes
five bear tags to be issued; however, there was no interest from the public in hunting bears on Tejon Ranch in
2011.
January 2013
Bear populations are densest in forested areas with a wide variety of seral stages. Habitats with both vegetative
and structural diversity provide alternate food resources when other foods are in short supply. Hard and soft
mast are especially important for bears and this includes acorn and manzanita berries. Acorns are likely very
important for bears on Tejon Ranch. Beyond that, it is difficult to speculate on the most important bear foods on
the Ranch. Most of Tejon is rated as having medium or high habitat suitability based on CDFG’s Habitat
Suitability Indices (HSI) (CDFG 2011).
Many of the important food plants in California (e.g., manzanita, oaks) grow only in forest openings. Therefore,
controlled burns or other management strategies aimed at creating a mosaic of forest openings can be especially
beneficial for black bears by providing abundant food resources close to cover. Additionally, retention and
recruitment of snags and large woody debris provide den sites and potential food sources (such as colonial
insects).
POPULATION DYNAMICS
Density
Densities of black bears range from 90 (in Alaska) to 1,300 (in Washington) per 1,000 km2 in western North
America (Kolenosky and Strathearn 1999, Miller et al. 1997). Densities and demographic rates are highest in
diverse early-successional forests with rich soils and in areas with relatively long foraging seasons (Schwartz and
Franzmann 1991).
Reproduction
If a female bear lives to age 15, she will generally produce a maximum of six litters during her lifetime (Kolenosky
and Strathearn 1999). Beston (2011) reported that mean fecundity (cubs per female per year) in the western
United States was 0.46.
Mortality
Most mortality of bears is caused by humans; causes include hunting, poaching, depredation control, and vehicle
collisions. Annual survival rates of adult females average 87% (Pelton 2000). Beston (2011) found that in the
western United States, adult survival was higher than in the east (88% v. 82%), and mean annual population
growth rate in western North America was 97% v. 99% in the east. Growth in California since 1982 has been
increasing significantly.
Spatial Structure and Dispersal
Individual bears exhibit little spatial or temporal avoidance of each other, and home ranges and core areas of both
sexes often overlap (Powell et al. 1997). Novick and Steward (1982) reported home range size of black bears to be
24.6 km2 in the San Bernardino Mountains. Woodroffe and Ginsberg (1998) found that home range size was 18.8
km2 in California. These ranges are smaller than the average home range size in western North America, 119 km2
for males and 49 km2 for females (Amstrup and Beecham 1976).
IMPACT ON PREY
In general, black bear predation has not been a significant concern for wildlife managers. Bears can be important
predators on newborn ungulates in some areas, however, especially when other predators are also present
(Griffin et al. 2011), including deer fawns (Kunkel and Mech 1994) and elk calves. White and colleagues (2010)
demonstrated that predation by black bears was the most important proximate mortality factor for elk calves
from birth through August in north-central Idaho. Because that mortality was additive to other sources of
mortality, increased bear harvest improved summer calf survival. Harvest of more than 10 bears per 600 km2 on
one study area and more than 50 bears per 600 km2 on a second study area reduced elk calf mortality. Black bear
harvest had a stronger direct effect on summer calf survival than did cougar harvest, although both effects were
January 2013
detectable. Because calves are generally most susceptible to bear predation in the first 28 days of life, spring hunts
that reduce bear densities or at least disrupt bear activities may be most effective. Increasing autumn bear harvest
may have a similar, though less immediate and predictable, effect. Reducing black bear harvest may decrease calf
survival, and this strategy could be used where the goal is to slow population growth of elk herds or decrease elk
population size.
In Idaho, calf birth mass and habitat structure also influenced calf survival (White et al. 2010). Thus, addressing
depressed elk recruitment with predator harvest alone may not be effective in achieving calf recruitment
objectives. Improving elk habitat may increase physical condition in adult female elk, which should lead to
heavier calves with higher summer survival and, perhaps, winter survival. Based on the results reported by White
and colleagues (2010), structural characteristics of good-quality elk habitat may also contribute to calf survival
by improving escapement. Fire and mechanical treatment could provide early seral forest conditions (Hershey
and Leege 1982).
ROLE IN ECOSYSTEM
In addition to having impacts on ungulate dynamics through neonate predation, bears have important effects on
ecosystems through scavenging, seed dispersal, and nitrogen transport via fish predation. Carrion use by
facultative scavengers is a key ecological process that has a strong influence on food webs (DeVault et al. 2003,
Wilson and Wolkovich 2011). Krofel and colleagues (2012) reported that, in Scandinavia, bears found 32% of lynx
prey remains and that 15% of all biomass of large prey killed by lynx was lost to bears. In response, lynx increased
their kill rate by 23% but were able to compensate for only 59% of the losses. Black bears and deer mice can play
important, but different, roles in dispersing fleshy-fruited plants with large seeds. Seed dispersal by black bears is
especially important for transporting seeds over relatively long distances (Willson 1993, Willson and Gende
2004).
CONNECTIVITY
Based on an assessment of the genetics of bear subpopulations in California, Brown and colleagues (2009)
reported that habitats that likely function as connectivity corridors for black bears, such as the corridor through
the Transverse and Tehachapi ranges, will need to be protected for the southern California and Central Coast
populations to remain genetically viable.
Lewis and colleagues (2011) used GPS collars on bears along US 95 in northern Idaho to assess impacts of the
highway on connectivity for bears. Even though US 95 was characterized by relatively low traffic volumes and
low levels of human disturbance, nearly all bears used the highway as a boundary for their home range and
movement patterns (Lewis et al. 2011). This finding is consistent with results from other studies of bears where
traffic volumes on roads were substantially greater (Brody and Pelton 1989, Kaczensky et al. 2003). Although
bears altered their patterns of movement and space use in relation to the highway, nearly half of Idaho study
animals crossed the highway. Importantly, when bears traversed the highway, they selected for specific habitat
characteristics at crossing locations, characterized by forested areas away from human development, with habitat
features including short distance to cover, more shrub along the highway, and short distance to water.
Most wildlife–highway studies have focused on roads with high traffic volumes, such as the Trans-Canada
Highway in Banff National Park, Alberta, Canada, with 14,500–21,500 average daily trips (Gibeau et al. 2002).
Consequently, the results for highway crossing behavior in the Idaho study were likely influenced by the
relatively low traffic volumes along US 95 (800–1,500 average daily trips).
Harvest
In hunted populations, harvest is the primary cause of mortality for adult black bears (Hellgren and Vaughan
1989, Schwartz and Franzmann 1991, Beringer et al. 1998, Koehler and Pierce 2005, Czetwertynski et al. 2007).
January 2013
Harvest in all states ranged from 2% to 25% of total population size, and the female portion of that harvest
ranged from 31% to 54%.
Garshelis (1994) concluded that increased mortality of dispersing subadult males would not be sufficient to
regulate bear population size unless females were also harvested. By reducing the non-reproducing females,
recruitment potential could be moderated. Harvest rates of 20% for females appear to be sustainable. On average,
California harvests 6–7% of the population with about 40% of the harvest being females (Hristienko and
McDonald 2007).
Beringer and colleagues (1998) reported that Harmon Den Bear Sanctuary in North Carolina, despite being only
57 km2, serves as a reservoir for adult female black bears and, to a lesser extent, for adult males. Reproductive
females produce subadult males that disperse at high rates and are subsequently harvested by hunters. If adult
female bears are protected, it appears that this form of spatial harvest control (McCullough 1996) is sustainable.
These small refuges may be essential to the viability of bear populations where hunting pressure is heavy.
Conflicts with Humans
The California Fish and Game Code states that landowners may kill a bear encountered in the act of molesting or
injuring livestock. The law provides for the issuance of a depredation permit to landowners or tenants who
encounter a “problem” bear (that is, a bear that causes property damage). The permit allows the permittee or
designee to kill the offending bear regardless of the time of year. A depredation permit, however, is the last in a
series of steps taken to eliminate the problem.
California’s bear depredation policy follows a progressive response system based on the degree of damage being
caused. Bear situations are categorized and then addressed:
▪
In the first category, a bear strays into a populated area and cannot readily return to bear habitat. In most
situations, removal of antagonists or distractions from the area will allow the bear to return to nearby
bear habitat with no other incident. Designated as “no harm, no foul,” techniques to remove the bear may
include, but are not limited to, the use of sound makers, pepper spray, rubber slug shot shells, or slingshot projectiles to drive the bear away or haze the bear out of the area. Tranquilizing and removing the
bear can be used if other methods are determined to be unsafe or have been unsuccessful.
▪
In the second category, a bear becomes habituated to humans and may create a nuisance problem (no
property damage involved) by raiding garbage cans, invading compost piles, walking across porches, and
so forth. Previously captured bears that have returned to areas of human habitation are included in this
category. In these cases, the landowner is informed of reasonable corrective measures as a solution to the
problem. These may include removal of trash or other food attractants, bear-proofing food storage areas,
electric fencing, and temporary closure of campsites. As mentioned above, techniques to remove the bear
may include the use of sound makers, rubber slug shot shells, or sling-shot projectiles to drive the bear
away or haze the bear out of the area.
▪
In the third category, a bear causes real property damage to a dwelling(s), structure(s), vehicle(s),
apiaries, or other property or is a repeat offender (has been captured or hazed previously by CDFW
employees). If the damage is minor and there are no reports of previous damage, the first action is
implementation of reasonable corrective measures to remove attractants, as outlined for the second
category. Corrective measures must be made before, or in addition to, issuing a depredation permit.
When a bear has caused extensive or chronic damage to private property (such as killing or injuring
livestock or entering a home or cabin), or in cases of repeated damage where corrective or bear-proofing
efforts have failed, CDFW issues a depredation permit.
In general, 50% of the depredation permits in California are issued for damage caused to structures or other
property such as vehicles, trailers, or recreational vehicles. Livestock represents the next most abundant
January 2013
categorywith 15%. Orchards and fowl (chickens, geese, and ducks) each represent 11% of the total, and beehives
represent 8%. Crops, safety, and pets represent the final 5%.
Despite a four-fold increase in the bear population in California from 1983 to 2009, bear depredation levels have
remained stable (CDFG 2011). This probably results largely from improvements in management of food around
areas bears occupy.
No conflicts have been reported between bears and livestock or between bears and humans on Tejon Ranch.
Climate Change Impacts
CDFG (2011) modeled impacts of climate change on bears. The model assumed a 100-year mean temperature
increase of 3.3°C and an 18% reduction in precipitation in California. The predicted plant distributions were
cross-referenced with the HSI model to predict changes in statewide distribution of HSI categories.
Results indicated a shift in oak woodlands and riparian woodlands away from the valleys and foothills and
toward the coast. They predicted a significant constriction of upper-elevation montane conifer forests (indicated
by Abies magnifica) throughout the state. These constrictions would be extreme in the southern California
mountains and the northern Coast Ranges. Models also predicted major upward shifts in chaparral (Q. wislizeni
var. fructescens) away from lower foothill areas. Although optimal bear habitat is predicted to shift toward the
Coast Ranges, much of the current bear range would still be considered suitable habitat and may support a viable
and healthy bear population. Based on mapping, much of Tejon Ranch would transition from marginal to suitable
habitat.
In 1995, CDFG developed a decision matrix (Table C2-1) for annually evaluating the status of California’s
statewide bear population (CDFG 2011). This matrix was based on the recommendations by Garshelis (1993) and
Garshelis and Hristienko (2006) that several monitoring techniques be employed simultaneously for monitoring
bear populations. The decision matrix details monitoring techniques and identifies thresholds of concern for each
monitored attribute of the bear population. The Black Bear Management Plan (CDFG 2011) commits CDFW to
recommend reducing hunter kill of bears in some manner when two or more of these thresholds of concern are
exceeded. Requiring changes from two thresholds accounts for natural annual variation in the estimates used in
this matrix. The use of a single threshold would be too sensitive and cause frequent regulatory changes
unsupported by the available scientific evidence, whereas exceeding three or all thresholds may not be sensitive
enough to detect actual changes in the bear population.
Table 2-1
Decision Matrix for Monitoring the Black Bear Population
Monitoring Technique
Threshold of Concern
Median ages of hunter-killed bears
Female ages less than 4.0 years or significant reduction in
median age for combined sexes
Percent females in harvest
More than 40%
Total harvest
Less than 1,000 or significant reduction compared to the
previous 3 years (not implemented in years when reduction
is attributable to administrative action)
Kill per hunter effort and population trend
Significant change in kill per hunter effort and population
index
Source:
CDFG 2011
January 2013
The sex ratio of the bear harvest is another important indicator of the health of the bear population. Male bears
are killed at a higher rate than they occur in the population as a result of hunter selectivity (Litvaitis and Kane
1994) and because male bears have larger home ranges and thus a correspondingly higher probability of being
encountered by hunters (Jonkel and Cowan 1971, Sitton 1982, Koch 1983, Elowe and Dodge 1989). Therefore, sex
ratios of harvested animals will continue to be biased toward males until fewer males are available for harvest.
The threshold for concern in the monitoring matrix is a population of more than 40% females in the harvest. In
2009, females constituted 40.4% of the California harvest. This was the only monitoring threshold exceeded in
2009.
The number of bears harvested in a season also reflects the condition of the bear population. Reductions in bear
populations would make it more difficult to find bears and, therefore, more difficult to harvest a bear. However,
year-to-year variability in the bear harvest is inevitable because changes in weather may also affect bear harvest.
For instance, an early winter makes it more difficult for hunters to kill a bear, especially hunters using dogs.
Changes in regulations can result in decreases in bear harvest; reducing the number of bears allowed to be
harvested in a season is one example. For this reason, the threshold identified in the matrix is not considered in
years following regulation changes that restrict harvest or hunter opportunity. The matrix threshold for this
criterion is a harvest of less than 1,000 or a significant reduction compared to the previous 3 years.
The fourth monitoring technique and threshold is a significant change in both the kill per hunter effort and the
population index. According to the Black Bear Management Plan, CDFW may monitor the kill per hunter effort
from either the Game Take Hunter Survey (a questionnaire administered to a random sample of sportspersons in
California regarding hunter success and effort) or information obtained from the mandatory return of bear tags.
Results of computer modeling efforts indicate that in California, bear populations greater than or equal to the
2010 bear population can sustain a statewide hunter harvest of 3,100 with illegal take equal to 25% of legal
harvest (775 bears) without causing the bear population to decline. With a combined legal–illegal harvest of
3,875 bears, total hunting mortality would be approximately 10% of the statewide population. This level is below
its maximum-sustained yield level of 14.2%. These modeling results, which are based on observed data, indicate
that any level of legal harvest less than 3,100 bears would not have significant adverse effects on the state’s bear
population.
Population Monitoring
The most common and (arguably) rigorous method now used for estimating bear population size is the
application of mark–recapture techniques to data from systematically collected hair samples (Gardner et al.
2010). Enough DNA is contained in the roots of mammalian hair to allow the identification of species, sex, and
individuality. This technique is advantageous in studying bears because they are easily attracted to hair traps
using bait or scent lures; therefore, samples can be collected more economically than with traditional capture–
recapture methods (Woods et al. 1999). The traps are often constructed with barbed wire and bait or an
attractant, and they are simple to design and inexpensive (Woods et al. 1999).
A trapping grid is overlaid on the study area. Otis and colleagues (1978) suggested that population studies be
designed so that each animals would have more than four traps in its estimated home range. The most
conservative estimate of home-range radius) is 2,779 m. Boersen and colleagues (2003) and Gardner and
colleagues (2010) placed traps approximately 3,000 m apart throughout the study area to exceed that minimum
trap density. Trap placement was subjective within those spacing guidelines. After microsatellite genotyping of
hair samples, researchers can create individual encounter histories for each bear that was captured at least once.
Such data can be applied within capture–recapture methods for estimating the size of a closed population
(Boulanger et al. 2006). Gardner and colleagues (2010) provide a technique for estimating density that accounts
for trapping biases and movement of bears.
January 2013
OVERALL CONSERVATION RECOMMENDATIONS
Woodroffe and Ginsberg (1998) found, based on 45 reserves, that the minimum critical reserve size for black
bears was more than 100 km2. This was the critical reserve size at which populations persisted with a probability
of greater than 50%. This is most certainly a conservative estimate, therefore, and does not include genetic
factors.
In a reserve of given size, wide-ranging carnivores are more likely to become extinct than those with smaller
home ranges, irrespective of population density. Thus, population size is a relatively poor predictor of extinction
among carnivores. Ranging behavior mediates contact with human activity, which accounts for a very high
proportion of adult mortality in carnivores. Among large carnivores isolated in small reserves, human-induced
mortality contributes more to the extinction of populations than do stochastic processes (Woodroffe and
Ginsberg 1998). Conservation measures that aim only to combat stochastic processes are therefore unlikely to
avert extinction. Instead, Woodroffe and Ginsberg recommended that priority should be given to measures that
seek to maximize reserve size or to mitigate carnivore persecution on reserve borders and in buffer zones.
TEJON R ANCH RESEARCH AND CONSERVATION RECOMMENDATIONS
Harvest Management
If significantly increased bear harvest is proposed on Tejon Ranch, a baseline population survey using hair snag
mark-recapture techniques should be conducted so that harvest levels can be kept below thresholds of
sustainability. Especially given no confirmed connectivity of Tejon Ranch to the regional bear population, a
sustainable harvest level of less than 10% is recommended. An important step would be to adopt a harvest
monitoring program similar to that used by CDFW, but limited data (small number of animals harvested) would
make this assessment difficult (Miller et al. 1997). Mountain Thinking also recommends that, before increasing
harvest significantly, an assessment be made of the potential impact of bear predation on feral pigs.
Regional Connectivity
USFWS (2012) did not find any use of crossing structures on Interstate 5 (I-5) on the western boundary of Tejon
Ranch by black bears, even though the work of Brown and colleagues (2009) indicated that connectivity in the
region was the most probable source of individuals that colonized the Coast Ranges from the Sierra Nevada. As
projections indicate increased traffic and development in the region, research should be conducted to determine
ways to develop passage of I-5 and Highway 58 by bears.
Clevenger and Waltho (2005) showed that structural and landscape factors were equally important in
explaining carnivore passage, whereas structural attributes were the most dominant features affecting ungulate
passage. For structural attributes, two clear patterns emerged. First, crossing structures with high openness
ratios (i.e., short in length, high and wide) strongly influenced passage by grizzly bears, wolves, elk, and deer.
Second, more constricted crossing structures (i.e., long in length, low, narrow, and with low openness ratios)
best explained passage by black bears and cougars.
Clevenger and Waltho (2005) compared 13 crossing structures on the Trans-Canada Highway in Banff National
Park, Alberta, Canada (average daily traffic of 15,000 vehicles per day) and found that, for black bears, distance to
the nearest drainage was the most important attribute facilitating passage and was positively correlated with
crossing structure use. Crossing structure openness was negatively correlated with black bear passage, whereas
structure length and distance to railroad tracks were both positively correlated with use.
Lewis and colleagues (2011) found that the most efficient and effective means of mitigating the effects of
roadways on animals was to identify important crossing areas for wildlife and to focus management activities
within those areas (Glista et al. 2009) by retaining or enhancing the characteristics along roads that promote
crossing behavior in animals. Lewis and colleagues (2011) assessed habitat selection by black bears at road
crossing locations, and this information was used to predict the probability of use of highway crossing areas by
animals within a landscape modified by multiple human activities. Because USFWS (2012) did not find use of
January 2013
crossing structures by bears, Mountain Thinking recommends monitoring bears with home ranges near I-5 and
Highway 58 to determine (using telemetry) if they cross these roads and where. If no evidence of crossing is
found, then Mountain Thinking recommends mapping likely crossing areas and working with the California
Department of Transportation to develop and test crossing structures for multiple species with a focus on bears.
Human-Bear Interaction
Merkle and colleagues (2011) found a positive relationship between probability of human-bear interaction (HBI)
and intermediate housing densities (6.6 houses per hectare). In areas with a moderate probability of interaction,
education programs should be developed with specific attractant-reducing goals (e.g., use bear-resistant
dumpsters, use bird feeders seasonally, pick ripe fruit off of trees) (Gore et al. 2006). Managers should also
implement ordinances outlawing human behaviors that provide available attractants, including garbage, fruit
trees, and bird feeders (Peine 2001). Such an approach is recommended for development on Tejon Ranch.
In undeveloped areas, wildlife managers involved in planning community development can integrate information
about proposed housing developments into a future model, allowing estimation of the relative probability of
future HBI. Hypothetical changes to housing development proposals can be tested, and the development plan
with the lowest probability of HBI can be recommended. This approach is recommended for proposed
development on Tejon Ranch.
January 2013
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Woods, J. G., D. Paetkau, D. Lewis, B. N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of freeranging black and brown bears. Wildlife Society Bulletin 27:616–627.
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3. Bobcat ( Felis rufus )
Bobcats are widely distributed in California and relatively
abundant. As carnivores, they are habitat generalists and
rely on stealth for ambush to capture small prey. As such,
cover for ambush is an important component of their
habitat. Optimal habitats in California are brushy stages of
low- and mid-elevation conifer, oak, riparian, and pinyonjuniper forests and all stages of chaparral (California
Department of Fish and Wildlife 2013). Bobcats are
managed as a nongame species in the state with
established seasons and a tag is required.
POPULATION DYNAMICS
Bobcat (© Tejon Ranch Company 2012
Density
Ruell and colleagues (2009) reported bobcat density estimates in Topanga and Simi Hills, California at 0.25–0.42
individuals per square kilometer (km2). Densities of 1.27–1.53 individuals per km2 were estimated from a small
(6.7-km2) study area within the Cleveland National Forest, south of Los Angeles. These latter densities were not
derived from population estimates but rather were calculated from the fraction of time that radio-collared
bobcats occupied the study area (Lembeck 1986).
When few alternate prey species are available, bobcat abundance is generally driven by prey abundance; when
their primary prey declines, bobcat density declines (Knick 1990).
The low population densities noted by Ruell and colleagues (2009) in both Topanga and Simi Hills were
indicative of population declines resulting from a notoedric mange epizootic (the animal equivalent of an
epidemic) that began in 2002, likely interacting with anticoagulant exposure (obtained by ingesting animals
killed by rodenticides) (Riley et al. 2007). Anticoagulants are common in agricultural areas and around buildings
and homes and golf courses. After the epizootic, densities of bobcats within the two smaller fragments in the
Santa Monica Mountains National Recreation Area had also declined, from 0.6 to 0.2 individuals per km2 (Riley
et al. 2007).
Larrucea and colleagues (2007) conducted work on the 130-km2 Gray Davis/Dye Creek Preserve managed by the
Nature Conservancy near Red Bluff, California. The preserve lies at the edge of the northern Sacramento Valley in
the foothills of the Cascade Range at elevations ranging from 50 to 700 meters (m). The best estimate by Larrucea
and colleagues (2007) of bobcat abundance based on camera traps was six in an effective area of 22 km2, for a
density of 0.27 bobcats per km2.
Based on a conservative estimate of 0.25 bobcat per km2 and including all habitats, Tejon Ranch would support
250 bobcats.
Mortality
In urban southern California, roads are the major source of bobcat mortality, even for animals with little or no
developed area within their home range (Riley et al. 2003). In the Santa Monica Mountains National Recreation
Area in coastal southern California, annual survival rates of bobcats dropped from 0.77 (5-year average from 1997
to 2001) to 0.28 in 2003, likely due to interactions between anticoagulant exposure and the notoedric mange
epizootic. The number of bobcat scats collected in these areas along established scat transects also indicated a
significant decrease in bobcat presence from 2002 through spring 2004 (Riley et al. 2007).
January 2013
Riley and colleagues (2003) reported that average annual survival rates were similar between bobcats (0.76) and
coyotes (0.74) and between sexes within species (male bobcats 0.82 v. female bobcats 0.75). Contrary to the
expectations of the researchers, no differences were seen in survival rate relative to urban association. Those
survival rates for bobcats were similar to rates reported in other unexploited populations (Fuller and Berendzen
1995, Chamberlain and Leopold 1999) and higher than those in harvested populations (Fuller and Berendzen
1985).
Riley and colleagues (2003) found that, in the Santa Monica Mountains National Recreation Area, adult female
home ranges averaged 1.7 km2 while home ranges for males averaged 3.2 km2. Bobcats maintain their solitary
spatial organization through a land-tenure system (Bailey 1974, Benson et al. 2004) in which home ranges are
occupied for years at a time by individuals that prevent others of the same sex from occupying the same area until
the death or departure of the original individual (Litvaitis et al. 1987, Anderson 1988, Lovallo and Anderson 1996).
Relationships among Carnivores
Fedriana and colleagues (2000) identified behavioral dominance of coyotes over gray foxes and bobcats in the
Santa Monica Mountains because seven of 12 recorded gray fox deaths and two of five recorded bobcat deaths
were due to coyote predation, and no coyotes died as a result of their interactions with bobcats or foxes. Coyotes
and bobcats were present in various habitats types (eight out of nine), including both open and brushy habitats,
whereas gray foxes were chiefly restricted to brushy habitats. Bobcats were solely carnivorous, relying on small
mammals (lagomorphs and rodents) throughout the year and at all three sites. Coyotes and gray foxes also relied
on small mammals year-round at all sites, although they also ate significant amounts of fruit. Although strong
overall interspecific differences were noted in the food habits of carnivores, average seasonal food overlaps were
high due to the importance of small mammals in all carnivore diets, as shown in Table C3-1.
Table 3-1
Average Seasonal Food Overlap among Carnivores
Species
Overlap Ratio
Number of Scats
Compared
Bobcat–Gray Fox
0.79
4
Bobcat–Coyote
0.69
6
Coyote–Gray Fox
0.52
4
Note:
An overlap ratio of 1.0 indicates complete overlap in the diets of the two species.
Source:
Fedriana et al. 2000
As Fedriana and colleagues (2000) had hypothesized, coyotes used more food types and more habitat types than
did bobcats and gray foxes; overall, coyotes were the most abundant of the three species and ranged more widely
than did gray foxes. The authors proposed that coyotes limit the number and distribution of gray foxes in the
Santa Monica Mountains. They also hypothesized that those two carnivores exemplified a case in which the
relationship between their body size and local abundance is governed by competitive dominance of the largest
species rather than by energetic equivalences. However, in the case of the intermediate-sized bobcat, no such
pattern emerged, likely due to rarity or inconsistency of agonistic interactions and/or behavioral avoidance of
encounters by subordinate species. Finally, it is possible that the combination of predation impact by more than
two predators on similar prey species can result in prey suppression (Knick 1990).
January 2013
CONNECTIVITY
The Tejon Ranch Company conducted a camera study at various undercrossings of Interstate 5 (I-5) during
2002–2007 (USFWS 2012). The camera study involved placement of paired motion-sensitive cameras at both
entrances to culverts and overpasses at five study sites in 2002 and at a total of 12 culverts and two underpasses
by 2007.
From 2002 to 2007, Tejon Ranch Company consulting biologists checked cameras and collected data generally
every other week from July through November, once every 3 weeks from December through March, and once
every other week from April through June. All photographs were reviewed by at least three biologists to
determine the species present in the photograph and the direction of movement, where possible. The study
generated approximately 18,000 photographs; 1,306 were of deer, coyotes, and bobcats. Large carnivore activity
was concentrated at the two northernmost Grapevine Canyon locations. These two underpasses accounted for
89% of all bobcat photographs and 90% of all coyote photographs taken during the study.
Harvest
Bobcat harvest nationwide peaked in the late 1970s and early 1980s because of a high demand for pelts. There was
much concern about the potential for overharvest. The harvest on Tejon Ranch peaked at 150 bobcats in 1978.
Since then, the harvest has been in decline on Tejon Ranch and nationally. Annual harvest on the Ranch ranged
from 0 to nine animals during 2002–2008, and 15 bobcats were harvested in 2011–2012. An estimated 1,195
bobcats were taken during the 2010–2011 hunting season in California. Trappers took 893 bobcats, sport hunters
took 238, and U.S. Department of Agriculture Wildlife Services personnel took 64. Likely because of relatively
high fur prices, the total take increased 57% from the 2009–2010 season.
Very little work has been done to assess impacts of harvest on bobcats. Knick (1990) completed computer
simulations based on social organization and population dynamics of female bobcats in sagebrush habitat of
southeastern Idaho to determine yield at different harvest intensities. Based on his results, he recommended
harvest rates that were less than 20% of the fall population. Increases in mortality of productive females that
orphaned kittens (which subsequently died) had a greater impact on yield than did increases in kitten mortality.
Knick (1990) proposed that establishing unharvested refugia would be a good way to reduce impacts of harvest,
and he suggested that the predicted size of refugia needed to maintain a harvested population must be large
enough to completely enclose three to five bobcat territories.
Knowledge of the time of kitten independence is important so that harvest seasons can be set to avoid orphaning
of dependent offspring. Knick (1990) reported that bobcat kittens in southeastern Idaho were independent by
January, although half of the kittens had not yet dispersed during the breeding (February–March) or denning
(April–September) periods.
Juvenile dispersal is not well described for bobcats, despite the important role of dispersers in filling vacancies
created by harvest (Litvaitis et al. 1987). Knowledge of the distance that individuals disperse is necessary to
assess the ability of refugia to provide individuals for surrounding regions. Almost all of the dispersals in
southeastern Idaho were less than 35 km from the natal range. The dispersals from refugia would likely affect
regions within a similar distance. Given these relatively short dispersal distances, Knick (1990) suggested that
managers may wish to maintain several refugia throughout a region rather than rely on a single large reserve to
serve an area.
Decreased adult survival is also indicative of increased harvest intensity. In Idaho, the baseline population could
not sustain itself when adult female survival rate was less than 0.52. In Maine, a population was maintained at an
adult survival rate of 57% (Litvaitis et al. 1987).
January 2013
Habitat Fragmentation and Impacts of Development
Riley (2006) found that, in the Golden Gate National Recreation Area near San Francisco, California, no radiocollared bobcats were located in developed areas outside the park. Female bobcats, in particular, had smaller
home ranges, smaller core areas, and greater core area overlap in the urban zone. Roads represented home range
boundaries for 75% of the bobcats that lived near them.
Crooks (2002) reported that bobcats were intermediate among carnivores in their sensitivity to fragmentation, a
degree of sensitivity commensurate to the scale of fragmentation across much of coastal southern California.
Bobcats were not identified in unfragmented blocks of less than 1 km2. Crooks’ models predicted that the
probability of occurrence of bobcats will be low in 10 1-km2 isolates but higher in a 10-km2 reserve. Bobcats were
less sensitive to disturbance than cougars, which were seldom found in fragmented areas; yet, bobcats were more
sensitive than coyotes and mesopredators, which were detected in even small urban habitat fragments.
Landscape connectivity appears to be the key to the persistence of bobcat populations in developing landscapes.
They can persist in fragmented habitats, but only in those landscapes with adequate movement linkages to larger
natural areas. The status of bobcat populations is therefore a valuable indicator of the degree of functional,
landscape-level connectivity across many of the fragmented landscapes of coastal southern California.
In a camera trap study in the South Coast Ecoregion of southern California, Ordeñana and colleagues (2010)
found that, unlike coyotes, bobcat occurrence declined with both increasing proximity and intensity of
urbanization. Similarly, other studies in southern California have found that bobcats are more sensitive to
urbanization and human activity than are coyotes (George and Crooks 2006, Riley et al. 2003, Tigas et al. 2002),
as well as less willing to move through urban development and across roads (Tigas et al. 2002). Bobcats are
strictly carnivorous and solitary, likely making them less adaptable to urban areas than carnivores with more
flexible diets and social structures such as coyotes (Crooks 2002, Riley et al. 2006).
Habitat Fragmentation and Connectivity
Riley and colleagues (2006) studied coyote and bobcat populations separated by the Ventura Freeway (U.S. 101),
a congested 10- to 12-lane road in the San Fernando Valley 40 km from downtown Los Angeles. More than
150,000 vehicles use the road daily, and the presence of a meridian fence largely restricts dispersal to underpasses
and culverts. Riley and colleagues (2006) reported that, from 1996 to 2003, five (4.5%) radio-collared coyotes and
10 (11.5%) radio-collared bobcats crossed the freeway, whereas 58 (52%) coyotes and 40 (45%) bobcats crossed
major secondary roads. Because a principal study objective was to understand the effects of roads, and in
particular the freeway, on carnivore movement, all radio-collared animals were captured within dispersal
distance, and many within an average home-range diameter, of both the freeway and secondary roads. However,
only 213 (2.3%) of 9,311 bobcat locations and 19 (0.4%) of 4,565 coyote locations were on the opposite side of the
freeway from the capture location of the individual. Home-range perimeters followed but did not cross roads
such as the freeway, implying that the freeway and roads functioned as artificial territorial boundaries. Although
the freeway is a barrier to movement, rates of migration of 3.4% per generation for bobcats and 1.3–9.1% per
generation for coyotes (as suggested by telemetry or genetic data) imply high rates of gene flow sufficient to
counteract drift (Vucetich and Waite 2000).
Despite moderate levels of migration, populations on either side of the freeway were genetically differentiated,
and modeling showed their genetic isolation was consistent with a migration fraction less than 0.5% per
generation (Riley et al. 2006). These results imply that individuals that crossed the freeway rarely reproduced
and that highways and development imposed artificial home-range boundaries on territorial and reproductive
individuals, decreasing genetically effective migration. Further, territory “pile-up at freeway boundaries” (i.e.,
higher densities of territories at highways compared to rest of study area may decrease reproductive
opportunities for dispersing individuals that do manage to cross. Consequently, freeways act as filters that favor
dispersing individuals and add to the migration rate but add little to gene flow. Freeways can restrict gene flow
even for wide-ranging species, suggesting that for territorial animals, migration levels across anthropogenic
barriers need to be an order of magnitude larger than commonly assumed to counteract genetic differentiation
(Riley et al. 2006).
January 2013
Monitoring
Given the advantage of unique pelage for individual bobcats, the difficulty of distinguishing species of scats, extra
cost for DNA work on scats, potential for assessing multiple species by camera, and the informational and
educational value of photographs, Mountain Thinking recommends using camera traps to determine bobcat
abundance on Tejon Ranch. Testing the technique in the proposed development areas is recommended to
determine local bobcat density and impacts of development. Testing multispecies monitoring approaches is also
recommended.
Scat DNA Surveys
Ruell and colleagues (2009) used noninvasive scat surveys and a DNA-based capture–recapture sampling
framework to estimate population sizes of urban bobcats in sites that had large numbers of scats of non-target
species. They used and compared estimates from two closed-population heterogeneity estimators in program
CAPTURE (White and Burnham 1999), which computes estimates of capture probability and population size for
closed population capture–recapture data, and the capwire estimator, which was created specifically for
noninvasive genetic sampling (Miller et al. 2005). They then combined the scat transects with GIS land-use
layers and bobcat home-range sizes to estimate effective sampling areas and population densities
Scat samples were collected in summer 2004 from two study areas located in the Santa Monica Mountains
National Recreation Area. The researchers systematically conducted surveys for scats along roads, trails, and dry
creek beds that thoroughly covered both study areas. Nonrandom sampling transects were necessary to obtain
adequately high capture probabilities (Mowat and Strobeck 2000, Woods et al. 1999); bobcats and other
carnivores frequently defecate along roads and trails, which are regular paths of movement (Kohn et al. 1999), and
random scat transects placed off roads or trails would have had low probabilities of encountering scats. Unbiased
population estimation requires that every individual had a reasonable chance of being sampled (White and
Burnham 1999). Because home ranges of female bobcats are smaller than those of males and often overlap (Riley
et al. 2003), Ruell and colleagues (2009) divided study areas into 1-km2 cells to avoid missing bobcat territories
and made a concerted effort to search for scats along carnivore movement routes within each cell (Mowat and
Strobeck 2000, Soisalo and Cavalcanti 2006). Each study area contained approximately 64 km of total transects.
Before sampling, the researchers cleared all scats from sampling routes so that scats collected in subsequent
sampling occasions were of known age. Scat transects were then sampled once every 4 days for four consecutive
sampling occasions over a total sampling period of 16 days. This sampling regime represented a balance of
sampling intensity with the risk of violating the geographic closure assumption. They traveled the identical route
on scat transects during each sampling. They estimated bobcat density in each study area by dividing the number
of scats by the effective sampling area size,. Effective sampling area sizes were estimated using GIS by buffering
scat transects with the radius (1.0 km) and then the diameter (2.0 km) of the average home range of male bobcats
(3.21 km2) (Riley et al. 2003) and measuring the area of natural habitat included in these buffers. Average homerange size of males was used because ranges of males are larger than ranges of females, and they chose to
potentially underestimate rather than overestimate bobcat densities because these populations are of
conservation concern. They only included natural habitat because bobcats in this area primarily use and rely on
native vegetative cover and avoid urban areas (Riley et al. 2003).
Scat surveys are a relatively easy and efficient method to noninvasively sample bobcats even when their
population numbers and densities are likely low. Even though detection of bobcat scat samples was unusually
low from 2002 to 2004 (Riley et al. 2007), the methods worked effectively and efficiently to estimate population
sizes and densities with minimal disturbance.
Long and colleagues (2007) found scat detection dogs to be substantially more effective and efficient (i.e., cost
per detection) than remote cameras and hair snares for documenting the presence of black bears, fishers (Martes
pennati), and bobcats in Vermont. They suggested that researchers seeking to detect carnivores and collect scat
samples should consider the use of detection dogs, especially when high detectability and minimal bias are
January 2013
priorities. It is essential that more studies be conducted to test and quantify the ability of detection dogs to
survey a diversity of species under a variety of field conditions, and to compare the effectiveness of dogs with
other survey methods.
Camera Traps
Larrucea and colleagues (2007) conducted population estimates for bobcats on the 130-km2 Gray Davis/Dye
Creek Preserve. Lower elevations are predominantly annual grasslands, while hills and ridges are covered in blue
oak (Quercus douglasii) woodland.
Bobcats were readily distinguished using a single camera per station. Sufficient variation in pelage markings
allowed individuals to be identified with confidence from photographs.
Particular attention was given to the placement of cameras at locations along trails and roads where bobcats
were likely to travel and to the blending of camera sets into the surroundings. These results support a grid-based
strategy where unproductive cameras can be moved to potentially better locations (e.g., where fresh tracks or
spoor are observed) within the same grid square. This preserves an even density of cameras, allowing all
individuals an opportunity to be photocaptured while increasing the potential of choosing a productive location.
The researchers calculated the area sampled as the area covered with camera traps plus a boundary strip. The
boundary strip accounted for individuals from outside the trapped area that may have been photographed
peripherally by cameras. This calculation represented the mean maximum distance moved (MMDM) by
individual bobcats that were captured more than once (Karanth et al. 2006, Kelly 2008). Half of this mean
distance was used as the width of the boundary strip around the outermost traps.
The sampling unit was defined as an individual adult bobcat at any particular camera station over a 24-hour
period. They divided each trial into five 1-week capture periods. If an individual bobcat was photo-captured one
or more times during a 1-week period, it was given a value of 1. If the individual was not photo-captured during
that week, it was given a value of 0. Although CAPTURE is able to estimate the density of a population, Larrucea
and colleagues (2007) used the program only to calculate abundances. They reported results from CAPTURE as
opposed to program MARK because similar studies on other species have been analyzed using CAPTURE,
allowing for better comparison. This estimate was the same for camera densities of 6 cameras per km2 and 8
cameras per km2.
One camera trial (1 camera per km2) was run for 9 weeks. Although the first 5 weeks of data were adequate for
the above estimates, the additional 4 weeks allowed the researchers to determine whether the density estimate
was improved by the longer data collection time. The effect of this was to increase the number of recaptures,
which in turn lowered the standard error of the density estimate.
Harvest Management
The high harvests in the late 1970s and early 1980s on Tejon Ranch were likely not sustainable. Based on the
modeling of Knick (1990), which recommended keeping harvest at less than 20%, the recent harvest of up to 20
bobcats per year is likely sustainable, assuming a population on Tejon Ranch of more than 200 bobcats (for a 10%
harvest rate) and good regional connectivity. If significantly increasing harvest (to more than 10%) is desired
Mountain Thinking recommends conducting a population estimate and ensuring that harvest is less than 20% of
the population. Furthermore, a spatial approach to harvest management is recommended, setting aside several
refugia or “no harvest” areas of 10–15 km2 on the Ranch.
Mountain Thinking recommends determining harvest rates for all species on areas surrounding Tejon Ranch.
This would allow the Conservancy to develop a regional meta-population map for each species and then develop
source and sink models for each species to ensure that the Ranch functions as a source for all populations rather
January 2013
than a sink (Ruth et al. 2011). These models should include estimates of all sources of mortality and estimates of
recruitment.
Furthermore, wildlife management objectives should be developed for harvest of species not used for food.
Harvest of carnivores is increasingly controversial, and sound justification should be developed to support it.
Carnivores play important ecological roles and, while harvest may not adversely affect populations, it can affect
important local ecological interactions (Henke and Bryant 1999, Roemer et al. 2009) that need to be considered
when the conservation goal may affect ecosystem function and health. One way to approach this issue is through
spatial harvest management. Tejon Ranch Conservancy could allow limited harvest in some regions and none in
others to reduce harvest impacts (via refugia, as recommended by Knick [1990]) and then test the ecological
impacts of such a strategy by comparing the ecological composition and functioning of harvested and
unharvested regions.
Rodenticides
Considering the high rate of mortality to bobcats and other carnivores caused by rodenticides, Mountain
Thinking recommends limiting or prohibiting their use in those areas away from human-occupied areas and
following the additional recommendations identified in the wildlife assessment for badgers.
REFERENCES
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Bailey, T. N. 1974. Social organization in a bobcat population. Journal of Wildlife Management 38:435–446.
Benson, J. F., M. J. Chamberlain, and B. D. Leopold. Land tenure and occupation of vacant home ranges by
bobcats (Lynx rufus). Journal of Mammalogy 85:983–988.
California Department of Fish and Wildlife. 2013. CWHR Life History Accounts and Range Maps‒Bobcat.
Database available at: http://www.dfg.ca.gov/biogeodata/cwhr/cawildlife.aspx. Available directly at:
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updated continuously).
Chamberlain, M. J., and B. D. Leopold. 1999. Survival and cause-specific mortality of adult bobcats in central
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Fedriani, J. M., T. K. Fuller, R. M. Sauvajot, and E. C. York. 2000. Competition and intraguild predation among
three sympatric carnivores. Oecologia 125:258–270.
Fuller, T. K., W. E. Berg, and D. W. Kuehn. 1985. Survival rates and mortality factors of adult bobcats in northcentral Minnesota. Journal of Wildlife Management 49:292-–96.
Fuller, T. K., and S. L. Berendzen. 1995. Survival and cause-specific mortality rates of adult bobcats (Lynx rufus).
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George, S. L., and K. R. Crooks. 2006. Recreation and large mammal activity in an urban nature reserve. Biological
Conservation 133:107–117.
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Karanth, K. U., J. D. Nichols, N. S. Kumar, and J. E. Hines. 2006. Assessing tiger population dynamics using
photographic capture-recapture sampling. Ecology 8711:2925–2937.
Kelly, M. J. 2008. Design, evaluate, refine: camera trap studies for elusive species. Animal Conservation 11:182–184.
Knick, S. T. 1990. Ecology of bobcats relative to exploitation and a prey decline in southeastern Idaho. Wildlife
Monographs 108.
Kohn, M., E. C. York, D. A. Kamradt, G. Haught, R. A. Sauvajot, and R. K. Wayne. 1999. Estimating population
size by genotyping faeces. Proceedings of the Royal Society of London 266:657–663.
Larrucea, E. S., G. Serra, M. Jaeger, and R. H. Barrett. 2007. Censusing bobcats using remote cameras. Western
North American Naturalist 67:538–548.
Lembeck, M. 1986. Long term behavior and population dynamics of an unharvested bobcat population in San
Diego County. Pages 305–310 in S. D. Miller and D. D. Everett (eds.), Cats of the World: biology, conservation, and
management. National Wildlife Federation, Washington, DC.
Litvaitis, J. A., J. T. Major, and J. A. Sherburne. 1987. Influence of season and human-induced mortality on spatial
organization of bobcats (Felis Rufus) in Maine. Journal of Mammalogy 68:100–106.
Long, R. A., T. M. Donovan, P. Mackay, W. J. Zielinski, and J. S. Buzas. 2007. Comparing scat detection dogs,
cameras, and hair snares for surveying carnivores. Journal of Wildlife Management 71:2018–2025.
Lovallo, M. J., and E. M. Anderson. 1996. Bobcat (Lynx rufus) home range size and habitat use in northwest
Wisconsin. American Midland Naturalist 135:241–252.
Miller, C. R., P. Joyce, and L. P. Waits. 2005. A new method for estimating the size of small populations from
genetic mark–recapture data. Molecular Ecology 14:1991–2005.
Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling,
and mark–recapture analysis. Journal of Wildlife Management 64:183–193.
Ordeñana, M. A., K. R. Crooks, E. E. Boydston, R. N. Fisher, L. Lyren, S. Siudyla, and D. H. Van Vuren. 2010.
Effects of urbanization on carnivore species distribution and richness. Journal of Mammalogy 91:1322–1331.
Riley, S. D. 2006. Spatial ecology of bobcats and gray foxes in urban and rural zones of a national park. Journal of
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urbanization and fragmentation on bobcats and coyotes in urban southern California. Conservation Biology
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Riley, S. P. D., J. P. Pollinger, R. K. Wayne, R. M. Sauvajot, E. C. York, and T. K. Fuller. 2006. A southern
California freeway is a physical and social barrier to gene flow in carnivores. Molecular Ecology 15:1733–1741.
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exposure and notoedric mange in bobcats and mountain lions in urban southern California. Journal of Wildlife
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mesocarnivore. Bioscience 59:165–173.
Ruell, E. W., S. P. D. Riley, M. R. Douglas, J. P. Pollinger, and K. R. Crooks. 2009. Estimating bobcat population
sizes and densities in a fragmented urban landscape using noninvasive capture–recapture sampling. Journal of
Mammalogy 90:129–135.
Ruth, T. K., M. A. Haroldson, K. M. Murphy, P. C. Buotte, M. Hornocker, and H. B. Quigley. 2011. Cougar survival
and source-sink structure on Greater Yellowstone’s Northern Range. Journal of Wildlife Management 75:1381–
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Soisalo, M. K., and S. M.C. Cavalcanti. 2006. Estimating the density of a jaguar population in the Brazilian
Pantanal using camera-traps and capture–recapture sampling in combination with GPS radio-telemetry.
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fragmentation and corridors in an urban environment. Biological Conservation 108:299–306.
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Vucetich, J. A., and T. A. Waite. 2000. Is one migrant per generation sufficient for the genetic management of
fluctuating populations? Animal Conservation 3: 261–266.
White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked animals.
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Woods, J. G., D. Paetkau, D. Lewis, B. N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of freeranging black and brown bears. Wildlife Society Bulletin 27:616–627.
January 2013
4. California Condor (Gymnogyps californianus )
The California condor has been a symbol of environmental
tragedy and triumph for more than 30 years (Snyder and
Snyder 2000). Today, the condor’s recovery is recognized
by the public as a success (Walters et al. 2010), with a
population of nearly 400 birds at the end of 2010,
approximately one-half of which are free-flying, although
environmental lead and micro-trash (bits of refuse and
litter attractive to condors) still appear to be significant
concerns.
If recovery is defined as establishment of a self-sustaining
population, however, the condor’s situation remains
unclear (Grantham 2007, Scott et al. 2010). As described
by Finklestein and colleagues (2012), intensive and
California condor (© J. Dodson 2010)
continuing management interventions are currently
required, including closely monitoring of all birds by radio
and/or global positioning system transmitters, regular provision of food, vaccination against West Nile virus,
removal of trash from around active condor habitat (e.g., nesting sites), and semiannual recapture of nearly every
bird for physical checkups and, if indicated by health status, extensive stays in captive facilities. Furthermore,
although the free-flying condor population within California has gone from 0 to almost 100 individuals over the
past two decades, this increase is largely because of the release of captive-raised birds. In California, there have
been 160 original releases, but only 24 chicks have fledged in the wild (Finklestein et al. 2012).
As defined in the Tehachapi Uplands Multiple Species Habitat Conservation Plan (TU MSHCP) (Dudek 2012),
the biological goals for the California condor are as follows:
1.
Enhancement of the conservation and recovery of the California condor in the wild by maintaining and
enforcing a permanent ban on all its lands of the use of lead ammunition in order to diminish lead
poisoning viewed as the principal obstacle to the species’ recovery.
2. Enhancement of the recovery of the California condor in the wild over the full range of geographic areas
used by the California condor prior to its removal from the wild by maintaining and promoting California
condor use of the Ranch, particularly through the preservation of foraging and traditional roosting
habitat within Covered Lands.
3. Enhancement of the recovery of the California condor in the wild by establishment and management by
USFWS of a new trap-and-release site in the Condor Study Area, as deemed appropriate by USFWS and
if needed to support recovery efforts for the species.
4. Enhancement of the recovery of the California condor in the wild through the maintenance of existing
practices that support the condor population on Tejon Ranch, such as grazing and hunting.
Studies conducted during the 1980s (Dudek 2012) showed that the last California condors remaining in the wild
before 1987 comprised a single population of birds occupying an area of approximately 2 million hectares
(4,942,000 acres). Insofar as could be determined, every California condor in the wild used the entire area and
was capable of soaring between any two points within the area in a single day. In addition to changes in climatic
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conditions, seasonal shifts that were noted seemed to be based generally on food availability. For example,
California condors tended to move to the Tehachapi Mountains area during the hunting season when deer gutpiles and abandoned deer carcasses were more abundant. Furthermore, during the calving season in the San
Emigdio area of the San Joaquin Valley foraging region, wild California condors were frequently observed feeding
on calf carcasses.
According to the TU MSHCP, most California condor foraging occurs in open terrain of foothill grassland and
oak savannah habitats and occasionally in open scrub habitat (Dudek 2012). California condor requires fairly
open spaces for feeding. This ensures easy take-off and approach and makes finding food easier. Foraging activity
within the Tejon Ranch is facilitated by the presence of open fields and low-density tree canopies that allow
condors to spot carcasses from the air or to land and access carcasses that may be under tree canopies. Condors
can more easily locate food sources under these conditions than in areas in which tree canopies are heavier and
open fields along ridgelines are less prevalent.
The California Condor Recovery Plan (USFWS 1996) states that the completion of an agreement with the Ranch
to maintain uses that benefit the condor, such as hunting, is a conservation goal for the species:
The Tejon Ranch was an important condor feeding area throughout the annual cycle, but especially in the
fall, when there is a high intensity of deer hunting on the ranch. A plan should be prepared with the consent
and participation of the affected landowner to maintain its value for condors.
Meretsky and Snyder (1992) indicated that the fall peak in condor use of the Tehachapi zone appeared, at least in
part, to be correlated with deer-hunting season, with many records of birds feeding on deer gut piles or cripplinglost deer (often in clear preference to the calf carcasses stocked at the feeding site).
The majority of breeding birds forage within 50–70 kilometers of their nesting areas, with core foraging areas
ranging from 2,500 to 2,800 square kilometers. This wide-ranging foraging pattern may be an important
adaptation to unpredictable food supplies (Meretsky and Snyder 1992).
Based on revised habitat modeling, USFWS has determined that the foothill grassland and oak savannahs of
Tejon Ranch provide the easiest access to food, protection from predators, and lowest risk of injury during
feeding. Based on reviews of extensive vegetation maps developed for the TU MSHCP and ground-truthing of
ranch vegetation community characteristics, USFWS determined the type and extent of habitat areas that are
conducive to successful foraging and feeding on the Ranch, given the presence of a consistent supply of carrion.
There are likely to be some areas within woodland vegetation communities where the understory vegetation
structure might allow condors to access a carcass. However, based on a field visit to look at the vegetation
structure of the habitat identified as “woodlands” (i.e., the broad category of vegetation types including greater
than 40% canopy cover), USFWS determined that “woodlands” were generally not open enough under the tree
canopy to allow condors access to any food sources that may occur there. Therefore, woodland, chaparral, and
most scrub vegetation types across the Ranch were not identified as suitable foraging habitat for California
condors.
While condors utilize various areas within the Ranch, the predominant use was historically noted to occur
within the Condor Study Area (CSA) where a historical roost site (Winters Ridge) occurs and in which much of
the hunting on the Ranch occurred and continues to occur. (Note: The CSA is equivalent to the 37,000-acre
TMV-A Dedicated Conservation Easement Area, as described in RWMP Volume 1.) However, beginning in early
to mid-2008, as described by Johnson and colleagues (2010), more captive-bred condors were being released into
the wild and condor use of other parts of the Ranch expanded, although the CSA continued to receive much of
the use by condors at that time. Johnson and colleagues (2010) reported that, based on GPS tags on condors, the
CSA was among the three land area units (along with Hopper and Bitter Creek) that received the highest
“average likelihood of occurrence” by condors in 2009 and had a higher average likelihood of occurrence than the
remainder of Tejon Ranch. The availability of feral pig carcasses because of increasing year-round pig hunting
January 2013
throughout the Ranch, as well as continued ranching and fall hunting for other game species, may also have
contributed to this increased use.
According to the TU MSHCP, no condors have attempted to nest within Tejon Ranch or anywhere within the
Tehachapi Mountains, likely due to the relative lack of suitable nesting habitat in this area (Dudek 2012). In
addition, no historical, traditional roost sites occur within the Tejon Mountain Village (TMV) Planning Area.
The only known traditional condor roost site is located on the northeast face of Winters Ridge, within the CSA.
Based on GPS tag data, Johnson and colleagues (2010) reported that 10 of 13 California condor home ranges
during 2008, and the home ranges of all 14 condors tracked in 2009, overlapped the CSA, TEJON, and TMV
management units. Johnson and colleagues (2010) indicated that, although nesting, foraging, and roosting habitat
in the Sierra Nevada have not yet been recolonized, the CSA, TEJON, and TMV management units provide the
only corridor (approximately 20 kilometers wide) that permits condor movement between the northeastern and
southern parts of the species’ historical range (Figure C4-1).
Historically, California condors traveled through these management units and the adjacent foothills and
mountains surrounding the San Joaquin Valley; reintroduced condors will most likely use this area to move
between the northeastern and southern parts of the range, given that a prior study reported that condors did not
typically fly directly across the San Joaquin Valley (Meretsky and Snyder 1992).
Source:
Johnson et al. 2010
Figure 4-1
Foraging Zone of California Condor on Tejon Ranch
January 2013
As scavengers, California condors must cope with a food supply that is spatially and temporally unpredictable,
and maintaining familiarity with food availability throughout the foraging range is likely adaptive (Meretsky and
Snyder 1992). California condors that travel widely throughout their range acquire greater information on food
availability than those that forage over a more limited area; in addition, wide-ranging condors also have the
opportunity to acquire greater information on predator and competitor (i.e., cougar, black bear, coyote, and
golden eagle) densities throughout the range (Meretsky and Snyder 1992). Incorporating prior information on
food, predator, and competitor densities into foraging behavior increases the probability of locating food,
decreases the amount of time required to locate food, and may reduce the probability of encountering both
predators and competitors, all of which can affect survival and reproduction (Meretsky and Snyder 1992).
POPULATION DYNAMICS
Diet
California condors are obligate scavengers, feeding only on the carcasses of dead animals, primarily medium- to
large-sized mammals. Typical foraging behavior includes long-distance reconnaissance flights, lengthy circling
flights over a carcass, and hours of waiting at a roost or on the ground near a carcass (Snyder and Snyder 2000,
Walters et al. 2010). Seasonal shifts in foraging behavior may result from changes in climatic conditions (e.g., fog,
thermal activity, wind intensities, rain) or in response to changes in food availability.
Chamberlain and colleagues (2005) examined isotope data from condors and found that their diet was a
combination of range livestock and wild ungulates, but a significant portion of their diet was provided by
humans in the form of stillborn calves of corn-) fed cattle. Approximately 45% of the diet of the condors that
were the source of the feathers analyzed had a corn-fed source. The dairy calves provided to the condors
constitute a substantial artificial support of the current population. It is unclear whether, if this source of food
were removed, the condors would rely more on wild prey. Wild prey carcasses would be more broadly dispersed
and thus would require more effort to locate (Chamberlain et al. 2005).
A free-flying California condor needs approximately 2.2 pounds of food per day based on caloric requirements
(Wilbur 1978). Assuming condors obtain a minimum of 50 pounds of food from the average ungulate carcass,
Wilbur (1978) calculated that a population of 50 condors would require 39,600 pounds of food or 720 carcasses
per year. Based on these calculations, an estimated 2,160 carcasses per year would be necessary to provide enough
food for a population of 150 condors (which would constitute one of the two such populations needed to meet
the down-listing criterion of the California Condor Recovery Plan [USFWS 1996]).
Based on average mortality, beef cattle in Kern, Los Angeles, San Luis Obispo, Santa Barbara, Tulare, Kings, and
Ventura counties would provide approximately 5,260 cattle carcasses within the range of the southern California
flock of condors (Dudek 2012). Sheep and lambs also historically provided an important food resource for
condors (Wilbur 1978). With the average mortality rate, 135,060 sheep and lambs in these three counties would
provide an estimated 6,212 sheep and lamb carcasses as potential food resources for California condor. Based on
this, it is estimated that 11,472 cattle and sheep carcasses would be produced within the current range of the
southern California subpopulation of condors, excluding Monterey and San Benito counties.
Certainly, not all carcasses that may be present within the southern California subpopulation’s current home
range are expected to be found and consumed by condors (Dudek 2012). Some carcasses may be disposed of by
landowners, consumed by other predators, or simply not discovered by condors. The variability in food
availability is consistent with the opportunistic scavenging and far-ranging foraging behavior characteristic of
condors (USFWS 1996, Wilbur 1978, Snyder and Snyder 2000). Nevertheless, when mortalities of cattle, sheep,
native ungulates, wild pigs, and other animals were combined, USFWS estimated that substantially more
carcasses per year would potentially be available within the range of the current southern California
subpopulation than would be needed (2,160 carcasses, as calculated above) to support 150 free-flying condors.
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Mortality
As of November 30, 2011, the world population of California condors was 391 individuals, including 182 in
captivity and 209 in the wild (USFWS 2011). The wild population includes 113 birds in central and southern
California (40 in the Tejon Ranch subpopulation); 23 birds in Baja California, Mexico; and 73 in Arizona.
Rideout and colleagues (2012) documented a total of 135 deaths from October 1992 (the first post-release death)
through December 2009, from a maximum population-at-risk of 352 birds, for a cumulative crude mortality rate
of 38%. A definitive cause of death was determined for 76 of the 98 cases, 70% of which (53 of 76 birds) were
attributed to anthropogenic causes. Micro-trash ingestion was the most important mortality factor in nestlings
(proportional mortality rate [PMR] 73%; 8/11), while lead toxicosis was the most important factor in juveniles
(PMR 26%; 13/50) and adults (PMR 67%; 10/15). The mortality factors thought to be important in the decline of
the historic California condor population, particularly lead poisoning, remain the most important documented
mortality factors today. Without effective mitigation, these factors can be expected to have the same effects on
the sustainability of the wild population as they have in the past. Other causes include power line collisions and
electrocutions, intentional killing, and West Nile virus infection.
Rideout and colleagues (2012) suggested that additional investigations will be required to determine annual
population-specific mortality rates and their projected impact on population sustainability. Modeling by
Meretsky and colleagues (2000) indicated that condor mortality must average less than 10% annually to achieve
stable or increasing populations.
Finklestein and colleagues (2012) indicated that condors in California remain chronically exposed to harmful
levels of lead; 30% of the annual blood samples collected from condors indicate levels of lead exposure that cause
significant subclinical health effects (blood levels of at least 200 nanograms per milliliter [ng/mL]). Furthermore,
each year, approximately 20% of free-flying birds have blood lead levels (at least 450 ng/mL) that indicate the
need for clinical intervention to avert morbidity and mortality (Finklestein et al. 2012). Lead isotopic analysis
shows that lead-based ammunition is the principal source of lead poisoning in condors. Finally, population
models based on condor demographic data show that the condor’s apparent recovery is solely attributable to
intensive ongoing management, with the only hope of achieving true recovery dependent on the elimination or
substantial reduction of lead poisoning rates.
Recently, regulatory efforts have been undertaken in California to mitigate the lead exposure hazard to California
condors through partial bans on lead ammunition use in condor habitat. In spring 2007, TRC announced a total
ban on the use of lead shot and bullets for hunting purposes on the Ranch, which took effect on January 1, 2008.
California subsequently enacted the Ridley-Tree Condor Conservation Act, which banned the use of lead
ammunition for hunting within the state range of the California condor effective July 1, 2008. Although these
regulations have been in place for only a few years, Finklestein and colleagues (2012) looked for evidence that
they had affected the prevalence of lead poisoning in California condors. They compared blood lead levels in birds
in 2006–2007 (before the ban) with levels in 2009–2010 (after the ban) and found no indication that blood lead
levels had declined, suggesting that, at least thus far, the regulations to help reduce lead exposure in condors have
resulted in lower blood lead levels.
When considering the need for long-lived birds to avoid lead poisoning for many years, the necessity for
extremely low carcass contamination rates is even clearer: If only 0.5% of carcasses are contaminated with lead,
the probability that, over 10 years, a condor will feed on a contaminated carcass is still 85–98%. Thus, very low
carcass contamination rates are required to avoid high probabilities of lead poisoning within the condor
population. The demographic model of Finklestein and colleagues (2012) clearly illustrates that, without reduced
lead poisoning, the California condor will require extraordinary management efforts in perpetuity to avoid again
declining to extinction in the wild. Additionally, their analyses show that, if the lead exposure hazard is removed
and lead deaths are halted or greatly reduced, California condors could once again achieve a sustainable wild
population.
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Assessing Role of Carcasses
White (2006) noted that the effect of food byproducts from harvesting on the ecology of scavenger species has
rarely been measured. Such nutritional subsidization of scavengers needs to be monitored because increases in
their populations may influence population dynamics of other species and alter natural community dynamics.
White (2006) quantified effects of the distribution of elk gut-piles generated by an intensive harvest program in
Jackson Hole, Wyoming, on common raven (Corvus corax) foraging behaviors, daily and seasonal movements, and
population distribution.
White (2006) located gut-piles during the fall elk harvest using daily harvest information relayed by local agency
biologists and hunters. White (2006) conducted fixed-width transect surveys along seven transect lines in
Jackson Hole’s harvest zone during the fall 2001 elk harvest to determine whether raven distribution coincided
with gut-pile distribution on any given day during the elk harvest. During Jackson Hole’s 2001 fall elk harvest,
the number of ravens detected during fixed-width transect surveys was positively correlated with concurrent,
sympatric gut-pile densities. Collectively, these findings suggest that the high concentration of elk gut-piles in
Jackson Hole is a significant supplemental food resource for ravens, and that wildlife harvesting in a terrestrial
environment is capable of influencing the foraging behaviors, movements, and population dynamics of scavenger
species.
Similarly, Wilmers and colleagues (2003) estimated carrion availability provided by predators and hunters and
consumption rates of scavengers. They reported that wolves provided 13,220 kilograms (kg) of carrion and
hunters provided (January to mid-February) 33,203 kg. They documented 12 scavenger species feeding at wolf
kills and four species feeding at hunter kills, and they estimated consumption rates.
The TU MSHCP covers many important research and management recommendations (Dudek 2012). This
assessment focuses on the role of wildlife on Tejon Ranch in providing forage for condors.
Although condors forage largely on ungulate carcasses generated by the hunting on Tejon Ranch and dead
livestock, the primary food items for condors on Tejon Ranch are unclear, as well as their abundance, seasonal
variations in availability, and how food availability influences on condor recovery. Mountain Thinking
recommends an investigation of condor use of carcasses on the Ranch to determine the source (cause of
mortality), amount of food available on the carcass, species, and abundance. GPS data and observations of
condors should allow some of this data to be gathered. Also recommended are systematic carcass surveys on the
ground to measure availability and use of carcasses (selection). The approaches of White (2006) and Wilmers
and colleagues (2003) are recommended. Placing GPS tags on condors greatly improves the efficiency of such an
analysis. They allow resource selection analysis (use v. availability of carcasses and which habitats the carcasses
occupy) and an estimation of the impact of carrion abundance on condor movements, productivity, and survival.
Such an approach also allows an estimation of the potential for Tejon Ranch to support more or fewer condors
and the relation of carrion abundance to condor recovery. While predators provide an abundant source of
carrion, those carcasses may be less available because of their location in denser woodlands; hunter-harvested
animals are likely more important to condors.
This assessment supports TU MSHCP biological goal 2 for the California condor, “promoting California condor
use of the Ranch.”
Because of the ecological damage caused by feral pigs, Mountain Thinking recommends a significant reduction in
their population (see the wildlife assessment on feral pigs in this appendix). As pigs are hypothesized to provide
a significant year-round source of carrion for condors on Tejon Ranch, assessing this current source and assessing
the impact of reducing the abundance of pigs are also recommended. Condors may readily switch to other carrion
on the Ranch. The increasing numbers of elk on Tejon Ranch may provide a potentially large new source of
carrion, and this possibility should also be assessed (as described above). Several studies have attempted to
estimate cougar kill rate, and estimates vary among studies from 15 to 53 ungulates per year. If Tejon Ranch
January 2013
supports 20 cougars, they would produce 300–1,060 carcasses per year. The percentage of these carcasses that
would occur in habitats that can be exploited by condors is unknown.
Mountain Thinking recommends monitoring samples of hunter-killed carcasses on Tejon Ranch for lead to
determine if lead levels are responding to the lead ban. Also recommended is use of Tejon Ranch as a
demonstration site for the effectiveness and value of non-lead ammunition to improve compliance and
effectiveness throughout the condor’s range.
REFERENCES
Chamberlain, C., J. Waldbauer, K. Fox-Dobbs, S. Newsome, P. Koch, D. Smiths, M. Church, S. Chamberlain, K.
Sorenson, and R. Risebrough. 2005. Pleistocene to recent dietary shifts in California condors. Proceedings of the
National Academy of Sciences of the United States of America 102:16707–16711.
Dudek. 2012. Tehachapi Upland Multiple Species Habitat Conservation Plan. Prepared for Tejon Ranchcorp. Draft,
January. Available at: http://www.fws.gov/ventura/endangered/habitat_conservation_planning/ hcp/docs/
draft/Tejon_Draft_MSHCP/.
Finkelstein, M. E., D. F. Doak, D. George, J. Burnett, J. Brandt, M. Church, J. Grantham, and D. R. Smith. 2012.
Lead poisoning and the deceptive recovery of the critically endangered California condor. PNAS 2012,
published ahead of print (June 25, 2012), doi:10.1073/pnas.1203141109.
Grantham, J. 2007. Reintroduction of California Condors into their historical range: the recovery program in
California. In A. Mee, L. S. Hall, and J. Grantham (eds.), California Condors in the 21st Century. Series in
Ornithology, No. 2. American Ornithologists Union, Washington, DC.
Johnson, M., J. Kern, and S. M. Haig. 2010. Analysis of California Condor (Gymnogyps californianus) Use of Six
Management Units Using Location Data from Global Positioning System Transmitters, Southern California, 2004–09—Initial
Report. Open-File Report 2010–1287. U.S. Geological Survey, Reston, VA.
Meretsky, V., N. Snyder, S. Beissinger, D. Clendenen, and J. Wiley. 2000. Demography of the California condor:
implications for reestablishment. Conservation Biology 14:957–967.
Meretsky, V. J., and N. Snyder. 1992. Range use and movements of California Condors. Condor 94:313–335.
Rideout, B. A., I. Stalls, R. Papendick, A. Pessier, B. Puschner, M. Finkelstein, and J. Grantham. 2012. Patterns of
mortality in free-ranging California condors (Gymnogyps californianus). Journal of Wildlife Diseases 48:95–112.
Scott, J. M., D. D. Goble, A. M. Hines, J. A. Wiens, and M. C. Neel 2010. Conservation-reliant species and the
future of conservation. Conservation Letters 3:91–97.
Snyder, N., and H. Snyder. 2000. The California Condor: A Saga of Natural History and Conservation. Academic Press, San
Diego, CA. 410 pp.
USFWS. See U.S. Fish and Wildlife Service.
U.S. Fish and Wildlife Service. 1996. California Condor Recovery Plan, third revision. Portland, OR.
U.S. Fish and Wildlife Service. 2011. Hopper Mountain National Wildlife Refuge Complex, California Condor
Recovery Program. Available at: http://www.fws.gov/hoppermountain/CACORecoveryProgram/
CACondorRecoveryProgram.html.
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Walters J. R. 2010 Status of the California condor (Gymnogyps californianus) and efforts to achieve its recovery. Auk
127:969–1001.
White, C. 2006. Indirect effects of elk harvesting on ravens in Jackson Hole, Wyoming. Journal of Wildlife
Wilbur, S. R. 1978. Supplemental Feeding of California Condors. Pages 135–140 in S. A. Temple (ed.), Endangered
Birds: Management Techniques for Preserving Threatened Species. University of Wisconsin Press, Madison, WI.
Wilmers, C. C., D. R. Stahler, R. Crabtree, D. W. Smith, and W. M. Getz. 2003. Resource dispersion and
consumer dominance: scavenging at wolf- and hunter-killed carcasses in Greater Yellowstone, USA. Ecology
Letters 6:996–1003.
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5. Cougar (Puma concolor)
Cougars presently occupy almost all of their historic range
in western North America. The cougar’s solitary nature,
use of remote and rugged landscapes, relatively uncommon
predation of livestock, and relatively high reproductive
rate helped the species escape the regional extinctions that
befell other large carnivores. The recovery of cougars in the
West occurred in the equivalent of only three cougar
lifetimes (Logan and Sweanor 2001).
In 1990, California voters approved a ballot measure that
prohibited sport hunting of cougars and required public
agencies to spend $30 million per year on a habitat
conservation fund, principally for the acquisition of
habitat for cougars, deer, and rare, endangered, and
threatened species.
Cougars (USFWS 2008)
Based on habitat density extrapolations, the California
Department of Fish and Wildlife (CDFW) estimates that there are 4,000–6,000 cougars in the state, and that the
population is stable (CDFW 2013). Trend data indicate that cougar activities, such as depredation, attacks on
people, and predation on prey populations, peaked in 1996, then decreased somewhat, and have remained stable
for the past several years.
Hopkins (1989) reported that the average size of the cougar’s annual home range varied from 61 square kilometers
(km2) to 117 km2 for females and from 135 km2 to 285 km2 for adult males. No seasonal shifts in home range use
were noted, and cougars exhibited only small differences in their annual home ranges. Female home ranges had a
weaker harmonic mean center than males, indicating that they used their smaller home ranges more intensively.
No home range overlap was seen between adjacent males with concurrent locations. The home ranges of four
females were 13-95% exclusive. However, the two females with the greatest amount of overlap shared less than
10% of their core area.
Steep mountain slopes or abundant cover provided by vegetation and topography are important habitat
components for cougars (Seidensticker et al. 1973, Logan and Irwin 1985, Logan et al. 1986, Van Dyke et al. 1986).
Cover improves success in ambush hunting and provides protection from bear and wolves (Kunkel et al. 1999,
Kunkel et al. 2012). Cougar dens are usually located in rock outcrops, in dense shrub fields, or under downed
conifers (Murphy et al. 1999). Travel corridors used by cougars in southern California were typically drainage
washes or ridges with abundant native woody vegetation that provided security from human disturbance (Beier
1995).
Dickson and Beier (2002) found that at two scales of selection and across seasons, cougars in the Santa Ana
Mountains of southern California preferred riparian habitats and avoided human-dominated habitats. Grasslands
were the most avoided natural vegetation type at both scales of selection. Although cougar home ranges tended
to be located away from high- and low-speed two-lane paved roads (second-order avoidance), cougars did not
avoid roads within their home range, especially when roads were in preferred riparian areas. Protection of habitat
mosaics that include roadless riparian areas is critical to the conservation of the cougar population in the Santa
Anas.
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Kunkel et al. (2012) found that cougar-killed prey were more often distributed in areas with greater structural
and topographical complexity than were wolf-killed prey. For example, cougar-killed prey were more likely to be
found in areas characterized by greater ruggedness, and less likely to be found in areas characterized by
structurally simple cover types such as grassland and pasture. Landscape physiography can influence the spatial
patterns of where wolves and cougars encounter and kill their prey (e.g., Kunkel et al. 1999, Atwood et al. 2007).
For example, for wolves, structurally simple cover types may facilitate prey detection and cursorial hunting
behavior, whereas rugged, structurally complex habitats may better enable the ambush hunting behavior of
cougars.
POPULATION DYNAMICS
Density
Cougar populations were thought to be regulated through socially controlled land tenure (Seidensticker et al.
1973). More recent research from California, however, indicates that cougars, like other carnivores, were limited
in abundance primarily by the supply of food rather than by land tenure (Pierce et al. 2000). Density of cougars
ranges from 5.8 to 47 cougars per 1,000 km2.
Based on telemetry of 24 cougars from 1984 through 1989, Hopkins (1989) estimated a population density of 1.2–
2.3 resident adults per 100 km2 in a 600-km2 study area in the Diablo Range of California. The study area
comprised public and private lands about 20 km east of San Jose. Elevations vary from 300 to 1,100 m, with the
majority of the land mass above 600 m. The study area is a mosaic of chaparral, oak woodland, north slope
woodland, oak-bigberry manzanita woodland, annual grassland, and oak savanna communities. Assuming that
all habitat on Tejon Ranch is suitable and using a similar population density to that in the Diablo Range, Tejon
Ranch would support 12–23 cougars.
Reproduction
Hopkins (1989) reported that 30 cougars less than 18 months of age in 19 separate litters indicated a mean litter
size of 1.6 cubs per litter. This was a conservative estimate because, in many cases, siblings may have gone
undetected. The maximum litter size was 3, but no cubs under 3 months of age were observed. Only one litter out
of seven was known to have more than one cub survive to the yearling class. The mean litter size for this study
was lower than reported for harvested populations. Fourteen cougars in this area were seasonal breeders with
small peaks in late winter and early fall. Birth intervals for two adult females varied between 20–24 and 30–34
months. Subadult males were about 21 months of age at dispersal and moved 29–58 km from their natal range.
Diet
Hopkins (1989) found 45 kills and collected 131 scats from 1983to 1989 to assess cougar diet. Deer remains made
up 82% (37 deer: 13 bucks, 17 does, 7 fawns) of the kills and 74% of the scats. Wild pig (Sus scrofa) were found in
only 5% of the 1983–1985 scat samples but occurred in 20% of the 1986–1989 samples. Pigs, however, made up
only 2% of the kill record. A higher frequency of pigs was noted in the scats during the wet season (38%) than in
the dry season (11%). A linear preference index indicated that cougars preferred bucks and avoided does. The
high incidence of pigs in the scats was consistent with the results of an earlier study (1978–1980). Pig populations
were known to fluctuate in the area, and the density of pigs may have influenced their use by cougars. Livestock
were found in less than 7% of scats in all three studies (1978–1980, 1983–1985, 1986–1989), and only 20
depredation incidents were reported from 1971 through 1989 in the study area. A deer: cougar ratio of 210–350:1
was calculated for this area. This relatively high ratio and the preference of cougars for a more reproductively
expendable segment of the deer population (i.e., bucks rather than does) suggests that cougars did not exhibit a
strong limiting force on the deer herd in the Diablo Range during the study period.
The minimum number of mule deer occupying Round Valley, California, east of the Sierra Nevada during winter
declined by 84%, from 5,978 in 1985 to 939 in 1991; annual surveys indicated that the population remained
between 900 and 1,400 during 1991–1995 (Villepique et al. 2011). Decreases in an index to abundance of cougars
lagged behind declines in populations of mule deer, with a reduction of approximately 50% during 1992–1996
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(Pierce et al. 2000). Even with this large decline in deer and a bighorn sheep population nearby, deer continued to
constitute 79% of the cougars’ diet.
Mortality
Quigley and Hornocker (2010:65) noted, ‘‘Two important extremes are evident in mortality factors for cougar
populations, one human caused and one driven by internal strife (supplemented by other factors, such as disease
and old age).’’ Few studies have been conducted on cougars in regions without harvest. Of three studies
conducted where no harvest occurred (at least during the study period) and in the largest sample to date, Logan
and Sweanor (2001) in New Mexico monitored 9–20 males and 7–24 females per year for 8 years to arrive at mean
survival rates of 0.91 and 0.82 for males and females, respectively. These rates compare to lower survival rates
from a series of studies with smaller sample sizes: a pooled male-female adult survival rate of 0.75 in California in
an area with a much higher density of humans (Beier and Barrett 1993).
Logan and Sweanor (2001) reported that 50 percent of radio-collared cougars died from interactions with other
cougars; the second and third most common causes of death for adults in this population were disease (i.e.,
plague and unidentified pathogens) and accidents (i.e., females injured during prey capture attempts). Beier and
Barrett (1993) determined that, in urbanized southern California, vehicle accidents caused more than half of adult
deaths, followed by disease, interspecific strife, and killing by wildlife authorities due to depredation by cougars.
In Florida (Lotz et al. 2005), this pattern also applied to Florida panthers, with intraspecific aggression, vehicle
accidents, and disease/infections being the top three causes of death.
Legal harvest is usually the greatest source of mortality for cougars (Logan et al. 1986, Anderson et al. 1992, Ross
and Jalkotzy 1992). In unhunted cougar populations or where cougar depredation of livestock is substantial,
control actions may be the greatest source of human-caused mortality (Cunningham et al. 1995). The strong
dispersal capability of cougars, leading to high immigration rates, may help ameliorate the effects of mortality
where cougar habitat is contiguous and exceeds 2,200 km2 (Beier 1993) and where travel corridors allow free
exchange of dispersers among subpopulations (Lindzey et al. 1992, Logan et al. 1996, Murphy et al. 1999).
Research and management, especially population data for cougars, are often inadequate for managing harvests;
thus, harvest or any source of human-caused mortality should be limited. Harvest of male cougars should not
exceed 8%, and hunting of females should be restricted (Logan et al. 1996).
Hopkins (1989) conducted work where no harvest of cougars occurred and reported that 11 radio-tagged and two
untagged cougars (five males, eight females) died of natural causes between March 1987 and April 1989. The mean
age at death for these cougars was 79 and 60 months for males and females, respectively. The mean age at death,
excluding cougars less than 24 months of age, was 79 and 90 months for males and females, respectively. The
average age of this unexploited population was much higher than reported for cougars in moderately to heavily
hunted areas.
Ruth and colleagues (2011) studied cougars in a partly protected ecosystem including northern Yellowstone
National Park. They found that females survived better than males. Survival increased as females and males aged
but then rapidly declined at older ages (more than 10 years for females and 8 years for males). Kitten survival
increased with age, was lower during winter, increased with increasing minimum estimates of elk calf biomass,
and increased with increasing density of adult male cougars. Estimates of annual kitten survival were 0.59,
similar to a study in New Mexico (0.59–0.66, Logan and Sweanor 2001). Ruth and colleagues (2011) found that to
generate an increasing population, adult female survival needed to be greater than 93%.
Riley and colleagues (2007) reported two cougars dying of anticoagulant toxicity (from rodenticide after
consuming coyotes poisoned). Coyotes made up 15% and 7% of the kills for these two radio-collared cougars but
only 4% of kills overall. Anticoagulant toxicity was previously documented as a leading cause of death for coyotes
in this area, and if coyotes are retaining anticoagulants, a cougar eating a coyote could ingest a large quantity of
toxicant at once (see the badger assessment for recommendations on rodenticides). Both cougars consumed
coyotes during the last month before they died.
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Spatial Structure and Dynamics
According to Hopkins (1989), cougars exhibited weak activity peaks at 0500–1000 hours and 1600–2100 hours,
with no difference between males and females. This pattern was similar to that of a black-tailed deer (Odocoileus
hemionus columbianus) in the area.
The mean age in the Diablo Range study (Hopkins 1989) at time of capture for cougars more than 24 months of
age was 69 months for 4 males and 67 months for 11 females. Three males and seven females survived to at least 7
years of age during the study. One female was at least 13 years old. The sex ratio for all adult cats (6 males, 11
females) sexed during the study did not differ from parity. In this small sample of 17 cougars, the ratio is nearly
2:1, but it may not be representative of the population.
The unexploited population of cougars in the Diablo Range consists of a relatively stable population of old
individuals with a low turnover of residents. The relatively low productivity, low juvenile survival, and older
dispersers are typical of an unharvested population. Because cougars are harvested almost everywhere, little is
known about the long-term population and social structure of “natural” cougar populations.
Impact on Prey
A fundamental component of cougar–ungulate interactions is the number of ungulates cougars kill annually;
several studies have attempted to estimate cougar kill rates, but estimates vary among studies by 350% within
cougar age–sex classes (e.g., 15 v. 53 ungulates per year for adult females; Knopff et al. 2009). The rate in the only
California study was 0.93 mule deer per week (Beier et al. 1995). Cougar kill rates (not accounting for the
influence of season or demography) averaged 0.8 ungulates per week or 8.28 kg/day, but kill rates were variable
among individuals (0.24–1.38 ungulates per week and 2.88–18.60 kg/day).
Hernández and colleagues (2006) modeled the impact of cougar predation on the decline and recovery of mule
deer in southern Idaho based on estimates of cougar numbers, predation rates of cougar, and reproductive
variables of deer. Deer populations peaked in 1992–1993, then declined more than 55% and remained low for the
next 11 years. Cougar numbers peaked 4–6 years after deer populations peaked but then declined to original
levels. Estimated cougar predation rates on the deer population before and after the decline were 2.2–3.3% and
3.1–5.8%, respectively. At high cougar densities (more than three cougars per 100 km2), predation by cougars
delayed deer recovery by 2–3 years. The percentage of winter mortality of fawns and adult female deer correlated
positively with December–January snowfall. Incorporation of winter snowfall amounts into the model produced
a pattern of deer population change matching estimated changes based on field survey data. The researchers
concluded that cougars probably were a minor factor in the decline of the deer population in the study area and
did not suppress deer recovery, and that winter snowfall was the primary, ultimate, and proximate factor in the
deer decline and in suppression of their recovery.
In one of the most comprehensive and best designed studies to date, Hurley and colleagues (2011) provided little
evidence that predator removal in southeastern Idaho changed the overall population status of mule deer,
especially with regard to coyote removal. Although mountain lion removal increased mule deer survival and fawn
ratios, the researchers were unable to demonstrate significant changes in population trend with mountain lion
removal. They concluded that benefits of predator removal appear to be marginal and short term in southeastern
Idaho and likely will not appreciably change long-term dynamics of mule deer populations in the intermountain
west. Amount and timing of precipitation, likely related to plant phenology and winter energy expenditure, had a
greater influence on population vital rates. Predation is a significant limiting factor of mule deer populations;
however, the effect on rate of increase is unpredictable because of yearly variations in climate-linked habitat
carrying capacity and populations of alternate prey. These changes in carrying capacity or increases in deer
numbers will ultimately dictate the role of predation in mule deer population dynamics. The limited effects of
predator removal from this study and the pervasive effects of enhanced nutrition from Bishop and colleagues
(2009) led them to conclude that enhanced nutrition will increase mule deer populations more effectively and
predictably than predator removal. The challenge now is to determine cost-effective methods of enhancing the
quality of naturally occurring forage in mule deer range in areas where increasing mule deer populations is an
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important goal. Research to answer this question for winter range is currently underway in Colorado, but
research documenting the effects of enhanced nutrition on summer range is needed.
Hurley and colleagues (2011) summarized their findings on mule deer populations with regard to cougar removal
as follows:
▪
Winter fawn survival increased.
▪
Adult female mule deer survival increased, up to 5.5% annually at maximum removal rates.
▪
Fawn-to-adult female ratios increased; they predicted a 6% increase at average removal and up to 27% at
maximum removal.
▪
A minimal, positive effect was noted on mule deer population growth rates.
ROLE IN THE E COSYSTEM
By preying on ungulates, cougars are important top-down ecosystem regulators (Terborgh et al. 1999). As human
visitation of Yosemite National Park increased in the early 1900s and cougars became increasingly scarce, the
mule deer population irrupted in the 1920s (Ripple and Beschta 2008). Significantly diminished oak recruitment
has occurred since the 1920s in stands accessible to deer, but continuous recruitment of oaks was found in cougar
refugia sites. Less oak recruitment was found in areas of high human activity near the park’s visitor center,
possibly due to behaviorally mediated effects of lower cougar and higher deer densities. Ripple and Beschta
(2006) reported that increased numbers of human visitors in Zion Canyon, Utah, apparently reduced cougar
densities there relative to other parts of Zion National Park. This change led to higher mule deer densities and
higher browsing intensities, which in turn reduced recruitment of riparian cottonwood trees (Populus fremontii),
increased bank erosion, and diminished abundance of terrestrial and aquatic species. Ripple and Beschta (2008)
found their results consistent with trophic cascade theory involving large predators, herbivores, and plants.
CONNECTIVITY
Ernest and colleagues (2003) found that the Tehachapi Mountains are the only likely corridor for movement of
cougars among the western Sierra Nevada, Central Coast, and southwest regions of California. The only likely
movement corridor between the Tehachapi Mountains and the southwest region is the Transverse Ranges (San
Gabriel and San Bernardino mountains).
Morrison and Boyce (2009) provided a warning about vigilance and action for conservation and connectivity.
Long ago, when land-conservation options were far less constrained, Beier (1993) foretold that continuance of the
status quo would lead to a loss of cougars. If cougars are lost in the Santa Ana Mountains, the loss will not be
attributable to a lack of science, or to a failure of science to enter the public arena (Beier 1996). Rather, it will be
because the conservation community at large failed to recognize how demanding the protection of connectivity
would be, and failed to mobilize accordingly.
In areas of low human population density, such as southern New Mexico and Montana, cougars are able to
disperse across large expanses; females averaged 13.1 km2 and males 116.1 km2 in New Mexico (Montana Fish,
Wildlife, and Parks 1996, Sweanor et al. 2000). In areas of high human density, such as southern California,
dispersal success has been poor, and subpopulations have become isolated with little chance of rescue (Beier
1993, 1995). Even so, cougars were able to use low-quality corridors for dispersal in these areas (Beier 1995). In
areas of extremely fragmented habitat and high human density, corridors should be created along natural travel
routes that contain ample woody cover. These routes should include underpasses with roadside fencing, areas
that lack artificial lighting, and less than 1 dwelling unit per 16 hectares (Beier 1995).
These area sizes are comparable to estimates reached by Shaffer (1983) for brown bears. From his modeling, Beier
(1993) concluded that natural catastrophes of moderate severity do not appear important to cougar persistence,
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similar to conclusions reached by Shaffer (1983) for brown bears. These models should be interpreted with
caution, however, as analytic models and simulation models incorporating density independence produced much
larger minimum areas necessary for cougars.
Cougar-Human Conflicts
Direct conflict between human and cougars is extremely rare. Since 1890 in California, only 16 people have been
killed by cougars. Conflict rates have not increased since protection and increase of the cougar population began
in California.
Depredation
The Cougar Management Guidelines Working Group (2005) found no scientific evidence to support the role of
hunting cougars in benefitting wild ungulate populations or in reducing livestock depredation. Recent research
also fails to support such a management approach (Hurley et al. 2011, Griffin et al. 2011).
In northwestern North America, rates of cougar predation on livestock are generally low. In Montana from 1984
to 1993, only 8.2 predation incidents occurred annually (Montana Fish, Wildlife, and Parks 1996). Claims for
compensation in Alberta for cougar kills averaged 4.4 per year from 1974 to1987. For every cougar claim, there
were five wolf, 13 bear, and 42 coyote claims over a similar period (Pall et al. 1988). Selective removal of offending
individuals is usually a more effective response than other management actions, especially translocation (Ruth et
al. 1998). The complete elimination of cougars from problem regions in New Mexico has been attempted three
times‒twice to protect domestic sheep and once for wild sheep. None of these efforts resulted in a reduction in
predation (Evans 1983). Wildlife officials in Wyoming, Colorado, and Alberta pay compensation to farmers for
confirmed livestock losses to cougars.
In Kern County, California, the mean number of cougars killed for depredations has been two per year with an
average of four permits issued. While depredations have taken place on Tejon Ranch, good records have not been
kept on the number of these or the number of cougars removed.
Choate and colleagues (2006) concluded that, despite extensive research, there remains no single reliable and
cost-effective technique for estimating cougar abundance. They found that track estimators performed poorly as
individual indices of population size; however, proportional changes over time were closely related to similar
proportional changes in indices. No single method, other than costly capture and radio-telemetry study, provides
a solution to the problem of enumerating cougar populations. They suggested that conservative application of
indices derived from multiple techniques will provide the most confidence in short-term management decisions;
however, better estimates require an initial population estimation period employing marking techniques to
establish a baseline for comparison in subsequent years. Despite the allure of lower cost index measures, the lack
of sensitivity to population changes by indices, particularly over time scales involved in management decisions
(e.g., annual harvests), warrants considerable caution in their application. Where surveys of any form are not
possible, alternative approaches may be used to assist in reducing uncertainty in management decisions. A largescale option has been proposed that recognizes the interconnected but patchy distribution of cougar
populations: a metapopulation approach (Laundre´ and Clark 2003, Stoner et al. 2006) and zone management
(Logan and Sweanor 2001, CMGWG 2005). A metapopulation approach considers the spatial arrangement and
connectivity of subpopulations to allow for several to serve as sources or refuges relative to more heavily hunted
sinks.
Kelly and colleagues (2008) assessed the reliability of photo-trapping for individual cougar identification using
double-blind observer identifications. Capture histories based on those identifications and use of capture–
recapture models allowed estimation of cougar abundance across study sites according to different researchers
(Kelly et al. 2008).
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Negrões and colleagues (2010) used remotely triggered cameras to collect data on cougar abundance and
occupancy in an area of tropical forest in Brazil. To evaluate factors influencing cougar occupancy, they used data
from five sampling campaigns in three consecutive years (2005–2007) and two seasons (wet and dry), at a state
park and a private forest reserve. They estimated cougar numbers and density for the 2007 sampling data by
developing a standardized individual identification method. They based individual identification on (1) timestable parameters (SP; physical features that do not change over time) and (2) time-variable parameters (VP;
marks that could change over time, such as scars and botfly marks). Following individual identification, they
established a capture–recapture history and analyzed it using closed population capture–mark–recapture
models. Cougar capture probability was influenced by camera placement (roads v. trails), sampling year, and prey
richness. Cougar occupancy was positively associated with species richness. Identifications enabled the
researchers to generate eight VP histories for each photographed flank, corresponding to eight individuals. They
estimated the sampled population at nine cougars, translating to a density of 3.40 cougars per 100 km2.
Balme and colleagues (2009) compared track counts and cameras against a known population of leopards, and
results demonstrated that, if applied correctly, camera-trap surveys represent the best balance of rigor and costeffectiveness for estimating abundance and density of cryptic carnivore species that can be identified
individually. Although track counts are less expensive to conduct than camera-trap surveys and easier to
implement across a large area, accuracy levels are poor. Track counts may be satisfactory when the objective is
simply to gauge trends in abundance over time. In their study, track counts yielded more precise results with a
similar amount of effort and fewer costs. Even so, caution should be exercised when using relative abundance
indices to make comparisons over space and time, and they recommended calibrating the index with more than
one other independent abundance estimate.
Since about 1980, conservation planning has increasingly emphasized efficiency‒that is, how to achieve
ambitious goals with limited financial resources, limited political will, and incomplete knowledge of how
biodiversity is distributed (Beir 2010, Kunkel et al. 2012). Beier (2010) comments that these changes in
conservation planning are best thought of as evolution rather than revolution. The past emphasis on large,
charismatic mammals still has a role to play. In particular, the need for efficiency bestows priority on species that
can attract dollars and political will, and on well-understood species needing such extensive habitat that
conserving them provides benefits for a spectrum of other species. Thus, conserving biodiversity and the cougar
fits the bill.
In continuation, Beier (2010) recommended that cougars should never be the sole focal species for a reserve
design or a corridor design; in other words, it is not a good “umbrella” species. Although cougars may need more
habitat than other species, cores based on cougars do not cover endemic species or communities particularly well
(Thorne et al. 2006). The cougar may be the first species to feel the impact of the loss of connectivity, but many
other species need linkages to maintain genetic diversity and metapopulation stability. Furthermore, as habitat
generalists, cougars can move through marginal and degraded habitats, and a corridor designed for them may not
serve many habitat specialists with limited mobility (Beier 2010). Indeed, successful implementation of a singlespecies “cougar corridor” could have a negative umbrella effect if land use planners and conservation investors
become less receptive to subsequent proposals to provide additional corridors for less charismatic species.
The cougar best serves biodiversity if it is one of many focal species used to design a network. For instance, before
developing linkage designs for 15 key wildlife corridors in southern California, Beier and colleagues (2006)
invited agency and academic biologists familiar with each corridor planning area to identify species that would
be a useful umbrella for other species sharing particular traits. Examples would be species that required intercore
dispersal for metapopulation persistence, had short or habitat-restricted dispersal movements, represented an
important ecological process (e.g., predation, pollination, fire regime), needed connectivity to avoid genetic
divergence of a now-continuous population, might change from being ecologically important to ecologically
trivial if connectivity were lost, or were reluctant to traverse barriers (e.g., culverts under roads). Each of the
resulting linkage designs had 10–20 focal species, often including reptiles, fish, amphibians, plants, and
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invertebrates. By serving as an excellent flagship for this suite of umbrella species and the most appropriate focal
species for specifying some attributes of corridors and cores, cougars will play their best role in reserve design.
Beier and colleagues (2006) also provided recommendations about quality and size of cores and corridors for
cougars, and these recommendations should be used to develop a formal habitat model that drives reserve design,
not as rules of thumb that planners can use to delineate cores and corridors in an informal way. Less formal
mapping is subjective and may not identify the best cores or corridors, especially when the needs of many species
must be considered. At worst, such seat-of-the-pants maps can be abused to rationalize a bad plan and avoid
hard decisions to conserve the best habitats. Instead, the Conservancy advocates a rigorous and transparent
approach (Beier et al. 2008) that enables all stakeholders to evaluate how well a proposed corridor or reserve
design serves each focal species.
Recommendations for Reserve Design
Beier (2010) summarized various reserve design recommendations. Where highways cross a core, large crossing
structures such as bridges, viaducts, or overpasses should be located no less than 1.5 km (0.94 mile) apart
(Clevenger and Waltho 2006). Density of small paved roads should be less than 2 km per km2. Some, but not
necessarily all, core areas in a network should be managed as strategically located refugia, where mortality of
cougars would be limited to natural causes (Logan and Sweanor 2001). Each refugium should contain at least
3,000 km2 of high-quality cougar habitat so that it can provide a source population in the network and provide
dispersers to restock adjacent populations depleted by hunting.
Beier (2010) further recommended that habitat corridors for cougars should have nearly continuous woody cover,
underpasses integrated with 3-m roadside fencing at crossings of high-speed roads, little or no artificial night
lighting, and less than one human dwelling per 16 hectares (Beier 1995). Beier (1995) suggested that gaps in
woody cover should not exceed 400 m. The approach to a road-crossing structure should give the animal a clear
view of the landscape on the other side of the road. Dirt roads or trails probably do not impede cougar movement
and could help to guide cougars through a corridor (Beier 1995, Dickson et al. 2005). In xeric landscapes, riparian
corridors and gentle terrain are favored movement routes (Dickson et al. 2005). Unrestrained pets should be
prohibited from corridors to prevent depredation and subsequent demands to remove the offending cougar.
Minimum width should be at least 400 m for corridors up to 7 km long (Beier 1995). Small patches of suitable
habitat along a linkage can provide enough space for a breeding female, transient sub-adult, or disperser, and thus
can enhance connectivity between larger patches, even if the small patch is not continuously occupied (Beier
1996).
T EJON R ANCH RESEARCH AND CONSERVATION RECOMMENDATIONS
Cougar–Human Conflicts
If housing development proceeds on Tejon Ranch, a significant need will arise for educating residents on living in
cougar country. Several states have developed good educational materials to follow, including California.
Mountain Thinking recommends also following the Cougar Management Guidelines (CMGWG 2005). If
conflicts develop, the Cougar Management Guidelines provides a good management protocol.
Depredation Management
As indicated in the Cougar Management Guidelines (CMGWG 2005), no research or assessment of livestock
husbandry for reducing conflicts with cougars has been completed. Mountain Thinking recommends
implementing and researching a program to promote livestock husbandry practices that will reduce risk of
depredations from large carnivores (Woodroffe et al. 2007, Beier 2010).
Killing carnivores is increasingly controversial and fraught with ethical issues that need to be understood (Hecht
and Nickerson 1999). Additionally, cougar populations are sensitive to low levels of harvest (less than 8% for
males and lower for females, or possibly as few as two cougars on Tejon Ranch). Mountain Thinking
recommends that the Conservancy develop a management policy for livestock depredations that would be
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reviewed by independent biologists for scientific rigor and objectivity. Such a policy would define monitoring of
livestock and predators and identify ways to measure and respond to depredations, including the use of nonlethal
approaches before any lethal approaches are used. TRC should be restricted to authorizing any removal only
following the use of nonlethal methods. Similar to recommendations for coyotes elsewhere in this wildlife
assessment, nonlethal cougar management techniques should be developed and tested following the
recommendations of Mitchell and colleagues (2004) and Knowlton and colleagues (1999). Tejon Ranch could be
a state-of-the-art demonstration site for such projects. Mountain Thinking has been developing a similar project
for large carnivores and livestock in the southwest United States and in Alberta. Defenders of Wildlife and the
Mountain Lion Foundation have also developed recommendations for similar programs.
Mountain Thinking recommends requiring TRC to keep a record of all animals killed by cougars and other
predators. Killed livestock need to be investigated by a professional biologist to determine cause of death. Data
on circumstances leading to the incident should also be collected, including site and animal characteristics.
The conventional wisdom on large carnivore management advocates that predators must be held in check to
reduce conflicts with humans. On the contrary, with no harvest of cougars on Tejon Ranch or in California for
more than 20 years, depredations and conflicts have not increased and remain low. There is a great need for
research to understand the possible mechanisms of cougar population dynamics and social structure (Quigley
and Hornocker 2010). This information has important implications for carnivore conservation and management
worldwide.
While Mountain Thinking recommends following CDFW depredation reporting guidelines, more work is
needed onsite to reduce conflict, even after a depredation has occurred. Increased vigilance is recommended near
the site where the depredation occurred, and cattle may need to be moved if the offending cougar remains in the
region. The animal should be captured and radio-collared instead of being killed to assess area use, and the
situation should be managed in relation to the resulting information, including a determination of whether the
cougar remains a threat or the depredation was a one-time incident. Removing cougars with established
territories creates openings for younger cougars to move in, and these immigrating animals can be more
problematic.
The most proactive approach is recommended, especially given the recent Tejon Ranch history on cougar
management. The management bar should be set as high as possible. California does not currently have a cougar
management plan, and work on Tejon Ranch could serve as the basis for developing one.
Almost no work has been done to assess the ecology of cougar populations protected over the long term. Because
cougars are harvested almost everywhere, little is known about the long-term population and social structure of
“natural” populations of cougars. Such an understanding is important for assessing the impacts of harvest. Such
populations also likely have very different impacts on prey and possibly on livestock. Understanding these
impacts will be important for prey and harvest management of prey in these populations. Other than relatively
small national parks, California is the only place where the present populations of cougars have been protected
for a long period.
Beier (1993) suggested that a habitat area of 1,000–2,200 km2 is needed to support a cougar population without
immigration (15–20 cougars) in southern California with greater than 98% probability of persistence for 100
years. With immigration of one female and three males per decade, areas of 600–1,600 km2 are needed. Such areas
are minimum sizes and do not ensure long-term persistence (i.e., centuries of survival). Thus, Tejon Ranch is at
the marginal size for population viability, and management cooperation within the region is needed to ensure
viability. Mountain Thinking recommends working with neighbors to estimate mortality rates and improve
livestock management to reduce depredations.
There is a great opportunity to develop a Tejon Ranch brand of “conservation beef,” where best management
practices are followed for wildlife and predator management, creating an added value to the beef in the market.
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As discussed in the wildlife assessment on feral pigs, the impact of cougar predation on pigs should be tested
before managers continue with cougar removals. As hypothesized above, cougar predation may have significant
impacts on pig populations. Based on average kill rates and a population of 20 individuals, cougars could kill 500
pigs per year.
Highway Crossing
Highway underpasses and overpasses have successfully facilitated cougar movement across freeways in Canada
(Clevenger and Waltho 2005), California (Beier 1995), and Florida (Lotz et al. 2005). Clevenger and Waltho
(2005) found a correlation with nine attributes during the summer months and three during winter. Cougar
passage in summer was negatively correlated with crossing structure height, openness, distance to forest cover
and town site; cougar passage was positively correlated with distance to railroad tracks. Cougars demonstrated a
negative relationship between passage and crossing structure width and distance to next structure, but a positive
relationship with crossing structure length. Cougars had a tendency to use divided structures more than
undivided structures. Winter passage by cougars was explained by fewer variables. Cougars tended to use
crossing structures near forest cover, near town sites, and far from tracks.
TRC consulting biologists did not find any use of crossing structures on Interstate 5 (I-5) on the western
boundary of Tejon Ranch by cougars (USFWS 2012), even though the work of Ernest and colleagues (2003)
indicated connectivity in the region. As projections indicate increased traffic and development in the region,
Mountain Thinking recommends research to determine ways to develop passage of I-5 and SR 58 by cougars
(similar to the recommendation for black bears in Section 2 of this appendix). Clevenger and Waltho (2005)
showed that structural and landscape factors were equally important in explaining carnivore passage. For
structural attributes, two clear patterns emerged. First, crossing structures with high openness ratios (i.e., short
in length, high and wide) strongly influenced passage by grizzly bears, wolves, elk, and deer. Second, more
constricted crossing structures (i.e., long in length, low, narrow, and with low openness ratios) best explained
passage by black bears and cougars. Thus, work on black bears and cougars could occur together.
Lewis and colleagues (2011) found that the most efficient and effective means of mitigating the effects of
roadways on animals was to identify important crossing areas for wildlife and focus management activities
within those areas (Glista et al. 2009), by retaining or enhancing the characteristics along roads that promote
crossing behavior by animals. Because Dudek (2009) did not find use of crossing structures by cougars, Mountain
Thinking recommends monitoring cougars with home ranges near I-5 and SR 58 to determine, through telemetry,
if they cross these roads and where. If no evidence of crossing is found, then biologists should map likely crossing
areas and work with the California Department of Transportation to develop and test crossing structures for
multiple species with a focus on cougars and bears.
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Beier, P. 1996. Metapopulation modeling, tenacious tracking, and cougar conservation. Pages 293–323 in D. R.
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6. Coyote (Canis latrans)
Coyotes are among the most widespread, opportunistic,
and resilient of mammalian carnivores. They are also
among the most challenging for humans, preying on
livestock and big game. Recent work increasingly
indicates the important ecological function they play in
ecosystems.
POPULATION DYNAMICS
Density
Kohn and colleagues (1999) reported a density of 2.5
coyotes per square kilometer (km2) in a small study area in
the Santa Monica Mountains National Recreation Area
near Los Angeles, California. Because of human food
Coyote (© Tejon Ranch Company 2013)
subsidies, Fedriani and colleagues (2001) found that
coyote density was highest in the more human-influenced
area (2.4–3.0 per km2) in the Santa Monica Mountains,
whereas coyote density was significantly lower in the least humanized area (0.3–0.4 per km2).
Knowlton and colleagues (1999) reported that estimates of coyote density range from 0.2 to 2.3 coyotes per km2,
with generally increasing densities from the northern to the southern regions of the United States. Available food,
especially in winter (Gese et al. 1996a), is the major factor regulating coyote abundance (Clark 1972), mediated
through social dominance and territoriality (Gese et al. 1989, Knowlton and Gese 1995, Windberg 1995). Food
abundance regulates coyote numbers by influencing reproduction, survival, dispersal, space-use patterns, and
territory density (Knowlton 1972, Todd and Keith 1983, Mills and Knowlton 1991, Gese et al. 1996a).
Young and colleagues (2008) found that, in Texas, removal created vacancies within the study area that were
filled by other coyotes, but few changes to locations of home ranges were observed for coyotes found before and
after removal. Instead, coyote home ranges that were present in 2004 showed a high level of overlap with their
locations in 2005. Even though neighboring coyotes were removed between 2004 and 2005, surviving coyotes
made only slight changes in the boundaries and sizes of their home ranges. The addition of food to territories did
not significantly change territory size or structure.
Young and colleagues (2006) examined coyote use of unexploited space in Texas 25 years after a previous study
(Andelt 1985) and found no differences. If coyotes experienced dramatic shifts in environmental conditions or
were intensively harvested, conditions they experience in much of their range, similarities may not have been
seen. Boundary shifts were evident in a coyote population that experienced high levels of mortality from canine
hepatitis (Camenzind 1978), and territory size fluctuated with prey abundance when coyotes experienced high
levels of human exploitation (Mills and Knowlton 1991). After 25 years, coyotes exhibited similar space use,
activity patterns, age structure, and overall diet in a relatively stable environment. Coyotes are frequent targets of
control programs, creating unstable environments in which coyotes must exhibit behavioral and spatial plasticity
to thrive.
Wilson and Shivik (2011) based on comparative study in Texas and Idaho proposed that, in regions with high
resource abundance, territory size of coyotes is determined by contender pressure and an inability to defend large
areas. Conversely, in low-resource areas, territory sizes are determined more by prey abundance and dispersion
because intrusion rates are reduced, given the lower density of conspecifics.
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Reproduction
Knowlton et al. (1999) summarized that unexploited coyote populations typically have older age structures, high
adult survival rates, low reproductive rates (especially among yearlings), and low recruitment into the adult
population (Andelt 1985; Gese et al. 1989, 1996a, 1996b; Windberg 1995). Such populations may have larger packs
or social units, depending on available food. Under heavy exploitation, populations are characterized by younger
age structures, lower adult survival rates, increased percentages of yearlings reproducing, increased litter size,
and relatively small packs (Knowlton 1972, Berg and Chesness 1978, Davison 1980). Although litter sizes may
increase in response to reduced coyote density (compensatory reproduction), this is likely a response to reduced
competition for food (Andelt 1996) or breeding among younger females.
Mortality
Riley and colleagues (2003) monitored radio-collared coyotes in the Santa Monica Mountains and reported
average annual survival rates were 0.74 and similar between sexes (0.75 male v. 0.73 female). Those survival rates
were similar to rates reported in other unexploited populations (Gese et al. 1989, Grinder and Krausman 2001)
and higher than those in harvested populations (Windberg 1995, Knowlton et al. 1999). Humans are the primary
cause of mortality in coyotes, either directly or indirectly.
Coyote predation primarily affects sheep; the threat to cattle, on the other hand, is very limited. Predation is a
minor cause of loss to the cattle industry; coyotes killed less than 0.1% of the United States’ total cattle
population in 2000 (NASS 2003). Respiratory problems, digestive problems, calving problems, and weather each
killed 6–17 times more cattle than did coyotes (NASS 2003). Nevertheless, coyotes were the dominant cattle
predator; they were implicated in 65% of cattle losses attributable to predation in 2000, or 8,000 cattle and
87,000 calves, worth a total of $31.8 million (NASS 2003). There is no available documentation of losses of cattle
on Tejon Ranch to coyotes or any other predator. No nonlethal management efforts have been attempted.
I MPACTS ON PREY
In one of the most comprehensive and best designed studies to date, Hurley and colleagues (2011) provided little
evidence that cougar or coyote removal in southeastern Idaho changed the overall population status of mule deer.
Amount and timing of precipitation, likely related to plant phenology and winter energy expenditure, had a
greater influence on deer population vital rates. Predation is a significant limiting factor of mule deer populations;
however, the effect on rate of increase is unpredictable because of yearly variation in climate-linked habitat
carrying capacity and alternate prey populations. Hurley and colleagues (2011) argued that these changes in
carrying capacity or increases in deer numbers will ultimately dictate the role of predation in mule deer
population dynamics. The limited effects of predator removal from this study and the pervasive effects of
enhanced nutrition seen by Bishop and colleagues (2009) led Hurley and colleagues (2011) to conclude that
enhanced nutrition will increase mule deer populations more effectively and predictably than predator removal.
Hurley and colleagues (2011) summarized their findings regarding coyote removal as follows:
1.
Neonatal fawn survival increased after coyote removal. Effectiveness of removal was dependent on the
abundance of primary prey (lagomorphs) for coyotes because coyotes appeared to switch to mule deer
fawns at low lagomorph densities.
2. Winter fawn survival and adult survival did not increase.
3. The effect on population growth rate was undetectable.
They also described factors affecting mule deer vital rates:
4. Pregnancy rates of adult females were high (91–98%).
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5. Fawn-at-heel ratios in June were high (1.62–1.81) in normal climate years.
6. Disease was not a factor in mule deer survival.
7. Age was an important factor in adult mortality.
8. Climate was the most important factor explaining survival of fawns in winter, adult females in summer,
fawn ratios, and population growth rate.
9. In conclusion, factors affecting mule deer vital rates were not related to coyote predation (Hurley et al.
2011).
Some western states have contracted with the U.S. Department of Agriculture, Wildlife Services (WS), to
remove coyotes for the benefit of pronghorn and mule deer (Harrington and Conover 2007). However, debate
remains whether current coyote removal programs can increase fawn survival. It is unclear if predator control
would increase mule deer and pronghorn densities or offspring survival because few well-designed experiments
have been conducted on the subject (Gill 2001). Until recently, studies examining the effects of coyote control
were conducted in areas of less than 1,000 km2 (Ballard et al. 2001). To date, only two predator control studies
have been conducted in areas of more than 1,000 km2.
Harrington and Conover (2007) conducted a study in Utah and Colorado in eight sites that encompassed more
than 1,900 km2. WS personnel spent a mean of 126 hours annually controlling coyotes at each site. This included
a mean of 24 hours of aerial gunning and 102 hours employing someone on the ground, either shooting or
trapping predators. A mean of 67 coyotes were killed per site. Aerial gunning was the most productive method,
taking 79% of all coyotes with only 19% of the person-hours. Data from that study showed no relationship
between coyote removal and fawn: adult female ratios, but a positive correlation was seen between the level of
coyote removal and densities of pronghorn and mule deer (Harrington and Conover 2007). The increase is
difficult to explain without understanding the mechanism of higher fawn survival. What these researchers found
may not have been a general increase in densities over a broad area due to coyote control, but rather local
movement of ungulates into sanctuaries from predators that were inadvertently created by WS coyote control
efforts.
Brown and Conover (2011) tested the hypothesis that predation by coyotes affects pronghorn and mule deer
populations. They examined the effects of coyote removal on pronghorn and mule deer populations within 12
large areas (more than 10,500 km2) in Wyoming and Utah during 2007 and 2008. Mule deer productivity and
abundance were not correlated with either the number of coyotes removed or the removal effort. These results
suggest that coyote removal conducted over large areas increases fawn survival and abundance of pronghorn but
not mule deer.
R OLE IN E COSYSTEM
Coyotes play a keystone role in the population regulation of microherbivores and mesopredators in certain
ecosystems (Henke and Bryant 1999). Mesopredator population increases following the eradication of big
predators (mesopredator release) has diverse cascading effects through the food chain that can result in major
changes in animal and plant populations and habitats (Prugh et al. 2009, Roemer et al. 2009, Estes et al. 2011).
In an experiment, Henke and Bryant (1999) reduced coyote density from 0.12 to 0.06–0.01 coyotes per km2 on
treatment sites. Density on comparison sites remained stable at 0.14 coyotes per km2. Within 9 months following
the initiation of coyote removal, rodent species richness and rodent diversity declined on treatment sites.
Without coyote predation, the Ord’s kangaroo rat (Dipodomys ordii) became the most abundant rodent in
shrublands, and it was the only rodent species caught in grasslands after 12 months of coyote removal. Rodent
density and biomass; black-tailed jackrabbit (Lepus californicus) density; and relative abundance of badgers
(Taxidea taxus), bobcats (Felis rufus), and gray foxes (Urocyon cineroargenteus) increased on treatment sites. Variation
in the density of desert cottontail rabbits (Sylvilagus audubonii) and in raptor richness, diversity, and density were
January 2013
not related to coyote density. These findings were consistent with the predator-mediated coexistence hypothesis,
which suggests that a keystone predator (e.g., coyote) can influence faunal community structure.
Harvest
More than 30 years of research on coyotes has demonstrated their resilience to harvest. Despite intensive and
novel attempts to control populations, only intensive and large harvests have had impacts on populations
(Knowlton et al. 1999). Connolly and Longhurst (1975) developed a simulation model and determined that a
minimum annual removal of 75% of the breeding population of coyotes was needed to consistently reduce coyote
density.
Depredation Management Efforts
Despite decades of research and widespread, significant control efforts, coyote removal efforts below the 75%
threshold level had minimal effect in reducing sheep depredation losses by coyotes (Conner et al. 1998). Berger
(2006) assessed the efficacy of long-term efforts by the U.S. government to improve the viability of the sheep
industry by reducing predation losses. She analyzed a 60-year data set to explore associations among changes in
sheep numbers and factors such as predator control effort, market price, and production cost. In addition, she
compared trends in the sheep industry in the western United States, where predator control is subsidized and
coyotes are abundant, with trends in eastern states that lack federally subsidized predator control and that were
(1) colonized by coyotes before 1950 or (2) colonized by coyotes between 1950 and 1990.
Notes:
“All Others” includes black bears, bobcats, wolves, and mountain lions; “1080 Use” identifies the period over which the toxicant compound
1080 was used to control predators; data were unavailable for 1977–1984.
Source:
Berger 2006
Figure 6-1
Carnivores Killed Annually by Federal Predator Control Agents (1939–1997)
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Berger (2006) found that, although control efforts were positively correlated with fluctuations in sheep numbers,
production cost and market price explained most of the model variation, with a combined independent
contribution of 77%. Trends in sheep numbers in eastern and western states were highly correlated independent
of the period during which they were colonized by coyotes, indicating either that control has been ineffective at
reducing predation losses or that factors other than predation account for the declines in both regions. These
results suggest that government-subsidized predator control has failed to prevent the decline in the sheep
industry and that alternative support mechanisms need to be developed if the goal is to increase sheep
production rather than simply to kill carnivores.
That control efforts have had little effect on trends in the sheep industry, Berger summarized, is remarkable,
given the enduring nature of the program, the considerable resources devoted to carnivore removal (about $1.6
billion in real dollars between 1939 and 1998), the number of carnivores removed, and the frequent assertion that
federal control of predators is necessary to maintain the sheep industry. If predation losses are the primary cause
of the sheep industry’s decline, then control, as practiced, has not been successful at reducing predation losses to
the level necessary to make sheep ranching economically viable (Berger 2006).
Mitchell and colleagues (2004) reported that, while nonlethal management (including varied animal husbandry
practices, coyote behavioral modification, or sterilization) show significant promise, they have not been tested in
controlled experiments. Therefore, many livestock producers rely on lethal control, and most employ nonselective strategies aimed at local population reduction. Sometimes this approach is effective; other times it is
not. This strategy can fail because, as Mitchell and colleagues (2004) continue, the alpha coyotes, which are most
likely to kill livestock, are the most resistant to non-selective removal techniques. An alternative is selective
lethal control. Livestock Protection Collars (LPCs) and coyote calling are the primary selective lethal approaches.
However, LPCs do not have support from the general public because of the toxicant used, and the factors
affecting the selectivity of coyote calling have not been studied.
Mitchell and colleagues (2004) argued that the greatest impediments to effective coyote depredation
management currently are a scarcity of selective control methods, the lack of understanding of the details of
coyote behavioral ecology relative to livestock depredation and wild prey abundance, the absence of solid
research examining the effectiveness of different control techniques in a variety of habitats and at multiple
predation intensities, and the dearth of rigorous controlled experiments analyzing the operational efficacy of
selective removal compared to population reduction. While this is no doubt true to some degree, the greater
truth likely is the resilience and adaptability of coyotes that will probably not be overcome by control techniques
and greater killing power.
As summarized by Knowlton and colleagues (1999), because coyote populations are dynamic and resilient, the
effects of coyote removal are ephemeral, with normal demographic responses attempting to return the population
to levels consistent with available food and habitat conditions. These responses include recolonization from
adjacent areas, increased breeding among younger females, increased litter size, and increased survival rates. The
speed with which populations return to “normal” levels is dependent on the size of the area involved and the
intensity of the removal program. On small management units, immigration of non-territorial coyotes from
surrounding areas should occur rapidly, probably within weeks or months. On larger areas, recruitment would
come from immigration as well as increased productivity by surviving coyotes. A temporary increase in juvenile
survival could also be expected. Although higher reproductive rates would be expected, speculations that more
pups might be recruited into a reduced population, and thus increase population density beyond the pre-removal
level, are unwarranted because competing rates of change are involved (i.e., any increased reproductive rate
would be applied to a smaller population). Knowlton and colleagues (1999) concluded that, at this point, the
relationship between the degree of reduction and increased productivity remains conjectural. Similarly, increased
survival of coyote pups could be expected, but expectations that population levels would exceed those dictated
by available food resources are unrealistic. The effectiveness of coyote population reduction on small
management units (Ballard et al. 2001) or with inadequate intensities of effort is apt to be disappointing (Beasom
1974).
January 2013
Kohn and colleagues (1999) tested the use of fecal genotyping on a population of coyotes from the Santa Monica
Mountains National Recreation Area near Los Angeles, California, that was traversed by trails and roads. During
a 2-week period beginning in July 1997, they removed all 651 recognizable carnivore-like feces from 381 sites along
six transects in a 15-km2 area. As deduced from the reduction in new genotypes detected, population size was
estimated at approximately 38 individuals.
Prugh and colleagues (2005) collected a total of 1,237 scats in the central Alaska Range during November 1999–
March 2000, January–March 2001, and January–March 2002. From these, they selected 850 scats for genetic
analysis by random sampling without replacement, and 834 of these scats were analyzed (16 samples were
contaminated during DNA extraction). The study area encompassed approximately 1,000 km2 of mountains and
foothills on the northern edge of the Alaska Range, and the researchers established more than 150 km of
snowmobile trails along the three major river drainages. Although trail routes were nonrandom due to
topographical constraints, it is highly unlikely that any coyotes lived exclusively in the rugged, high-elevation
areas between trails. The researchers searched for scats along the trails on a daily basis, and also collected scats
while following coyote tracks on foot. The study area was stratified and tracks were chosen from within these
areas to ensure equal representation from each area and independence of samples between each monthly capture
period. Distances travelled in search of scats were recorded as a measure of scat collection effort. The researchers
recorded the GPS location, estimated maximum age of the scat (based on travel and snowfall history), and
certainty level that the scat was from a coyote. Coyote scats could have been confused with those of gray wolves
(Canis lupus), red foxes (Vulpes vulpes), lynx (Lynx canadensis), and dogs (Canis familiaris).
Prugh and colleagues (2005) used flexible maximum-likelihood models to study coyote population dynamics,
and they tested model performance against radio-telemetry data. The staple prey of coyotes, snowshoe hares
(Lepus americanus), dramatically declined during this study, and the coyote population declined nearly two-fold
with a 1/2-year time lag. Survival rates declined the year after hares crashed but recovered the following year. The
researchers concluded that long-term monitoring of elusive species using fecal genotyping is feasible and can
provide data that are useful for wildlife conservation and management. They highlight some drawbacks of
standard open-population models, such as low precision and the requirement of discrete sampling intervals, and
suggest that the development of open models designed for continuously collected data would enhance the utility
of fecal genotyping as a monitoring tool.
Similar to the recommendations for cougars, Mountain Thinking recommends that nonlethal coyote management
techniques be developed and tested, following the recommendations of Mitchell and colleagues (2004) and
Knowlton and colleagues (1999). Tejon Ranch could be a state-of-the-art demonstration site for such projects.
Mountain Thinking has been developing such a project for large carnivores and livestock in the southwest and in
Alberta, Canada. Defenders of Wildlife and the Mountain Lion Foundation have also developed
recommendations that may be appropriate for Tejon Ranch.
Killing carnivores is increasingly controversial and fraught with ethical issues that need to be understood (Hecht
and Nickerson 1999). Mountain Thinking recommends that the Conservancy develop a management policy for
livestock depredations that would be reviewed by independent biologists for science scientific rigor and
objectivity. Such a policy would define monitoring of livestock and predators and identify ways to measure and
respond to depredations, including the use of nonlethal approaches before any lethal approaches are used.
Mountain Thinking recommends that any removal only be authorized by TRC following the use of nonlethal
methods. Lessees and TRC personnel should be required to keep records of all animals killed by coyotes and
other predators and the factors affecting this predation. Calf depredation rates should then be compared between
north and south Tejon Ranch, where the two lessees appear to practice different management techniques for
coyotes.
January 2013
As recommended elsewhere in this wildlife assessment for work on feral pigs, the impact of coyote predation on
pigs should be tested before coyote removal continues.
As recommended for pronghorn, primary limiting factors for the pronghorn population should be assessed,
including a determination of the role of coyote predation on fawns. While coyote control is not recommended to
enhance pronghorn survival because of the unsustainability of such an enterprise, given the small pronghorn
population (as discussed in the assessment of pronghorn), such an assessment would indicate long-term viability
of pronghorn on Tejon Ranch. Such a project would also be useful for mule deer management.
While coyotes can sustain relatively high levels of mortality, Mountain Thinking recommends establishing goals
and limits and identifying a clear justification and management objectives for a hunt program. High harvest of
coyotes occurred in the 1980s, but no data have been collected since that time. Establishing a reliable estimate of
density on Tejon Ranch would allow development of harvest objectives. The range of density for coyotes reported
in California (0.2–2.3 per km2) would produce a population range of coyotes on Tejon Ranch of 200–2,000. At the
lower end of this density range, the harvest on the Ranch in the 1980s (112–261) would not have been sustainable.
Mountain Thinking also recommends developing an index to indicate coyote population trends. Developing scat
collection routes in areas important to pronghorn and deer, and then using DNA as indicated above to estimate
minimum number of animals, would be a good approach.
R EFERENCES
Andelt, W. F. 1985. Behavioral ecology of coyotes in south Texas. Wildlife Monograph 94.
Andelt, W. F. 1996. Carnivores. Pages 133–155 in P. R. Krausman (ed.), Rangeland Wildlife. Society Range
Management, Denver, CO.
Ballard, W. B., D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos, Jr. 2001. Deer–predator relationships: a
review of recent North American studies with emphasis on mule and black-tailed deer. Wildlife Society Bulletin
29:99–115.
Beasom, S. L. 1974. Intensive short-term predator removal as a game management tool. Transactions of the North
American Wildlife Conference 39:230–240.
Berg, W. E., and R. A. Chesness. 1978. Ecology of coyotes in northern Minnesota. Pages 229–247in M. Bekoff
(ed.), Coyotes: Biology, Behavior, and Management. Academic Press, New York, NY.
Berger, K. 2006. Carnivore-livestock conflicts: effects of subsidized predator control and economic correlates on
the sheep industry. Conservation Biology 20:751–761.
Bishop, C. J., G. White, D. Freddy, B. Watkins, and T. R. Stephenson. 2009. Effect of enhanced nutrition on mule
Brown, D., and M. Conover. 2011. Effects of large-scale removal of coyotes on pronghorn and mule deer
productivity and abundance. Journal of Wildlife Management 75:876–882.
Camenzind, F. J. 1978. Behavioral ecology of coyotes on the National Elk Refuge, Jackson, Wyoming. Pages 267–
294 in M. Bekoff (ed.), Coyotes: Biology, Behavior, and Management. Academic Press, New York, NY.
Clark, F. W. 1972. Influence of jackrabbit density on coyote population change. Journal of Wildlife Management
36:343–356.
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Conner, M., M. Jaeger, T. Weller, and D. McCullough. 1998. Effect of coyote removal on sheep depredation in
northern California. Journal of Wildlife Management 62:690–699.
Connolly, G. E., and W. M. Longhurst. 1975. The effects of control on coyote populations: a simulation model.
Bulletin 1872. Division of Agricultural Science, University of California, Davis, Davis, CA.
Davison, R. P. 1980. The effect of exploitation on some parameters of coyote populations. Ph.D. Dissertation, Utah
State University, Logan, UT.
Estes, J., J. Terborgh, J. Brashares, M. Power, J. Berger, W. Bond, and J. Shurin. 2011. Trophic downgrading of
planet Earth. Science 6040:301–306.
Fedriani, J., T. Fuller, and R. Sauvajot. 2001. Does availability of anthropogenic food enhance densities of
omnivorous mammals? An example with coyotes in southern California. Ecography 24:325–329.
Gese, E. M., O. J. Rongstad, and W. R. Mytton. 1989. Population dynamics of coyotes in southeastern Colorado.
Gese, E. M., R. L. Ruff, and R. L. Crabtree. 1996a. Social and nutritional factors influencing the dispersal of
resident coyotes. Animal Behavior 52:1025–1043.
Gese, E. M., R. L. Ruff, and R. L. Crabtree. 1996b. Foraging ecology of coyotes (Canis latrans): the influence of
extrinsic factors and a dominance hierarchy. Canadian Journal of Zoology 74:769–783.
Gill, B. R. 2001. Declining Mule Deer Populations in Colorado: Reasons and Responses. Terrestrial Wildlife Research Special
Report 77. Colorado Division of Wildlife, Denver, CO.
Grinder, M., and P. Krausman. 2001. Morbidity-mortality factors and survival of an urban coyote population in
Arizona. Journal of Wildlife Diseases 37:312–317.
Harrington, J., and M. Conover. 2007. Does removing coyotes for livestock protection benefit free-ranging
ungulates? Journal of Wildlife Management 71:1555–1560.
Hurley, M., J. Unsworth, P. Zager, M. Hebblewhite, E. Garton, D. Montgomery, and C. Maycock. 2011.
Idaho. Wildlife Monographs 178.
Knowlton, F. F. 1972. Preliminary interpretations of coyote population mechanics with some management
implications. Journal of Wildlife Management 36:369–382.
Knowlton, F. F., and E. M. Gese. 1995. Coyote population processes revisited. Pages 1–6 in D. Rollins, C.
Richardson, T. Blankenship, K. Canon, and S. Henke (eds.), Coyotes in the Southwest: A Compendium of Our
Knowledge. Texas Parks Wildlife Department, Austin, TX.
January 2013
Knowlton, F., E. Gese, and M. Jaeger. 1999. Coyote depredation control: an interface between biology and
management. Journal of Range Management 52:398–412
Mills, L. S., and F. Knowlton. 1991. Coyote space use in relation to prey abundance. Canadian Journal of Zoology 69:
1516–1521.
Mitchell, B., M. Jaeger, R. Barrett, and J. Applegate. 2004. Coyote depredation management: current methods and
research needs. Wildlife Society Bulletin 32:1209–1218.
NASS. See National Agricultural Statistics Service.
National Agricultural Statistics Service. 2003. Agricultural Statistics 2003. U.S. Department of Agriculture,
Washington, DC.
Prugh, L., C. Ritland, S. Arthur, and C. Krebs. 2005. Monitoring coyote population dynamics by genotyping
faeces. Molecular Ecology 14:1585–1596.
Prugh, L. R., C. J. Stoner, C. W. Epps, W. T. Bean, W. J. Ripple, A. S. Laliberte, and J. S. Brashares. 2009. The rise
of the mesopredator. BioScience 59:779–791.
Riley, S. P. D., M. Sauvajot, D. Kamradt, E. York, C. Bromley, T. Fuller, and R. Wayne. 2003. Effects of
urbanization and fragmentation on bobcats and coyotes in urban southern California. Conservation Biology
17:566–576.
mesocarnivore. Bioscience 59:165–173.
Wilson, R. R., and J. A. Shivik. 2011. Contender pressure versus resource dispersion as predictors of territory size
of coyotes (Canis latrans). Canadian Journal of Zoology 89: 960–967.
Todd, A. W., and L. B. Keith. 1983. Coyote demography during a snowshoe hare decline in Alberta. Journal of
Windberg, L. A. 1995. Demography of a high-density coyote population. Canadian Journal of Zoology 73:942–954.
Young, J., W. Andelt, P. Terletzky, and J. Shivik. 2006. A comparison of coyote ecology after 25 years: 1978 versus
2003. Canadian Journal of Zoology 84:573–582.
Young, J., S. Glasscock, and J. Shivik. 2008. Does spatial structure persist despite resource and population
changes? Effects of experimental manipulations on coyotes. Journal of Mammalogy 89:1094–1104.
January 2013
7. Elk (Cervus elaphus )
The subspecies of elk native to the Tejon Ranch region is
tule elk (Cervus elaphus nannodes). Tule elk were isolated
from other populations during the Wisconsin glacial
period and are endemic to California. They declined from
more than 500,000 in the open country of the Central
Valley to fewer than five animals by 1875. They are smaller
and paler? than Rocky Mountain elk (Cervus elaphus nelsoni)
(McCullough et al. 1996). Through reintroductions, the
statewide population had increased to 3,500 in 21
populations, ranging from 20 to 600 elk each (with eight
populations above 100), by the 1990s (Howell et al. 2002).
Tule elk were reintroduced to the Wind Wolves Preserve
(95,000 acres), the southernmost extension of their
historic range. That elk herd has grown to more than 200
Rocky Mountain Elk (Thadani 2009)
elk, and the California Department of Fish and Wildlife
(CDFW) (formerly California Department of Fish and
Game [CDFG]) estimates the preserve can support up to 2,500 elk. No elk have been recorded moving between
Tejon Ranch and Wind Wolves Preserve (Dudek 2009).
Rocky mountain elk were first found on Tejon Ranch in 1964 after dispersing from a Tehachapi hunting
operation. The first Rocky Mountain elk hunts were held on the Ranch in 1978. The number of elk on Tejon
Ranch, classified by age and sex, has increased from 68 in 1995 to 320 in 2011 (Table 7-1). The total population
size is unknown. A significant increase was also noted in count over time (0.80; p < 0.0001). The rate of increase,
based on number classified by age and sex, was 6% per year.
Table 7-1
Tejon Ranch Elk Composition Counts
Fall
Bulls per 100 Cows
Calves per 100 cows
Number Classified
1995
53
47
68
1996
83
44
82
1997
85
45
143
1998
73
41
137
1999
71
48
162
2000
68
38
142
2001
74
40
164
2002
78
37
139
2003
68
42
156
2004
74
38
142
2005
72
39
163
Table 7-1
January 2013
Tejon Ranch Elk Composition Counts
Fall
Bulls per 100 Cows
Calves per 100 cows
Number Classified
2006
54
28
190
2007
58
31
173
2008
51
29
124
2009
38
30
261
2010
42
40
307
2011
40
44
320
Note
“Classified” indicates that the animals were categorized by age and sex.
Genetics
As analyzed and summarized by Meredith and colleagues (2007), subspecific status of North American elk has
been hotly debated (see O’Gara [2002| for a discussion of the taxonomy of North American elk). Tule elk are
considered the smallest subspecies of North American elk and are typified by having lower body masses, lighter
pelage, and the longest tooth rows of any North American subspecies. Roosevelt elk reportedly have the largest
body mass and display different antler and jaw morphologies from the others (McCullough 1969, O’Gara 2002).
Of the three subspecies, Rocky Mountain elk typically have the largest antlers. Although tule elk do not currently
display the effects of reduced fitness, such as low reproductive output and morphological deformities, the
individual herds are definitely at risk if they remain genetically isolated. Work by Meredith and colleagues
(2007) supports previously published studies suggesting that tule, Roosevelt, and Rocky Mountain elk should be
designated as discrete subspecies (Polziehn et al. 2000) and as evolutionarily significant units.
The only “pure” population of Rocky Mountain elk within California identified by Meredith and colleagues
(2007) occurs at Tejon Ranch. These animals originated in Yellowstone National Park, Wyoming. California
Department of Fish and Game managers had expressed concern that these animals had bred with tule elk at one
point in time, but no evidence was found.
Elk readily disperse over long distances. Petersberg and Alldredge (2000) found that the maximum distances
moved by emigrant 2 year old elk in Colorado averaged 87–149 km. Survival of this age class of emigrants was
0.25, while resident survival was greater at 0.89. These results suggest that elk movement between management
areas is prevalent in northwest Colorado and, thus, is likely between Tejon Ranch and Wind Wolves Preserve.
Interstate 5, however, bisects the two reserves and may not allow much movement between the separated
populations (Dudek 2009).
At Starkey Experiment Station in Oregon, female elk selected habitat far from roads and characterized by gentle
slopes and westerly aspects (Johnson et al. 2000, Rowland and Wisdom 2000, Stewart et al. 2002). Foraging
strategy was predominately grazing, and diets consisted primarily of high-quality forbs, with grasses selected
secondarily (Stewart et al. 2003). In contrast, female mule deer selected habitat closer to roads and characterized
by steeper slopes, easterly aspects, and more convex topography than did elk (Johnson et al. 2000). Stewart and
colleagues (2003) classified mule deer at Starkey as browsers, with diets consisting largely of sedges but also
containing moderate quantities of shrubs and grasses. In addition, Johnson and colleagues (2000) and Stewart
and colleagues (2002) concluded that habitat selection by mule deer could be explained largely by avoidance of
areas used by elk.
January 2013
As Long and colleagues (2008) indicate, large-scale habitat manipulations are being conducted with increasing
frequency in western forests, often in an attempt to reduce fuel loadings and, therefore, risk of high-severity
wildfires. Understanding ecological consequences of fuels reduction is critical for sound management of wildlife
habitat in forest ecosystems. Prescribed fire, in particular, often is assumed to benefit large herbivores. In areas
with seasonal climatic patterns and vegetation associations similar to those at Starkey, maintaining a mixture of
burned and unburned (e.g., late successional) forest habitat might provide the best long-term foraging
opportunities for large herbivores as a result of rapidly declining forage abundance in burned stands between
spring and summer.
Long and colleagues (2008) believed habitat manipulation via prescribed fire might be more beneficial to elk than
mule deer, which is an important consideration for managers because mule deer are declining throughout much
of their range whereas elk populations are stable or increasing. If improving habitat for elk is the primary goal,
these results indicate that larger burns located far from roads might provide the greatest benefit to elk.
POPULATION DYNAMICS AND DRIVERS
Reproduction
Elk exhibit high reproductive potential and survival, especially when reintroduced to new habitats. Sargeant and
Oehler (2007) examined reintroduced elk at Theodore Roosevelt National Park, North Dakota. Pregnancy rates
in January averaged 54.1% for subadults and 91.0% for adults, and 91.6% of pregnancies resulted in recruitment at
8 months. Annual survival rates of adult females averaged 0.96 with hunting included and 0.99 with hunting
excluded. Although the study found no evidence of temporal variation in vital rates, variation in population
composition caused substantial variation in projected rates of increase (lambda = 1.20–1.36). McCorquodale and
colleagues (2003), studying a hunted population in Washington, found male survival of 0.65 and female survival
of 0.83.
Between 1995 and 2011 reproduction at Tejon Ranch has varied from a low of 27 calves:100 cows to a high of 48
calves:100 cows (Table 7-1). The trend in calf: cow ratio is variable but has been significantly declining over time
(0.74; p = 0.01), possibly indicating that the population is nearing carrying capacity. Not surprisingly, the Tejon
Ranch data appear to indicate recruitment associated with precipitation. The correlation between previous year
precipitation and calf ratio is 0.73; this relationship is significant (p = 0.03).
Climate
Howell and colleagues (2002) calculated the population doubling time for the Point Reyes National Park
(29,000-hectare [ha]) tule elk herd (370–550 elk), using the estimated exponential rate of increase (r = 0.194), to
be 3.6 years in 1996–1998, 20 years after elk reintroduction. Gogan and Barrett (1987) noted that a higher rate
occurred from 1982 to 1984, the period coinciding with the first El Niño event after reintroduction. Combining
Gogan and Barrett’s (1987) strong El Niño observations with those of Howell and colleagues (2002) shows a
significant increase in growth rate of the population during these events. During the herd growth period between
El Niño precipitation events in 1982 and 1994, there was evidence of a declining rate of increase with increasing
population, supporting the idea that growth rates may be related to density during dry years. However, higherthan-normal precipitation during the El Niño years of 1995–1997 resulted in higher forage and higher calf
production, overriding density effects that appeared before 1995. Cow survival was 0.95 and calf survival was
0.85 during this period.
Hallbritter and Bender (2011), studying the Sacramento Mountains of southern New Mexico, agreed that dry
range conditions reduced reproductive performance of ungulates (Cook et al. 2004). For both densityindependent and density-dependent effects, timing of precipitation in arid environments is important, as highquality forage is essential during critical periods such as during lactation or late gestation (Cook et al. 2004).
Timing of spring emergence of plants influenced survival of juvenile elk (Bender and Piasecke 2010) in New
Mexico and was related positively to cumulative precipitation through the late gestation period. However, as
seen with survival of juveniles in the Sacramento Mountains, this seasonal relationship does not need to be
positive if it increases density-independent mortality of juveniles. Survival of adult females (excluding harvestRanch-wide Management Plan, Volume 2
January 2013
related losses) was 0.95–1.00 and was comparable to the highest rates documented for free-ranging elk
(unhunted population 0.97, hunted population 0.93) (Ballard et al. 2000). Thus, excluding harvested adult
females, elk in the Sacramento Mountains had essentially no mortality, other than that predicted from senescence
alone.
Predation
Griffin and colleagues (2011) conducted a meta-analysis of elk mortality in the northwestern United States in
systems with varying numbers of large predators. They found that average calf survival was 0.65 with three
predators (cougars, black bears, and coyotes, as on Tejon Ranch), 0.55 with four predators, and 0.50 with five
predators. Average cause-specific mortality rates on calves were 0.15 for ursids, 0.11 for cougars, 0.02 for coyotes,
0.01 for wolves, and 0.10 for all other mortalities.
When Griffin and colleagues (2011) compared the relationship between calf mortality rate and neonatal survival
among study areas, only ursid predation appeared additive, showing that survival decreased linearly with
increasing ursid predation. For all other predators, cause-specific mortality was not significantly related to
survival, supporting the partially compensatory hypothesis. Neonatal elk survival to 3 months declined following
hotter previous summers and increased with higher May precipitation, especially in areas with wolves and/or
grizzly bears.
Given that annual elk calf survival can explain 73% of the variation in population growth rate (Raithel et al.
2007) and a mean adult female survival rate reported by Raithel and colleagues (2007) of 0.87, their observed calf
survival rates could be consistent with growing (three predator systems), stable (four predators), and declining
elk populations (five predators). This simple approach emphasizes the importance of understanding both adult
and annual calf survival, not just neonatal survival, to assess the impact of predators. Consistent with this coarse
interpretation, recent experimental predator reductions in Idaho (White et al. 2010) also show that reducing
bear densities increased neonate calf survival, in agreement with the finding of bear predation being a dominant
cause of additive mortality for neonates.
Bear predation may be additive because bears become specialist predators during early calving before mobility
body condition can start to mediate vulnerability to predation (White et al. 2010). Alternately, increased bear
predation could simply be attributed to spatial overlap. White and colleagues (2010) examined predation on elk
in north-central Idaho. Wildfire has shaped the vegetative communities of their study areas. Several large fires
between 1900 and 1935 burned approximately 63% of the Lochsa River watershed, creating large shrubfields and
other seral habitats preferred by elk (Skovlin et al. 2002). Such shrubfields were productive and vigorous for 2–3
decades after fire, after which shrub productivity and elk habitat suitability declined (Skovlin et al. 2002). The
data also suggested that habitat, as it influenced adult female elk body condition, was an important ultimate
factor affecting calf mortality. Females in better condition typically give birth to larger calves that survive better
(Cook et al. 2004). When females are in better condition, calf growth rates are more favorable, and their
vulnerability to predation declines quickly. Additionally, habitat functioned directly by structural characteristics
(i.e., plant shape and form) to affect calf escapement and security cover. This suggested that large-scale habitat
management can play an important, though subtle, role in elk population dynamics.
The results of White and colleagues (2010) provided insights that may be generalized to other areas where
managers are dealing with low elk calf recruitment. They demonstrated that predation by black bears was the
most important proximate mortality factor for elk calves from birth through August in north-central Idaho.
Because that mortality was additive, aggressive black bear harvest improved summer calf survival. Black bear
harvest had a stronger direct effect on summer calf survival than did cougar harvest, although both effects were
detectable. Because calves are generally most susceptible to bear predation in the first 28 days of life, spring bear
hunts that reduce bear densities or at least disrupt bear activities may be most effective. Increasing autumn bear
harvest may have a similar, though less immediate and predictable, effect. Reducing black bear harvest may
decrease calf survival, and this strategy could be used where the goal is to slow population growth or decrease elk
population size.
January 2013
Calf birth mass and habitat structure also influenced calf survival in the study by White and colleagues (2010).
Thus, addressing depressed elk recruitment with predator management alone may not be effective in achieving
calf recruitment objectives (White et al. 2010). The researchers summarized that improving elk habitat may
improve physical condition in adult female elk, which should lead to heavier calves with higher summer survival
and, perhaps, higher winter survival. Structural characteristics of habitat that allow calves to evade predators
may also contribute to calf survival by improving escapement. Fire and mechanical treatment could provide early
seral forest conditions. Because factors vary spatially, one management strategy will probably not have the same
effect on calf survival when applied in different areas. Collective evidence indicates that, as agencies formulate
management strategies for declining elk populations, densities of predators and habitat quality and condition
should be primary considerations in an integrated ecological approach.
In one of the most compelling recent meta-analyses of predations and climate effects, Melis and colleagues (2009)
showed that predation and primary productivity interacted in roe deer (Capreolus capreolus) across 79 populations
in continental Europe, spanning a wide latitudinal gradient. At a low primary productivity (northern latitudes),
predation had a dramatic effect on roe deer, reducing densities by almost 50%. Yet at high primary productivity,
no difference was found between roe deer densities with and without predation. Therefore, they predicted that
predation will be largely compensatory where primary productivity is high and mostly additive where primary
productivity is low.
Livestock Interactions
The results of research examining competition between elk and cattle are somewhat mixed but mostly indicate a
negative effect. Long and colleagues (2008) found that the presence of cattle might substantially reduce the
benefits of prescribed fire to elk, because elk often demonstrate strong avoidance of cattle, which would be
particularly pronounced if cattle were attracted to treated areas (Coe et al. 2001, Stewart et al. 2002). Stewart
and colleagues (2002) found that, in comparisons of elevation and slope prior to and following addition of cattle
during spring and prior to and following removal of cattle in autumn, competitive displacement likely occurred
between cattle and elk, although they could not control for effects of season in that analysis. During spring and
autumn, elk used lower elevations when cattle were not in the study area and used higher elevations when cattle
were present. The researchers suggested that the corresponding shift in niche breadth of elk indicates
competitive displacement by cattle. Mule deer shifted to more level slopes following removal of cattle during
autumn. During spring, however, shifts in use from higher to lower elevations following the introduction of cattle
indicated a more complicated response. During spring, mule deer may have responded to elk movements to
higher elevations following the addition of cattle to the study area. Niche partitioning among populations at high
densities becomes more difficult as resources become more limiting, leading to more competition.
Deferred rest rotation grazing (resting one pasture each year and rotating through use of the other non-rested) is
being used in late spring and summer (in northern latitudes) to “condition grasses” for later use by elk. Success is
achieved where (1) cattle are removed by mid-growing season to allow sufficient grass regrowth, (2) cattle use is
light to moderate, and (3) sufficient rest is provided to ensure survival and recovery (Wisdom and Cook 2000).
In assessing elk–cattle competition from the side of impacts to cattle, Weisberg and colleagues (2002) found
that, although cattle forage and condition were reduced at greater elk population levels, this effect was small
compared to effects from climate variability. Cattle forage was markedly reduced in areas where elk concentrated
in severe winters but was reduced much less, or even improved, elsewhere. These results, showing minor effects
of elk population level on cattle (a difference of 6 kg, or 1%, in cow weights for the historical experiment and 11
kg, or 2%, for the stochastic experiment) were surprising because a field experiment for a nearby area found far
greater effects (Hobbs et al. 1996). In their study, Hobbs and colleagues (1996) report delayed calf birth dates,
decreased calf body mass at the end of the growing season, and decreased total cattle production as elk
population density increased in a controlled experiment. However, decreases in cow body mass, the variable
reported in that study, were not significantly associated with increasing elk population density (Hobbs et al.
1996). Minor negative effects on cattle condition may have resulted from interactions involving decreases in
forage quantity, as well as increases in forage quality associated with an increased live/dead ratio of spring forage.
Source:
Figure 7-1
January 2013
Unpublished TRC data
Association between Calf Recruitment (elk calves:100 cows [ECALF]) and Year on Tejon
Ranch, 1995–2011
R OLE IN E COSYSTEM
Johnson and Cushman (2007) found that elk significantly altered the species composition of California
grasslands; the response of annual species (dominated heavily by exotic taxa) was dramatically different from
that of perennial species. Elk herbivory increased the abundance and aboveground biomass of native and exotic
annuals, whereas it either had no effect on or caused significant decreases in perennials. Elk also decreased the
cover of native shrubs, suggesting that they play an important role in maintaining open grasslands. In addition,
elk significantly reduced the abundance and biomass of a highly invasive exotic grass, Holcus lanatus, which is a
major problem in mesic perennial grasslands. These results demonstrate that the successful reintroduction of a
charismatic and long-extirpated mammal had extremely complex effects on the plant community, yielding both
desirable and undesirable outcomes from a management perspective.
Harvest Management
Lubow and Smith (2004) estimated annual natural survival (excluding harvest) of mature (at least 1 year old) elk
of 96.8% for males and 97.2% for females in the Jackson, Wyoming elk herd. Natality was 60.4 juveniles per 100
mature females. The dynamics of this population were well explained by annual variation in survival of neonates
(birth to July 31), juvenile survival during late winter (Feb20–May 19), and harvest. Survival of neonates was
correlated with several weather covariates that apparently affected the nutritional status of their mothers.
Survival of juveniles during late winter was related to weather conditions during the preceding summer and early
winter. This study found a compensatory effect of juvenile harvest on subsequent juvenile survival in late winter;
January 2013
89% of increased juvenile harvest was offset by reduced natural mortality. Lubow and Smith (2004) also found
evidence for a decline in survival of neonates with increasing population size (i.e., density dependence).
The simulations of Lubow and Smith (2004) suggested that harvest rates of mature females must be increased to
15.1% from recent levels of 11.9% to reduce the current population of 15,680 elk to the target population size of
11,029. Sensitivity of equilibrium population size to harvest rate at the target level was very high, requiring
regular monitoring and adjustment of harvest to maintain a stable population.
A single harvest rate cannot maintain a relatively constant population, given the combination of natural
variability attributable to weather and estimated sensitivity to harvest rate. Thus, these researchers
recommended a process of adaptive management that uses annual feedback of observed population size to
further improve their model and adjust the recommended harvest rate. However, the need for a higher harvest
rate to achieve the target population size was supported by the observation that the Jackson elk herd has not
been at or below the observed population level since 1985. Risk of overharvest should not be an impediment to
testing higher harvest rates because rapid population recovery is possible in this population at its current size—
14% growth in 1 year if harvest of antlerless elk were temporarily halted.
Bender and Miller (1999) documented bull: cow ratios, bull age structure, and annual bull mortality rates under
four differing bull harvest strategies (any-bull harvest for all hunters, minimum-three-point harvest, and two
levels of limited-entry bull harvest) in southwest Washington. Mean annual bull: cow ratios increased from 22 to
54 per 100 from any-bull harvesting to the most restrictive limited-entry strategy, reflecting a decrease in mean
annual bull mortality rates from 0.70 to 0.36. Limited-entry harvesting allowed significantly greater bull
survivorship into prime age classes (22–26%) than did open-entry harvesting (10%). The magnitude of
population response to limited-entry harvesting was dependent on the degree of hunter-access restriction.
Among open-entry strategies, three-point strategies allowed greater yearling survivorship, and consequently
slightly increased bull: cow ratios, compared to the any-bull strategy, but did not increase survivorship into older
age classes. Herd productivity did not differ among strategies
Minimum-point regulations have been used as a strategy to promote bull elk survival without limiting hunter
opportunity. In the northern Oregon Coast Range, average annual survival of bull elk was 0.57 (Beiderbeck et al.
2001). Bull survival did not differ among units with any-bull and minimum-point regulation types. In all three
units, more than 90% of the bulls were harvested before age 4, regardless of hunting regulation strategy. Based on
post-harvest elk population surveys and telephone harvest data, bull survival and proportion of bulls killed when
first legally available for harvest did not differ under any-bull and minimum-point regulations. With great hunter
pressure in the Oregon Coast Range, minimum-point regulations are not likely to increase the number of older
bulls without limiting hunter numbers
Bender and colleagues (2002) examined the Washington Department of Fish and Wildlife’s strategy allowing
open-entry spike-bull, limited-entry branched-bull elk harvest in the Blue Mountains (1989), Yakima (1994), and
Colockum (1994) herd areas of Washington, with goals of increasing the numbers of adult bulls to increase
breeding efficiency and possibly calf recruitment. The numbers of total bulls per 100 cows (x = 5.4) and branched
bulls per 100 cows (x = 5.3) increased with the change in harvest strategy, while the numbers of yearling bulls per
100 cows remained unchanged and the numbers of calves per 100 cows declined (x = -8.6). Calves per 100 cows
were always negatively correlated with both total bulls per 100 cows and branched bulls per 100 cows in each
area; correlations were significant in five of nine comparisons with total-bull ratios and five of nine comparisons
with branched-bull ratios. Open-entry spike-bull, limited-entry branched-bull harvesting can be used to increase
total-bull and branched-bulls ratios in hunted elk populations. However, the increased ratios of total bulls and
branched bulls were unimportant in influencing calf recruitment, likely because of the importance of female
condition on the production and survival of young.
Harvest on Tejon Ranch
Ten bull elk tags were authorized under the Tejon Ranch PLM for the fall 2011 season. Eight tags were issued,
and five trophy and three management bulls were harvested.
January 2013
Protection through the Private Lands Management Program
CDFG created the Private Lands Wildlife Enhancement and Management Area (PLM) Program, which offers
landowners incentives to manage their lands for the benefit of wildlife. This increases the benefits to a landowner
while preventing the conversion of private lands to land uses that are not compatible with wildlife, such as urban
development, cattle grazing, and logging. Landowners who enroll in this “ranching for wildlife” program consult
with biologists to make biologically sound habitat improvements that benefit wildlife, such as providing water
sources, planting native plants for food, and making brush piles for cover. In return for these habitat
improvements, landowners can charge fees for wildlife viewing, hunting, and fishing. This partnership between
wildlife managers and private landowners helps conserve and maintain wildlife habitat in California.
Participation in the program requires the submission and acceptance of a sound management plan. PLM areas are
licensed for a 5-year period; annual reviews ensure that agreed-upon habitat improvements have been made.
Working with CDFG, Tejon Ranch conducted a 3-year trial run from 1979 through 1982 of the PLM Program,
which allowed TRC to issue tags for the take of the state’s wildlife, set seasons that differ from CDFG’s, and also
required TRC to enhance habitat. The program proved successful, and TRC obtained a Private Lands Habitat
Enhancement and Management Area license permit through CDFG to continue it.
At 5-year intervals, TRC completes an application for the license, which CDFG (now CDFW) reviews and
approves at its discretion. In addition, each year, TRC completes an annual renewal application, which is then
approved by CDFW. Wildlife management activities are administered by TRC’s Ranch Operations department
and include a variety of individual hunts (both guided and unguided), hunting area leases, an upland game
hunting club, and fishing. Provisions of the PLM Program for all harvested species on Tejon Ranch include the
following:
▪
Generally, TRC directs guests and has developed incentive programs to encourage guests to pursue older
animals, thereby leaving younger, healthier animals to enhance species populations.
▪
When requested by the U.S. Department of Agriculture (USDA) or deemed appropriate by TRC, TRC
coordinates with USDA to perform sample blood tests and tissue samples on harvested animals and
submits those tests for USDA analysis.
▪
Upon request from CDFW, TRC submits samples from harvested animals to CDFW for analysis and
inclusion in CDFW’s ‘DNA database.
▪
TRC has banned 2-, 3-, and 4-wheeled off-highway vehicles to limit the ability of guests to go off
designated roads, limiting impacts to natural resources.
▪
TRC requires guests to remain on paved or dirt roads while traveling on the Ranch. If guests are found to
be in violation of this requirement and such violation results in environmental damage, TRC may require
the violator to restore the damaged areas to their pre-existing condition or may rescind the guest’s right
to access the Ranch.
▪
TRC informs guests of the ban on lead ammunition for protection of condors and requires that guests
comply with this lead ammunition ban.
Highway Crossings
Clevenger and Waltho (2005) found that seven attributes were correlated with summer use of crossing
structures by elk. Elk passage during summer was positively correlated and explained by structure width, height,
and openness. Crossing structure length and noise levels were negatively correlated with summer elk passage.
Elk passage during summer also showed a positive relationship with distance to forest cover and human use.
During winter, elk passage was positively correlated with crossing structure width, height, and openness and
negatively correlated with noise levels. Elk tended to use crossing structures far from forest cover in winter.
January 2013
Juvenile survival is the first parameter expected to change as resources decline, and it may be the predominant
driver of large herbivore population dynamics (Raithel et al. 2007). Thus, monitoring the cow: calf ratio among
elk is important.
Rabe and colleagues (2002) summarized recommendations for monitoring populations, including recommending
that direct methods to estimate wildlife population size (e.g., distance sampling, sightability adjustment
methods, mark–resight, quadrat counts) should be used whenever possible. Stratification by habitat type is a
logical choice, with separate surveys conducted in different habitat strata. For example, if the study area contains
five distinct habitats, managers could randomly select units from within each habitat and survey only those units.
Randomly selecting different units within each habitat during each survey year would provide the strongest
statistical inference to units not surveyed. Alternatively, selecting the same units during each survey year would
allow managers to detect population trends. The ideal protocol is a two-stage effort in which select,
representative units within each habitat stratum are surveyed during each survey year, while other units are
selected randomly and surveyed from within habitat strata. Survival estimates should be part of any survey effort
because survival of adult females and offspring has a large potential effect on population size over the long term.
Biologists have found that the best method for monitoring elk is through aerial surveys. To overcome the
potential biases associated with unequal detection probabilities in different conditions, researchers often develop
sightability models (Anderson et al. 1998). Using radio-collared elk, biologists determine the factors that
influence elk detectability. A predictive model is then used to correct subsequent population estimates
(Anderson et al. 1998). However, a sightability function must be developed for each elk population prior to use,
which requires extensive data (Eberhardt et al. 1998). Noyes and colleagues (2000) found that helicopter surveys
were able to detect population changes of 30–90%, which was no better than much less expensive fixed-wing
surveys ($28,000 v. $1,000).
Harvest Monitoring
Bender and Spencer (1999) believed that wildlife population estimators involving reconstruction from harvest
data and population ratios are an underused tool in wildlife management. They estimated population sizes for elk
in Michigan (1986 and 1991) and in Washington’s Green River watershed (1993 and 1996) by reconstruction from
harvest numbers, sex and age ratios, and mortality estimates. They constructed confidence intervals for the
population estimates using repeated population sampling and compared the estimates with independent
population estimates using mark–resight (Green River), total count (Michigan), and aerial sightability
(Michigan) methods. Population estimates from reconstruction did not differ from other population estimates,
and confidence interval widths (30–66% of mean estimates) were comparable to those of the other techniques
(22–47%) despite less sampling effort. Because harvest numbers and herd sex and age composition are commonly
collected for elk population trend analysis, population estimation from these parameters can provide managers
with a simple and useful tool to complement other population assessment techniques. Reconstruction can be a
simple and useful technique to estimate elk population size. Numerous regional elk bull mortality studies have
been developed, providing bull mortality rates, the lack of which have previously limited the utility of
reconstructing bull harvesting rates (Unsworth and Kuck 1993).
As White and Lubow (2002) indicate, the use of population models based on several sources of data to set
harvest levels is a standard procedure most western states use for management of mule deer, elk, and other game
populations. Thus, they presented a model-fitting procedure to estimate model parameters from multiple sources
of observed data. Typical data required include age and sex ratios, antlered and antlerless harvest, and population
size. Estimates of young and adult survival are highly desirable. Although annual estimates are desirable, the
procedure also can be applied‒albeit with less precision‒to data sets with missing values in any of the data series.
The model-fitting procedure adjusts input estimates and provides estimates of unobserved parameters to achieve
the best overall fit of the model to the observed data. The researchers believed that rigorous, objective procedures
such as those they described are required as a basis for wildlife management decisions because diverse
stakeholder groups are increasing the intensity with which they scrutinize such management decisions.
January 2013
Sutherland (2001) reviewed sustainable harvest and concluded that, for very many species, the simplest methods
are often the most practical. Often it is difficult to assess effort or demographic components such as density
dependence or population growth rates at a level of reliability that will provide estimates that are sufficient to
provide a basis for relatively accurate exploitation. The simple means, especially monitoring populations and
adjusting regulations according to long-term population changes, are probably often the best methods. In
applying these methods, it is very useful to be able to estimate the likely population in the absence of
exploitation. Studies on factors affecting the unexploited population size are thus particularly useful. Harvest
data (gathered using hunter success and reconstruction models following Bender and Spencer 1999) can be useful
for monitoring, but the harvest sample size on Tejon Ranch at present is probably too small for a robust model.
Mountain Thinking recommends much the same intensive approach for elk planning, management, harvest, and
monitoring that is described for mule deer (Section 10 of this wildlife assessment). Given the current trend,
numbers of elk will likely continue to increase on Tejon Ranch in the short term, and this will have important
implications for predator and scavenger abundance and possibly ecology of mule deer. Elk will likely be more
resistant than deer to predation and to competition with pigs because elk are grazers and rely on mast (acorns)
less than deer. Increased elk hunting opportunities may reduce pressure for more intensive deer management and
reduce the need for monetary return from feral pig harvest. Mountain Thinking believes there is good potential to
increase elk harvest. Also recommended is a cost-benefit assessment of ungulate harvest (including monitoring
costs) on Tejon Ranch and development of overall harvest objectives. Restricting bull harvest to oldest classes
appears to be a good strategy to increase bull survival to older age classes.
Mountain Thinking recommends producing a population estimate via aerial surveys to determine the current
level of harvest and the potential for increasing it. Follow-up surveys are recommended at 3- to 5-year intervals.
Continued monitoring of elk is also recommended via documentation of cow: calf ratios, and standardization of
those methods should be ensured, along with collection of hunter effort data. Mountain Thinking recommends
collecting similar types of data to those indicated for deer, including hunter success, age, weight, and score.
If elk were not already present on Tejon Ranch, Mountain Thinking would recommend reintroduction of the
native subspecies, tule elk. Given the relatively large population of Rocky Mountain elk established, however, it
would be difficult to start over, and nearby Rocky Mountain elk would again disperse to Tejon Ranch. Given the
proximity of tule elk on Wind Wolves Preserve and the ability of elk to move long distance, it is likely only a
matter of time before the two populations hybridize. This is not a significant concern for Tejon Ranch, but it is
for the tule elk on Wind Wolves Preserve, given the small population status of tule elk statewide.
Mountain Thinking recommends potentially reducing livestock densities to benefit ungulates on Tejon Ranch.
Experiments are also recommended to assess impacts of high densities of livestock and pigs on the Ranch. Also
recommended are increased use of prescribed fire or testing of mechanical methods to benefit elk and deer. All
such work should be done as an adaptive experiment to learn the optimal approach for Tejon Ranch.
R EFERENCES
Anderson, C., D. Moody, B. Smith, F. Lindzey, and R. Lanks. 1998. Development and evaluation of sightability
models for summer elk surveys. Journal of Wildlife Management 62:1055–1066.
Ballard, W., H. Whitlaw, B. Wakeling, R. Brown, J. De Vos, and M. Wallace. 2000. Survival of female elk in
northern Arizona. Journal of Wildlife Management 64:500–504.
Bender, L., and P. Miller, 1999. Effects of elk harvest strategy on bull demographics and herd composition. Wildlife
Society Bulletin 27:1032–1037.
January 2013
Bender, L., and J. Piasecke. 2010. Population demographics and dynamics of colonizing elk in a desert grasslandscrubland in northwestern New Mexico. Journal of Fish and Wildlife Management 1:152–160.
Bender, L., and R. Spencer. 1999. Estimating elk population size by reconstruction from harvest data and herd
ratios. Wildlife Society Bulletin 27:636–645.
Bender, L., P. Fowler, J. Bernatowicz, J. Musser, and L. Stream. 2002. Effects of open-entry spike-bull, limitedentry branched-bull harvesting on elk composition in Washington. Wildlife Society Bulletin 30:1078–1084.
Biederbeck, H., M. Boulay, and D. Jackson. 2001. Effects of hunting regulations on bull elk survival and age
structure. Wildlife Society Bulletin 29:1271–1277.
Coe, P. K., B. K. Johnson, J. W. Kern, S. L. Findhot, J. G. Kie, and M. J. Wisdom. 2001. Responses of elk and mule
deer to cattle in summer. Journal of Range Management 54:A51–A76.
Cook, J. G., B. K. Johnson, R. C. Cook, R. A. Riggs, T. Delcurto, L. D. Bryant, and L. L. Irwin. 2004. Effects of
summer–autumn nutrition and parturition date on reproduction and survival of elk. Wildlife Monographs 155.
Village, LLC. May. Eberhardt, L., R. Garrott, P. White, and P. Gogan. 1998. Alternative approaches to aerial
censusing of elk. Journal of Wildlife Management 62:1046–1055.
Gogan, P., and R. H. Barrett. 1987. Comparative dynamics of introduced tule elk populations. Journal of Wildlife
Griffin, K. A., M. Hebblewhite, H. S. Robinson, P. Zager, S. M. Barber-Meyer, D. Christianson, S. Creel, N. C.
Harris, M. A. Hurley, D. H. Jackson, B. K. Johnson, W. L. Myers, J. D. Raithel, M. Schlegel, B. L. Smith,
C. White, and P. J. White. 2011. Neonatal mortality of elk driven by climate, predator phenology and predator
community composition. Journal of Animal Ecology 80: 1246–1257.
Halbritter, H., and L. Bender. 2011. Condition, survival, and productivity of elk (Cervus elaphus) in the Sacramento
Mountains of southern New Mexico. Southwestern Naturalist 56:305–314.
Hobbs, N. T., D. Baker, G. Bear, and D. Bowden. 1996. Ungulate grazing in sagebrush grassland: effects of resource
competition on secondary production. Ecological Applications 6:218–277.
Howell, J., G. Brooks, M. Semenoff-Irving, and C. Greene 2002. Population dynamics of tule elk at Point Reyes
National Seashore, California. Journal of Wildlife Management 66:478–490.
Johnson, B., and J. Cushman. 2007. Influence of a large herbivore reintroduction on plant invasions and
community composition in a California grassland. Conservation Biology 21:515–526.
Johnson, B. K., J. W. Kern, M. J. Wisdom, S. L. Findholt, and J. G. Kie. 2000. Resource selection and spatial
separation of mule deer and elk during spring. Journal of Wildlife Management 64:685–697.
Long, R. A., J. Rachlow, and J. Kie. 2008. Effects of season and scale on response of elk and mule deer to habitat
manipulation. Journal of Wildlife Management 72:1133–1142.
January 2013
Lubow, B., and B. Smith. 2004. Population dynamics of the Jackson elk herd. Journal of Wildlife Management 68:810–
829.
McCorquodale, S., R. Wiseman, and C. Marcum. 2003. Survival and harvest vulnerability of elk in the Cascade
Range of Washington. Journal of Wildlife Management 67:248–257.
McCullough, D. R., J. Fischer, J. Ballou, and D. McCullough. 1996. From bottleneck to metapopulation: recovery
of the tule elk in California. Pages 375–403 in D. R. McCullough (ed.), Metapopulations and Wildlife Conservation.
Island Press, Washington, DC.
McCullough, D. R. 1969. The tule elk: its history, behavior, and ecology. University of California Publications in Zoology
88:1–209.
Melis, C., B. Jędrzejewska, M. Apollonio, K. Bartoń, W. Jędrzejewski, J. Linnell, and B. Zawadzka. 2009.
Predation has a greater impact in less productive environments: variation in roe deer, Capreolus capreolus,
population density across Europe. Global Ecology and Biogeography 18:724–734.
Meredith, E., J. Rodzen, J. Banks, R. Schaefer, H. Ernest, T. Famula, and B. May. 2007. Microsatellite analysis of
three subspecies of elk (Cervus elaphus) in California. Journal of Mammalogy 88:801–808.
Noyes, J., B. Johnson, R. Riggs, M. Schlegel, and V. Coggins. 2000. Assessing aerial survey methods to estimate elk
populations: a case study. Wildlife Society Bulletin 28:636–642.
O’Gara, B. W. 2002. Taxonomy. Pages 3-67 in D. Toweil and J. Thomas (eds.), Elk of North America: Ecology and
Management. Smithsonian Institution Press, Washington, DC.
Petersburg, M., and A. Alldredge. 2000. Emigration and survival of 2-year-old male elk in northwestern Colorado.
Wildlife Society Bulletin 28:708–716.
Polziehn, R., J. Hamr, F. Mallory, and C. Stroobeck. 2000. Microsatellite analysis of North American wapiti
(Cervus elaphus) populations. Molecular Ecology 9:1561–1576.
Rabe, M., S. Rosenstock, and J. deVos. 2002. Review of big-game survey methods used by wildlife agencies of the
western United States. Wildlife Society Bulletin 30:46–52.
Raithel, J. D., M. J. Kauffman, and D. H. Pletscher. 2007. Impact of spatial and temporal variation in calf survival
on the growth of elk populations. Journal of Wildlife Management 71:795–803.
Rowland, M., and M. Wisdom. 2000. Elk distribution and modeling in relation to roads. Journal of Wildlife
Management 64: 672–684.
Sargeant, G., and M. Oehler. 2007. Dynamics of newly established elk populations. Journal of Wildlife Management
71:1141–1148.
Skovlin, J. M., P. Zager, and B. K. Johnson. 2002. Elk habitat selection and evaluation. Pages 531–555 in D. E.
Toweill and J. W. Thomas (eds.), North American Elk: Ecology and Management. Smithsonian Institution Press,
Washington, DC.
Stewart, K. M., R. Bowyer, J. Kie, N. Cimon, and B. Johnson. 2002. Temporospatial distributions of elk, mule deer,
and cattle: resource partitioning and competitive displacement. Journal of Mammalogy 83:229–244.
January 2013
Stewart, K., R. Bowyer, J. Kie, B. Dick, and M. Ben-David. 2003. Niche partitioning among mule deer, elk, and
cattle: Do stable isotopes reflect dietary niche? Ecoscience 10:297–302.
Sutherland, W. J. 2001. Sustainable exploitation: a review of principles and methods. Wildlife Biology 7:131–140.
Unsworth, J., and L. Kuck. 1993. Elk mortality in the Clearwater drainage of north-central Idaho. Journal of Wildlife
Weisberg, P. J., N. T. Hobbs, J. E. Ellis, and M. B. Coughenour. 2002. An ecosystem approach to population
management of ungulates. Journal of Environmental Management 65:181–197.
White, G., and B. Lubow. 2002. Fitting population models to multiple sources of observed data. Journal of Wildlife
White, C. G., P. Zager, and M. Gratson. 2010. Influence of predator harvest, biological factors, and landscape on
elk calf survival in Idaho. Journal of Wildlife Management 74:355–369.
Wisdom, M. J, and J. G Cook. 2000. North American elk. Pages 694–735 in S. Demaris and P. R. Krausman (eds.),
Ecology and Management of Large Mammals in North America. Prentice Hall, Upper Saddle River, NJ.
PHOTO REFERENCES
Thadani, Ramesh. “Rocky Mountain Elk” July 2009 via Wikimedia Commons, Public Domain.
January 2013
8. Feral Pig ( Sus scrofa )
California’s feral pigs or hogs (Sus scrofa), sometimes also
referred to as “wild pigs,” are descendents of domestic pigs
kept by Spanish settlements in the late 1700s and Eurasian
wild boars introduced in the 1920s and 1950s (Mayer and
Brisbin 1991). Populations of feral hogs occur in at least 39
states (Gipson et al. 1998), with Texas harboring the
greatest population, estimated at more than 2 million. By
the early 1980s, feral pigs had spread to 33 of California’s
58 counties and were estimated to number 70,000–80,000;
they are now in 56 counties, and the current population
has been estimated at more than 133,000 individuals
(Waithman et al. 1999, Sweitzer and McCann 2007).
Preliminary results from analysis of pig harvest records
(Sweitzer and McCann, 2007) indicate that pigs have
expanded their range in California by more than 7,000
square miles between 1992 and 2004.
Feral Pig (© Tejon Ranch Company 2007)
Feral pigs were first recorded on Tejon Ranch in the early 1990s, having expanded from a ranch in the Cummings
Mountain area outside of the town of Tehachapi. Pigs are present in the Tehachapi Mountains and into the Piute
Mountain foothills, northeast of Caliente Creek. Young pigs have been seen west of Interstate 5 in the Lebec area.
Habitat Selection and Suitability
The Wildlife Society (TWS) (2011) calls feral hogs “extreme habitat generalists” and states that they can survive
in most areas of North America, feeding on plants and animals and changing their food preference based on
availability. Suitable habitats for hogs in California are described as oak woodlands, oak woodlands and mixedconifer forests, oak grasslands, and chaparral shrublands (Mayer and Laudenslayer 1988). In the central and
north-coast regions of California where hogs are most abundant, habitat conditions are ideal, with permanent
water and widespread oak woodlands providing forage. In these areas, sows may be able to reproduce at their
maximum rate of two litters of 5–6 piglets per year. Relatively low densities of wild pigs are found in more xeric
inland areas, where oaks and other suitable habitats are limited; this may be attributable to reduced survival of
offspring weaned during hot summer months (Barrett 1978).
Diet
Although feral pigs are omnivores, much of their diet (as reported in four studies from the Southeast) comprised
acorns, seeds, nuts, or roots (Gaines et al. 2005). However, more recent research is documenting a significant
amount of animals in the diets of pigs (Jolley et al. 2010, Wilcox and Van Vuren 2009).
POPULATION DYNAMICS
Density
Home range size of wild pigs in California ranged from 2.3–7.5 km2 (Sweitzer et al. 2000); the average was 2.5
km2. Density estimates for wild pigs in California ranged from 0.7 to 3.8 pigs per km2 (Sweitzer et al. 2000).
Applying Sweitzer and colleagues’ (2000) statewide density range to Tejon Ranch would yield a population
range of 764–4,150 individuals.
January 2013
Reproduction
According to TWS (2011), the hog is one of the most prolific large mammals and the most prolific ungulate in
North America. In productive habitat, female pigs can begin breeding as juveniles and, while most produce a
single litter annually, they are physiologically capable of reproducing twice a year. Individual sows may have
litters of more than 10, although litter sizes of three to eight are most common. These reproductive traits and a
typically low natural mortality rate result in the potential for high population growth.
In California, Sweitzer and colleagues (2000) reported in one study that the reproductive status of 82 females
derived from serum progesterone concentrations indicated that none of 14 subadult females and 40 of 68 (59%) of
adult females were pregnant. The number of suckled teats for lactating females indicated that they had an average
of 4.3 + 1.9 surviving offspring (range 2–8). Similar to data on population structure, annual and regional
differences were found in the reproductive status of female wild pigs (Sweitzer et al. 2000). For example, the
percentage pregnant females declined from 93 in 1994 to 13 in 1995 in the north coast region.
Predation
Predation may influence hog numbers and density in some areas. Gray wolves (Canis lupus) and Florida panthers
(Felis concolor coryi) are important predators of wild pigs in different parts of the pigs’ range (Maehr et al. 1990). In
California, mammalian predators capable of preying on wild pigs or their subadult offspring include black bears
(Ursus americanus), mountain lions (Puma concolor), coyotes (Canis latrans), and bobcats (Lynx rufus). Research in the
Central Coast region of California indicates that mountain lions’ diet comprised 5–38% hogs, depending on the
season (Hopkins 1989). A higher frequency of pigs was noted in the scats during the wet season (38%) than in
the dry season (11%). Regional variation was seen in densities of mountain lions in California, but data are
unavailable regarding whether predation on wild pigs by mountain lions contributes to regional variation in
densities of wild pigs. Pig populations were known to fluctuate within the study area of Hopkins (1989), and the
density of pigs may have influenced their use by mountain lions. Pigs comprised 42% of the diet of Florida
panthers (Maehr et al. 1990). Based on these two studies, cougars may be a significant predator of pigs on Tejon
Ranch. In addition, no data are available on whether, or how frequently, black bears, coyotes, or bobcats prey on
wild pigs.
Although pig populations increase rapidly, it is less clear at what rate pigs expand spatially. Few data are
available on the rate and distance of pig dispersal. Hampton and colleagues (2004), using genetic analysis of pigs
in Australia, reported that a relatively low estimate of 1.5 migrants per year was reached between pig populations.
Estimates of absolute dispersal distance ranged between 17.5 and 172 km per year (mean of 84 km per year),
suggesting that containment/control areas would need to be relatively large to ensure that pigs do not disperse
into new regions. Such scenarios assume that no deliberate, illegal relocation of feral pigs will take place through
human intervention; reinvasion from neighboring, independent pig populations is assumed to occur relatively
slowly because the movement of pigs between discrete populations is low.
Currently, the largest impediment to successful programs for feral pig control in Australia, including efforts to
achieve localized eradication, has arguably been the inability to delineate natural sub-population boundaries so
that control activities can be focused to ensure that density is reduced in those areas and reduction efforts
prevent impacts of pigs from extending beyond those boundaries (Saunders and Hedy 1988). Without reliable
knowledge of the spatial structure of feral pig populations, arbitrary boundaries are often chosen for establishing
eradication/containment zones for exotic disease contingencies (Saunders and Bryant 1988) and/or routine
control programs. Although the ability of such boundaries to reflect the true behavior and structure of feral pig
populations is unknown, they are unlikely to be always appropriate.
Brendan and colleagues (2009) selected 20 kilometers (km) to represent the possible natural dispersal of feral
pigs on the basis of previous Australian research, which had indicated that, although most pigs are sedentary
through time, some large movements occur (Saunders and Bryant 1988), including several pigs moving
approximately 20 km during an extended period under natural conditions in open country.
January 2013
Although pigs have been documented to move as far as 172 km, they typically exhibit a strong attachment to their
home ranges. Female pigs in Sweden were observed to disperse an average of only 4.5 km from their natal sites,
whereas males dispersed an average of 16.6 km (Truvé and Lemel 2003).
Social Organization
Social organization of pigs is believed to be typified by female sounders (matrilineal groups consisting of several
generations of related females and their offspring) and solitary adult boars (Martys 1991, Boitani et al. 1994).
Boitani and colleagues (1994) considered sounders to be “consistent and stable units,” although spatial overlap
between sounders was high (93%).
Groups of female feral pigs had a fission-fusion society such that a sounder formed subgroups that fused,
fissioned, and exchanged members. Gabor and colleagues (1999), working on a radio-collared population of pigs
in west Texas defined a sounder as a stable group of breeding-age females and their young that share a common
range and often form non-random subgroups. Sounders in Gabor’s study appeared to be territorial and, in
contrast to the report by Boitani and colleagues (1994), Gabor’s study showed little spatial overlap between
adjacent sounders. Ilse and Hellgren (1995) also reported little overlap between adjacent radio-collared females.
I MPACT ON P REY
Wild pigs may consume the eggs of ground-nesting birds, amphibians, and reptiles (Merton 1977, Jolley et al.
2010). In one study, wild pigs destroyed up to 28% of northern bobwhite (Colinus virginianus) nests in northcentral Texas (Tolleson et al. 1995). Feral hogs accounted for 10–25% of losses of simulated quail and turkey
(Meleagris gallopavo) nests in the rolling plains of Texas (Tolleson et al. 1995).
Direct consumption of native small mammals, such as ground squirrels (Spermophilus beecheyi) and voles (Microtus
sp.) has also been identified as a potential adverse impact of feral pigs (Loggins et al.2002, Wilcox and Van Vuren
2009).
In the Diablo Range of California, of 104 wild pigs collected, stomachs of 42 (40.4%) contained vertebrate
remains totaling 167 individual prey animals (Wilcox and Van Vuren 2009). The researchers identified prey
representing 20 species that included 11 mammals, five birds, three snakes, and one frog. California voles (Microtus
californicus) were the dominant prey species, totaling 109 individuals and occurring in more than one-third of all
pig stomachs. Botta’s pocket gophers (Thomomys bottae) also were common prey, with 26 individuals in 13% of
stomachs. The remaining 18 prey species were recorded as single occurrences in 1–6% of stomachs. These results
confirm that wild pigs in oak woodlands of the Diablo Range are consuming substantial numbers of vertebrates,
and that this phenomenon is common among pigs and persistent over time. The prevalence of multiple
vertebrates per stomach indicates that this is not an occasional event.
Bratton (1975) found that species richness of small mammal and herpetofaunal communities was reduced
because of habitat deterioration where wild pigs forage. Jolley et al. (2010) found that a substantial number of
herpetofauna are consumed by wild pigs on Fort Benning, Georgia, each year, and that some species appeared to
be focused on by pigs, which could potentially threaten those populations.
ECOSYSTEM DAMAGE
Aquatic systems. Feral hogs can have detrimental impacts on local water quality and aquatic biota (Kaller et al.
2007). At Pinnacles National Monument (PNM), California, the National Park Service (NPS) noted with great
concern that feral pigs were adversely affecting the limited wetland areas; these areas are a vital resource for
native wildlife, including the threatened California red-legged frog (Rana aurora) and California tiger salamander
(Ambystoma californiense) (NPS 2003, McCann and Garcelon 2008).
Competition. Considering the limited food available for native wildlife at PNM, feral pigs were viewed as
potential competitors with native animal species, including peccaries and deer (Ilse and Hellgren 1995, Focardi et
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al. 2000, Sweitzer and Van Vuren 2002). Feral hogs are a serious competitor for mast with white-tailed deer
(Yarrow 1987).
Plant communities. The deeper feral hogs root into the ground, the more plant roots or rhizomes are exposed to
the atmosphere, leading to reduced plant growth and increased plant mortality (Bratton 1975). Exposed roots
also make the plant vulnerable to mortality, either from exposure or because of subsequent herbivory by hogs or
other animals upon those exposed roots. In addition, feral hog uprooting of flood debris and leaf litter, even at
low to moderate intensities of impact, may adversely affect natural ecological processes (Kastdalen 1982, Lacki
and Lancia 1986). Plant debris and leaf litter on the ground surface serve as protective cover for small vertebrates
and invertebrates, and they also aid in the regeneration and succession of various plant species. Campbell and
Long (2009) reported that rooting by feral swine mixed the A1 and A2 soil horizons and reduced ground
vegetative cover and leaf litter, which nearly extirpated northern short-tailed shrews (Blarina brevicauda) and
southern red-backed voles (Clethrionomys gapperi) from intensively rooted areas (Singer et al. 1984).
The overall damage to vegetation from hog rooting or wallowing averaged 28% within three units of the Big
Thicket National Preserve (Chavarria et al. 2007). Singer and colleagues (1984) noted that understory plants
were absent in hardwood stands where wild pigs regularly root. Feral pigs may reduce oak (Quercus spp.)
regeneration through consumption of mast (Loggins et al. 2002). Some believe that pigs can facilitate dispersal of
nonindigenous plant species by exposing soil for colonization (Aplet et al. 1991, Cushman et al. 2004).
Tierney and Cushman (2008) showed that native and exotic plants from different functional groups varied
greatly in how they recovered from pig disturbances. Exotic taxa were generally able to colonize rapidly and
persist in pig disturbance areas, whereas native taxa usually exhibited a slow but steady rebounding following
pig disturbance. The researchers suggested that the health of coastal California grasslands may be enhanced
substantially by eliminating or greatly reducing the size of feral pig populations.
Summary of Impacts
While much of the information is more qualitative than quantitative, the mass of potential impacts of pigs to
plant and animal communities leaves little doubt of significant costs (Conservation Biology Institute 2009;
USDA, Forest Service 2012). Further quantitative data would be useful, but the evidence shows an overwhelming
need to act to reduce impact. Given the unique and imperiled resources on Tejon Ranch, the Conservancy should
begin work to reduce pigs rather than wait for unequivocal evidence of impacts.
Harvest
Feral pigs are a popular game species in California and are officially recognized as a game mammal by the State
(Waithman et al. 1999). Annual harvest of pigs in the 1990s averaged 30,000 individuals. Efforts to control
populations of wild pigs in parts of Australia and New Zealand suggest that it may be necessary to remove
upwards of 70% of the wild pigs annually in an area to reduce or maintain population numbers (Dzieciolowski et
al. 1992, Caley and Ottley 1995, Saunders 1993).
Evidence indicates that heavy hunting pressure on public lands and some private lands in California has been
effective in maintaining or reducing feral pig population sizes (Long 1993, Sweitzer et al. 2000). For coastal areas
of California, Pine and Gerdes (1973) reported densities of wild pigs of 0.5–0.8 pigs per km2 for a heavily hunted
area in Monterey County, whereas Schauss and colleagues (1990) reported densities of 3.2–4.7 pigs per km2 for an
unhunted regional park in Santa Clara County. Although the use of recreational or sport hunting to control wild
pig numbers in California is controversial, it appears that densities are lower in localized areas with moderate to
high hunting pressure. A problem for large-scale eradication is that more than 85% of the current statewide
population of wild pigs is in areas where hunting access is limited, such as state and federal parks, reserves and
natural areas, and private lands (Sweitzer and McCann 2007).
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Hebeisen and colleagues (2008) reported that, in Geneva, Switzerland, food availability affects the reproductive
success of wild boar and largely explains variation in population size between years. Even if hunting can
efficiently reduce population size (Geisser and Reyer 2004), it can also favor the regeneration of a hunted
population by increasing compensatory reproduction and survival attributable to greater availability of resources
for the remaining animals (Fernandez-Llario et al. 2003, Massolo and Mazzoni della Stella 2006). Therefore,
hunting may not be the most important factor to explain density variations, as similar population densities are
reported in hunted (Dardaillon 1986, Boitani et al. 1995b) and non-hunted (Fernandez-Llario and colleagues 1996,
Massei et al. 1997) areas. More likely, patchy distribution and changing availability of resources contribute to
lower (Spitz and Janeau 1990, Fernandez-Llario et al. 2003) or fluctuating (Sweitzer et al. 2000, Merli and
Meriggi 2006) densities. Geographic confinement (Baber and Coblentz 1986), absence of predators, and
abundant year-round food supply (Ickes 2001) can lead to extreme densities above those in the native range of
the wild boar in Europe. In many areas of California, the diversified habitat constituted by patches of oak forests,
wetlands, and agricultural areas provides good year-round feeding conditions and suitable resting sites.
Toigo and colleagues (2008) reported that, for wild boar in France, the overall yearly mortality rate was 50% for
all sex and age classes. Low survival was primarily attributable to high hunting mortality; a wild boar had a 40%
of chance of being harvested annually, and this risk was as high as 70% for adult males. Natural mortality rates of
wild boar were similar for males and females (approximately 15%).
Despite high mortality at all ages, the population still increased, with a five-fold increase in the number of pigs
harvested over the past 20 years. Toigo and colleagues (2008) found that harvest focused on adult males and
limited hunting pressure was directed to adult females and piglets, reducing the effectiveness of hunting to
control growth of wild boar populations. The researchers concluded that, to reduce the growth of wild boar
across a broad, agro-forested landscape highly sensitive to wild boar damage, wildlife managers need to be
willing to harvest piglets and females.
Between 2004 and 2006, Hanson and colleagues (2009) reported that 182 feral pigs were killed by lethal trapping
and shooting in a heavily harvested area in Georgia. Using hunter-returned ear tags, hunting success was found
to be slightly higher in the moderately harvested area (26% hunting mortality of ear-tagged pigs) than in the
heavily harvested area (19% hunting mortality of ear-tagged pigs). Lethal manipulation resulted in a total of 46%
of ear-tagged pigs being killed by both hunters and lethal control in the heavily harvested area, whereas 26% of
ear-tagged pigs were killed in the moderately harvested area. This research suggests that the most commonly
used management techniques for controlling feral pig populations in the United States may have limited success
for reducing pig densities or damage because density-dependent increases in reproduction and immigration can
easily outpace typical rates of removal, especially when the managed area is not fenced off or large enough to
provide a buffer to immigration. Further, effectiveness of these techniques is likely to diminish strongly as pig
densities and survival are reduced to low levels, suggesting they are unlikely to result in eradication.
Bieber and Ruf (2005) found that, for growing populations under good environmental conditions, particularly
following a full mast of acorns, yearly survival of juveniles should be reduced most, to approximately 15%
(including natural postnatal mortality), assuming 60% survival in yearlings and 70% in adults, to produce a
declining population growth rate.
The goal of pig harvest on Tejon Ranch is to reduce pig expansion and to provide revenue. Pig harvest peaked at
937 in 2003 and declined to 425 in 2005 and 160 in 2010. It is unclear whether this drop resulted from a decline in
pig abundance and availability or from hunter effort. In the 2012/2013 hunting season, TRC is targeting a harvest
of 1,200 pigs.
R OLE IN THE E COSYSTEM
According to TWS (2011), feral swine are one of the most significant modifiers of natural plant communities
worldwide. Damage by feral swine to property, agriculture, and natural resources results primarily from their
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aggressive rooting in the soil. In sandy soils, feral swine may root to a depth of 1 meter, but even shallow rooting
can cause significant soil erosion. Wallowing may reduce water quality and disrupt sensitive wetland
ecosystems. Hogs also destroy fencing and prey on young livestock, ground-nesting birds, amphibians, reptiles,
and other wildlife. Sweitzer and McCann (2007) indicated that 97 types of vertebrates and plants identified as
threatened, endangered, or rare are exposed to rooting and other activities of wild pigs in California.
No work has been done on Tejon Ranch to directly assess impacts of pigs, but anecdotal observations by
Conservancy biologists indicate that visible pig disturbance is extensive and the Conservancy considers feral pigs
to be a primary threat to conservation values.
SOCIETAL COSTS AND BENEFITS
Economic Costs
Economic losses from feral swine in North America are estimated at more than $1 billion per year and are
increasing (TWS 2011). A 2004 survey of Texas landowners found that, since feral hogs first appeared on private
property, damage estimates have averaged $7,515 per landowner statewide, with an estimated $2,631 per
landowner spent on control efforts and damage correction (Adams et al. 2005).
Estimating the amount and the associated value of hog damage allows for the application of benefit-cost analyses
to evaluate the need for and success of hog control from an economic perspective, or to compare the economics of
different hog management approaches (Engeman et al. 2007a). As outlined by Engeman and colleagues (2007b),
the benefit-cost model approach to hog management involves estimating the monetary value of the benefits
(measured in damage saved per hectare) and comparing this to the costs (measured in damage lost per hectare
plus control costs). The objective of minimizing opportunity costs is equivalent to maximizing net benefits.
Benefit-cost ratios (BCRs) can be calculated using the standard format of the ratio of benefits to costs. If a BCR is
greater than 1, then the rewards for hog removal exceed the costs, whereas a BCR of less than 1 would suggest
that hog removal conducted in that fashion is not economically efficient. When comparing management
approaches, the benefits of one approach are represented as the opportunity cost of pursuing an alternate
approach. Measured this way, the benefits of following approach 1 in lieu of approach 2 are represented by the
per-hectare value of damage saved by not pursuing approach 2. This implies that the benefits of approach 1 in
comparison to those of approach 2 are represented by the opportunity costs of pursuing approach 1. Or, seen in
another way, the benefits that accrue to each approach will be measured in terms of the cost savings compared to
alternate approaches. The BCRs must be evaluated in terms of the other approaches available. The benefits
accruing to approach 1 depend on the value of per-hectare habitat loss in the alternate approaches not followed.
The results of Engeman and colleagues (2007a) from many hog control projects have universally demonstrated
extraordinary economic benefits relative to the costs of control. For example, in Jonathan Dickinson State Park in
southeast Florida, damage to wet pine flatwood habitat was only 1%, but the value of that damage level to only 1
hectare exceeded the costs for control applied to the entire park (Engeman et al. 2003). In nearby Savannas
Preserve State Park, during only the first year of control in the vicinity of the remnant basin marsh, damage was
reduced from 19% to 7%. That reduction in lost habitat was valued between $1 million and $3 million, and the
corresponding benefit-cost ratios showed control to be 134 to 436 times greater in value than its costs (Engeman
et al. 2007b, 2004). On Eglin Air Force Base, which covers a large area of wildlands in Florida’s Panhandle,
recreational hunting was shown to have a beneficial effect on hog damage levels to imperiled seepage slope
habitat, with seepage slopes in areas open to hunting having 11% damage versus damage in 25% of unhunted
areas. However, less than a year after instituting hog removal in only the unhunted areas, damage there was
reduced to 7%. Moreover, an additional carryover effect was noted to the hunted (uncontrolled) areas whereby
damage dropped to 6%, making damage levels in the controlled (unhunted) and uncontrolled (hunted) areas
statistically indistinguishable. The resulting benefit-cost ratio for control was 55 to 1 (Engeman et al. 2007a).
Disease
Feral swine are highly mobile disease reservoirs and can carry at least 30 important viral and bacterial diseases,
along with a minimum of 37 different parasites that affect people, pets, livestock, or wildlife (TWS 2011). Some of
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the more important diseases potentially affecting people include leptospirosis, salmonellosis, toxoplasmosis,
trichinosis, bovine tuberculosis, brucellosis, and balantidiasis. Recently, there has been growing concern over the
role feral swine may play in the establishment of new strains of influenza viruses (e.g., pandemic H1N1 virus). The
potential for disease transmission from feral to commercial swine has serious implications for the U.S. economy.
Large, widely distributed populations of feral swine jeopardize ongoing efforts to control various livestock
diseases and the considerable financial investments that support those efforts (Hartin et al. 2007). For example,
the U.S. commercial swine industry recently achieved pseudorabies-free status after a 17-year effort and the
expenditure of approximately $200–250 million.
The role that feral swine could play in spreading and perpetuating exotic diseases is particularly troublesome.
For example, foot-and-mouth disease, which was eradicated in the US in 1929, would be essentially impossible to
eradicate again if it re-emerged in areas with feral swine. This would cripple the U.S. pork industry and would
likely have adverse impacts on wild species such as black-tailed and white-tailed deer, American bison, and
pronghorn. Landowners, outdoor recreationists, and state natural resources agencies also could be affected by
strict quarantines that would be necessary, preventing access to lands for hunting, wildlife viewing, and other
activities.
Benefits of Feral Pigs
Hunting income. In some cases, the presence of pigs can be seen as economically beneficial. For example, pigs
can be an asset to landowners who charge a hunting fee (Adams et al. 2005). During the past 10 years, the
California Department of Fish and Game (CDFG, now California Department of Fish and Wildlife) made
between $340,000 and $877,000 annually from the sale of pig hunting tags (CDFG unpublished data). However,
the state also invests a great deal of resources in pig management, and it is unknown if profits from tag sales can
offset the cumulative costs of management, damage to agricultural resources, and the extensive but difficult-toquantify impacts to natural resources. As TWS (2011) states, although feral swine are the second most popular
large mammal among hunters in North America (white-tailed deer are first), the problems they cause far
outweigh any positive benefits they provide.
Condor food. On Tejon Ranch, condors feed on both hunter-killed mammals and naturally deceased livestock. In
particular, because the hunting of wild pigs essentially occurs year-round, gut piles and discarded carcasses of
pigs, as well as other hunted animals, likely serve as primary attractants to condors on the Ranch.
Even so, when mortalities of cattle, sheep, native ungulates, wild pig, and other animals were combined, the U.S.
Fish and Wildlife Service estimated that substantially more carcasses per year would potentially be available
within the current Southern California population’s range than would be needed (2,160 carcasses) to support one
(California population) of the two populations of 150 free-flying condors identified in the Recovery Plan’s
downlisting criteria (Dudek 2012). Although pig harvest has declined significantly in recent years, there is no
indication of lower use of Tejon Ranch by condors as a result.
POPULATION M ANAGEMENT
Nonlethal Management
The use of chemosterilants to limit pig reproduction has been explored but is not yet feasible because of
continued methodological challenges (Sweitzer 2003). Nonlethal means on a large scale are not used for pig
control efforts because methods such as sterilization or relocation of animals are complex, labor intensive, and
not practical given the magnitude of the problem (Sweitzer 2003). Currently, no long-term methods for feral pig
sterilization are available that do not require field surgery of captured animals to implant hormone release
devices. Shorter term injection hormones are being tested, but none are currently approved for use in feral pig
control (West et al. 2009).
Lethal Management
On the Galapagos Islands, Cruz and colleagues (2005) removed 18,000 pigs over 30 years using a combination of
ground hunting and poisoning. A sustained effort, an effective poisoning campaign concurrent with the hunting
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program, access to animals by cutting more trails, and an intensive monitoring program all proved critical to the
successful eradication. Success required a continuous, minimum effort of 1,500 hunter-days per year. Hunter
access to pigs was critical. Extra trails were cut and goats were not hunted in order to keep vegetation
suppressed, allowing hunters and dogs access to all areas of the island. It is likely that pig-specific trained dogs
would have improved the efficiency of the hunting program. Feral pigs have also been eradicated from Santa
Catalina Island, Santa Rosa Island, Pinnacles National Monument, and Annadel State Park (Klinger et al. 2011)
and from Santa Cruz Island (Morrison 2008) by combinations of ground and aerial hunting.
The most widely accepted methods for control and eradication include trapping, snaring, shooting, use of trained
dogs, and aerial gunning. At levels of control most commonly observed, the reproductive potential of the residual
population may be stimulated because of density-dependent factors, necessitating the use of an array of control
methods. Although hunting is important for controlling feral hogs, hunting alone cannot eradicate feral hog
populations (TWS 2011).
It is important to note that hunting pressure, whether by recreational or professional hunters, can result in pigs
learning to avoid detection, such as by becoming more nocturnal or retreating to dense vegetation and/or
unhunted areas (Barrett and Birmingham 1994), so it is important to account for this factor in planning the
overall management strategy (Morrison et al. 2007, Morrison 2008). The effectiveness of shooting efforts can be
increased with the use of specially trained dogs (Schuyler et al. 2002), which may be especially useful in finding
individual pigs when population densities have declined, such as after other methods have been used or are found
to be ineffective. Effectiveness can also be increased by the use of “Judas pigs” (Wilcox et al. 2004, Morrison et al.
2007). In this case, pigs are captured, collared with radio or GPS collars, and released, and then are used to find
other, uncollared pigs. This may be most useful toward the end of an eradication effort, when densities are low
and the remaining pigs are difficult to find.
Cage traps have been used extensively in pig control and eradication programs, and this may be the most effective
control method in areas where pig densities are high. Although the timing and location of trapping need to be
carefully considered (to increase the probability of animals entering the trap), this method has been highly
successful, with as many as 14 pigs captured in one trap during one night (Barrett and Birmingham 1994).
Sweitzer and McCann (2007) reported that trapping was a primary method used by natural land managers in
California in their efforts to control or eradicate feral pigs. This method likely exhibits declining success as
population densities decline, as pigs learn, or during periods of high food availability, so it may work best in
combination with other methods such as shooting, possibly with the assistance of dogs or Judas pigs (Morrison
et al. 2007, Sweitzer and McCann 2007). Sweitzer and McCann (2007) reported that, during their survey of
natural lands managers, the most common method of lethal control was a combination of trapping and hunting.
Eradication v. Control
The selection of methods may be influenced by whether the goal is to control or completely eradicate feral pigs
from an area. Sweitzer and McCann (2007), in their survey of natural lands managers, determined that, although
most managers would prefer a complete eradication program, it was determined by many to be infeasible and
they therefore focused their efforts on control. Eradication programs may be infeasible due to lack of resources
(e.g., financial, personnel, equipment) and the complex logistics of removing large numbers of pigs from extensive
wild lands (Waithman et al. 1999, Bengsen et al. 2008). However, long-term costs of the two options should be
considered (Morrison 2008). Although eradication programs may initially exceed the cost of control programs,
the long-term cost of control options, including costs to natural landscapes and resources, should be accounted
for. Parkes and colleagues (2010) suggested that managers may opt for an eradication program over a control
program if the eradication option is less expensive in the long term than an ongoing control program, even when
complete eradication is not necessary to protect resources.
Other Management Options
Based on testing of one-, two-, and three-wire electric fencing, Reidy and colleagues (2008) suggested that
electric fencing is a valuable tool for excluding pig to reduce damages and should be included in a land manager’s
repertoire. No electric fence design they tested was 100% pig proof; however, electric fencing can significantly
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restrict feral pig movements. Therefore, combining electric fencing with other damage control methods in an
integrated management program may be the best method for alleviating feral pig damages and controlling
populations. However, efficacy of electric fencing to protect other economically and ecologically important areas
(such as orchards, livestock, and wetland habitats) from feral pig damage needs scientific evaluation.
Management Considerations
Feasibility. Because pigs may be well established throughout the region, eradication at Tejon Ranch could be
extremely difficult without fencing the Ranch. Work needs to be done to assess abundance, distance, and
management of neighboring populations to determine the feasibility of control and eradication efforts on Tejon
Ranch. Work also needs to be done to see what level of mortality can be imposed on pigs by hunting and other
means on the Ranch.
Exclusion fencing of small, very high-priority areas to reduce damage in the short term may be a viable option and
should be assessed.
Sociological and welfare issues. Any control work must be thoroughly justified and must meet stringent ethical
and scientific standards (Hecht and Nickerson 1999). Intensive killing of any species, especially beyond fair-chase
hunting, is always controversial, and a rationale and public information and education should be developed for
such work.
Cost. A high-intensity eradication program must be conducted to have any chance of pig eradication in a short
period (Dzieciolowski et al. 1992, Morrison et al. 2007). As discussed by Morrison and colleagues (2007), an
advantage of a high-intensity program is that fewer animals need to be destroyed because populations are not
allowed to mount an effective reproductive response. Although an intensive eradication program is costly, it is
lower than the cost of perpetual control or an eradication program that continues for decades. These trends are
apparent when comparing duration, number of pigs removed, and costs between eradication programs in
California and elsewhere (McCann and Garcelon 2008).
Donlan and Wilcox (2007) pointed out the lack of economic data for invasive mammal eradication campaigns.
Until such data are available, prioritization of invasive mammal eradications should proceed without input costs,
relying instead on biodiversity value, risk, urgency, and other important factors.
NPS spent $1.5 million to construct a pig-proof fence around Pinnacles National Monument (57 km2 or 1/20 the
size of Tejon Ranch) in central California. Pinnacles consists of contiguous stands of thick chaparral vegetation
across most canyons and ridge tops, ranging in elevation from 254 m to 1,007 m. NPS staff at Pinnacles allocated
$844,000 to eradicate pigs within the fenced area, and they have spent approximately $55,000 annually to
maintain the fence (Kreith 2007, McCann and Garcelon 2008). They removed 200 pigs over 3 years using
trapping, ground hunting, hunting dogs, and radio-collaring pigs. Trapping techniques removed most pigs, but a
combination of techniques was required to achieve eradication. McCann and Garcelon (2008) compared the
costs of seven pig eradication projects ranging in size from 20 km2 to 585 km2 and found costs to range from
$90,000 to $2,000,000 (the cost of eradication in the 585-km2 area was not given).
Capture–Mark–Recapture
Photographs obtained from automatic camera systems can identify individual wild pigs and yield a minimum
population value that is similar to population estimates based on mark–recapture estimates (Sweitzer et al.
2000). The estimated cost of sighting wild pigs at one research site in California, with populations ranging from
nine to 107 pigs, including initial purchase of four camera systems ($550 each), labor, and supplies, was $3,942–
$4,539.
Camera systems were placed in areas with wild pig activity near trap locations. The sighting effort varied
between years. The researchers most frequently used one camera station per successful trap in 1994, while in 1995
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they generally used two camera stations per successful trap. Camera stations were pre-baited with fermented
corn until trapping was completed, whereupon they were set for operation. To reduce estimate bias caused by a
closed population, resighting was completed within 1 month of captures at each research site. Camera stations
were equipped with transmitter and receiver units 8–12 m apart with the light beam positioned 25–30 cm above
ground.
Mark-sighting data were analyzed with program NOREMARK, which uses the Lincoln-Petersen model for
closed populations to estimate population size and offers four different estimators of population abundance
(White 1996). Sweitzer et al. 2000 used the Bowden estimator because of sighting heterogeneity among
individual wild pigs. The estimated area sampled by all traps at each site was determined by calculating the area
enclosed by the circles around traps minus areas of overlap. Because the home range sizes of wild pigs are
variable, an upper and lower range of the areas sampled by pig traps was estimated at each site based on the 95%
confidence interval (CI) for the mean. Mean densities were calculated by averaging (1) the NOREMARK estimate
of population size divided by the size of area trapped based on mean home range; (2) the lower value of the 95%
CI range for the estimated population size divided by the area trapped based on the upper 95% CI value for the
mean home range; and (3) the high value of the 95% CI range for the population size divided by the area trapped
based on the lower 95% CI value for the mean home range.
Hebeisen and colleagues (2008) estimated wild boar abundance and density using capture–resight methods in
the western part of the Canton of Geneva, Switzerland, in early summer from 2004 to 2006. Ear-tag numbers and
transmitter frequencies enabled identification of individuals during each of the counting sessions. The
researchers used resights generated by self-triggered camera traps as recaptures. Program NOREMARK provided
Minta-Mangel and Bowden estimators to assess the size of the marked population. The minimum numbers of
wild boars belonging to the unmarked population (juveniles and/or piglets) were added to the respective
estimates to assess total population size. Over 3 years, both estimators showed a stable population with a slight
diminishing tendency. Hebeisen and colleagues (2008) used mean home range size determined by telemetry to
assess the sampled areas and densities. The mean wild boar population densities calculated were 10.6 individuals
per km2 –with a variation of 0.8 standard deviation (SD) and 10.0 individuals per km2 –with a variation of 0.6 SD
with both estimators, respectively; these mean population densities are among the highest reported from western
Europe.
Line Intercept Transects
Line transects are recognized as one of the most practical and reliable methods for estimating densities of larger
mammals in most habitats (Buckland et al. 1993, Varman and Sukumar 1995, Williams et al. 2001). Ickes (2001)
conducted a line transect survey in a 2,000-hectare area in tropical forest in Malaysia. The 13 transects were 500–
1,600 m in length and each was walked five to 10 times over the course of the study period for a total transect
length of 12,880 meters; they detected 47 pigs per km2. The perpendicular distance to all pigs seen was recorded,
as was group size. Distance data were analyzed using program DISTANCE.
Steinmetz and colleagues (2010) conducted a pilot survey in 1999 (using four transects) to determine the sample
size required to track changes in pig and other ungulate indices in Thailand. Steinmetz and colleagues (2010)
determined that 30 transects should provide adequate power (greater than 80% chance) to detect a 25% change
in the population trend. Thirty straight strip transects (400 m long, 2 m wide, 15 transects in each habitat) were
monitored each year (2000–2005), except in year 1 when 13 longer (750-m) transects were used. Transects were
placed in each 1-km2 cell of the study area, separated by at least 400 m. Transects were not permanent and did
not follow animal or human trails. Each transect was divided into eight contiguous 50-m segments. Two
observers walked slowly (less than 1 km per hour) along transects, recording animal signs (e.g., tracks, dung) as
present or absent (undetected) in each segment. Surveys were conducted during the same month each year
(December) to avoid environmental and seasonal variation that might affect substrate (i.e., tracking conditions)
and animal activity. Species abundance and habitat use were inferred from the proportion of transect segments
with signs. Transects were the sample units.
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Tracking Index
Engeman and colleagues (2007b) found that indices of abundance, rather than absolute abundance estimates,
were the only practical means for monitoring hogs because of the difficulty of actually measuring feral hog
density. They developed a passive tracking index (PTI) that has been an efficient means to monitor feral hogs
(Engeman et al. 2001). Collection of these data has been vital for adapting and optimizing management strategies
to achieve maximal impact on hog populations with the resources available. The PTI was originated for
monitoring wild canids in Australia and subsequently proved effective for hogs (Engeman et al. 2001). This lowtech method involves placement of tracking plots throughout the area of interest in hog travel routes, such as dirt
roads or tracks. At each plot, the number of hog track sets (number of intrusions into the plot) is recorded for
two consecutive days at each assessment time. After 24 hours, the plots are examined for spoor and resurfaced
(tracks erased and surface smoothed) for the next day’s observations. The PTIs and associated variances are
calculated according to methods developed by Engeman (2005), where a mixed linear model describes the
number of intrusions on each plot each day. Adding to the robustness of the index, the variance formula
derivation was based on a nonzero covariance structure among plots and among days, that is, without
assumptions of independence among plots or days (Engeman 2005).
Maintaining permanent passive tracking plot locations maximizes index comparability over time, providing a
useful means to assess the changes in feral hog abundance while simultaneously providing information to
describe the spatial distribution of their activity.
For most study sites, the researchers created tracking plots 3 m long that spanned the dirt road or track
(Engeman et al. 2001). However, for Eglin Air Force Base, an extraordinarily expansive property, they dragged
chains behind a pickup truck to prepare plots 1.6 km long (Engeman et al. 2007a). While the same index
calculations are applicable to data from both plot designs, the resulting index values should be considered
different statistics that are not directly comparable because of the different dimensions of the tracking plots
(Engeman 2005). Applications of the tracking plot information and the PTI have included (1) optimizing the
timing and strategy for hog removal, (2) minimizing labor by identifying areas where hog removal would have
maximal effect, (3) assessing efficacy of removal efforts, and (4) serving as a detection method for reinvasion and
identification of directions from which reinvasion occurs.
Assessing and Monitoring Damage and Success of Removals
Engeman and colleagues (2007b) developed practical damage assessment methods to assess the need for and
success of hog management efforts. Protection and improvement of habitats have been the ultimate goals of these
hog removal efforts. Therefore, reliable and practical means to estimate damage levels provide a true evaluation of
the need for and efficacy of hog control. The ability to value the habitat resource provides an effective economic
management tool for evaluating conservation approaches. Economic analyses can greatly assist managers to
allocate limited funds toward habitat conservation most efficiently and effectively.
Due to variability among habitats and associated difficulty in traversing the terrain, the sampling methods of
Engeman and colleagues (2007b) had to be adaptable to different circumstances.
Chavarria and colleagues (2007) used several indices to quantify feral hog damage at Big Thicket National Park.
Sign type, especially that representing damage from hog activity, conforms to descriptions found throughout the
literature. These included sightings of live hogs, tracks and feces, wallowing areas, and rooting areas. Locations of
hog signs were georeferenced with GPS units. The GPS locations of hog damage were merged with the
vegetation-type shape files in ArcView to associate the area of impact and intensity of damage within each
vegetation type. Chavarria and colleagues (2007) estimated the area of each patch of hog disturbance by
calculating the area of a simple polygon and multiplied the longest length of the patch by its width through the
patch’s center. For clarification, disturbances that were outside the strip transects were not included. Only those
parts of a disturbance that were within the strip transect were included in the calculations. The summed area of
all patches of hog disturbance within the strip transects produced estimates of the total area affected for a given
unit of Big Thicket National Park. An index for intensity of hog damage, where x represents the depth of
disturbance for an individual patch, was created to note five categories of depth of soil disturbance: category 1
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was soil disturbance to a depth of 0.6–2.5 centimeters (cm), category 2 was 2.5–10 cm, category 3 was 10–20 cm,
category 4 was 20–30 cm, and category 5 was disturbance of 30 cm or more. Depth of soil disturbance for each
impact site was visually estimated by comparing the soil level of disturbed patches with the soil level of normal
(undisturbed) areas closest to the impact site. Two to four points of reference within each disturbed patch were
measured and averaged to provide a better estimate of depth of disturbance.
Random stratified sampling of vegetation. Chavarria and colleagues (2007) measured the extent and intensity
of rooting and wallowing activities by feral hogs in April–September 2005 in the BSU, LRU, and TCU units of
the Preserve. The surveys consisted of walking along strip transects comprising fixed segments 10 m wide by
approximately 1 km long. Transect locations were selected from a set of randomly generated options. From 24 to
40 transects were surveyed in each unit. A random, stratified sample of survey segments was selected for each
major vegetation type. Distance to water, park roads, oil and gas pipelines, and park recreational trails were also
recorded. Half of the selected transects were located less than 50 m from major water sources (i.e., creeks and
rivers), while others were more than 500 m from these water sources. Likewise, half of the selected transects
were less than 50 m from a park road, while others were more than 500 m from a park road. All transect locations
were at least 100 m from the park boundary.
Quadrat sampling. The researchers developed a quadrat sampling method for use in conjunction with the PTI
plot locations for estimating habitat damage by hogs (Engeman et al. 2003). Each tracking plot location defined
the location for two damage assessment plots. On one end of the tracking plot, they created a damage plot
located 1 m in perpendicular distance away from the tracking plot’s edge. Each damage plot was a 5-m x 1-m
rectangle, with the long dimension paralleling the road and located 1 m outward from it. Each 5-m x 1-m plot was
established using a 1-m x 1-m square constructed of PVC pipe. This square was folded over four more times
beyond its initial placement to establish the plot. The researchers placed sand-colored, wooden stakes in
diagonal corners to define the plot for future reference. They used string to divide the 1-m x 1-m square into four
equal quadrants. The second damage plot, defined at the same road location, was constructed in the same manner
on the opposite side of the road beginning 3 m in the opposite direction and leading away from the first damage
plot. In this way, the researchers could measure damage over 20 of these 0.25-m2 quadrants for each of the 5-m x
1-m plots. Damage was estimated as the mean percentage of area of damage across each plot.
The researchers also sampled seepage slopes for hog damage using 1-m x 1-m square quadrats, although the
quadrat placement was considerably different. Rather than being able to associate quadrat location with tracking
plot location, the isolated and confined nature of seepage slopes was best sampled by randomly placing the 1-m x
1-m quadrats throughout the seepage slope, with the same plot coordinates maintained over years (Engeman et
al. 2007a).
Line intercept sampling. Engeman and colleagues (2007a) also employed a line intercept sampling scheme to
effectively assess damage to the last remnant of a once-extensive basin marsh system in Florida (Engeman et al.
2004b). They spaced tape-measure transects through the area from the water’s edge to the interface between the
marsh and the surrounding community of upland vegetation (Engeman et al. 2004b). They then measured the
total distance of each transect, as well as the distance directly on the transect that was damaged by hogs. This
amount could represent a single patch of habitat or the combined distances of multiple patches. Damage was
estimated as the proportion of the mean transect that overlay areas damaged by feral hogs. The same approach
has also been designed (but not yet used) to estimate damage by a burgeoning feral hog population along stream
drainages in southeastern Colorado, and this approach could be applied to many riparian situations.
The Pigs and Peccaries Specialist Group (Oliver and Brisbin 1993) makes the following conservation
recommendations regarding wild pigs:
▪
Wild pigs or peccaries of any species or subspecies (or their domestic or feral derivatives) should never
be deliberately released to range freely outside their known recent and original distribution, and all
possible efforts should be made to prevent the accidental naturalization of domestic or wild populations
January 2013
of these animals. The only presently conceivable exception to this tenet might be in the event that such
an introduction was considered essential to the future survival prospects of a wild species or subspecies
that was extinct or seriously threatened throughout its original known range, and where (a) neither of
the preferred alternatives of reintroduction or translocation were possible or practicable, and (b)
available information was sufficient to indicate that any such introduction would not prejudice the
survival prospects of any other threatened organisms or communities that were native to the proposed
introduction site.
▪
All existing naturalized populations should be regarded as exotic pests that should be controlled,
reduced in numbers, or eradicated wherever possible and appropriate, unless and excepting those
(genetically isolated and threatened) populations that are considered to be of sufficient importance to
warrant their continued in-situ conservation.
The Wildlife Society (2011) has identified the following policies regarding feral swine:
▪
Promote the maintenance of biological diversity and ecosystem integrity and oppose the modification
and degradation of natural systems by feral swine.
▪
Encourage state and provincial agencies to eradicate feral swine wherever feasible.
▪
Support feral swine damage management actions that are cost effective and demonstrate results.
▪
Encourage research by public and private agencies and organizations on methods to control, reduce, or
eliminate feral swine and their impacts.
▪
Support programs to monitor diseases in feral swine and their impact on humans, domestic livestock,
pets, and wildlife.
▪
Encourage the collaboration of state, provincial, and federal agricultural and natural resources agencies;
private landowners; and organizations to develop and support educational programs and materials that
discuss the agricultural, ecological, and social damages caused by feral swine.
▪
Encourage the passing and enforcement of effective new laws and regulations at the state, provincial, and
federal level that would help reduce and combat the spread of feral swine and eliminate feral swine on
state, provincial, federal, and private lands.
▪
Encourage state, provincial, and federal agencies to share technical data on feral swine, such as maps of
local populations and other information for management purposes.
▪
Encourage the Association of Fish and Wildlife Agencies to provide leadership and consistent direction
on feral swine issues, including increased collaboration among all regulatory agencies and other
organizations involved with feral swine management.
▪
Support the establishment of a lead agency within each state or province to assume responsibility for
feral swine management.
Based on this assessment and the significant research of professional groups, biologists, and agencies (NPS 2003;
USDA, Forest Service 2012), the adverse impacts of pigs appear incontrovertible, and the Conservancy strongly
recommends that the goal on Tejon Ranch should be a significant reduction of pig abundance to substantially
reduce any serious impacts to high-priority plant and animals on the Ranch. A significant increase in hunting
pressure is recommended to start this effort.
January 2013
Mountain Thinking recommends following the general concepts of Campbell and Long (2009): Several step-wise
components will increase the likelihood of success of feral swine damage management programs (VerCauteren et
al. 2005). First, the problem should be clearly identified, including the types and timing of damage being caused,
as well as other biological, ecological, or sociological issues relating to the conflict. Second, the Conservancy
should obtain an understanding of the ecology and life history of feral swine as they relate to the conflict. Next,
the most effective, cost-efficient, humane, and socially acceptable management techniques should be selected and
implemented, using information gained through the first and second steps, to reduce the conflict. Lastly, an
assessment of the reduction in damage over time should be performed that considers multiple factors, such as
costs and impact of management action on feral swine and non-target populations, to evaluate the effectiveness
of the program.
The first step is to fully identify the problem. A comprehensive baseline assessment of the impacts of pigs should
be completed that will drive where pig reduction efforts are spatially focused and then conditions should be
monitored to assess success and allow adaptive management. Mountain Thinking recommends starting with
maps of the distribution of high-priority imperiled plants and animals; identifying the pigs’ impacts on and use of
various habitats may be a beneficial starting point. Field assessment of pig impacts on these areas should be
conducted using the monitoring techniques of Engeman and colleagues (2007b) or Chavarria and colleagues
(2007) described above. An assessment of pig diet on Tejon Ranch should also be conducted.
Mountain Thinking then recommends testing various options to reduce damage, including enclosure fencing in
small areas of high priority for imperiled species (although management may not be driven by imperiled species
per se on Tejon Ranch) where damage has been found, increasing hunting pressure in these sites, and monitoring
success. The response of pigs and the ecological community should be monitored to measure success and adapt
and to determine thresholds.
The program should be goal driven, and Mountain Thinking recommends as goals the significant reduction of the
threat that feral pig pose to unique or imperiled species or systems on Tejon Ranch and the ecological damage
that pigs cause overall. Quantitative measures should be developed for these goals.
Mountain Thinking recommends an adaptive approach focused first on assessing whether an intensive hunting
program can achieve these goals and, if not, then identifying additional methods. Incentives should be developed
for the hunt to allow maximum impacts. A good first step is to reduce pig density to half its current level, as this
appears to be the minimum level of harvest required to make a significant impact on the population and will be a
test of hunting potential. Any control work must be thoroughly justified and meet stringent ethical and scientific
standards (Hecht and Nickerson 1999).
In addition to a telemetry project (described below), Mountain Thinking recommends monitoring pig abundance
and testing techniques for efficiency on Tejon Ranch. Relative abundance can be monitored via the track survey
technique of Engeman and colleagues (2007b). A sampling methodology should be developed to test the power
and efficiency of that technique for long-term monitoring, especially with regard to hunting and impacts. The
camera trap and line transect techniques, outlined above, should also be tested. Mark–recapture methods using
cameras traps may be the most robust technique; as recommended for bobcats (Section 3 in this wildlife
assessment), these methods have many inherent advantages. The technique could apply an open-population
model whereby monitoring continues long term and employs a removal estimator using program MARK that
accounts for hunting removals (Williams et al. 2001). Finally, the Conservancy recommends monitoring the
population trend through catch per unit of effort. Hunter days of effort and success should be recorded for this
technique.
Mountain Thinking also recommends developing a comprehensive review and summary of efforts to reduce or
eliminate pigs in other places to learn the most appropriate approach and techniques. A cost-benefit analysis
would be especially useful.
Because complete eradication will likely be extremely costly and perhaps not possible, a suggested approach
would examine what level of hunting mortality can be imposed on pigs in addition to natural mortality and
January 2013
would monitor the ecological improvements as a result. The Conservancy recommends a project to assess causespecific mortality rates on pigs to determine if hunting and natural predation (e.g., by bear, cougar, bobcat, and
coyote) can keep pig density below a threshold where impacts are significantly reduced. Placing radio-collars on
a large sample of pigs (more than 50) with mortality sensors allows researchers to determine cause of death and
mortality rates (Kunkel and Pletscher 1999). Depending on results, this approach could be enhanced by
measuring kill rates (via telemetry) of the primary predator(s). It is anticipated that, in combination, bears,
cougars, coyotes, and bobcats may be significant limiting factors for pigs (especially on piglets). A telemetry
project will also allow Tejon Ranch to directly measure the ecological impacts of pigs on high-use areas to focus
control efforts, help determine pig abundance, and measure pig reproduction rates to determine the rate of
population change and level of harvest needed to reduce the population significantly. Pig density levels could be
correlated with plant and animal impact levels to develop management thresholds. Finally, such a project could
improve kill rates on pigs by determining high-use areas and leading hunters to pigs.
To assess what level of eradication is possible, relative pig abundance in the Tejon region should be assessed to
determine the likelihood of dispersal of pigs onto Tejon Ranch. Surveys of local landowners and government
agencies would be a first step, and then track surveys could be implemented in selected regions. Another
advantage of the telemetry project is the ability to assess dispersal rate and distance in pigs to determine
population boundaries and determine whether neighboring pig populations are a threat to Tejon Ranch.
Assessing the potential for highways to act as barriers to pig expansion could also be done. If neighboring
populations are small and distant, and low dispersal rates and short dispersal distances are found, then control
results on Tejon Ranch that approach eradication may be possible. Of course, unless these neighboring
populations are also controlled, over time their abundance and nearness will increase and dispersal to the Ranch
will become more likely. If neighboring populations are large and located nearby, then the work will be much
more difficult and expectations may need to be lowered. Alternately, TRC could develop harvest plans with these
neighbors to reduce abundance outside the Ranch to reduce the likelihood of high dispersal to Tejon Ranch. The
California harvest map indicates that the population on and around Tejon Ranch appear to be somewhat
isolated. It would be useful to explore this possibility further to determine if pigs could be eradicated with no
nearby source available to recolonize.
If increased hunting pressure along with natural predation cannot achieve the Conservancy’s objectives, use of
other tools should be examined, including training dogs, trapping, increasing hunter access in difficult areas, and
possibly employing professional hunters. Multiple, intensive, and focused control efforts are probably more
efficient than less intensive, long-term methods because pigs are very resilient. Again, measuring success and
adapting strategies is important.
Mountain Thinking recommends monitoring the behavior of condors as pig numbers decline on the Ranch to
detect any adverse consequences for condors; if an impact is noted, alternative food sources should be considered
for condors on Tejon Ranch, including domestic livestock carcasses.
Mountain Thinking advocates using Tejon Ranch as a demonstration site for conservation value of and
techniques for reducing pig abundance.
An assessment should be conducted of the economic impact that reducing pig abundance on Tejon Ranch would
have to hunting income, as well as ways to mitigate this. In the most likely scenario, pig harvest will continue on
the Ranch for the long term, but after intensive harvest over possibly a decade, the harvest should decline
significantly, perhaps to one third or less. Mountain Thinking advocates intensifying management of other
species for hunting to replace lost revenue (e.g., controlled burns for elk and deer management). Impacts to deer
populations with reduction in pigs should also be assessed. Work indicates that pigs and deer may compete for
resources, and reduction in pigs may increase availability of deer for harvest. This increase may readily
compensate for loss of pig harvest, as deer hunts cost four times as much as pig hunts. To investigate this
possibility, more intensive efforts to monitor deer populations should be conducted (Section 10 in this wildlife
assessment). Reducing pig density and the abundant food they supply to predators may also result in a reduction
of predator density, allowing an increase in deer and elk abundance.
January 2013
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Schauss, M. E., H. J. Coletto, and M. J. Kutilek. 1990. Population characteristics of wild pigs, Sus scrofa, in eastern
Santa Clara County, California. California Fish and Game 48:68–77.
Singer, F. J., W. Swank, and E. Clebsch. 1984. Effects of wild pig rooting in a deciduous forest. Journal of Wildlife
Spitz, F., and G. Janeau. 1990. Spatial strategies: an attempt to classify daily movements of wild boar. Acta
Theriologica 35:129–149.
Steinmetz, R., W. Chutipong, N. Seuaturien, E. Chirngsaard, and M. Khaengkhetkarn. 2010. Population recovery
patterns of Southeast Asian ungulates after poaching. Biological Conservation 143:42–51.
Sweitzer, R. A. 2003. Wild Pig Management Plan for Pacheco State Park. University of North Dakota Press, Grand
Forks, ND.
Sweitzer, R. A., and B. E. McCann. 2007. Natural areas ecological damage and economic costs survey report.
Unpublished report submitted to all interested survey respondents. Prepared by R. A. Sweitzer and B. E.
McCann. Department of Biology, University of North Dakota, Grand Forks, North Dakota, U.S.A. 37pp.
Sweitzer, R. A., and D. Van Vuren. 2002. Rooting and foraging effects of wild pigs on tree regeneration and acorn
survival in California’s oak woodland ecosystems. Pages 218–231 in R. B. Standford, D. McCreary, and K. L.
Purcell (technical coordinators), Proceedings of the Fifth Symposium on Oak Woodlands: Oaks in California’s Changing
Landscape. U.S. Forest Service, General Technical Report PSW-GTR-184. Pacific Southwest Research Station,
Albany, CA.
Sweitzer, R. A., D. Van Vuren, I. Gardner, W. Boyce, and J. Waithmann. 2000. Estimating sizes of wild pig
populations in the north and central region of California. Journal of Wildlife Management 64:531–534.
September 18.
January 2013
The Wildlife Society. 2011. Final Position Statement on Feral Swine in North America. Washington, DC.
Tierney, T. A., and J. H. Cushman 2008. Temporal changes in native and exotic vegetation and soil characteristics
following disturbances by feral pigs in a California grassland Biological Invasions 8:1073–1089.
Toigo, C., S. Servanty, J. Gaillard, S. Brandt, and E. Baubet. 2008. Disentangling natural from hunting mortality in
an intensively hunted wild boar population. Journal of Wildlife Management 72:1532–1539.
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Bethesda, MD.
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White, G. 1996. NOREMARK: population estimation from mark–resighting surveys. Wildlife Society Bulletin 24:50–
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Yarrow, G. K. 1987. The potential for interspecific resource competition between white-tailed deer and feral hogs
in the post oak region of Texas. Ph.D. dissertation, Stephen F. Austin State University, Nacogdoches, TX.
January 2013
9. Gray Fox (Urocyon cinereoargenteus )
Gray foxes (Urocyon cinereoargenteus) are widely distributed
from southern Canada to northern South America. They
are associated with woodland and scrub habitats and are
omnivorous. While relatively common, they are the least
studied fox, with very little work being completed on
them (Cypher 2003). For example, no estimates of density
are available from anywhere within their range.
In California, gray foxes are classed as furbearers and may
be taken from November 24 through the last day of
February with no limit. Dogs may be permitted to pursue
gray fox in the course of breaking, training, or practicing
dogs. There is no apparent record of California gray fox
harvest levels or any management objectives.
On Tejon Ranch, annual fox harvest ranged from 0 to 17
individuals from 1975 to 1986. There are no records of
harvest available since that time.
Gray fox (USFWS 2008)
Fedriani and colleagues (2000) identified behavioral dominance of coyotes over gray foxes and bobcats in the
Santa Monica Mountains because seven of 12 recorded gray fox deaths and two of five recorded bobcat deaths
were attributable to coyote predation and no coyotes died as a result of their interactions with bobcats or foxes.
Coyotes and bobcats were present in a variety of habitats types (eight of nine), including both open and brushy
habitats, whereas gray foxes were chiefly restricted to brushy habitats. A negative relationship was seen between
the abundances of coyotes and gray foxes across habitats, suggesting that foxes avoided habitats with high risk of
coyote predation. Bobcats were solely carnivorous, relying on small mammals (lagomorphs and rodents)
throughout the year and at all three sites. Coyotes and gray foxes also relied on small mammals year-round at all
sites, although they also ate significant amounts of fruit. Although there were strong overall interspecific
differences in food habits of carnivores, average seasonal food overlaps were high (that is, the ratio between the
two species being compared was close to 1.0, which would indicate complete overlap) because of the importance
of small mammals in all carnivore diets (bobcat–gray fox: 0.79, n = 4; bobcat–coyote: 0.69, n = 6; coyote–gray fox:
0.52, n = 4).
As hypothesized by Fedriani and colleagues (2000), coyotes used more food types and more habitat types than
did bobcats and gray foxes; overall, coyotes were the most abundant of the three species and ranged more widely
than did gray foxes. The authors proposed that coyotes limit the number and distribution of gray foxes in the
Santa Monica Mountains, and that those two carnivores exemplify a case in which the relationship between their
body size and local abundance is governed by competitive dominance of the largest species rather than by
energetic equivalences. However, in the case of the intermediate-sized bobcat, no such pattern emerged, likely
due to rarity or inconsistency of agonistic interactions and/or behavioral avoidance of encounters by subordinate
species.
Neale and Sack (2001) found high dietary-overlap indices between foxes and coyotes during summer and fall
(0.89), when fruits were prevalent in scats of both species. These were primarily manzanita (Arctostaphylos spp.)
berries. Rodents were highest in spring fox scats. Insects were also high in fox scats.
January 2013
POPULATION DYNAMICS
Density
Temple and colleagues (2010) studied radio-collared foxes in Georgia and found that they had larger home ranges
during winter (152.4 hectares [ha]) relative to breeding (91.4 ha) and kit rearing (99.6) seasons. Sizes of core
areas also differed among seasons, with larger core areas during winter (33.1 ha) than breeding (17.8 ha) and kit
rearing (21.0 ha) seasons.
Riley (2006) found that, in Golden Gate National Recreation Area, California, more than 50% of radio-collared
gray foxes were located in developed areas outside the park, particularly at night. For gray foxes, home range size,
core area size, home range overlap, and core area overlap did not differ significantly between the urban and rural
zones of the park. Roads represented home range boundaries for only one in five foxes; otherwise, human
structures seemed to affect foxes little. In a highly fragmented landscape in southern California (Riley et al.
2003), foxes actually appeared to reach their highest densities in areas near and including urbanization.
Harrison (1997) compared gray fox ecology and recorded bobcat sightings in rural residential and undeveloped
landscapes in New Mexico. Foxes appeared to tolerate and even benefit from residential areas as long as the
human density was not too high (fewer than 125 residences per km), and home range size was not significantly
different between foxes in the residential and undeveloped landscapes (Harrison 1997). This study also found
that gray foxes could coexist with roads, especially if culverts were present.
Ordeñana and colleagues (2010) found that the occurrence of gray foxes declined with both proximity and
intensity of urbanization, a somewhat surprising result for a species considered adaptable because of an
omnivorous diet and behavioral plasticity (Riley et al. 2003, 2006). In previous studies, gray foxes in southern
California were found to be tolerant of urban areas (Riley 2006) and were considered ‘‘fragmentation enhanced’’
because they were more abundant in smaller urban fragments (Crooks 2002). However, gray foxes typically
prefer natural vegetation, park interiors, and highly vegetated and wide corridors over human-altered landscapes
(Hilty and Merenlender 2004, Markovchik-Nicholls et al. 2008, Riley 2006). Gray foxes also may face intra-guild
predation by coyotes and, thus, may avoid sites in urban areas where coyotes are more active (Crooks and Soulé
1999, Farias et al. 2005, Fedriani et al. 2000).
In the Santa Monica Mountains north of Los Angeles, Fedriani and colleagues (2001) reported that gray foxes
were restricted largely to brushy habitat and suggested that they may avoid grasslands where coyotes were
particularly abundant, consistent with findings that gray foxes select for oak woodlands and against grasslands.
Although this may suggest that gray foxes have a threshold of tolerance for urban intensity, they can persist even
in small habitat fragments in southern California that are surrounded by high-density urban development,
particularly those with lower coyote activity (Crooks and Soulé 1999, Farias et al. 2005).
M ORTALITY
Generally in harvested populations, the major source of fox mortality is legal trapping (Cypher 2003). In
populations that are not trapped, gray foxes may more commonly be killed by other carnivores and raptors
(Cypher 2003) or by diseases such as distemper (Nicholson and Hill 1984), which can cause local population
reductions. The removal of larger predators has resulted in increases in the numbers of gray foxes, suggesting that
predation may limit some fox populations (Crooks and Soule 1999, Henke and Bryant 1999).
Temple and colleagues (2010) reported that mean annual survival was 0.61 for gray foxes in Georgia. Humanrelated factors (e.g., vehicle collisions and trapping) accounted for 63% of fox mortalities.
Farias and colleagues (2005) monitored radio-collared foxes in the Santa Monica National Recreation Area and
found that pup (0.4–1.0 year old) foxes had an 8-month (September–April) survival rate of 0.34, lower than the 8month (0.77) or 12-month (0.58) estimates for adult foxes. Interference competition was evident; 92% (11 of 12) of
January 2013
fox mortalities were the result of predation by sympatric coyotes or bobcats. Also, five of seven gray fox
mortalities were outside of, or on the border of, the home range of the killed fox.
The calculations of Farias and colleagues (2005) indicated that the fox population would remain stable if survival
of pups was greater than 0.68 during their first 4 months of life, greater than 0.58 for older pups, and greater than
0.75 for adults during September–April. This seems reasonable, yet sympatric carnivores, mainly coyotes, clearly
influence the fox population in southern California. Farias and colleagues (2005) found that the adult annual
survival rate (0.58) was somewhat lower in southern California than for a fox population in South Carolina that
was not trapped (0.69) (Weston and Brisbin 2003), but about the same as that of a trapped population in
Mississippi (0.56, calculated from data in Chamberlain and Leopold 2000).
In examining the genetic structure of a fox population in western Texas, DeYoung and colleagues (2009)
reported that the genetic data were consistent with recent field observations derived from radiotelemetry and tag
returns, which have indicated that gray foxes may move 20 kilometer (km) from their initial capture site. Their
data suggested that long-distance movements in Texas gray fox (on the order of tens of kilometers) may be more
common than previously suspected. A high rate of dispersal appears a likely explanation for the lack of
population structuring they observed.
Ruell and Crooks (2007) described a novel hair-snare design and sampling protocol that successfully sampled
four sympatric carnivore species (bobcat, mountain lion, coyote, and gray fox) in three habitat blocks in coastal
southern California. Scat surveys were also successful at sampling bobcats and other carnivores in the area. Hair
and scat sampling methods had similar species identification success (81% and 87%, respectively) using
mitochondrial DNA amplification and restriction enzyme digestion patterns. Therefore, for studies focused on
the distribution and activity of a suite of carnivore species, the authors recommended a combination of
noninvasive methodologies, such as targeting hair and scat surveys toward species and sites where they are most
effective.
Foxes may be relatively easy to trap and handle in box traps, similar to island foxes and kit foxes. As such,
capture–mark–recapture population methods (using PIT tags) may work well for population estimation (Kunkel
and Neale 2010).
Fox populations persist in highly urban areas and disperse well, so it is anticipated that connectivity is not a
critical issue for foxes. However, no foxes were recorded moving through highway crossings on and near Tejon
Ranch (Dudek 2009). As for other species, Mountain Thinking recommends continued monitoring of these
crossings.
Given that hunters receive no food or economic benefit from harvest of foxes (fur price for a gray fox pelt in 2012
was $10 in Maine), Mountain Thinking recommends that the Conservancy develop objectives for any fox harvest.
A comprehensive gray fox management plan for Tejon Ranch would be of much benefit for the Ranch and would
be an excellent example, given that the California Department of Fish and Wildlife has no plan for or limit to fox
harvest. If harvest is proposed, Mountain Thinking recommends establishing low levels of harvest, given the high
level of predation from coyotes and the lack of any density estimates for foxes. An assessment is recommended of
the effects of harvest on foxes if the proposed harvest is substantial. Developing the first density estimate for
foxes anywhere within their range would be a valuable contribution to gray fox conservation.
January 2013
R EFERENCES
Chamberlain, M. J., and B. D. Leopold. 2000. Spatial use patterns, seasonal habitat selection, and interactions
among adult gray foxes in Mississippi. Journal of Wildlife Management 64:742–751.
16:488–502.
Crooks, K. R., and M. Soulé. 1999. Mesopredator release and avifaunal extinctions in a fragmented system. Nature
400:563–566.
Cypher, B. L. 2003. Foxes‒Vulpes species, Urocyon species, and Alopex lagopus. Pages 511–546 in G. A. Feldhamer,
B. Thompson, and J. Chapman (eds.), Wild Mammals of North America: Biology, Management, and Conservation,
second edition. Johns Hopkins University Press, Baltimore, MD.
DeYoung, R., A. Zamorano, B. Mesenbrink, T. Campbell, B. Leland, G. Moore, R. Honeycutt, and J. Root. 2009.
Landscape-genetic analysis of population structure in the Texas gray fox oral rabies vaccination zone. Journal
Village, LLC. May.
Farias, V., T. K. Fuller, R. K. Wayne, and D. Sauvajot. 2005. Survival and cause-specific mortality of gray foxes
(Urocyon cinereoargenteus) in southern California. Journal of Zoology 266:249–254.
Fedriani, J. M., T. K. Fuller, R. Sauvajot, and C. York. 2000. Competition and intraguild predation among three
sympatric carnivores. Oecologia 125:258–270.
Harrison, R. L. 1997. A comparison of gray fox ecology between residential and undeveloped rural landscapes.
Hilty, J. A., and A. M. Merenlender. 2004. Use of riparian corridors and vineyards by mammalian predators in
northern California. Conservation Biology 18:126–135.
Kunkel, K. E., and G. Neale. 2010. Island Fox (Urocyon littoralis clemente) Monitoring and Research on Naval
Auxiliary Landing Field, San Clemente Island, California. U.S. Navy.
Markovchick-Nicholls, L., H.M. Regan, D. H. Deutschman, A. Widyanata, B. Martin, L. Noreke, and A. T.
Hunt.2008. Relationships between human disturbance and wildlife land use in urban habitat fragments.
Conservation Biology 22:99–109.
Neale, J. C., and B. Sacks. 2001. Food habits and space use of gray foxes in relation to sympatric coyotes and
bobcats. Canadian Journal of Zoology 79:1794–1800.
Nicholson, W. S., and E. Hill. 1984. Mortality in gray foxes from east-central Alabama. Journal of Wildlife
Ordeñana, M., K. Crooks, E. Boydston, R. Fisher, L. Lyren, S. Siudyla, and D. Van Vuren. 2010. Effects of
urbanization on carnivore species distribution and richness. Journal of Mammalogy 91:1322–1331.
January 2013
Riley, S. 2006. Spatial ecology of gray foxes and bobcats in urban and rural zones of a national park. Journal of
Riley, S. P. D., J. P. Pollinger, R. M. Sauvajot, E. C. York, C. Bromley, T. K. Fuller, and R. K. Wayne. 2006. A
southern California freeway is a physical and social barrier to gene flow in carnivores. Molecular Ecology 10:1–9.
Riley, S. P. D., R. M. Sauvajot, T. K. Fuller, E. C. York, D. A. Kamradt, C. Bromley, and R. K. Wayne. 2003. Effects
of urbanization and habitat fragmentation on bobcats and coyotes in southern California. Conservation Biology
17:566–576.
Ruell, E. W., and K. R. Crooks. 2007. Evaluation of non-invasive genetic sampling methods for felid and canid
populations. Journal of Wildlife Management 71:1690–1694.
Temple, D. L., M. Chamberlain, and M. Conner. 2010. Spatial ecology, survival and cause-specific mortality of
gray foxes (Urocyon cinereoargenteus) in a longleaf pine ecosystem. American Midland Naturalist 163:413–422.
Weston, J. L., and I. Brisbin. 2003. Demographics of a protected population of gray foxes (Urocyon cinereoargenteus)
in South Carolina. Journal of Mammalogy 84:996–1005.
January 2013
10. Mule Deer ( Odocoileus hemionus )
Populations of mule deer declined throughout most of
their historic range (western United States) in recent
decades, and numbers in the 1990s were well below peak
population levels documented during the 1940s–1960s
(Johnson et al. 2000, Stewart et al. 2002). This led several
agencies to reexamine their management strategies for
deer (Gill et al. 2001), in the same way they dealt with
similar concerns in the 1970s. Previous research on mule
deer population declines has evaluated potential effects of
predators (Whittaker and Lindzey 1999, Pierce et al. 2004,
Bishop et al. 2005), weather (Unsworth et al. 1999),
hunting (White et al. 2001, Erigüson et al. 2003), grazing
by domestic livestock (Bowyer and Bleich 1984, Kie et al.
Mule deer (© Natalie Bruno 2012)
1991, Ragotzkie and Bailey 1991), interspecific interactions
(Johnson et al. 2000, Stewart et al. 2010) and changes in
habitat (Sawyer et al. 2009) on mule deer demographics.
The relative importance of those factors across the range of mule deer, however, is poorly understood and
continues to be debated.
As Unsworth and colleagues (1999) outlined, the mule deer decline that occurred throughout the American West
from the late 1960s through the mid-1970s prompted a symposium of deer experts from various state and federal
agencies, but no consensus on causes was reached (Workman and Low 1976). The evidence for a decline was
even questioned, and the debate exposed problems in techniques for collecting and evaluating deer population
data. Whatever the causes contributing to the apparent decline during that period, populations apparently
rebounded over the next 15 or more years. Concern arose once again when another widespread decline occurred
during the 1990s. Thus, it appears that large-scale environmental conditions can trigger widespread declines in
mule deer populations.
T EJON R ANCH S TATUS
The deer population on Tejon Ranch has generally followed the overall trend. Asserson (1984) reports that, from
1965 to 1972, the mule deer herd on Tejon Ranch declined to 2,000–3000 animals from more than 6,000 (probably
because of African louse from cattle), but he provided little evidence for this. Fawn: doe ratios declined from 58
fawns per 100 does in the 1950s to 25–30 fawns per 100 does in the late 1970s and early 1980s. Asserson
speculated that additional problems were likely plant succession, cattle competition, and rural development, but
he provided no evidence to support his speculations. The herd increased to 6,200 in the 1970s. Population
estimates were made during 1956–1984 following the methods of Dasmann (1952) and Longhurst and colleagues
(1952). No population estimates have been made since 1984, when the deer population was found to be 4,374
(Asserson 1984).
No long-term trend in doe: fawn ratios has been seen since 1980, but significant year-to-year cycles have been
observed (Figure 10-1). Tejon Ranch data appear to suggest that recruitment (as measured by doe: fawn ratio) is
associated with precipitation (Figure 10-2). The correlation between the previous year’s precipitation and the
fawn: doe ratio was 0.25; however, the relationship was not significant (p = 0.25).
January 2013
Source:
Based on unpublished TRC data
Figure 10-1
Trend in Fawn: Doe Ratios on Tejon Ranch, 1980-2010.
Note:
Doe: fawn ratio (mdfawn) is positively correlated with the previous year’s annual precipitation (PREPRECIP), but the correlation is not
statistically significant.
Source:
Based on unpublished TRC data
Figure 10-2
Relationship between Mule Deer Doe: Fawn Ratio and Precipitation on
Tejon Ranch.
January 2013
Tejon Ranch Harvest
The Tejon Ranch herd management unit occupies 450 mi2 and consists of three sub-herds, with most of the unit
located on the Ranch. High harvest occurred in the 1950s and 1960s (an average of 480 bucks per year), declining
in 1970 to 333 bucks per year. Antlerless hunts were first conducted in 1968 and have taken place off and on since
that time. Harvest has declined generally and slightly since the mid-1990s. Hunter days have not been monitored
consistently since 1993, so it is unclear whether the decline relates to a decline in deer abundance.
Based on TRC guide reports, the population of deer on the Ranch continues to be low compared to pre-1998
levels. Of the 250 either-sex tags (170 regular-season tags and 80 late-season tags) authorized under the Tejon
Ranch Private Lands Wildlife Enhancement and Management Area (PLM) Program for fall 2011, 210 tags were
issued; 100 buck deer were harvested (42 regular-season deer and 58 late-season deer). In addition, TRC decided
to reduce the number of antlerless tags issued to the California Deer Association for the Junior Hunt because of
the decrease in overall herd size; of the 30 antlerless tags authorized, 12 were issued (all to the California Deer
Association Junior Hunt) and 11 antlerless deer were harvested.
Table 10-1
Tejon Ranch Deer Harvest, 1997–2011
Buck Harvest
Antlerless Harvest
Fall
Regular
Late
Total
Buck
Either Sex
Antlerless
Total Antlerless
Total Harvested
1997
100
53
153
1
29
30
183
1998
121
40
161
2
33
35
196
1999
91
70
161
–
–
0
161
2000
90
71
161
–
30
30
191
2001
69
50
119
8
37
45
164
2002
74
37
111
13
37
50
161
2003
59
36
95
16
34
50
145
2004
39
49
88
15
26
41
129
2005
41
47
88
12
32
44
132
2006
48
38
86
1
20
21
107
2007
65
34
99
–
19
19
118
2008
57
53
110
–
25
25
135
2009
52
54
106
–
25
25
131
2010
47
47
94
–
24
24
118
2011
42
58
100
–
11
11
111
Note
– = no data collected
Source:
Fall 2011 marked the 10-year anniversary of the Quality Deer Management (QDM) Program at Tejon Ranch,
which encourages hunters to harvest older deer and hunters not harvesting a deer would be permitted to take
January 2013
additional pigs in exchange for unused deer tags. Generally, the QDM Program is effective, but Ranch
management is committed to improving deer management techniques going forward.
Table 10-2
Tejon Ranch Deer Herd Composition, 1999–2012
Fawns per 100 Does
Bucks per 100 Does
Total Deer Classified
Year
Fall
Spring
Fall
Fall
Spring
1999–00
41
32
42
178
– **
2000–01
48
–
32*
211
158
2001–02
12
–
24
151
–
2002–03
17
16
27
2003–04
29
–
46
182
–
2004–05
31
7
26
442
249
2005–06
59
–
28
457
–
2006–07
22
24
24
250
159
2007–08
53
11
40
487
66
2008–09
17
15
34
252
178
2009–10
39
29
27
227
180
2010–11
73
–
41
374
–
128
Gross Numbers of Deer Observed
Year
Bucks
Does
Fawns
Total Deer
2011–12
34
142
113
289
Notes: – = no data collected
All observations are on the ground (observations from the air were eliminated due to infrequency of
counts).
*
Counts were conducted post-season, so number of bucks per 100 does is slightly lower than
counts conducted pre-season.
**
Composition counts for this period were conducted in conjunction with CDFG; these were
the first counts conducted using GPS and spotlights
Source:
In southern Idaho, using a long-term data set on cougars and mule deer, Laundré (2010) found that, within a
heterogeneous landscape, which species ‘‘wins’’ the predator-prey response race depends on where the race takes
place. Deer ‘‘win’’ in open areas; cougars ‘‘win’’ in forest edges. Across the landscape, the overall outcome of the
response race will depend on relative amounts and sizes of safe v. risky habitat. If a landscape is predominantly
safe habitat, the prey’s response will dominate and researchers can predict high prey densities and prey: predator
ratios, as in the Serengeti of Africa. If risky habitat predominates, the predator wins and researchers can predict
lower prey densities and prey: predator ratios or even local extinctions of prey. Of course, these outcomes change
with diversity of predators (Kunkel et al. 2012).
January 2013
POPULATION DYNAMICS
Effects of Habitat Management
Bishop and colleagues (2009), studying mule deer in western Colorado, conducted an experiment to assess the
impact of improving habitat quality on deer population dynamics. They hypothesized that the causes of deer
decline in the American West include lower habitat quality resulting from altered fire regimes and associated
plant successional changes, invasion of noxious weeds, overgrazing, energy development, and urban development
(Watkins et al. 2007). Many pinyon–juniper communities are considered degraded, primarily because of altered
fire patterns and excessive grazing, and therefore warrant proactive management (West 1999). Proposed
strategies to restore pinyon–juniper communities could likewise improve deer habitat productivity (Watkins et
al. 2007). However, there is a need to evaluate the effectiveness of various habitat treatments for mule deer
(Bergman 2008).
Hurley and colleagues (2011) conducted an intensive predator control study in southeast Idaho measuring deer
population parameters in response to reductions in coyote (Canis latrans) and mountain lion (Puma concolor)
numbers. Coyote reductions caused an increase in neonatal deer survival during some years, although coyote
predation on neonates was found to be partially compensatory. Coyote reductions had no measurable effect on 6month-old fawn survival, adult female survival, or population size. Cougar reductions caused an increase in deer
survival that resulted in a small increase in population size.
Bishop and colleagues (2009) conducted a complementary study in Uncompahgre, Colorado, manipulating deer
nutrition but not manipulating coyote and mountain lion predation. Winter-range habitat predominantly
comprised late-seral pinyon (Pinus edulis)–Utah juniper (Juniperus osteosperma) woodlands with minimal
understory vegetation and limited species diversity. In contrast, anecdotal evidence indicated that summer range
(mosaics of aspen [Populus tremuloides], mountain shrub, mountain big sagebrush [Artemisia tridentata], and Gambel
oak [Quercus gambelii] with vigorous understory) was highly productive for deer. The researchers hypothesized
that poor habitat quality on winter range contributed to the observed decline of the deer population. Predation
by coyotes and mountain lions was presented as a competing hypothesis for the cause of the population decline.
Bishop and colleagues (2009) implemented an instantaneous increase in nutritional carrying capacity (NCC) of
winter-range habitat by supplemental feeding of deer and measured deer population responses. They did not
manipulate predator numbers or any other potential limiting factor. Their study evaluated the effect of enhanced
nutrition on pregnancy rates and numbers of fetuses produced; fetal, neonatal, and overwinter fawn survival; and
annual survival of adult females. They then used these estimates to quantify the effect of enhanced nutrition on
the rate of population change. Their ultimate goal was to determine whether habitat was limiting a deer
population in which predation was the most common proximate mortality factor.
They observed a large treatment effect in overwinter fawn survival. Overwinter survival of fawns receiving the
treatment averaged a survival rate of 0.91, whereas overwinter survival of control fawns averaged 0.68. Nutrition
treatment had a positive effect on yearling recruitment, expressed as the product of fetal, neonatal, and
overwinter survival rates. Survival of treatment fetuses to the yearling age class was 0.45, whereas survival of
control fetuses to the yearling age class was 0.27. Nutrition treatment had a positive effect on annual survival of
adult females (treatment survival rate 0.88, control survival rate 0.83).
Combining all fecundity and survival rates into a matrix population model, Bishop and colleagues (2006)
observed an increase in population growth rate (lambda) in response to enhanced nutrition. Average population
growth rate was 1.17 for treatment deer and 1.03 for control deer. Treatment caused population growth rate to
increase by 0.14 during 2001–2002, 0.11 during 2002–2003, and 0.155 during 2003–2004. Averaged across years,
treatment caused population growth rate to increase by 0.13.
Increased production and survival of young (i.e., fetal, neonatal, and overwinter survival) accounted for 0.08 of
the overall increase in population growth rate, and increased survival of adult females accounted for the
remaining 0.05 increase in population growth rate. The treatment effect on overwinter fawn survival alone
January 2013
accounted for 0.04 of the increase in population growth rate. Enhanced deer nutrition caused a reduction in
coyote and mountain lion predation of 6-month-old fawns and adult females. The large increase in population
growth rate in response to enhanced nutrition indicates that the deer population was food limited and, therefore,
limited by habitat in terms of forage quality.
The large effect of enhanced nutrition on carrying capacity in the presence of ongoing predation suggests that
habitat was ultimately the critical limiting factor of the Uncompahgre, Colorado deer population. The degree to
which disease may be adversely affecting the deer population remains unclear; however, these findings indicate
that disease would not restrict population growth if the deer obtained adequate nutrition.
An ongoing study is quantifying the effects of habitat treatments in pinyon–juniper woodlands on deer
population parameters (Bergman et al. 2007). Habitat treatments in the pinyon–juniper woodlands could
improve habitat productivity by increasing the quantity and diversity of higher quality forage. Treatments would
likely cause the greatest increase in diet quality during winter, although late fall and spring diets might also
improve because of increased forage availability. During the past decade, roller-chop and hydro-axe treatments
have been used to reduce pinyon–juniper woodlands and then reseed them with mostly native species, with the
intent to increase the quantity and diversity of forbs, grasses, and certain browse species.
The current late-seral status of pinyon–juniper woodlands on the Uncompahgre Plateau, which was the basis for
the hypothesis for causes of deer decline, is not unique. Many pinyon–juniper communities are considered
degraded, primarily because of altered fire patterns and excessive grazing, and therefore these habitats warrant
pro-active management (West 1999).
The study by Bergman and colleagues (2007) provides support for evaluating the effectiveness of habitat
treatments for deer in pinyon–juniper winter range. Specifically, research is needed to determine whether habitat
improvement, as opposed to artificial nutritional supplementation, is capable of causing an increase in
population growth rate.
Bishop and colleagues (2009) and Gaillard and colleagues (2000) provided detailed reviews of density-dependent
effects on the fecundity and survival of ungulates. If a population is limited by NCC and demonstrates densitydependent feedback, wildlife managers have two main options for improving fawn production and survival. One
option is to increase adult female harvest to reduce adult female density and thereby provide more forage per
individual, which will increase fawn production and survival. Under this option, the management goal is to
optimize age and sex ratios to increase the number of adult males available for harvest (McCullough 1979, 2001).
A second option is to improve habitat quality for deer to increase total deer numbers. When deer populations are
below NCC, predation will more likely be a source of additive mortality and biological concern (Ballard et al.
2001). If a population is limited by predation, wildlife managers should pursue management options other than
those mentioned above. First, adult female harvest should be minimized, or at least managed conservatively, to
maximize production and survival of young. Second, predator control or increased harvest of predator species
may reduce mortality and increase deer numbers. Habitat treatments and predator control can be costly in terms
of both economic and social capital. Neither option should be pursued without adequate justification.
In another study assessing impact of habitat quality on mule deer, specifically changes in habitat over 20 years,
Anderson and colleagues (2012) documented an increase in grassland from 3.5% to 30.7% of the study area in
southeast Idaho and a corresponding decrease in agricultural land, which provides high-quality forage for mule
deer, from 37.8% to 12.5% of the study area. Patterns of resource selection were generally similar between the two
periods. Nevertheless, selection of agricultural fields and areas far from roads by mule deer increased significantly
between the 1980s and 2007–2009. In addition, juniper stands were strongly selected in all years, and importance
values for grassland and sagebrush steppe increased between past and current periods. The results of this study
indicated that mule deer responded behaviorally to declining availability of high-quality forage (i.e., agricultural
land) by increasing selection of agricultural fields. Such functional responses in habitat selection may have
important consequences for the dynamics of mule deer populations.
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Habitat and Climate
Lomas and Bender (2007) found that survival of radio-collared fawn mule deer in north-central New Mexico was
driven by an interaction of total and seasonal precipitation and its effects on plant production, consequential
effects on female nutrition, and ultimately, fawn birth attributes. They found that habitat conditions were so
poor throughout north-central New Mexico during 2002 and 2003 (and likely during other drought years) that,
based on birth attributes, few fawns could have survived, regardless of proximate causes of mortality. In 2004,
precipitation enhanced security cover, maternal body condition, birth attributes, and, thus, survival of fawns.
Deer populations in north-central New Mexico were ultimately limited by the poor condition of females and,
consequently, by low fawn survival. Signs that a population is nearing habitat carrying capacity include poor
body condition, low natality rates, low fawn: doe ratios, high utilization of available forage, and high deer
densities (Ballard et al. 2001). Most of these characteristics, aside from high deer densities, were evident in mule
deer in north-central New Mexico. Odds of fawn survival increased as precipitation increased; the principal
effect of precipitation on fawn survival was likely increased plant growth, resulting in better forage conditions
and, consequently, increased female body condition and hiding cover. Much previous work has shown that
habitat conditions for deer improved with increased precipitation during the growing season. Although adequate
precipitation alone in the Southwest may enhance deer condition enough to maintain high survival, additional
habitat improvements, such as establishment of more drought-tolerant foods (shrubs v. forbs or grasses), are
likely needed to realize the high rates of population increase necessary for rapid recovery of mule deer
populations.
Pojar and Bowden (2004) captured and radio-collared more than 200 fawns in western Colorado over three years
and identified the following recommendations for management. Mule deer have high reproductive potential and,
given adequate resources, will produce positive-growth recruitment. Reduced herd density and increased range
production are two means of increasing resources for individual animals. The herd they studied had been
managed with bucks-only harvest for more than 10 years, which typically results in the population trending
toward carrying capacity. Reduced density through doe harvest is a management strategy that fits the theory of
population dynamics and should be applied cautiously, with adequate monitoring of population response.
Mature monoculture stands of pinyon–juniper woodlands and aging sagebrush stands are being modified by land
management agencies to enhance forage production. Although expense limits the amount of terrain that can be
treated annually, these management practices will produce long-term benefits and should be continued to the
extent possible.
Pojar and Bowden (2004) observed that, because of political pressure, the prime management action proposed to
increase herd recruitment was predator control, ignoring numerous possible causes for deer population declines
(Ballard et al. 2001). These results do not provide evidence to suggest that predators are the cause of low
recruitment. Coyote predation accounted for 13% of the neonatal mortality, whereas bear and feline predation
accounted for 4% and 3%, respectively. The researchers were uncertain, however, about how much of this
predation is additive mortality, although some portion of the predation is certainly compensatory mortality that
would have occurred even in the absence of predators. Regardless, implementing a predator control program
would require a societal value judgment based on logistic feasibility, cost, and the ethics of reducing one species
to enhance another.
Bender and colleagues (2007), working in northern New Mexico, found that body condition of adult does was
negatively related to the amount of pinyon-juniper woodland in their home range. Pinyon-juniper communities
typically produce little understory vegetation (unless disturbed), for various reasons. As a consequence, little
forage is generally available in pinyon-juniper communities as canopy cover increases. These researchers found
that forbs and shrubs (considered moderate- or better-quality forage for mule deer) constituted 0% and 5.7% of
the total ground cover in pinyon-juniper communities, respectively. This lack of preferred forage likely
contributed to the strong negative relationship between deer body-fat levels and the proportion of pinyonjuniper communities in home ranges.
January 2013
Mule deer are sensitive and vulnerable to human-related and other disturbance, and they depend on cover to
limit the energy losses from having to flee disturbance or from being killed by natural or human predators;
pinyon-juniper communities provided this cover. Management strategies aimed at enhancing deer condition
must improve nutritional attributes of pinyon-juniper communities while maintaining the role of these
communities as security cover.
Bender and colleagues (2007) found that montane conifer was the third predominant habitat type in their study
area and showed similar vegetation characteristics as pinyon-juniper woodlands, but with less understory
development because of higher overstory stem densities and canopy cover. Thinning of the overstory canopy in
montane conifer types has consistently been shown to be the key management strategy to allow development of a
diverse and productive understory in the Southwest. Shrub communities, primarily oak brush and mountain
mahogany (Cercocarpus montanus) in north-central New Mexico, are highly preferred by mule deer for both food
and cover (, and shrubs typically make up more than 80% of mule deer diets in pinyon-juniper woodlands and
other arid habitats (Boeker et al. 1972).
Bender and colleagues (2007) recommend that management should include opening of the canopy in strips or
savannahs, but not complete removal unless other habitat features (such as deciduous shrubs) are present that
could similarly serve as security cover. Prescribed burning after canopy removal, in late winter or early spring,
could also help increase forage quality by freeing nutrients bound in litter and slash and enhancing protein levels
in forage during the late gestation and early lactation periods. Management treatments emphasizing late winter
or spring burns can be used to keep communities in early successional stages and, thus, can be of greatest
potential benefit to mule deer.
The minimum number of mule deer occupying Round Valley, California, east of the Sierra Nevada, during winter
declined by 84%, from 5,978 in 1985 to 939 in 1991; annual surveys indicated that the population remained
between 900 and 1,400 during 1991–1995 (Villepique et al. 2011). Subsequently, the deer population rose to 2,165
(24 deer per km2) by January 1999. The decline in deer population was associated with a severe drought during
1987–1990, when the water content of the winter snowpack was 27% of the long-term mean. Decreases in an
index to abundance of cougars lagged behind declines in populations of mule deer, with a reduction of about 50%
during 1992–1996 (Pierce et al. 2000). Pierce and colleagues (2012) examined whether top-down or bottom-up
forces were driving the mule deer population. They reported that, for mule deer, bitterbrush (Purshia tridentata) in
diets, per-capita availability of bitterbrush, kidney fat indexes, fetal rates (young per adult female), fetal weights,
and survivorship of adults and young indicated that the period of decline was typical of a deer population near or
above the carrying capacity of its environment. Numbers of mountain lions also declined, but with a long time
lag. The period of increase was typified by deer displaying life-history characteristics of a population below its
environmental carrying capacity, yet the finite rate of growth (lambda = 1.10) remained below what would be
expected for a population rebounding rapidly toward its carrying capacity (lambda = 1.15–1.21) in the absence of
limiting factors. Life-history characteristics indicated that the mule deer population may be regulated by bottomup forcing through environmental effects on forage availability relative to population density. However,
predation (mostly by mountain lions) was likely additive during the period of increase; thus, top-down forcing
slowed, but did not prevent, population growth of mule deer.
Lawrence and colleagues (2004) found that, in western Texas, variation in weather patterns (i.e., drought) was
associated with‒if not causative of‒annual variation in survival patterns. Survival of adult females and young had
the strongest correlation with drought.
Harvest
Pac and White (2007) compared harvest regulations on two sites in the Bridger Mountains of Montana and
found that few males on the West Slope lived beyond 4 years to enter age classes associated with maximum
antler size because of combined effects of non-hunting and hunting mortality. Hence, the two-point buck
January 2013
regulation provided ample hunting opportunity to unrestricted numbers of hunters but failed to enhance
representation of older, large-antlered males.
Restricted hunter participation and lower harvest rates associated with the outfitted hunt on South 16 Mile did
not result in greater representation of males aged 4 years compared to the West Slope. The South 16 Mile
population experienced higher non-hunting mortality of fawns, yearlings, and mature males, essentially negating
any survival benefits related to lower harvest.
Overwinter survival of male fawns exerted a primary influence on potential recruitment of males into older age
classes. Although survival of male fawns was consistently lower on South 16 Mile compared to the West Slope,
both populations fluctuated in synchrony across the 6-year study period. Apparently, environmental conditions
associated with year-to-year differences in fawn survival affected both study areas simultaneously.
Unsworth and colleagues (1999) reported that wide year-to-year variation in environmental conditions is
characteristic of the northern Rocky Mountains and represented the primary source of variation in overwinter
fawn survival. Consequently, the adult age structure was periodically subjected to recruitment of numerically
small cohorts. In both populations that Pac and White (2007) studied, this tendency adversely affected the
relative abundance of adult males to a greater degree than adult females because males comprised fewer age
classes. At the conclusion of the study, poor survival of the 1994 and 1995 cohorts in the West Slope population
contributed to a 77% decrease in the number of adult males counted on helicopter surveys during 1995–1997 and
a decline in the adult male: female ratio from 18: 100 to 5: 100 (Mackie et al. 1998).
Unsworth and colleagues (1999) summarized that cumulative effects of non-hunting mortality among all age
classes reduced the effectiveness of two hunting regulations designed to enhance survival of males to age class of
4 years associated with maximum antler development, despite accomplishing reductions in harvest rates. Low
and variable fawn survival and relatively high non-hunting-related losses of yearling and mature males might be
typical of many populations in the northern Rocky Mountains. When implementing harvest regulations to
improve representation of mature males, deer managers should avoid populations coexisting with a diversity of
large predators in environments with strong annual weather impacts.
Lukacs and colleagues (2009) found that overwinter fawn survival rates in Colorado were considerably higher
than values reported by Unsworth and colleagues (1999). Mean overwinter fawn survival was 0.72 in the study
by Lukacs and colleagues (2009), whereas Unsworth and colleagues (1999) reported mean overwinter fawn
survival for Colorado, Idaho, and Montana as 0.44. Given the estimates by Lukacs and colleagues (2009) of fawn
and adult female survival, the average inflection point dropped and the ratio needed for increasing population
was 0.47 fawn per adult female. The average fawn: doe ratio in the period of their data collection was 0.55, with
most years greater than 0.47; this suggests that the decline in mule deer populations in Colorado noted by
Unsworth and colleagues (1999) had likely ended, and the population now has the potential to increase
depending on the rate of female harvest.
Moreover, the similarity of results from Lukacs and colleagues (2009) and Unsworth and colleagues (1999) for
doe survival suggest that doe survival is a relatively constant value, and the estimates in these two publications
provide a sound reference point for areas without information about adult female survival.
The process distribution of fawn survival presented by Lukacs and colleagues (2009), in conjunction with the
distribution presented in Unsworth and colleagues (1999), suggests that managers should consider both the
immediate environmental conditions and those in a broader window of time. For example, scenarios should be
considered in which fawn survival and fawn: doe ratios have been high for several years, followed by a hard
winter with low survival, compared with a hard winter following a series of years with lower fawn survival. The
apparent serial correlation in fawn survival suggests that less conservative actions are needed in the first scenario
than in the second when setting hunting license allocations because fawn survival rates are likely to return to
levels observed in recent years.
January 2013
Bishop and colleagues (2005) documented that, in Colorado, changes in the population structure occurred, but
they concluded that limiting sales of antlered deer licenses was useful as a tool for improving hunt quality, rather
than for achieving population performance objectives. According to Bergman and colleagues (2011),
circumstantial evidence indicates that, in response to statewide limits on buck harvest (although not designed as
a density-dependence experiment), limiting deer license numbers in Colorado resulted in the replacement of
fawn mule deer with adult males. Although the statewide deer herd grew between 1999 and 2006, it did so
disproportionately in favor of adult males.
McCullough (2001) tested density dependence in black tailed deer at the Hopland Research Station (HREC) in
northwestern California to determine the value of female harvest management. In this region (as in most of the
arid western United States), it has been reported that rainfall drives vegetation productivity and, consequently,
deer carrying capacity (Longhurst et al. 1952). Furthermore, the acorn crop is thought to be important to deer
productivity (Longhurst et al. 1952). In this study, however, neither rainfall nor acorn crop was related to male
harvest or female reproductive rate. The fact that male harvest increased during the worst rainfall conditions on
record, and independently from acorn crop, underscored the concept that density reduction is the most plausible
variable accounting for this result.
The HREC pre-hunt estimates were 315 deer by the line-transect method and 332 by the mark–resight method.
The total harvest of all deer was 68, or 21.5% of the pre-hunt population by the line-transect estimate and 20.5%
by the mark–resight estimate. This is a high rate of removal for a mule deer population. McCullough (1979)
reported the average maximum sustainable yield of white-tailed deer at the George Reserve to be an annual
removal of 32.9%, but an average rate of removal would overexploit the population in below-average recruitment
years. A simulated fixed removal rate that was sustainable with environmental stochasticity was 26.8%. Based on
simple models, McCullough (2001) estimated the maximum sustainable yield in a mule deer population in a good
environment to be about 27% of the pre-hunt population.
The response of the deer population to reduced density at HREC was expressed mainly as increased male
harvest, and less as increased male quality as measured by body mass and antler size. This was in agreement with
Brownlee (unpublished, as cited by Connolly 1981), who found that mean male mass and antler size declined
with increased harvest on the Black Gap Management Area in Texas. Based on Brownlee’s study and modeling,
Connolly (1981) concluded that the highest yield and highest trophy quality were incompatible. The results from
HREC support this conclusion.
Rainfall and acorn crops, the environmental variables thought to be most important to deer in coastal California,
showed no statistical relationship to male harvest at HREC during this study (Connolly 1981), whereas female
removal did. Although HREC shows high variation between years in rainfall and acorn production, it appears
that the effect of female removal, and the consequent changes in density of the population, overrode the influence
of environmental variables.
The HREC population sustained a harvest of both sexes of an estimated 20.5–21.5% of the pre-harvest numbers.
This harvest rate was sustained for 7 years during the most extended drought in the California rainfall record.
Female harvest must be evaluated in terms of the relative importance of environment and density acting on a deer
population, which vary with the severity of the environment. Furthermore, the risks of proactive management
must be weighed against the periodic occurrence of catastrophic events, such as extremely hard winters or
droughts, which typically are devastating for high-density populations. The relative decline in numbers of the
oldest, largest males at HREC during the treatment period (if real; it was not statistically significant), might be a
disadvantage to proactive management in locales where trophy quality is the goal of management. These changes
were a consequence of the downward shift in age structure with heavier harvest. Still, antler size of young males
that composed the bulk of the harvested animals at HREC increased during the treatment period. Thus, hunters
took not only more males during the treatment period, but males of higher average quality; only the largest
trophy class declined. The trade-off between a few superior males and many more good-quality males must be
considered in judging the benefits and costs of proactive management.
January 2013
Proactive approaches can lead to overexploitation, so prudence is advisable. Proactive management should be
pursued in the context of a management experiment or adaptive management. It is imperative to monitor the
population (McCullough 1990) so that management can be altered if the results differ from predictions. Even if
the population can be monitored effectively, interpreting population declines is difficult because, in a sustainable
harvest, an initial decline of the population in response to increased harvest is inevitable before stability is
reached (McCullough 1979). This non-intuitive response is easily misinterpreted as overharvest. It is difficult to
distinguish a decline resulting from a sustainable harvest that will lead to stability from a decline that will not
achieve stability because of overharvest. For this reason, it is advisable to implement harvests incrementally and
allow the population to achieve stability at each step before taking the next step.
Competition with Other Species
Johnson and colleagues (2000) examined resource selection between elk and mule deer and found that mule deer
avoided elk. Whether direct competition led to reductions in mule deer numbers was not determined. Hamlin
and Mackie (1989) concluded that the mule deer population in Montana reached two all-time peaks despite a
three-fold increase in elk numbers during the previous 20 years. A third, apparently higher peak in mule deer
numbers occurred in 1993–94. It is unknown whether further increases in elk numbers will negatively influence
mule deer populations. Elk-deer interactions are also addressed in Section 7 of this wildlife assessment.
No significant annual trend has been seen between the invasion of pigs and their increase in abundance on Tejon
Ranch in the early 1990s and mule deer doe: fawn ratios (Figure 10-1). Research elsewhere, however, has found
that pigs have a significant impact on deer (as described in Section 8 of this wildlife assessment).
Interactions with Livestock
Kie and colleagues (1991) found that, in the Sierra Nevada, deer spent more time feeding and less time resting
when cattle stocking rates were increased. During 1984, a year of average precipitation, deer spent more time
feeding per day in late summer than in early summer in range units grazed by cattle, but did not do so in
ungrazed range units. In 1985, a drier year, deer spent less time feeding per day in late summer in grazed range
units. Time spent feeding by deer was negatively correlated with standing crops of herbaceous forage in meadowriparian habitats. Deer increased their time spent feeding by shortening the length of resting bouts and including
more feeding bouts each day, not by increasing the length of each foraging bout. Companion studies indicated
that in areas with cattle grazing, deer home-range sizes were larger and hiding cover for fawns was reduced (Loft
et al. 1988). These results are consistent with the hypothesis that cattle competed with deer, particularly at high
stocking rates and during years of below-average precipitation. The researchers suggested that female mule deer
were acting as time minimizers to meet the high energetic demands of lactation while minimizing their exposure
to predators.
Results of Kie and colleagues (1991) suggested that competition occurs between cattle and female mule deer in
McCormick Creek Basin, and that such competition likely has adverse population consequences for deer. Several
cattle management strategies could reduce these adverse effects (Loomis et al. 1991):
▪
Hold cattle stocking rates at moderate levels, particularly through the end of the first week of August.
The goals of this strategy would be to minimize the loss of hiding cover for fawns until they are at least a
month old, ensure the availability of maximum levels of forage for adult females (allowing them to meet
the energetic demands of lactation while minimizing their exposure to predators), and ensure good
carryover of forage until the fawns are weaned.
▪
Delay grazing entirely until early August, and then graze at moderate levels for the remainder of the
summer, with the same goals as above.
▪
Institute a deferred-rotation grazing system. One half of each allotment would be grazed in early summer
and the other half in late summer, both at moderate levels. Rotate the order of grazing each year.
January 2013
▪
Institute a multi-allotment, rest-rotation grazing system and only graze each allotment 1 or 2 years out of
every 3-year cycle. This alternative represents the greatest change from the current situation, but the
economic benefits would be great as well.
Stewart and colleagues (2002) found that cattle in northeastern Oregon were generalists with respect to habitat
selection; elk and mule deer avoided areas used by cattle. Mule deer and elk avoided one another during the short
temporal window (6 hours) used in the study, although spatial differences in habitat use often were not
maintained over 7 days. Elk used lower elevations when cattle were absent and moved to higher elevations when
cattle were present, indicating shifts in niche breadth and competitive displacement of elk by cattle and
demonstrating strong partitioning of resources among these three species, as well as evidence that competition
likely has resulted in spatial displacement.
The economics of rest-rotation cattle grazing were examined in a California deer hunting unit. The value of the
unused forage for cattle was $71,000 each year. The increased deer population and hunting, however, far
outweighed this loss and were valued at $2.3 million annually (Loomis et al. 1991).
M ONITORING TECHNIQUES AND S URVEY METHODS
Adaptive Management
According to White and Bartmann (1998), to manage population size at a desired level, optimal rates of female
harvest would vary in response to annual changes in fawn survival or recruitment to age 1, adult doe survival, and
population size. Reliable estimates of all of these parameters would need to be obtained from a carefully designed
monitoring effort. At a minimum, managers should annually monitor overwinter fawn survival and adult doe
survival, and December recruitment data should be collected on a few core populations representative of adjacent
populations (White and Bartmann 1998). Optimally, population size should be monitored annually, but, if other
parameters are monitored carefully, then less frequent monitoring may be appropriate.
The Montana Department of Fish, Wildlife, and Parks (2001), in Helena, Montana, developed an adaptive harvest
management (AHM) plan (Figure 10-3) that serves as an example of how such a framework might guide ungulate
harvest management through the type of standardized, rigorous approach that Mason and colleagues (2006)
advocate for monitoring deer. The framework is based on the premise that environmental variation affects mule
deer recruitment and mortality; it has the explicit goals of managing for the long-term welfare of mule deer and
providing for maximum recreational opportunities linked to the dynamic nature of deer populations. Most
notably, the Montana AHM strategy is responsive to mule deer population parameters rather than deer harvest
levels. The framework has four elements:
1.
2.
3.
4.
clearly stated objectives,
a set of regulation packages (restrictive, standard, liberal harvest),
a monitoring program, and
computer models that project population status from monitoring data.
In Montana, 13 representative populations were intensively surveyed to obtain relatively precise estimates of
population size and composition. These estimates were obtained with one full-coverage post-season flight and
one full-coverage spring flight with two replicates. Mark–resight estimates of population size were measured
with radiotelemetry samples on a subset of the 13 census areas on a staggered schedule.
Source:
January 2013
Montana Department of Fish, Wildlife, and Parks (2001)
Figure 10-3
Adaptive Harvest Management Plan Developed by Montana Department of Fish, Wildlife,
and Parks
Habitat Monitoring
McCullough (2001) monitored acorn production in northern California for four species of oaks (valley [Quercus
lobata], black [Q. kelloggii], blue [Q. douglasii], and live [Q. wislizenii, Q. agrifolia]) in 10 catchment traps placed
randomly under the canopy of each species. Traps were constructed of welded-wire fencing rolled into cylinders,
staked in place, and fitted with heavy-gauge black plastic bags with an opening area of 0.22 m2. Placing marked
acorns into the traps verified that acorns were not being removed from the plastic bags by animals. The acorn
crop index was the number of acorns collected yearly for all oak species in the total array of 40 traps.
Management Goals
The research and management goals for mule deer outlined in the Tejon Deer Herd Management Plan (Asserson
1984) include the following:
▪
▪
▪
▪
▪
▪
▪
Maintain 5,000–7,000 deer
Maintain herd in healthy and productive condition
More than 40 fawns per 100 does in spring when population is below objective
More than 25 bucks per 100 does after the hunting season
Burn or crush more than 400 acres of brush per year
Implement state chaparral management program
Reduce livestock take of forage
January 2013
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
▪
Conduct composition counts in August, November, March/April
Continue to collect hunter check station data
Collect acorn production data
Collect weather data
Collect browse and forb data
Conduct research to determine seasonal habitat use and fawning areas
400 bucks harvested per year
Provide interpretation and non-consumptive use of deer
Increase law enforcement
Update plan annually
A maximum sustainable yield plan could yield 10,000 deer and a doubling of the buck harvest, but
significant reduction in cattle and more burning would be required
To identify and meet management goals, including those defined above, a deer management plan (a component of
an overall wildlife management plan) should be developed that contains the details of these goals, alternative
methods for achieving them, and ways to monitor success and adapt. For example, without a population survey,
there is no way to know the deer population or how to manage for it. A quantitative goal should be established of
how much to reduce livestock forage and why and how to monitor the implications of that strategy. As another
example, it is unclear how the maximum sustainable yield goal was determined.
Mountain Thinking recommends that the Conservancy collate and analyze all data (including those from original
data sheets), including harvested deer age (from teeth slicing), hunter success, Boone and Crockett scores,
composition counts, harvested deer weights, and total counts. The goal of this analysis would be to determine
past trends and effects on the deer population, to allow a determination of optimal management (fitting the
objectives above). Excellent analysis strategies and programs are available for such purposes. Going forward,
these data need to be collected and entered into spreadsheets for analysis on a regular basis to assess success in
meeting the goals. Such an analysis will provide an indication of herd and habitat condition and will show ways
to improve both. Even with the success of the QDM Program to date, opportunities are available to improve
more, perhaps by restricting harvest of older deer classes further and with better economic returns.
Mountain Thinking recommends significantly expanding efforts to improve deer habitat using fire and
mechanical methods as long-term tools to increase carrying capacity for deer, which should be coordinated with
TRC fuel management planning. Such work should be conducted as an experiment to learn as much as possible
regarding the best ways to enhance habitat, and then adapting accordingly; such studies should also assess
impacts on other species. A consensus on the cause of the cyclical decline of deer in the American West has been
habitat degradation, largely due to lack of fire, and work is very much needed to determine the role of managing
this impact and its role in deer population trend.
Little value is seen in predator (coyote) control for deer (as discussed in Section 6 of this wildlife assessment).
Predator control is highly controversial and requires strong justification before risking social capital to
implement it (Hecht and Nickerson 1999, Bishop et al. 2009).
Doe: fawn ratios on Tejon Ranch, as elsewhere, appear cyclical and precipitation driven. The population is likely
not in significantly poorer condition overall compared to the past. This hypothesis should be tested, however.
Given the increasing elk population, a high density of cattle, and low doe harvest, it is possible that deer on Tejon
Ranch have been near carrying capacity for some time and that the following four steps should be taken to
improve deer on Tejon Ranch:
1.
2.
3.
4.
habitat improvement,
reduction of cattle population,
reduction of pig populations, and
possible increased doe harvest.
January 2013
Doe harvest, however, must be managed and monitored carefully. Along with this strategy should come more
robust measures of deer abundance and population trend. Mountain Thinking recommends making these
changes as part of an adaptive management experiment. In addition, the economic aspects of management
decisions should be followed closely to assess tradeoffs for management. While more intensive monitoring
typically costs more, the resulting increased and more consistent harvest may justify the cost. The tradeoff on
deer v. cattle management costs and outputs should also be measured.
Recruitment of deer will always be challenging, given the highly variable precipitation in the area and the
relatively high densities and diversity of predators. Continued monitoring of doe: fawn ratios will allow longterm assessment of overall conditions for deer; large swings in numbers should be expected, but long-term
decline should indicate a need for management changes. The improvements identified above should limit the
potential for such declines, but increasing elk density may lead to long-term reduction in carrying capacity for
mule deer. Development that may take place in the future will also decrease capacity overall. Mountain Thinking
recommends that residents of such developments be educated to expect and tolerate the presence of deer.
Monitoring
A key to developing the most efficient monitoring strategy is to establish management objectives. Mountain
Thinking recommends developing aerial surveys for deer and elk using sightability methodology, and then using
these surveys to monitor populations at 3- to 5-year intervals. Also, because of its importance in deer population
dynamics, an assessment of cause-specific mortality of does should be conducted. A 3-year project with 50 radiocollared does could probably provide the baseline doe survival data needed for long-term population modeling
and monitoring. Further, such a project would identify seasonal use and fawning areas, one of the goals of the
Tejon Deer Herd Management Plan (Asserson 1984). This project is recommended because no cause-specific
mortality rate has been estimated for deer in the region that can be readily used. These data and analyses will be
well worth the time and cost to improve deer management and economics.
Harvest
Fall doe: fawn ratios in half the years since 1980 have been above 40: 100, a threshold (based on the work of
Unsworth et al. 1999 and Lukacs et al. 2009) that is probably sufficient to yield population stability or increase;
however, the accuracy of this threshold needs to be determined for Tejon Ranch. The estimates in these studies,
however, were spring ratios, which provide a better measure of recruitment than fall ratios. Mountain Thinking
recommends measuring doe: fawn ratios in spring. To better assess harvest rate impacts, adult doe survival rates
should also be assessed, given the likely high cougar, bear, and coyote populations on the Ranch
Lubow and colleagues (1996) indicated that male-only harvests are robust and have been conducted safely over
extended periods with a minimum of information. However, they did not believe that game managers can avoid
the costly and difficult process of obtaining reliable knowledge if they seek to optimize harvests of females.
Population parameters and size should be estimated (Seber 1992), and optimal harvest strategies that incorporate
stochastic environmental influences and information uncertainty should be determined, possibly using stochastic
optimization techniques such as dynamic programming (for examples involving big game, refer to Stocker 1983).
Managers should consider carefully whether the benefits of female harvests justify the costs of research and
population measurement that would be required to properly manage such a harvest.
Mountain Thinking also recommends consideration of adopting an adaptive management harvest structure
similar to that adopted by the Montana Department of Fish, Wildlife, and Game (Figure 10-3).
Habitat Monitoring
Because mast production influences deer condition and because of possible competition between pigs and deer, a
monitoring system for acorns should be developed, as described above (McCullough 2001). Range and browse
condition assessments should be developed to measure long-term habitat trends. These assessments should also
incorporate the impacts of competition with pigs and elk. A full-range assessment is recommended as well to
determine carrying capacity (animal unit months) for deer, elk, and cattle.
January 2013
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Pac, D. F., and G. C. White. 2007. Survival and cause-specific mortality of male mule deer under different hunting
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January 2013
11. Pronghorn (Antilocapra americana )
The pronghorn is a grassland and shrub-steppe obligate
and the sole surviving member of a taxonomic family
(Antilocapridae) unique to North America. Adapted to
outrun American cheetahs (Miracinonyx trumani), an extinct
predator that once roamed the North American plains, the
pronghorn can reach a top speed of nearly 100 km/h,
making it the fastest land mammal on the continent. With
its exceptionally large eyes set far back on the skull, it can
detect movements up to 5 km away, and with a burst of
speed it can quickly deter any modern predator from
giving chase.
Pronghorn antelope were once abundant in grasslands of
throughout California, but likely reached their greatest
Pronghorn (© T. Maloney 2011)
abundance in the Central Valley. They disappeared from
the Central Valley in the early 1900s due to a combination
of overhunting and the conversion of native grasslands to
cultivated crops (Yoakum 2004). To reestablish the population, approximately 350 pronghorn antelope were
translocated into the region between 1987 and 1990 (Longshore and Lowrey 2008). About 90 of these animals
were released onto the Carrizo Plain National Monument. Initially, the population thrived and, by 1995, an
estimated 150 pronghorn inhabited the monument. Since then, the population has declined and, in 2002, was
estimated at 54 animals (Stafford, personal communication, 2013).
Tejon Ranch Status
Little is known about the historical status of pronghorn in the Mojave Desert. Pronghorn were historically
present in the Antelope Valley (i.e., extreme western Mojave Desert) but were extirpated in the early 1900s
(Cunningham 2010). Seventeen males and 34 females were translocated from Modoc County to Tejon Ranch in
1985, and an additional three males and 37 females were translocated in 1987 (Stafford, personal communication).
All the animals were released on Antelope Valley side of Tejon Ranch, and apparently they account for the
entirety of California’s Mojave pronghorn population.
According to Bob Stafford (personal communication) 5–10 pronghorn inhabit the Tehachapi area northeast of
Tejon Ranch and it is unknown if these animals use the Ranch. Another small band (approximately five) was
located on the San Joaquin Valley side of Tejon Ranch. These animals were believed to have originated from the
Carrizo releases but have not been seen in many years.
On the Mojave Desert side, the pronghorn are in three groups: Oso Canyon to Quail Lake; the Coe field (four
animals) bordered by State Route 138 on the south, the aqueduct to the west and north, and 300 Street on the
east; and the Berrendas (from the cement plant on the west to Bitterwater on the east). The group in the
Berrendas comprises up to 22 animals at different times of year. The pronghorn remain in the general area of the
Berrendas year-round. Minimum ground counts since 1995 have ranged from 28 to 46, with 37 counted in 2011.
According to T. Mattias (Tejon Ranch Wildlife Supervisor, personal communication, 2013), one of the main
issues for these animals is the lack of fawning cover. The area is grazed by steers that are brought in from August
to September and left for two seasons (1–2 years). With good rain, the steers are shipped in April or May,
depending on their weight gain and market conditions. The continued grazing and disruption by the cattle
during fawning season may significantly reduce fawn production and survival. Fawn survival appears higher
January 2013
when cattle are shipped from the area in April rather than in late June. When cattle remain in the area later, it
appears that grass remains short. Lack of fencing makes pasture management difficult.
Pronghorn depend on speed and their ability to detect moving predators at long distances; thus, they prefer
habitat with no greater than 30% slopes and vegetation structure averaging 15–24 inches (38–61 cm) in height
(Yoakum 2004). Vegetation tall enough to conceal fawns is essential during the fawning period (Alldredge et al.
1991, Clemente et al. 1995, Ockenfels et al. 1996, Canon and Bryant 1997). Areas with relatively more herbaceous
and grass cover and relatively less shrub cover are considered optimal for both foraging and predator avoidance
(O’Gara and Yoakum 1992). Pronghorn prefer a diversity of forbs, and forb preference ratios exceed those of
shrubs or grasses. When forbs are not available, both seasonally and during periods of drought, shrubs are more
important (O’Gara and Yoakum 1992). Graminoids provide a minor part of the pronghorn diet in all biomes.
However, pronghorn on grasslands consume twice as much grass as those on shrub steppes (Kitchen 1974,
McNay and O’Gara 1982, O’Gara 2004). Unobstructed access to permanent water is especially critical during the
dry months (Yoakum 1982, Okenfels et al. 1996). Pronghorn are generally found within 8.0 km of water (Yoakum
2004). Results of a food habits study by Longshore and Lowrey (2008) indicated that, in the Carrizo Plains,
shrubs are important forage during autumn months. During dry years, low shrub diversity and cover, coupled
with low production of herbaceous vegetation during spring and summer, can indicate low carrying capacity.
Longshore and Lowrey (2008) assessed pronghorn habitat on the Carrizo National Monument (Table 11-1).
Drought conditions necessitated supplemental feeding of pronghorn on Carrizo during 2002 (Yoakum 2004),
and during 2003 and 2004 precipitation was lower than average. During their surveys, at least 27 pronghorn were
located on private land outside the monument. These animals may have been part of the monument herd. If
pronghorn are moving off the monument during dry years, their movement may be an indication of low carrying
capacity.
Table 11-1
Habitat Variables
2
Habitat Suitability Criteria for Pronghorn in Grassland
and Grassland-Scrub Communities
Grassland
Habitat
2
Grassland-Scrub Habitat Quality
High
≥ 5 km
Moderate
2
>1 < 5 km
2
Low
< 1 km2
Area (km )
≥ 5 km
Slope (%)
≤5%
≤5%
> 5 ≤ 20%
> 20%
Herb cover (%)
10–20%
10–30%
5–10%
< 5%
Grass cover (%)
50–80%
30–50%
15–30%
< 15%
Shrub cover (%)
< 5%
5–15%
2–5%
< 2%
Bare ground cover (%)
20–30%
20–30%
10–20%
< 10%
Vegetation height (cm)
25–45 cm
25–45 cm
15–25 cm
< 15 or > 50 cm
Distance to water (km)
≤ 3 km
≤ 3 km
> 3 ≤ 6 km
> 6 km
Species diversity: herbs/forbs
≥ 4 species
≥ 4 species
≥ 2 < 4 species
< 2 species
Species diversity: grass
≥ 4 species
≥ 4 species
≥ 2 < 4 species
< 2 species
Species diversity: shrubs
≥ 4 species
≥ 4 species
≥ 2 < 4 species
< 2 species
Note:
Habitat categories for high, moderate, and low quality were not available for grassland habitat.
Sources:
Allen et al. (1984), O’Gara and Yoakum (1992), Okenfels et al. (1996), and Yoakum (2004).
January 2013
POPULATION DYNAMICS
After overexploitation in the 19th century throughout the American West, restoration of pronghorn has been a
significant wildlife conservation success. The population declined from 30–40 million historically to fewer than
13,000 in 1915. Pronghorn have increased since that time to around 1 million. Over the last two decades, however,
that success has diminished somewhat for various reasons. Populations of pronghorn have not suffered the same
widespread declines as mule deer, but pronghorn populations have decreased in many areas (Jacques et al. 2007).
Drought, severe winters with deep crusted snow, malnutrition, disease, hunter harvest, poisonous plants, and
coyote predation have been identified as mortality factors affecting pronghorn survival (Barrett 1982, Yoakum
and O’Gara 2000).
In parts of the western United States, the greatest source of mortality for pronghorn fawns is coyote predation
(Smith et al. 1986, Gregg et al. 2001, Jacques et al. 2007). For example, in a recent study, coyote predation was the
primary cause of mortality for neonates in western South Dakota (Jacques et al. 2007). Hunting, however, was
the primary cause of mortality for adult females (26%) in western South Dakota from 2002 to 2005, yielding
survival rates of 86–100%. Although good records are not available, more than 100 coyotes were killed annually
on Tejon Ranch by hunters and for predator control through 1988, including for reducing predation rates on
pronghorn fawns.
Hoffmann and colleagues (2010) modeling results suggesting that pronghorn density in the Sioux pronghorn
management unit in western Nebraska was correlated positively with both density-dependent and densityindependent variables (cattle density and spring precipitation) that could directly affect the quality and quantity
of available forage. During periods when spring precipitation and cattle grazing are low, densities of pronghorn
might decrease because these factors stimulate growth of forbs. Spring precipitation commonly has been
associated with higher pronghorn densities (Brown et al. 2006, Simpson et al. 2005, Yoakum 2004). Rangelands
that receive more precipitation typically produce higher diversities of forbs, which are the preferred diet of
pronghorn (Yoakum 1990). Lack of nutritious forage because of low precipitation can result in higher mortality
rates for both fawns and adults (Bright and Hervert 2005). Higher densities of cattle also could lead to improved
forage on pronghorn rangelands. The grazing activities of domestic cattle have been shown to increase forb
diversity (Loeser et al. 2005). Also, little evidence can be found that the diets of cattle and pronghorn overlap,
suggesting that competition for food resources likely is minimal (Yoakum 2004).
Simpson and colleagues (2007) evaluated the relationships between pronghorn abundance and productivity and
precipitation (i.e., raw precipitation, Palmer drought indices) for the Trans-Pecos district of Texas from 1977 to
2004. Pronghorn productivity (range = 305–4,407 fawns) and abundance (range = 5,061–17,266) showed high
variability. Precipitation was also highly variable, ranging from 18 cm to 57 cm. Pronghorn abundance was
positively influenced by precipitation indices (R= 0.790). The relationship between fawn production and raw
precipitation (R = 0.869) suggested that fawn production may be more closely related to immediate moisture
conditions, whereas pronghorn abundance in general was more influenced by long-term precipitation trends.
Chronic low survival of fawns has long been considered a major management problem in Arizona (McKinney et
al. 2008), but its causes are poorly understood. Survival of fawns is believed to be a key element affecting viability
of populations, and 60% of populations in their study had mean recruitment below the statewide mean of 27
fawns per 100 females for 1983–2002. This statewide mean is low compared to estimates of recruitment reported
for more northern areas of the geographic range of pronghorns. Populations with recruitment levels of at least 40
fawns per 100 females might be expected to increase in size, but changes in the size or trends of populations
depend on differences between recruitment and mortality, not merely on the level of recruitment. Mid-summer
drought conditions that reduce the abundance of adult females might affect population trends more than direct
effects of winter precipitation on recruitment (Brown et al. 2006).
January 2013
Note:
Precipitation data were obtained by combining measurements from the Lebec and Tehachapi weather stations.
Source:
Western Regional Climate Center 2013; unpublished TRC data
Figure 11-1
Total Pronghorn Counted on Tejon Ranch, 1995–2011.
Prolonged or severe droughts might correspond with increased mortality of adults and fawns and could
contribute to declines of populations (Bright and Hervert 2005, Brown et al. 2006, Simpson et al. 2005); frequent
occurrence of drought and periods of winter rainfall less than 8 cm likely reduce survival of fawns (Brown et al.
2002). Drought occurred during winter in the study area reported by McKinney and colleagues (2008) in 26–
58% of years, and winter precipitation was less than 8 cm during 37–100% of years on 70% of these areas.
The results of McKinney and colleagues (2008) support the hypothesis that winter precipitation is a factor
influencing recruitment in pronghorns through late summer in Arizona, and inadequate winter precipitation
potentially contributes to chronically lower recruitment. Correlations they documented represent arid and semiarid southwestern habitats and likely do not represent populations of pronghorns occupying more mesic and
more northern habitats. Moreover, winter precipitation alone likely does not fully explain the high amount of
annual variability they observed in recruitment among and within populations, and they suggested that other,
unidentified factors warrant further research.
Population size on Tejon Ranch has remained surprisingly consistent for this environment Figure 11-1. Not
surprisingly, the Tejon Ranch data appear to also indicate that recruitment is driven by precipitation (Figure
11-2). There is a significant (p = 0.06) correlation between previous-year precipitation and fawn: doe ratio (0.43).
The 2 years with highest recruitment, 1999 and 2006, occurred after high precipitation during the previous year.
However, there has been a significant (p < 0.0001) declining trend (0.65) in fawn: doe ratios in relation to
precipitation (Figure 11-2) when the high values of 89 fawns per 100 does is omitted (see Table 11-2).
January 2013
Note:
pfawn = pronghorn fawn ratio (fawns per 100 does); PREPRECIP = previous-year precipitation.
Fawn: doe ratios are significantly positively correlated with the previous year’s annual precipitation, unless the outlier value of 89
fawn: doe (upper right point) is omitted.
Source:
Western Regional Climate Center 2013; unpublished TRC data
Figure 11-2
Correlation between Previous-Year Precipitation and Pronghorn
Fawn Ratio on Tejon Ranch, 1995–2011.
Based on composition counts, TRC determined that the pronghorn herd did not warrant issuing any tags for
pronghorn buck harvest in 2011 (Table 11-2). Many factors determine the decision to harvest a buck, particularly
herd size and growth. In 2012, the herd showed significant signs of improvement as the overall Tejon Ranch herd
size grew 16% (from 32 to 37 pronghorn) but no pronghorn were harvested in 2012. TRC changed the system of
pronghorn composition counts in 2011 (Table 11-2) from a ratio system to gross number of animals observed.
Table 11-2
Pronghorn Composition Counts on Tejon Ranch, 2011
Fall
Bucks/100 Does
Kids/100 Does
Number Classified
Bucks Harvested
1995
53
12
28
–
1996
33
22
41
–
1997
29
14
38
–
1998
48
24
36
–
1999
52
32
46
–
Table 11-2
January 2013
Pronghorn Composition Counts on Tejon Ranch, 2011
Fall
Bucks/100 Does
Kids/100 Does
Number Classified
Bucks Harvested
2000
45
22
37
–
2001
42
16
35
3
2002
45
12
38
2
2003
39
14
32
2
2004
38
12
34
0
2005
33
17
36
3
2006
21
89
40
0
2007
23
26
46
2
2008
24
9
44
0
2009
27
11
38
2
2010
25
9
32
0
2011*
6
25
6
0
Notes:
Source:
– = no data collected.
*TRC changed the system of pronghorn composition counts in 2011 from a ratio system to gross number of animals observed.
Data compiled by Tejon Ranch Company
Interactions with Livestock
Debate exists about the relationship of livestock to pronghorn populations. Much of the effect that cattle have on
pronghorn populations can be related to grazing intensity and rangeland condition. Rangelands with an
abundance of grasses can be heavily grazed by livestock, resulting in increased amounts of the forbs and shrubs
that are preferred by pronghorn (Yoakum and O’Gara 2000). Competition for forage does not seem to be an issue
on healthy rangelands because of differing consumption of forage classes.
Cattle grazing is often implicated, however, as a factor that reduces vegetative cover and the abundance of
important forage plants for wildlife. Recent declines in northern Arizona populations of pronghorn have focused
public and scientific attention on the factors contributing to low fawn recruitment and the potential benefits of
cattle removal. To further understand the effects of cattle grazing, Loeser and colleagues (2005) studied the
potential hiding cover provided by standing live and dead herbaceous matter, as well as forb richness and canopy
cover, following 5 years of cattle removal. Cattle removal increased horizontal hiding cover by 8% at a distance of
5 m (p = 0.025), but had no statistically significant effect on the potential hiding cover at distances of 10 m (p =
0.105) or 25 m (p = 0.746). Forb species richness was 16% lower in exclosures than in an adjacent grazed pasture
in 2001 (p = 0.036), but no differences were observed in 2002 (p = 0.636). The canopy cover of forbs was generally
unaffected by cattle removal. These results suggest that curtailing or removing cattle is unlikely, by itself, to lead
to rapid improvements in the hiding cover or forb availability for pronghorn on similar rangelands in northern
Arizona. McNay and O’Gara (1982) reported that livestock displaced parturient females in Nevada. When cattle
are present, pronghorn females tended to relocate their fawning sites to less favorable habitats (McNay and
O’Gara 1982).
January 2013
Predator Control
Coyote removal has coincided with an increase in fawn survival and pronghorn density in some studies (Smith et
al. 1986, Phillips and White 2003). As a result, some western states have contracted with the U.S. Department of
Agriculture, Wildlife Services to remove coyotes for the benefit of pronghorn and mule deer (Harrington and
Conover 2007). However, debate remains whether current coyote removal programs can increase fawn survival.
Until recently, studies examining the effects of coyote control were conducted in areas of less than 1,000 km2
(Ballard et al. 2001). To date, only two predator control studies have been conducted in areas of more than 1,000
km2. Harrington and Conover (2007) conducted a study in Utah and Colorado that encompassed an area of more
than 1,900 km2. Data from that study showed no relationship between coyote removal and fawn: adult female
ratios, but there was a positive correlation between the level of coyote removal and densities of pronghorn and
mule deer (Harrington and Conover 2007).
Brown and Conover (2011) tested the hypothesis that predation by coyotes (Canis latrans) affects pronghorn and
mule deer (Odocoileus hemionus) populations. They examined the effects of coyote removal on pronghorn and mule
deer populations within 12 large areas (more than 10,500 km2) located in Wyoming and Utah during 2007 and
2008. They found that pronghorn productivity (fawn: adult female ratio) and abundance were positively
correlated with the number of coyotes removed and with removal effort (hours spent hunting coyotes from
aircraft), although the correlation between pronghorn productivity and removal effort was not statistically
significant (p = 0.08). Mule deer productivity and abundance were not correlated with either the number of
coyotes removed or with removal effort. Coyote removal conducted during winter and spring provided greater
benefit than removals conducted during the prior fall or summer. These results suggest that coyote removal
conducted over large areas increases fawn survival and abundance of pronghorn but not mule deer.
The effects of predators are site- and time-specific. Primary factors influencing the impact of coyotes on
pronghorn are the predator: prey ratio and the status of the pronghorn population with respect to carrying
capacity. High abundance of coyotes relative to pronghorn may maintain pronghorn at relatively low densities. If
pronghorn density is high relative to habitat carrying capacity, predators have fewer effects.
Small Populations
A severe drought occurred in summer 2003 on the National Bison Range in western Montana. Dunn and Byers
(2008) found that, of the 34 males, 66 females, and 10 fawns that were alive in the November 2003 census, only
7ºmales, 41 females, and 2 fawns survived until May 2004. There was 100% mortality of males in most age
categories, except ages 1–3 years. Mortality of females occurred across all age categories, but none reached 100%.
Thirty-four (83%) of the surviving females did not give birth. The age–sex distribution of pronghorn on the
National Bison Range in August 2004 consisted of 7 males between the ages of 2 and 4 years and 41 females
between the ages of 1 and 9 years. Dunn and Byers (2008) found that survival of females was influenced by prior
energy expenditure and genetic variation, implicating inbreeding depression as the mechanism. Fecundity of
females also was influenced by prior energy expenditure and genetic variation, with heterosis as the apparent
mechanism. These results agree with those of other studies that have emphasized the need to maintain genetic
variation and limit inbreeding in small, isolated populations.
When population size is reduced below a critical threshold, individuals become exposed to several factors that
could facilitate an Allee effect, including inbreeding, mate limitation, higher rates of predation due to a relative
increase in abundance of predators, demographic stochasticity, and reduction in cooperative defense (Kramer et
al. 2009).
Cooperative defense might be the most pertinent factor for pronghorn because it involves each individual of the
population remaining vigilant for potential predation. O’Gara (2004) suggested that pronghorn form herds
primarily for protection from predators. Lipetz and Bekoff (1982) showed that, as herd size increased, the
proportion of pronghorn that were vigilant decreased. They hypothesized that this was due to an increase in
awareness and detection of predators, which allowed individuals to spend more time feeding and resulted in
greater overall fitness for individuals in the herd. Allee effects have multiple conservation implications for natural
January 2013
populations because even slight increases in mortality can cause dramatic collapses in populations and increase
probabilities of extinction (Courchamp et al. 1999).
On the other end of the spectrum, White and colleagues (2007) found that small populations of pronghorn can
irrupt. They reported counts of pronghorn on the northern range of Yellowstone Park remaining between 100 and
190 animals during 1967–1981. However, the population irrupted to a peak abundance of approximately 600
pronghorn during 1982–1991, with a slowing in growth rate as counts exceeded 500. The factors leading to the
irruption are unknown.
Population Monitoring
The greatest concerns for the Tejon Ranch pronghorn population are its small size and its occurrence in a very
arid and stochastic environment. Hoffmann and colleagues (2010) recommended that pronghorn management
plans should include calculations of critical density thresholds for individual management areas. Their results
indicate that Allee effects can be present in pronghorn populations and should be considered when developing
management and conservation programs. As population density fell below these thresholds (approximately 1
pronghorn per km2 in three of the four populations they studied), the per-capita rate of change became negative
and the population faced a greater chance of extinction. As population densities approach the critical threshold,
management actions may need to be taken. The annual declining trend in fawn: doe ratios supports the notion of
an Allee effect. There might also be a correlation on Tejon Ranch with reduced number of coyotes killed over
time, given the high harvest in the 1980s. However, TRC has not collected data on this on the number of coyotes
killed since the 1980s. Mountain Thinking recommends developing a coyote index to relate to the pronghorn
index to assess the role of coyotes.
The population on Tejon Ranch, while very small, has generally remained stable. Continued intensive monitoring
is recommended; if declines occur over more than 2 consecutive years, a response may be warranted. The cause of
the decline needs to be assessed and then mitigated. If it can be mitigated, one option is to translocate more
animals to augment the population. If the causes of the decline cannot be mitigated and are not simply a factor of
small population size itself, then augmentation will probably not help.
Predator Management
Coyote control for such small pronghorn populations in such variable and marginal environments does not
appear to be a sustainable or useful strategy. Programs that must be conducted in perpetuity are not sound or
biologically justifiable strategies for predators or prey. The primary limiting factors for this population appear to
be small size, low and variable precipitation, and possibly cattle grazing. Further, there remains much doubt and
debate as to the effectiveness of control (Berger 2006, as discussed in Section 6, “Coyote,” of this wildlife
assessment). Finally, there are significant negative impacts to ecosystems resulting from coyote control
(Section 6).
Improving Forage Quality
Implementing programs aimed at improving the quality of forage during periods of drought or when availability
of other forage (i.e., winter wheat) is low will reduce the loss in population numbers and improve reproductive
output. The food habits study of Longshore and Lowrey (2008) indicated that, in the Carrizo Plain, shrubs are
important forage during autumn months. Work should be conducted to determine if shrubs respond to
decreased cattle grazing. Management plans should include drought contingencies, including reduced livestock
stocking rates and harvest quotas. Knowing how local populations of pronghorn respond to annual fluctuations
in density-dependent and density-independent variables will provide the basis for more sound management
plans.
Because the population is so small, the Ranch is a very arid environment, and anecdotal information and research
from elsewhere suggest impacts of cattle on pronghorn, work should be conducted to assess the impact of cattle
January 2013
on this small population, especially with regard to fawning areas. For the Tejon Ranch population, the potential
impacts of cattle to push pronghorn out of fawning areas and the negative impact of high grazing on fawning
cover outweigh the benefit of grazing to improve forb production. A project aimed toward assessing how to time
spring cattle grazing and its intensity and spatial array would be valuable.
Fencing
According to the Interim Ranch-wide Management Plan (Tejon Ranch Company and Tejon Ranch Conservancy
2009), approximately 650 miles of fencing exist on Tejon Ranch, which includes fencing surrounding the entire
boundary of the Ranch. Conventional fencing designed to contain cattle (three or four strands of barbed wire),
with the bottom wire set at about 25 cm above grade, is relatively impermeable to pronghorn (Gates et al. 2011).
Woven-wire fencing is permeable with the lower wire more than 40 cm above the ground. As an example,
Alberta provided a design for a wildlife-friendly fence that considered passage by pronghorn and deer species
(http://fwpiis.mt.gov/content/getItem.aspx?id=34461). Mountain Thinking recommends modification to make all
the fences in the range of pronghorn passable by pronghorn, in accordance with the wildlife-friendly best
management practices described above. Citizen groups may volunteer to modify fence lines to accommodate
pronghorn movements in local areas. In the late 1980s, the California Department of Fish and Game reintroduced
pronghorn into the Carrizo Plain. A joint effort between the Sierra Club, ForestWatch, Desert Survivors, and the
California Department of Fish and Game was organized to remove or modify fences, with the goal of restoring
free pronghorn movements. Together, the nonprofit organizations and state and federal agencies worked to
remove or modify more than 240 km of fencing. A similar effort may be possible on Tejon Ranch.
R EFERENCES
Alldredge, A.W., R. D. Deblinger, and J. Peterson. 1991. Birth and fawn bed site selection by pronghorns in a
sagebrush-steppe community. Journal of Wildlife Management 55: 222–227.
Allen, A. W., J. G. Cook, and M. J. Armbruster. 1984. Habitat Suitability Index Models: Pronghorn. U.S. Fish and
Wildlife Service. FWS/OBS-82/10.65. Fort Collins, CO. 22pp.
Ballard, W. B., D. Lutz, T. W. Keegan, L. H. Carpenter, and J. C. deVos Jr. 2001. Deer–predator relationships: a
29:99–115.
Barrett, M. W. 1982. Distribution, behavior, and mortality of pronghorns during a severe winter in Alberta. Journal
Bright, J. L., and J. J. Hervert. 2005. Adult and fawn mortality of Sonoran pronghorn. Wildlife Society Bulletin
33:43-50.
Brown, D., and M. Conover. 2011. Effects of large-scale removal of coyotes on pronghorn and mule deer
productivity and abundance. Journal of Wildlife Management 75:876–883.
Brown, D. E., W. F. Fagan, R. Lee, H. G. Shaw, and D. Turner. 2002. Winter precipitation and pronghorn fawn
survival in the Southwest. Proceedings of the Pronghorn Workshop 20:115–122.
Brown, D. E., D. Warnecke, and D. McKinnney. 2006. Effects of midsummer drought on mortality of doe
pronghorn (Antilocapra americana). Southwestern Naturalist 51:220–225.
Berger, K. 2006. Carnivore-livestock conflicts: effects of subsidized predator control and economic correlates on
the sheep industry. Conservation Biology 20:751–761.
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Canon, S. K., and F. C. Bryant. 1997. Bed-site characteristics of pronghorn fawns. Journal of Wildlife Management
61:1134–1141.
Clemente, F., R. Valdez, J. L. Holechek, P. J. Zwank, and M. Cardenas. 1995. Pronghorn home range relative to
permanent water in southern New Mexico. Southwestern Naturalist 40:38–41.
Courchamp, F., T. Clutton-Brock, and D. B. Grenfell. 1999. Inverse density dependence and the Allee effect. Trends
in Ecology & Evolution 14:405–410.
Cunningham, L. 2010. A State of Change: Forgotten Landscapes of California. Heyday, Berkeley, CA.
Dunn, S. J., and J. A. Byers. 2008. Determinants of survival and fecundity through a population bottleneck in
pronghorn (Antilocapra americana). Journal of Mammalogy 89:1124–1129.
Gates, C. C., P. Jones, M. Suitor, A. Jakes, M. Boyce, K. E. Kunkel, and K. Wilson. 2011. The influence of land use
and fences on habitat effectiveness, movements and distribution of pronghorn in the northern mixedgrasslands of North America. Pages 277–294 in M. W. Hayward and M. J. Somers (eds.), Fencing for
Conservation: Restriction of Evolutionary Potential or a Riposte to Threatening Processes?
Gregg, M., and M. Bray. 2001. Birth synchrony and survival of pronghorn fawns. Journal of Wildlife Management
65:19–28.
Harrington, J. L., and M. R. Conover. 2007. Does removing coyotes for livestock protection benefit free-ranging
ungulates? Journal of Wildlife Management 71:1555–1560.
Hoffman, J. D., H. Genoways, and R. Jones. 2010. Factors influencing long-term population dynamics of
pronghorn (Antilocapra americana): evidence of an Allee effect. Journal of Mammalogy 91:1124–1134.
Jacques, C. N., J. Jenks, J. Sievers, D. Roddy, and F. Lindzey. 2007. Survival of pronghorns in western South
Dakota. Journal of Wildlife Management 71:737–743.
Kitchen, D. 1974. The social behavior and ecology of the pronghorn. Wildlife Monograph 38.
Kramer, A. M., B. Dennis, A. M. Liebhold, and J. M. Drake. 2009. The evidence for Allee effects. Population Ecology
51:341–354.
Lipetz, V. E., and M. Bekoff. 1982. Group size and vigilance in pronghorns. Zeitschrift fur Tierpsychologie 58:203–216.
Loeser, M. R., S. D. Mezulis, T. D. Sisk, and T. C. Theimer. 2005. Vegetation cover and forb responses to cattle
exclusion: implications for pronghorn. Rangeland Ecology and Management 58:234–238.
Longshore, K., and C. Lowrey. 2008. Habitat Analysis and Food Habits of Pronghorn Antelope in the Carrizo Plains National
Monument, California. Final Report prepared for the Bureau of Land Management, Bakersfield, CA.
Mattias, T. Tejon Ranch Wildlife Supervisor. Personal communication, 2013.
McKinney, T., D. Brown, and L. Allison. 2008. Winter precipitation and recruitment of pronghorns in Arizona.
Southwestern Naturalist 53:319–325.
McNay, M. E., and B. W. O’Gara. 1982. Cattle-pronghorn interactions during the fawning season in northwestern
Nevada. Pages 593–606 in J. M Peek and P. D Dalke (eds.), Wildlife-Livestock Relationships Symposium. Proceedings
10. University of Idaho Forest, Wildlife and Range Experiment Station, Moscow, ID.
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O’Gara, B. W. 2004. Mortality factors. Pages 379–394 in B. W. O’Gara and J. D. Yoakum (eds.), Pronghorn Ecology
and Management. University Press of Colorado, Boulder, CO.
O’Gara, B. W., and J. D. Yoakum.1992. Pronghorn management guides. Proceedings of the 15th Biennial Pronghorn
Antelope Workshop. 101 pp.
Ockenfels, R., C. Ticer, A. Alexander, and J. Wennerlund. 1996. A Landscape-Level Pronghorn Habitat Evaluation Model
for Arizona Landscape-Level Pronghorn Habitat Evaluation Model for Arizona. Arizona Game and Fish Department
Research Branch Technical Report No. 19.
Phillips, G. E., and G. C. White. 2003. Pronghorn population response to coyote control: modeling and
management. Wildlife Society Bulletin 31:1162–1175.
Simpson, D. C., L. A. Harveson, C. E. Brewer, R. E. Walser, and D. Sides. 2005. Influence of precipitation on
pronghorn demography in Texas. Journal of Wildlife Management 71:906–910.
Smith, R. H., D. J. Neff, and N. G. Woolsey. 1986. Pronghorn response to coyote control—a benefit: cost analysis.
Stafford, B. CDFW. Personal communication.
September 18.
Western Regional Climate Center. 2013. Recent climate in the West; Tejon Rancho, California (048839).
Available at: http://www.wrcc.dri.edu/summary/Climsmsca.html.
White, P., J. Bruggeman, and R. Garrott. 2007. Irruptive population dynamics in Yellowstone pronghorn.
Ecological Applications 17:1598–1606.
Yoakum, J. D. 1982. Habitat Management Guides for the American Pronghorn Antelope. U.S. Bureau of Land Management
Technical Note 347.
Yoakum, J. 1990. Food habits of the pronghorn. Proceedings of the Pronghorn Antelope Workshop 14:102–111.
Yoakum, J. D. 2004. Habitat characteristics and requirements. Pages 409–445 in B. W. O’Gara and J. D. Yoakum
(eds.), Pronghorn Ecology and Management. University Press of Colorado, Boulder, CO. Available at:
http://www.wrcc.dri.edu/summary/Climsmsca.html.
Yoakum, J. D., and B. W. O’Gara. 2000. Pronghorn. Pages 559–577 in S. Demaris and P R. Krausman (eds.), Ecology
and Management of Large Mammals in North America. Prentice Hall, Upper Saddle River, NJ.
January 2013
12. Red Fox (Vulpes vulpes )
With the exception of an ecologically distinct subspecies
endemic to the Sacramento Valley of California (Sacks et
al. 2010), red foxes native to the American West were
thought to have been restricted to the subalpine parklands
and alpine meadows of the western mountain ranges
(Aubry and colleagues 2009, Grinnell et al. 1937). Sacks
and colleagues (2011) found that the native Sacramento
Valley red fox (Vulpes vulpes patwin) is endemic where its
current distribution appears closely associated with
grassland habitats (Grinnell et al. 1937, Sacks et al. 2010).
Red fox on Tejon Ranch are considered to be a nonnative
species.
Similar in size to the Sacramento Valley red fox and also
Red Fox (USFWS 2010)
smaller than the mountain phenotype, nonnative red foxes
in California occur in the lowlands, where they come into
direct contact with, and possibly overlap, the range of the
Sacramento Valley population (Sacks et al. 2010). The nonnative population became established in California
over the last several decades, primarily as individuals released (or escaped) from fur farms, which were common
throughout California in the mid-1900s (Lewis et al. 1999, Statham et al. 2012). They were first recorded in
southern Kern County after 1993 (Carrizo Plain) and abundant around Los Angeles at the same time. The
nonnative population is highly admixed, stemming largely from eastern Canadian as well as Alaskan individuals
captured in the late 1800s and early 1900s (Sacks et al. 2010). These ancestral populations correspond to two
lineages, which are phylogenetically distinct from the western lineage and from one another, approximately as
divergent as the interspecific kit fox and swift fox (Vulpes velox) clades (Aubry et al. 2009).
I MPACT ON P REY
Nonnative red foxes have been implicated in significant impacts on several endangered prey species in California
(Lewis et al. 1999). Disease transmission (Davidson et al. 1992), resource competition (Estes et al. 2012), and
interbreeding are other threats nonnative red foxes pose to native species. Red foxes also present a threat to
humans and their pets through disease transmission (particularly rabies), especially in urban areas where foxes
can become abundant and interactions between foxes and humans are common (Golightly et al. 1994).
Nonnative red foxes have been increasing in the San Joaquin Valley in the past two decades (Cypher et al. 2001).
The effects of this species on native wildlife are unknown. Of potential concern are impacts to endangered kit
foxes through interference and exploitation competition (Cypher et al. 2001, Clark et al. 2005). However, there is
no evidence to suggest that red foxes are displacing kit foxes. Coyotes appear to effectively limit or even exclude
red foxes in natural habitats (Cypher et al. 2001). Thus, red foxes in the San Joaquin Valley are mostly relegated
to anthropogenic habitats such as agricultural and urban areas. As recommended by Clark et al. (2005),
conservation of large blocks of good-quality, arid habitat with healthy coyote populations, as called for in
recovery strategies for San Joaquin kit fox (U.S. Fish and Wildlife Service 1998) should help limit impacts of red
foxes on kit foxes.
G ENERAL M ANAGEMENT R ECOMMENDATIONS
Given the political climate and biological realities, Lewis and colleagues (1999) noted that new, proactive
management strategies for nonnative red foxes are needed, including the following:
January 2013
▪
preventing introductions and translocations;
▪
identifying needs for protecting native species where the range of the nonnative red fox is expanding and
for species particularly vulnerable to fox predation;
▪
developing management strategies at larger scales, such as the regional or statewide level;
▪
developing alternatives to the use of body-gripping traps to control predators as part of endangeredspecies protection efforts;
▪
assessing fox distributions and densities on a regular basis, especially in urban areas;
▪
developing plans for preventing or managing epidemics of fox-transmitted disease; and
▪
improving communications with the public about fox management issues.
Site-specific management is valuable and may continue to receive most of the attention; however, it is unlikely
that site-specific management will provide a long-term solution.
Cypher and colleagues (2010) photographed two red foxes on the north side of Tejon Ranch while conducting
camera surveys. The Conservancy should monitor the population periodically to ensure that it remains small and
likely of insignificant impact. If the population grows substantially, then control actions should be implemented,
as it is difficult to determine impacts on other species and the Conservancy should act conservatively in this
regard. Harvest of red foxes should be promoted but is currently limited by CDFW regulations. Mountain
Thinking suggests working with CDFW to explore the feasibility of establishing a hunting program for red fox
on Tejon Ranch where there is no possibility of range overlap with native red fox species.
R EFERENCES
Aubry, K. B., M. J. Statham, B. N. Sacks, J. D. Perrine, and S. M. Wisely. 2009. Phylogeography of the North
American red fox: vicariance in Pleistocene forest refugia. Molecular Ecology 18:2668–2686.
Clark, H. O., G. Warrick, B. Cypher, P. Kelly, D. Williams, and D. Grubbs. 2005. Competitive interactions
between endangered kit foxes and nonnative red foxes. Western North American Naturalist 65:153–163.
Cypher, B. L., H. O. Clark Jr., P. A. Kelly, C. Van Horn Job, G. W. Warrick, and D. F. Williams. 2001. Interspecific
interactions among mammalian predators: implications for the conservation of endangered San Joaquin kit
foxes. Endangered Species Update 18:171–174.
Cypher, B., C. Van Horn, E. Tennant, and S. Phillips. 2010. Mammalian Species Surveys in the Acquisition Areas on the
Tejon Ranch, California. California State University, Stanislaus Endangered Species Recovery Program, Turlock,
CA.
Davidson, W., J. Max, L. Gary, E. Osborne, and F. John. 1992. Diseases and parasites of red foxes, gray foxes, and
coyotes from commercial sources selling to fox-chasing enclosures. Journal of Wildlife Diseases 28:581-589.
Estes, J. A., J. Terborgh, J. S. Brashares, M. E. Power, J. Berger, W. J. Bond, and J. B. Shurin. 2012. Trophic
downgrading of planet Earth. Science 6040:301–306.
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Golightly, R. T., M. R. Faulhaber, K. L. Sallee, and J. C. Lewise. 1994. Food habits and management of introduced
red fox in southern California. Proceedings of the Vertebrate Conference 16:15–20.
Lewis, J. C., K. L. Sallee, and R. T. Golightly Jr. 1999. Introduction and range expansion of nonnative red foxes
(Vulpes vulpes) in California. American Midland Naturalist 142:372–381.
Sacks, B. N., M. J. Statham, J. D. Perrine, S. M. Wisely, and K. B. Aubry. 2010. North American montane red foxes:
expansion, fragmentation, and the origin of the Sacramento Valley red fox. Conservation Genetics 11:1523–1539.
Sacks, B. N., M. Moore, M. J. Statham, and H. U. Wittmer. 2011. A restricted hybrid zone between native and
introduced red fox (Vulpes vulpes) populations suggests reproductive barriers. Molecular Ecology 20:326–341.
Statham, M., B. N. Sacks, K. B. Aubry, J. D. Perrine, and S. M. Wisely. 2012. The origin of recently established red
fox populations in the United States: translocations or natural range expansions? Journal of Mammalogy 93:5265.
U.S. Fish and Wildlife Service. 1998. Recovery Plan for Upland Species of the San Joaquin Valley, California. Region 1,
Portland, OR. 319 pp.
January 2013
13. Ringtail (Bassariscus astutus )
The ringtail, a nocturnal mammal belonging to the raccoon
family, has no federal designation, but is a fully protected
species in California, a designation that provides
additional protection to animals that are rare and facing
possible extinction. Formerly classified as a furbearer, the
ringtail has been protected from trapping in California
since 1967 when it was designated a Fully Protected
mammal by the California legislature. This species is listed
as Least Concern by the International Union for
Conservation of Nature (Timm and Helgen 2008), as the
species is common and widely distributed from central
Mexico to the central western United States (Barja and
List 2006).
Ringtail (© Lorrie Jo Williams 2008)
Ringtails are found throughout California. Abundance of
ringtail is reported to be highest along riparian areas in
northern California, and they are most scarce in the
Mojave and Colorado Deserts, the east slope of the Sierra Nevada, the San Joaquin Valley, and northeastern
California (Belluomini 1983, Orloff 1988). Mountain Thinking is not aware of any surveys done by the California
Department of Fish and Wildlife to establish the species’ present status and trends.
Ringtails, although omnivorous, show a preference for animal matter. Principal food items are arthropods,
mammals, and fruits. Seasonal diet varies with food availability and location. Arthropods of the orders
Orthoptera, Coleoptera, and Lepidoptera are favored, as are arachnids (Davis 1960, Toweill and Teer 1977, Trapp
1973). Mammals eaten typically include cricetine rodents, rabbits (Sylvilagus), hares (Lepus), squirrels
(Spermophilus), and carrion (Davis 1960, Toweill and Teer 1977, Trapp 1973). Plant matter eaten includes Juniperus,
Celtis, Diospyros, Quercus, Ficus, Phoradendron, Arbutus, Arctostaphylos, Opuntia, Cereus giganteus, and Pinus cembroides
(Davis 1960, Toweill and Teer 1977, Trapp 1973). Nectar feeding from Agave havardiana has been reported (Kuban
and Schwartz 1985). Passerines, Columbinae, and Perdicinae complete the diet along with cold-blooded
vertebrates, chiefly lizards and snakes and occasionally frogs and fish (Davis 1960, Toweill and Teer 1977, Trapp
1973). Plant material (seeds and miscellaneous vegetation) and animal material were found in 74.6% and 86.6% of
summer and winter scats, respectively (Ackerson and Halverson 2006). Ringtails commonly seek food and
shelter among human habitations in rural and urban areas.
Ringtails change dens frequently; an individual rarely spends more than three consecutive days in the same
shelter, except during inclement weather. In one study, two females with new litters began to move their young
from den to den 10 days after giving birth; they moved the young almost daily after day 20 (Toweill 1976).
Ringtails rarely are active in daytime (Davis 1960, Grinnell and Linsdale 1937), and behavior studies indicate an
aversion to daylight beginning soon after birth (Toweill and Teer 1982) that persists through adulthood
(Kavanau and Ramos 1975). Of 390 observations at a feeding station, 94% were after dusk and the remaining 6%
occurred during dusk. Activity of 34 radio-tracked individuals showed 47% beginning in darkness, 26%
beginning in dusk, and 9% within the 45 minutes before dusk. Termination of activity showed a similar
distribution at and around dawn (Trapp 1978).
Ringtails are found from sea level to 8,800 feet elevation in California (Zielinski et al. 2005). Ringtail habitat is
most commonly rocky, riparian areas in oak and mixed-conifer vegetation types. Based on survey work by
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Zielinski and colleagues (2005), ringtail distribution in the Sierra Nevada has not changed since studies were
conducted by Grinnell and Linsdale (1937). That distribution does not appear to have been affected by human
activities in the region, including the pattern of residential development or the change in distribution of late-seral
vegetation that occurred between assessment periods (Zielinski et al. 2005).
In west Texas, ringtails preferred catclaw (Mimosa biuncifera), persimmon (Diospyros texana), oak (Quercus sp.)
bottom communities, as well as catclaw/goldeneye (Viguiera stenoloba) and sideoats (Bouteloua curtipendula) slope
communities (Ackerson and Halverson 2006). Rock dens were used exclusively by ringtails, with 80.6% of dens
found on slopes between 30% and 60% (Ackerson and Halverson 2006).
Ringtails also occur in broken, semi-arid country characterized by pinyon pine (Pinus edulis) or juniper (Juniperus)
woodland, and may also inhabit montane conifer forests, chaparral, desert, and dry tropical habitats, provided
that rocky outcroppings, canyons, or talus slopes are present (Poglayen-Neuwall and Toweill 1988). The relative
abundance of food in riparian forests, as well as the availability of open water, attracts ringtails (Grinnell and
Linsdale 1937, Lacy 1983, Toweill and Teer 1982). Ringtail dens are most often located in rock crevices, boulder
piles, or talus, but they also use hollows in trees and under roots, burrows dug by other animals, brush piles, and
rural buildings (Grinnell and Linsdale 1937, Toweill and 21980, Trapp 1978).
Telemetry studies have shown no tendency toward monogamy but indicate a social structure based on land
tenure, with males defending territories (Toweill and Teer 1982, Trapp 1978). Ringtails are found singly or as
pairs in local concentrations, with individuals denning separately (Grinnell and Linsdale 1937).
Based on a review of the literature, modeled suitable habitat on Tejon Ranch for the ringtail includes riparian
scrub, riparian woodland, riparian/wetland, washes, seeps, springs, and intermittent streams and incorporated a
1-km buffer (Dudek 2009, USFWS 2013). Based on that modeling, Tejon Ranch supports approximately 99,000
acres of ringtail habitat.
POPULATION DYNAMICS
Density
Population density has been estimated (by mark–recapture) to be as high as 10.5–20.5 individuals per km2 in the
northern Central Valley of California (Belluomini 1983, Belluomini and Trapp 1984). Lacy (1983) estimated a
density of 7–20 individuals per km2 from a radiotelemetry study in the Central Valley, concentrated along
shorelines of ponds and sloughs. Grinnell and Linsdale (1937) estimated a density of 0.08–2.3 individuals per km2
in the chaparral country of the Pacific drainage of the Sierra Nevada, California. Based on radio-monitoring of
free-ranging ringtails, density estimates of 1.5–2.9 individuals per km2 were derived for Zion National Park in a
habitat with a mixture of juniper woodland, blackbrush (Coelogyne), and riparian vegetation (Trapp 1978);
estimates were 2.2–4.2 individuals per km2 for Edwards Plateau, Texas, a habitat characterized by juniper and
oak woodland (Toweill and Teer 1977). Population trends are not known or reported from any locale.
Survival
Annual survival rate for 17 ringtails at the Elephant Mountain Wildlife Management Area of west Texas was 0.19,
with most mortalities occurring in spring. Mortalities were recorded as avian (n = 3), mammalian (n = 3), and
unknown (n = 1). The survival estimates at Elephant Mountain may have been lower than the actual survival
because of the addition of radio-collars. However, no other survival rates on ringtails have been published for
comparison. The primary predators in the Texas study appeared to be similar to those reported by PoglayenNeuwall and Toweill (1988), including great-horned owl (Bubo virginianus) and, to a lesser extent coyotes (Canis
larans), raccoons (Procyon lotor), and bobcats (Felis rufus). Poglayen-Neuwall and Toweill (1988) reported that
carcasses of ringtails killed by mammalian predators were not fed upon on several instances, perhaps because of
the strong flavor of the flesh. Poglayen-Neuwall and Toweill (1988) speculated that diseases such as rabies, feline
and canine panleucopenia, and parasites may play a large part in population control.
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In Texas, the ringtail harvest is estimated at 75,000–100,000 individuals annually (Deems and Pursley 1983). Fur
is of poor quality and is used as trim only (Leopold 1959). Although ringtails have legal protection in many states,
many fall victim to traps set for other furbearers. The minimum population density for ringtails in the Elephant
Mountain Wildlife Management Area from November 1999 to November 2000 was 5.9–6.3 per km2 (Ackerson
and Halverson 2006).
SPATIAL STRUCTURE AND DISPERSAL
Ackerson and Halverson (2006) found that, in the Elephant Mountain Wildlife Management Area of west Texas,
the mean summer and winter range sizes (100% minimum convex polygon) for ringtails (a population of five)
were 28 hectares (ha) and 63 ha, respectively. Overlap between ringtail ranges averaged 33.3%.
Seasonal shifts of home ranges were seen on the Edwards Plateau, Texas (Toweill and Teer 1982) and in Zion
National Park, Utah, and some individuals used completely different home ranges in different months (Trapp
1978). Home range areas used by ringtails vary widely based on habitat, estimation techniques, and perhaps by
sex. Lacy (1983) reported that four home ranges in riparian habitat ranged from 5.0 ha to 13.8 ha during 8 months.
Home range areas used by ringtail (minimum convex polygon) over a 15-month period in an oak woodland
averaged 43.4 ha for two males (35– 51.7 ha) and 20.3 ha for three females (15.7–27.7 ha) (Toweill and Teer 1982).
In another study, a mean home range (modified minimum area) for nine males and four females averaged 136 ha
(49–233 ha) over a 1- to 2-month period in canyonlands of Zion National Park. Little or no intrasexual overlap in
ringtail home ranges was found, although home ranges of males and females overlapped routinely (Trapp 1978).
Competition
Poglayen-Neuwall and Toweill (1988) reported that, although ringtail is sympatric with either gray fox (Urocyon
cinereoargenteus) or kit fox (Vulpes macrotis) over much of its range, these species are not true competitors because
they differ in the mode of habitat usage, technique of habitat exploitation, temporal use of habitat, and food
habits (Trapp 1978). Ringtails shared den sites with hog-nosed skunk (Conepatus mesoleucus) and armadillo
(Dasypus novemcinctus) in Kerr County, Texas (Toweill and Teer 1982). There is evidence of competition for food
with raccoon (Procyon lotor), opossum (Didelphis marsupialis), gray fox, and striped skunk (Mephitis mephitis). Ringtail
typically yields to Urocyon, Procyon, Mephitis, and spotted skunk (Spilogale), or there is mutual avoidance (Lemoine
1977).
No protocol has been established for conducting ringtail surveys. In fact, no reported monitoring surveys have
been completed for ringtails anywhere. Dudek (2009) developed a survey protocol for Tejon Ranch based on a
review of applicable survey methods and literature related to the habitat preferences, behavior, survey methods,
and trapping methods (including Zielinski et al. 2005, Jameson and Peeters 1988, Trapp 1973, and Campbell
2004). This review indicated that baited cameras and sooted track plates located within suitable habitat
constituted the most effective method for detecting the presence of ringtail within a landscape.
Dudek (2009) placed camera stations on Tejon Ranch in 2007 in the TMV Planning Area along perennial or
longer-lasting intermittent streams, other permanent water sources (e.g., cattle troughs, springs), and Castac
Lake, at approximate 0.25 km intervals (820 ft) and at the distal ends of linear water courses and adjacent to
springs or other point source water sources throughout the Tejon Mountain Village (TMV) Planning Area.
Where multiple point sources (e.g., cattle troughs or springs) occurred near each other (i.e., not more than 0.25
km from each other), a single camera station was placed near the center of these locations. Camera stations
included one camera and an opposing bait station. Bait and camera batteries were reapplied and replaced on the
first and eighth day of the camera trapping session. Cameras were maintained in place for 16 days.
Potential ringtail scat was observed in the TMV Planning Area in 2006, but no photographs, samples, or
descriptions were provided to validate the observation. Camera/scent station surveys during 2007 in the TMV
Planning Area did not detect ringtail (Dudek 2009).
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Ackerson and Halverson (2006) reported that the canyons found in the Trans-Pecos area of Texas are an
important area for ringtails, where they use the canyon bottoms and the slopes for food and dens. Therefore,
management practices should conserve the vegetation and structure of the slopes and bottoms of canyon
habitats. Based on this study and reported impacts by cattle to some riparian areas (Applebaum et al. 2010),
Mountain Thinking recommends excluding cattle from these areas to the degree feasible. Similarly, pigs should
also be excluded or their density significantly reduced. Protection of habitat by regulation of grazing and wood
cutting is beneficial (Kaufmann 1982).
No ringtails were found on Tejon Ranch during the most recent survey (Dudek 2009), population trends are
unknown, and reported survival is extremely low. Mountain Thinking recommends conducting more surveys on
the Ranch to establish baselines for monitoring. Ackerson and Harveson (2006) trapped by placing an average of
eight Havahart live box traps (107 cm x 38 cm x 38 cm and 81 cm x 25 cm x 31 cm) placed 50 m apart in shaded
areas where physical evidence suggested ringtail presence. Traps were baited with canned fish, set for 6 days, and
checked daily. No population abundance assessment has been done anywhere in California for more than 30
years, and no trend work has been done anywhere in the state. Tejon Ranch is an excellent place to conduct such
a current inventory and to establish trend monitoring.
As part of assessing impacts of cattle on Tejon Ranch, Mountain Thinking recommends monitoring ringtails by
measuring behavior and survival in areas with differing levels of grazing impacts using radiotelemetry. Should
impacts be found to be significant, mitigation strategies should be developed, including exclusion of cattle from
important ringtail habitat. A telemetry study would also allow for assessment of movement of ringtails across
Interstate 5.
R EFERENCES
Ackerson, B. K., and L. Harveson. 2006. Characteristics of a ringtail (Bassariscus astutus) population in Trans Pecos,
Texas. Texas Journal of Science 58:169–184.
Applebaum, J., E. Brown, S. Forsyth, L. Kashiwase, and D. Murray. 2010. Developing conceptual models and
ecological baselines to support creation of an adaptive management plan for Tejon Ranch, California. Group
Master’s Project, Bren School of Environmental Science and Management, University of California, Santa
Barbara, Santa Barbara, CA. March.
Barja, I., and R. List. 2006. Faecal marking behaviour in ringtails (Bassariscus astutus) during the non-breeding
period: Spatial characteristics of latrines and single faeces. Chemoecology 16: 219–222.
Belluomini, L. 1983. Ringtail (Bassariscus astutus) distribution and abundance in the Central Valley of California.
Unpublished M.S. thesis, California State University, Sacramento, CA. 42 pp.
Belluomini, L., and G. Trapp. 1984. Ringtail distribution and abundance in the Central Valley of California. Pages
906–914 in California Riparian System: Ecology, Conservation, and Productive Management. University of California
Campbell, L. A. 2004. Distribution of habitat associations of mammalian carnivores in the central and southern
Sierra Nevada. PhD. Dissertation, University of California, Davis, CA.
Davis, W. B. 1960. The mammals of Texas. Bulletin of Texas Game and Fish Commission 41:1–267.
January 2013
Deems, E. F., Jr., and D. Pursley. 1983. North American Furbearers. A Contemporary Reference. International Association
of Fish and Wildlife Agencies with Maryland Department of Natural Resources and Wildlife Administration.
223 pp.
Dudek. 2009. Tejon Mountain Village Biological Resources Technical Report. May 2009.
Grinnell, J., J. Dixon, and J. Linsdale. 1937. Fur-bearing Mammals of California. University of California Press,
Berkeley, CA.
Jameson, E. W., and H. Peeters. 1988. California Mammals. University of California Press, Berkeley and Los Angeles,
CA, and London, England.
Kaufmann, J. H. 1982. Raccoon and allies. Pages 578–585 in J. A. Chapman and G. A. Feldhamer (eds.), Wild
Mammals of North America: Biology, Management, and Economics. Johns Hopkins University Press, Baltimore, MD.
1,147 pp.
Kavanau, J. L., and J. Ramos. 1975. Influence of light on activity and phasing of carnivores. American Naturalist
109:391–418.
Kuban, J., and G. Schwartz. 1985. Nectar as a diet of the ring-tailed cat. Southwestern Naturalist 30:311–312.
Lacy, M. K. 1983. Home range size, intraspecific spacing, and habitat preference of ringtails (Bassariscus astutus) in
a riparian forest in California. Unpublished M.S. thesis, California State University, Sacramento, CA. 64 pp.
Lemoine, J. 1977. Some Aspects of Ecology and Behavior of Ringtails (Bassariscus astutus) in St. Helena, California.
University of California Press, Berkeley, CA. 568 pp.
Leopold, A. S. 1959. Wildlife of Mexico. University of California Press, Berkeley, CA. 568 pp.
Orloff, S. 1988. Present distribution of ringtails in California. California Fish and Game 74:196–202.
Poglayen-Neuwall, I., and D. E. Toweill. 1988. Bassariscus astutus. Mammalian Species 327:1–8.
Timm, R., and K. Helgen. 2008. Bassariscus astutus. In IUCN 2011, IUCN Red List of Threatened Species. Version 2011.2.
Available at: www.iucnredlist.org.
Toweill, D. 1976. Movements of ringtails in Texas’ Edwards Plateau region. M.S. Thesis, Texas A&M University.
Toweill, D., and J. Teer. 1977. Food habits of ringtails in the Edwards Plateau of Texas. Journal of Mammalogy
58:660–663.
Toweill, D., and J. Teer. 1982. Home range and den habits of Texas ringtails. Pages 1103–1120 in J. Chapman and D.
Pursley (eds.), Worldwide Furbearer Conference, Frostburg, MD.
Trapp, G. R. 1972. Some anatomical and behavioral adaptations of ringtails, Bassariscus astutus. Journal of Mammalogy
53:549–557.
Trapp, G. R. 1978. Comparative behavioral ecology of the ringtail and gray fox in southwestern Utah. Carnivore
1:3–32.
U.S. Fish and Wildlife Service. 2012. Supplemental Draft Environmental Impact Statement for the Tehachapi
Uplands Multiple Species Habitat Conservation Plan. Volume 1. Ventura Fish and Wildlife Office, Ventura,
CA.
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Zielinski, W. J., R. Truex, F. Schlexer, L. Campbell, and C. Carroll. 2005. Historical and contemporary
distributions of carnivores in forests of the Sierra Nevada, California, USA. Journal of Biogeography 32:1385–
1407.
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14. San Joaquin kit fox ( Vulpes macrotis mutica )
The San Joaquin kit foxes (Vulpes macrotis mutica), a
federally Endangered species and California Threatened
species, historically occupied much of the San Joaquin
Valley of California (Grinnell and Linsdale 1937).
However, in the last 50 years, much of the natural land
within the San Joaquin Valley has been converted to
farmland, and this conversion is a major factor in the
endangerment of this subspecies (U.S. Fish and Wildlife
Service 1998, Warrick et al. 2007).
Cypher (2006) reported that, in the San Joaquin Valley,
optimal habitats for San Joaquin kit foxes generally are
San Joaquin kit fox (© Christine Van Horn Job 2012)
those in which conditions are more desert-like. These
include arid shrublands and grasslands (U.S. Fish and
Wildlife Service 1998). These areas are characterized by
sparse or no shrub cover, sparse ground cover with patches of bare ground, short vegetative structure
(herbaceous vegetation less than 18 inches tall), and sandy to sandy-loam soils. The distribution of San Joaquin
kit fox populations in the Central Valley is shown in Figure 14-1 (Smith et al. 2006).
Tall and/or dense vegetation generally is less optimal for foxes (Smith et al. 2005). Such conditions make it
difficult for foxes to detect approaching predators or capture prey. Kit foxes also tend to avoid rugged, steep
terrain. Predation risk apparently is higher for foxes under such topographic conditions (Warrick and Cypher
1998). In general, flat terrain or slopes of less than 5% are optimal, slopes of 5–15% are suitable, and slopes greater
than 15% are unsuitable. For this reason, the foothills of the Coast Ranges generally are considered to demark the
western boundary for suitable kit fox habitat.
Cypher (2006) classifies kit fox habitat quality as follows:
Arid grasslands
This is an aridland habitat with few or no shrubs, and which is dominated by non-native grasses,
particularly red brome (Bromus madritensis ssp. rubens). Vegetation structure is low and patches of bare
ground are common. Kangaroo rats are abundant. This habitat is optimal for kit foxes. Grazing can
further reduce the vegetative structure rendering this habitat even more suitable.
Mesic grasslands
This habitat type is more common in the eastern and northern portions of the Valley where precipitation
is more abundant. This type tends to have few or no shrubs and is dominated by non-native wild oat
grasses (Avena spp.). Vegetation structure may be higher than 18 inches and dense, particularly in years
with above-average precipitation, and this could result in increased predation risk for kit foxes. Bare
ground may be sparse. The rodent community tends to be dominated by California ground squirrels
instead of kangaroo rats. This habitat can be suitable for kit foxes, particularly if it is moderately to
heavily grazed.
Source:
January 2013
Smith et al. 2006
Figure 14-1
San Joaquin Kit Fox Populations in the Central Valley of California
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Oak woodland savanna
This habitat occurs primarily off the Valley floor up in the Coast Ranges and Sierran foothills. Oak trees
(Quercus spp.) tend to form a sparse to moderate canopy, and the herbaceous cover is dominated by nonnative wild oats and other grasses. Vegetation structure and density tends to be high with little bare
ground. Kangaroo rats are not abundant and California ground squirrels are common. This type probably
is marginally suitable for kit foxes at best, although grazing can improve permeability for kit foxes.
Orchards (e.g., fruit trees, nut trees)
Lands with these crops are not always “sanitized” of all herbaceous vegetation, and therefore sometimes
may support some prey (primarily ground squirrels, deer mice, and house mice). Also, the open
understory of orchards facilitates predator detection by kit foxes. Kit foxes have been observed to forage
in orchards as well as to occasionally spend a day or so resting, usually in man-made structures (e.g.,
pipes, rubble piles). Orchards are probably relatively permeable for kit foxes, although the risk of an
unsuccessful crossing most likely increases with distance.
Cypher and colleagues (2005) found that, although kit foxes may not be able to occupy agricultural lands, such
lands may not constitute impenetrable barriers to fox movements. Recent research also indicated that kit foxes
occasionally travel up to 1.5 km into croplands. Thus, kit foxes potentially can cross croplands to travel between
areas of more suitable habitat. Because kit foxes are nocturnal, such travel likely would occur at night. This
would allow foxes to avoid most human activities. However, because of the absence of dens in agricultural lands,
kit foxes would be subject to an increased risk of predation while crossing such lands. Kit foxes rely on dens to
avoid or escape from predators (Cypher and Spencer 1998, Koopman et al. 1998) such as coyotes and nonnative
red foxes (Vulpes vulpes). Thus, the absence of escape cover could discourage foxes from attempting to cross
croplands, and could reduce the success rate of foxes that do attempt to cross.
Kit foxes appear to be strongly linked ecologically to kangaroo rats. Kit foxes are especially well adapted for
preying on kangaroo rats and, consequently, kit fox abundance and population stability are highest in areas
where kangaroo rats are abundant (U.S. Fish and Wildlife Service 1998, Cypher et al. 2003). Kangaroo rats also
are arid land–adapted species, and thus, reach their greatest densities in the San Joaquin Valley in arid habitats.
Even so, foxes can persist on a variety of diets including leporids.
Although heteromyid rodents are a frequent prey item for kit foxes, murid rodents usually are not an important
food source (White et al. 1995, Cypher et al. 2000). However, kit foxes in a study conducted by Cypher and
colleagues (2005) in agricultural lands were able to take advantage of the relatively high numbers of deer mice
and house mice in the study area. A similar reliance on nontraditional food sources by kit foxes also occurred in
an intensively developed oil field (Cypher et al. 2000). Murid rodents were the most commonly captured small
mammals in December 1998 (95%) and December 1999 (81%), and they were found in 79% of the kit fox scats
collected in 1999. Botta’s pocket gophers and California voles were the only two species of rodents found in kit
fox scats that were not captured during the trapping sessions. However, mounds and digging by pocket gophers
were seen within almond orchards. Voles are also known to inhabit agricultural areas, so it is probable that kit
foxes preyed on both these species while foraging in farmlands (Cypher et al. 2005).
Habitat on Tejon Ranch
Penrod and colleagues (2003) noted that the distance between the Carrizo-Elkhorn and eastern Bakersfield
populations is at least 70 miles (113 km), and they believed that conservation of enough habitat to support a
satellite population of kit foxes between these two larger populations is necessary to ensure long-term
demographic exchange between them. In this context, Tejon Ranch supports grassland habitat essential to
maintaining connectivity between populations of kit foxes on the western and eastern sides of the San Joaquin
Valley. San Joaquin kit foxes have been detected in these grasslands on Tejon Ranch (Cypher et al. 2010).
Penrod and colleagues (2003) summarized that good-quality breeding habitat can be a limiting factor in the longterm sustainability of kit fox populations; thus, they used breeding habitat requirements for kit fox to develop
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the reserve boundary. Kit foxes occur in grasslands up to 1,000 m (3,281 ft) in elevation, with slopes less than
10%. Habitat with slopes less than 5% are the highest quality, while habitat with 5–10% slopes are considered to
be fair quality (Haight et al. 2002). The kit fox has a home range size of 640–7,600 acres (USFWS 1998), and
breeding pairs require a minimum of about 988 acres (4 km2) of good-quality habitat and 1,976 acres (8 km2) of
fair-quality habitat (Haight et al. 2002). Penrod and colleagues (2003) excluded land in the northwest portion of
Tejon Ranch that is dominated by agriculture or already disturbed from a proposed kit fox habitat linkage, but
ensured that the reserve includes a 2-km-wide swath of high-quality habitat. Thus, the linkage includes 18,384
acres and 12,855 acres of high- and fair-quality kit fox habitat, respectively. The linkage potentially supports as
many as 25 individuals that would serve as a satellite population between the three large populations adjacent to
Tejon Ranch. Such a satellite population on the Ranch is not expected be completely viable in isolation, but
would be supported by, and in turn would support, demographic exchange between the two adjacent core
populations (i.e., the Carrizo-Elkhorn and eastern Bakersfield populations).
Population Dynamics
White and colleagues (2000) noted that populations of kit foxes are characterized by marked instability in
population size, with density often varying five-fold or more from year to year (Cypher et al. 2000). This
instability appears to be intrinsic to desert systems owing to year-to- year fluctuations in weather and
population density (White and Garrott 1997, Dennis and Otten 2000). Unpredictable fluctuations in
precipitation contribute to high-amplitude, high-frequency fluctuations in abundance of leporids and rodents
because of variations in seed banks and vegetation biomass. In turn, these fluctuations contribute to densityindependent variations in reproductive rates of foxes (White and Garrott 1997) because leporids and rodents
usually comprise the majority of kit fox diets (White et al. 1996). Hence, periods of prey scarcity from drought or
excessive precipitation can contribute to episodes of low reproduction and lead to population crashes, whereas
high densities of prey in response to favorable precipitation levels can contribute to foxes reproducing at their
biotic potential and lead to population irruptions.
Small Satellite Populations
A small, relatively isolated population of San Joaquin kit foxes inhabits the California Army National Guard
Training Site, Camp Roberts, in west-central California. This population is unusual because it occurs outside of
the Central Valley in an area where dominant vegetation associations are oak woodland and annual grassland;
rainfall is higher than in arid, inland areas where kit foxes are more abundant. Also, the predominant prey of kit
foxes at Camp Roberts is often diurnal ground squirrels, rather than leporids or nocturnal rodents (1992White et
al. 2000). This population highlights the importance of focusing on proactive conservation strategies that will
promote the persistence and recovery of small, relatively isolated populations of San Joaquin kit foxes. These
populations are subject to extinction owing to inbreeding, loss of genetic variation, high demographic variability,
and catastrophes such as droughts or disease epidemics. Corridors between core and satellite populations need
to be maintained or established to enhance interpopulation dispersal. Also, suitable habitats for kit foxes could
be modified to promote a diversified prey base and discourage occupancy by predators or competitors (Warrick
and Cypher 1998).
Predation
Another factor that may strongly limit or regulate kit fox populations is interference competition by coyotes
(White and Garrott 1997, Cypher and Spencer 1998). Injuries by coyotes are the primary mortality factor for most
populations of San Joaquin kit foxes, accounting for 50–87% of the mortalities of radio-collared foxes (Ralls and
White 1995, Cypher et al. 2000).
Competition
Coyotes often associate with habitats that provide relatively large amounts of vegetative cover because, unlike kit
foxes, they do not commonly use dens for protective cover except when raising pups. San Joaquin kit foxes
occupy a variety of habitats, including both grassland and shrubland habitats (as described below) (Cypher et al.
2000). Kit foxes may minimize their use of shrub areas by selecting for habitats less frequented by coyotes
(substandard habitats). Partitioning of habitat, space, and diet in a heterogeneous landscape appeared to allow
January 2013
for stable coexistence of kit foxes and coyotes in the Lokern Natural Area in Kern County, California(Nelson et
al. 2007).
In a study examining relationships between foxes and coyotes, Nelson and colleagues (2007) found that food
item use by coyotes and kit foxes differed significantly, with kit foxes primarily consuming rodents and insects
and coyotes primarily consuming rabbits and rodents. Short-nosed kangaroo rats (Dipodomys nitratoides) were
more abundant in the grasslands, where Heermann’s kangaroo rats (D. heermanni) were rarely trapped;
Heermann’s were more abundant than short-nosed in shrub habitats. However, kit foxes exhibited a strong
selection for Heermann’s over short-nosed in both habitats.
During 2001–2004, Nelson and colleagues (2007) recorded 25 kit fox deaths from a sample of 62 foxes, resulting
in an annual average survival rate of 0.84. Known predation accounted for 48% (12 of 25) of total kit fox
mortalities, although probable predation and known predation combined constituted 76% (19 of 25) of total kit
fox mortalities.
Disease
Wildlife diseases do not appear to be primary mortality factors that consistently limit kit fox populations
(McCue and O’Farrell 1988, Miller et al. 2000). Central California has a high incidence of wildlife rabies cases
(Schultz and Barrett 1991), however, and high seroprevalences of canine distemper virus and canine parvovirus
indicate that populations of San Joaquin kit fox have been exposed to these diseases (McCue and O’Farrell 1988).
Hence, disease outbreaks potentially could cause substantial mortality or contribute to reduced fertility in
seropositive females, as was noted in closely related swift foxes (Vulpes velox) (Miller et al. 2000).
White and colleagues (2000) reported that captures of San Joaquin kit foxes during annual live-trapping sessions
at the California Army National Guard Training Site, Camp Roberts, decreased from 103 individuals to 20
individuals from 1988 to 1991. This decrease continued through 1997, when only three kit foxes were captured.
Similar trends in relative abundance were evident in scent-station visitations and spotlighting observations. An
outbreak of rabies virus may have contributed to this catastrophic decrease in abundance because two foxes were
found dead from rabies in 1990. Striped skunks (Mephitus mephitus) are the primary vectors of rabies virus in this
region, and a rabid skunk was trapped at Camp Roberts during 1989. Captures of foxes were positively correlated
with captures of skunks and negatively correlated with proportions of rabies-positive skunks submitted for
testing to the health department during the previous 2 years. Interference competition by coyotes also may have
contributed to this catastrophic decrease because relative abundances of foxes and coyotes were negatively
correlated from 1988 to 1997, and coyotes were responsible for 59% of fox deaths during a 4-year telemetry study
(1988–1991). The negative effects of inbreeding and interference competition by coyotes may hamper the recovery
of this relatively isolated population of foxes or eventually lead to its extinction if recruitment continues to be
poor.
CONNECTIVITY
Cypher and colleagues (2009) indicated that, currently, San Joaquin kit foxes persist as a metapopulation
consisting of two to three larger core populations and approximately 10–20 smaller satellite populations (Figure
X.14-1). The remaining number of individuals is unknown, but because habitat loss continues, kit fox numbers
are assumed to still be declining (U.S. Fish and Wildlife Service 1998).
Harrison and colleagues (2011) stressed that maintaining genetic and demographic exchange between these areas
is critical to the long-term viability of kit foxes in the San Joaquin Valley. Core areas support self-sustaining
populations that exhibit high degrees of genetic robustness and temporal stability, whereas satellite areas
typically exhibit lower population numbers and levels of genetic diversity and are generally more susceptible to
environmental stochasticity and localized extinction events. Thus, satellite populations probably rely heavily on
movement corridors to sustain gene flow or even recolonization through the dispersal of individual foxes.
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As Harrison and colleagues (2011) continued, large-scale human development of the Central Valley has not only
resulted in the loss and fragmentation of important core habitat, but also in a reduction of the quality and
availability of satellite and linkage habitats. Loss of linkage habitat may be a factor in the failure of at least two
satellite areas to be recolonized following catastrophic population declines. Fox populations have yet to
reestablish at the Camp Roberts Army National Guard Base in San Luis Obispo County following a possible
disease epidemic in the mid-1990s (White et al. 2000), or in the Pixey-Allensworth area in Tulare County
following a precipitous crash in kangaroo rat abundance in the late 1990s (White et al. 2000).
Harrison and colleagues (2011) believed that den availability may be a significant impediment to use of satellite
and linkage areas by kit foxes. Dens are a critical habitat component for kit foxes. Kit foxes use dens on a daily
basis for daytime resting, avoiding temperature extremes, conserving body water, avoiding predators, and bearing
and rearing young. Kit foxes establish dens throughout their home ranges and each fox uses, on average, 11
different dens per year (Koopman et al. 1998). In satellite and linkage areas, kit foxes may occur at low densities
or only intermittently. Thus, dens may be in low abundance or even absent. This is particularly true in linkage
areas that may be used only during annual or even multi-annual dispersal events, and in satellite areas where kit
foxes are extirpated. Low den availability could severely inhibit kit fox survival, movement, recolonization, and
reproductive success in these areas.
The installation of artificial dens in satellite and linkage areas could significantly enhance use of these areas by kit
foxes. Based on previous research conducted by the California State University, Stanislaus, Endangered Species
Recovery Program, kit foxes readily use artificial dens, including for rearing young. Thus, installing these dens
would constitute a significant habitat enhancement that could facilitate movements between areas,
recolonization of areas, and survival and reproduction within these areas. This will provide further security for
fox populations and provide connectivity between populations.
Cypher and colleagues (2007) indicated that the potential efficacy of corridors increases with width and
continuity. The wider the corridor and the more continuous the habitat (i.e., not fragmented or interrupted), the
more likely the corridors are to be found and used by kit foxes. The feasibility of establishing such corridors will
depend upon such factors as land retirement patterns and the availability of willing land sellers within the
designated corridors. At a minimum, 10-acre parcels of suitable habitat spaced at 0.25- to 0.5-mile intervals in a
“stepping stone” pattern are likely necessary to provide a reasonable probability that foxes will successfully reach
retired lands. As with the blocks of retired lands, managing corridor lands to create a suitable vegetative
structure and installing artificial dens could significantly increase the probability of use by kit foxes. The most
economically feasible, as well as the most effective, management techniques will likely involve grazing with
livestock. Factors that need to be evaluated include type of livestock, timing of grazing, grazing intensity, and
effects of infrastructure (e.g., stock tanks, access roads, corrals). Developing effective habitat management
prescriptions will increase the potential for colonization of retired lands by kit fox and prey populations, as well
as increase the long-term viability of such populations.
Koopman and Cypher (2000) outlined the challenge of linking populations. They found annual dispersal (percent
of individuals) ranged from 0% to 79% for juvenile males, 0% to 50% for juvenile females, and 0% to 52% for all
foxes. Sixty percent of all foxes that survived to breeding age reproduced, except among dispersing females, none
of which reproduced.
Cypher and colleagues (2009) noted that road-associated threats to kit foxes are likely to increase in the San
Joaquin Valley as the human population expands by an expected 100–200% over the next 40 years. On the
Lokern Natural Area, roads did not appear to affect kit fox survival. Only one of 60 radio-collared kit foxes was
killed by a vehicle during their 33-month study in which foxes were monitored for a total of 19,909 radio-days.
The observed mortality rate from vehicles was similar to or lower than rates reported from other studies of kit
foxes in natural habitats.
These researchers cautioned that their results only apply to two-lane roads, which are the most common road
type within remaining habitat for San Joaquin kit foxes. Also, traffic volume on the roads in their study was low
to moderate (800–1,500 vehicles per day). For comparison, volume on the nearby Interstate 5 (I–5) was
January 2013
approximately 32,000 vehicles per day. I-5 at Lebec (adjacent to Tejon Ranch) had 65,000 vehicles per day in
2002. Furthermore, road density on their study area was low, and negative effects could become apparent as
additional roads are constructed within kit fox habitat. Swift fox mortality from vehicles was higher on a site
with 125 km of roads compared to a study site with only 66 km of roads. Effects of larger, busier roads on kit
foxes have not been examined but are likely to be more significant. In nearby Bakersfield, urban kit foxes were
struck by vehicles proportionally more frequently on roads with more lanes, higher speed limits, and higher
traffic volumes (Cypher et al. 2009).
Schauster and colleagues (2002) evaluated survey methods for swift fox, including catch per unit effort (trapping
surveys), mark–recapture estimates, scent-post surveys, spotlight counts, scat deposition rate surveys, and an
activity index. All surveys were conducted along five 10-km transects during three seasons annually. All methods
except spotlight counts were reliable and consistent for detecting swift fox presence across the five survey
transects. Regression analyses indicated that the correlation between swift fox density and survey method varied
among methods and seasons, with mark–recapture estimates being the highest predictor (r = 0.711), followed by
scat deposition surveys (r = 0.697), scent-post surveys (r = 0.608), spotlight surveys (r = 0.420), trapping surveys
(r = 0.326), and the activity index (r = 0.067). Stepwise regression analysis of all survey methods indicated that the
combination of mark–recapture estimates and scent-station indices was the highest predictor of swift fox
density (r = 0.853). The combination of these two surveys would be economical and reliable for monitoring swift
fox population trends. The combination of scent-station indices and scat deposition surveys was almost as
reliable (r = 0.829) but was far less costly than surveys involving mark–recapture estimates. A combination of
more surveys did little to increase the level of prediction.
Smith and colleagues (2005) assessed methods for kit foxes and indicated that, according to previous studies,
under optimal conditions, spotlight surveys were only marginally effective in detecting kit foxes, and the number
of foxes observed during spotlight surveys was highly correlated with terrain (Ralls and Eberhardt 1997). Thus,
although the combination of spotlight surveys and distance sampling shows promise as a method to estimate
abundance of kit foxes in some high-density core populations, spotlight surveys alone are not optimal for
mapping distribution. Furthermore, trapping methods can be costly and have a risk of injury, and capture success
can be poor in areas where abundance is low (Schauster et al. 2002). Finally, low visitation rates have been
known to contribute to poor reliability of scent stations to monitor kit fox populations (Warrick and Harris
2001).
Given the limitations of these methods, Smith and colleagues (2005, 2006) tested the use of scat detection dogs
to monitor kit foxes. They reported that collection of scats of various canid species has been shown to be a
successful technique for estimating relative abundance (Kohn et al. 1999). Recently, collection of scats followed
by genetic analysis was found to be the most efficient method for estimating relative abundance of swift foxes,
surpassing scent stations, trapping, searching for tracks, spotlighting, and calling. To optimize effort, they
created transect routes that were looped or continuous, did not require backtracking, and covered an adequate
representation of the suitable kit fox habitat present on the property. Their prior research indicated that
detection dogs found scats at a mean distance of 4.8 meters from the transect line (maximum distance was 38.40
meters) (Ralls and Smith 2004). Length of survey routes on each property varied depending on the amount of,
and access to, suitable kit fox habitat (mean of 10.57 km, range of 1–37 km). Previously, they had found that scat
collection on 30 1-km transects in six areas with known kit fox populations revealed approximately 29.8 scats
per km (range of 1–130). Thus, they chose 1-km transects as the minimum to be searched. Ralls and colleagues
(2010) recommended conducting scat surveys outside the reproductive season to minimize bias associated with
reduced movements of females.
The maintenance of suitable corridor habitat for kit foxes is identified as an essential goal in multiple tasks in the
recovery plan for the San Joaquin kit fox (U.S. Fish and Wildlife Service 1998):
▪
January 2013
Task 5.3 Maintain linkages of natural lands around the fringe of the Valley and elsewhere for San Joaquin
kit fox and other listed and sensitive species.
As indicated by Cypher and colleagues (2010), areas on the north side of Tejon support foxes and could perhaps
support enough foxes to become part of a key region of connectivity for foxes. We agree with recommendations
in Cypher and colleagues (2010) to continue monitoring, build artificial dens, and graze these areas intensively to
improve habitat quality for kit foxes. It is important to conduct telemetry studies to monitor demographic
parameters and rates of increase of satellite populations; assess sizes and degree of isolation of satellite
populations; and estimate effective dispersal between populations. To monitor, we recommend capturing foxes
and radio collaring. Should population viability appear marginal, we recommend testing translocations of foxes
to increase viability and connectivity.
Finally, we recommend surveys on the Mojave side of Tejon to determine the status of kit foxes (non-endangered
subspecies). Almost no work has been done on kit foxes in the Mojave Desert. We recommend trapping and
marking studies to monitor these foxes.
REFERENCES
Cypher, B.L. 2006. Kit Fox Conservation in the San Luis Drainage Study Unit. Unpublished report to the U.S. Bureau of
Reclamation South-Central California Area Office. California State University, Stanislaus, Endangered
Species Recovery Program. Fresno, CA.
Cypher, B. L., and K. A. Spencer. 1998. Competitive interactions between coyotes and San Joaquin kit foxes.
Cypher, B. L., C. Bjurlin, and J. Nelson. 2009. Effects of roads on endangered San Joaquin kit foxes. Journal of
Cypher, B. L., H. O. Clark, Jr., P. A. Kelly, C. Van Horn Job, G. W. Warrick, and D. F. Williams. 2001. Interspecific
interactions among mammalian predators: implications for the conservation of endangered San Joaquin kit
foxes. Endangered Species Update 18:171–174.
Cypher, B. L., P. A. Kelly, and D. F. Williams. 2003. Factors influencing populations of endangered San Joaquin
kit foxes: implications for conservation and recovery. Pages 125-137 in M. A. Sovada and L. Carbyn (eds.), The
Swift Fox: Ecology and Conservation in a Changing World. Canadian Plains Research Center, Regina, Saskatchewan.
Cypher, B. L., P. A. Kelly, D. F. Williams, H. O. Clark, Jr., A. D. Brown, and S. E. Phillips. 2005. Foxes in Farmland:
Recovery of the Endangered San Joaquin Kit Fox on Private Lands in California. California State University, Stanislaus,
Endangered Species Recovery Program, Fresno, CA.
Cypher, B., S. Phillips, and P. Kelly 2007. Habitat Suitability and Potential Corridors for San Joaquin Kit Fox in the San Luis
Unit. California State University, Stanislaus, Endangered Species Recovery Program, Fresno, CA.
Cypher, B., C. Van Horn, E. Tennant, and S. Phillips. 2010. Mammalian Species Surveys in the Acquisition Areas on the
Tejon Ranch, California. California State University, Stanislaus, Endangered Species Recovery Program, Turlock,
CA.
Cypher, B. L., G. D. Warrick, M. R. M. Otten, T. P. O’Farrell, W. H. Berry, C. E. Harris, T. T. Kato, P. M. McCue, J.
H. Scrivner, and B. W. Zoellick. 2000. Population dynamics of San Joaquin kit foxes at the Naval Petroleum
Reserves in California. Wildlife Monographs 145.
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Dennis, B., and M. R. M. Otten. 2000. Joint effects of density dependence and rainfall on abundance of San
Joaquin kit fox. Journal of Wildlife Management 64:388–400.
Grinnell, J., and J. Linsdale. 1937. Fur-Bearing Mammals of California. University of California Press, Berkeley, CA.
Harrison, S., and B. Cypher. 2007. Feasibility and Strategies for Reintroducing San Joaquin Kit Foxes to Vacant or Restored
Habitats. California State University, Stanislaus, Endangered Species Recovery Program, Fresno, California. 74
pp.
Harrison, S., B. Cypher, and S. Phillips. 2011. Enhancement of Satellite and Linkage Habitats to Promote Survival,
Movement, and Colonization by San Joaquin Kit Foxes. U.S. Bureau of Reclamation and California State
University, Stanislaus, Endangered Species Recovery Program. Fresno, CA.
Koopman, M. E., and B. L. Cypher. 2000. Dispersal patterns of San Joaquin kit foxes (Vulpes macrotis mutica).
Koopman, M. E., J. H. Scrivner, and T. T. Kato. 1998. Patterns of den use by San Joaquin kit foxes. Journal of Wildlife
McCue, P. M., and T. O’Farrell. 1988. Serological survey for selected diseases in the endangered San Joaquin kit
fox (Vulpes macrotis mutica). Journal of Wildlife Diseases 24:274–281.
Miller, D., D. Covell, R. McLean, W. Adrian, M. Niezgoda, J. Gustafson, O. Rongstad, R. Schultz, L. Kirk, and
T. Quan. 2000. Serologic survey for selected infectious disease agents in swift and kit foxes from the western
United States. Journal of Wildlife Diseases 36:798–805.
Nelson, J. L., B. Cypher, C. Bjurlin, and S. Creel. 2007. Effects of Habitat On Competition Between Kit Foxes and
Coyotes. Journal of Wildlife Management 71:1467–1475.
Penrod, K., C. Cabañero, C. Luke, P. Beier, W. Spencer, and E. Rubin. 2003. South Coast Missing Linkages: A Linkage
Design for the Tehachapi Connection. Unpublished report. South Coast Wildlands Project, Monrovia, CA.
Ralls, K., and L. Eberhardt. 1997. Assessment of abundance of San Joaquin kit foxes by spotlight surveys. Journal of
Ralls, K., and P. White. 1995. Predation on San Joaquin kit foxes by larger canids. Journal of Mammalogy 76:723–729.
Ralls, K., S. Sharma, D. Smith, S. Bremner-Harrison, B. Cypher, and J. Maldonado. 2010. Changes in kit fox
defecation patterns during the reproductive season: implications for noninvasive surveys. Journal of Wildlife
Schauster, E. E., M. Gese, and A. M. Kitchen. 2002. An evaluation of survey methods for monitoring swift fox
abundance. Wildlife Society Bulletin 30:464–477.
Schultz, L. J., and L. R. Barrett. 1991. Controlling rabies in California 1990. California Veterinarian 45:36–40.
Smith, D. A., K. Ralls, B. L. Cypher, and J. E. Maldonado. 2005. Assessment of scat-detection dog surveys to
determine kit fox distribution. Wildlife Society Bulletin 33:897–904
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Smith, D. A., K. Ralls, B. L. Cypher, H. O. Clark Jr., P. A. Kelly, D. F. Williams, and J. E. Maldonado. 2006. Relative
abundance of endangered San Joaquin kit foxes (Vulpes macrotis mutica) based on scat-detection dog surveys.
Southwestern Naturalist 51:210–219.
U.S. Fish and Wildlife Service. 1998. Recovery Plan for Upland Species of the San Joaquin Valley, California. Region 1,
Portland, OR. 319 pp.
White, P. J., and R. A. Garrott. 1997. Factors regulating kit fox populations. Canadian Journal of Zoology 75:1982–
1988.
White, P. J., K. Ralls, and C. White. 1995. Overlap in habitat and food use between coyotes and San Joaquin kit
foxes. Southwestern Naturalist 40:342–349.
White, P. J., C. A. Vanderbilt-White, and K. Ralls. 1996. Functional and numerical responses of kit foxes to a
short-term decline in mammalian prey. Journal of Mammalogy 77:370–376.
Warrick, G., and B. Cypher. 1998. Factors affecting the spatial distribution of San Joaquin kit foxes. Journal of
White, P. J., W. H. Berry, J. J. Eliason, and M. T. Hanson. 2000. Catastrophic decrease in an isolated population of
kit foxes. The Southwestern Naturalist 45:204–211.
Warrick, G., and C. Harris. 2001. Evaluation of spotlight and scent-station surveys to monitor kit fox abundance.
Warrick, G. D., H. Clark, P. Kelly, D. Williams, B. Cypher, and H. Clark. 2007. Use of agricultural lands by San
Joaquin kit foxes. Western North American Naturalist 67:270–277.
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15. Upland Birds
T URKEY
Status and Distribution
Merriam turkeys (Meleagris gallopavo spp. merriami) were
introduced to Tejon Ranch in 1989, and hunting started in
1991. Merriam turkeys are native to the southwestern
United States as far west as north-central Arizona.
Bochenski and Campbell (2006) conducted an extensive
study of the comparative osteology of turkeys
(Meleagrididae) and confirmed the validity of the extinct
California turkey (Meleagris californica). The study included
all major and many minor skeletal elements of adult
specimens of M. californica, best known from the asphalt
deposits at Rancho La Brea, California, and both species of
extant turkeys: Meleagris gallopavo and Meleagris ocellata. The
study also confirmed that M. californica is more closely
Turkey (© Tejon Ranch Conservancy 2005)
related to M. gallopavo than to M. ocellata, the distribution of
which is southern Mexico. A review of turkey remains
from locations other than Rancho La Brea confirmed the
presence of M. californica in California within a relatively small geographic range extending from Orange County
in the south, through Los Angeles County, to Santa Barbara County in north. Other unconfirmed records of fossil
turkeys in the western United States suggest that the species might have been more widespread. M. californica
went extinct soon after the arrival of aboriginals.
Harvest
Diefenbach and colleagues (2012) tagged eastern turkeys over a large region of New York, Pennsylvania, and Ohio
and found that annual survival was approximately twice as high for juveniles (0.64–0.87) as adults (0.30–0.41).
Spring harvest rates for adult turkeys were greater for adults (0.35–0.39 killed) than juveniles (0.17–0.27).
Because of greater harvest rates for adult males, the proportion of adult males in the population was less than the
proportion in the harvest and ranged from 0.40 to 0.81 among all states and years. The high harvest rates observed
for adults may be offset by greater recruitment of juveniles into the adult age class the following year, such that
these northeastern states can sustain high harvest rates and still maintain a relatively high proportion of adult
males in the harvest and population.
For male wild turkeys, spring harvest is the single greatest mortality factor (Wright and Vangilder 2005) and is
thought to be additive to other sources of mortality because most natural mortality occurs during the spring
breeding season (Holdstock et al. 2006, Moore et al. 2008). Diefenbach and colleagues (2012) reported that nonhunting mortality was low for juveniles (0–0.20), especially compared to adults (0.21–0.31), which included
illegal kills, crippling loss, harvest during the fall hunting season, and natural causes of mortality (such as
predation and disease). Although fall harvest is thought to have the greatest influence on population growth
(Vangilder and Kurzejeski 1995, Alpizar-Jara et al. 2001, McGhee et al. 2008), spring harvest can influence the
number and proportion of adult gobblers in the population (Vangilder and Kurzejeski 1995). For example,
Vangilder and Kurzejeski (1995) modeled a wild turkey population and saw that, by increasing overall spring
harvest rates from 25% to 50%, the proportion of the population composed of adults declined from 72% to 56%.
Consequently, spring hunting–related mortality rates (legal harvest, illegal kills, and crippling loss) of more than
30–35% of the male population are thought to adversely affect hunter satisfaction because the proportion of
adults in the population and harvest is predicted to decline (Vangilder and Kurzejeski 1995).
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Habitat Management
Wakeling and colleague (1998) examined the nesting success of Merriam’s turkeys in the southwest United
States and recommended retention of greater numbers of large-diameter trees and the avoidance of timber
treatment in areas with limited nesting habitat to ensure that suitable, productive nesting habitats are available.
In addition to timber harvest, activities that reduce horizontal screening cover (e.g., prescribed burning) in
nesting habitat may similarly reduce the productivity of that habitat for nesting Merriam’s turkeys until nesting
habitats return to pre-treatment levels of screening cover (low shrubs).
Rumble and Anderson (1996), working in the Black Hills of South Dakota, reported that production of pine seed,
a major food item of Merriam’s turkeys, differed among years. A strong relationship was seen between abundance
of pine seeds and microhabitats selected by turkeys. Basal area of microhabitats between October and March was
positively correlated with annual production of ponderosa pine seed. Abundance of ponderosa pine seeds in
turkey microhabitats during this period was at least four times the estimated average annual production
Research suggested that, for deer and elk habitat, no more than one third of the area should be cleared of junipers.
However, Scott and Boeker (1977) indicated that, for turkeys, cleared areas should be no wider than 200 meters
(m) and that uncleared woodlands left between clearings should be at least as wide as the treated areas. Cleared
strips of 200 m were wider than desired for turkeys. Since turkeys seldom feed in open areas farther than 45 m
from cover, cleared strips no wider than 90 m would be more appropriate for turkey management. Good roosting
sites are also important, and removal of pinyon-juniper should be planned so that travel lanes are maintained to
stands of mature ponderosa pines, particularly those where turkeys already roost.
Rumble (1992) summarized the literature and found that roosts are apparently important to sustaining
populations of turkeys (Mackey 1984, Kilpatrick et al. 1988). Merriam’s turkeys abandoned areas in Arizona
where the basal area at roost sites was reduced to 16.8 m2 per hectare (ha) (73 ft2 per acre) (Scott and Boeker
1977). Roost trees selected by Merriam’s turkeys typically have been large (more than 40 cm in diameter at breast
height [dbh]), mature, or overmature (large-diameter old trees with flat tops and large, horizontal branches)
ponderosa pine (P. ponderosa) (Hoffman et al. 1993, Boeker and Scott 1969). Narrowleaf cottonwood (Populus
agustifolia), Engelmann spruce (Picea engelmannii), white fir (Abies concolor), and Douglas-fir (Pseudostuga menziesii)
also are used for roosting (Mackey 1984, Lutz and Crawford 1987).
Trees more than 40 cm dbh are uncommon in the Black Hills, but the area supports large and sustaining turkey
populations. Roosting habitats should be dispersed throughout the forest and can be included in winter habitats
(Rumble 1992). In terms of U.S. Forest Service management criteria, stands of ponderosa pine more than 22.5 cm
dbh and with 70–100% overstory canopy cover would meet these criteria. Timbered stands that are managed to
provide roosting habitats for turkeys should include trees on the upper third of the slope with layered horizontal
branches, spaced at 0.9-m intervals, in the upper half of the tree. These forest and tree characteristics may be
partially related to the diameter at breast height of the tree.
Tejon Ranch Management
Tejon Ranch does not have a formal survey procedure for turkeys but relies on observations by guides. Harvests
from 2001 to 2008 ranged from 8 to 41 individuals and averaged 25 birds per year. According to Tejon Ranch
guides, the number of turkeys on the Ranch appeared to remain stable from 2010 to 2011. Conditions for hunting
during spring 2011 were extremely difficult because of weather conditions and accessibility on the Ranch. Of the
50 tags authorized by the Tejon Ranch Private Lands Management (PLM)Program, 20 tags were issued and four
bearded birds were harvested, for a 20% success rate (including the California Department of Fish and Game’s
Junior Hunt). The hunter-days per bird harvested were difficult to track because of weather conditions. As a
result of the suspension of normal hunting operations on the Ranch for a portion of spring 2012, the Ranch will
not issue any turkey tags in 2012 and will closely observe what a season of rest does for the turkey population.
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Monitoring Techniques and Survey Methods
Butler et al. (2006) indicated that the Texas Parks and Wildlife Department has conducted brood counts
(Schwertner et al. 2003), winter roost counts (Butler et al. 2006), and harvest surveys (Cook 1973) to monitor
population trends. However, these index-based techniques lack power to detect anything less than drastic
changes in populations (Schwertner et al. 2003, Butler et al. 2007). For example, brood counts had 0.50 power to
detect long-term changes of 0.20% (Schwertner et al. 2003). Also, brood counts can index reproduction and
recruitment on a localized level, but they do not indicate actual abundance (Weinstein et al. 1999, Butler et al.
2007). Winter roost counts can estimate abundance on a localized level (Butler et al. 2006), but the effort needed
at an ecoregional scale is prohibitive.
Road-based distance sampling is a common technique used to survey avian species such as mountain quail
(Oreortyx pictus), red-legged partridge (Alectoris rufa), ring-necked pheasants (Phasianus colchicus), wild turkeys, and
red-tailed hawks (Buteo jamaicensis) (Brennan and Block 1986, Borralho et al. 1996). Distance sampling is popular
because it alleviates problems associated with indices by accounting for incomplete detectability (Rosenstock et
al. 2002, Butler et al. 2006). Butler and colleagues (2007) evaluated distance sampling as a method for surveying
wild turkeys in the Texas Rolling Plains and found that road-based surveys provide sufficient power (0.80) to
detect a 10–25% change in turkey populations over an 8- to 12-year period; more drastic changes (35–50%) were
detectable in shorter periods (3 years). That study suggested that road-based distance sampling may effectively
monitor wild turkey populations on ecoregional scales at a lower cost than other methods (e.g., aerial surveys,
mark–resight) (Butler et al. 2006, Butler et al. 2007).
If surveys are restricted to riparian communities, 128 16-km transects surveyed during afternoons in the Edwards
Plateau and 246 16-km transects surveyed during mornings in the Rolling Plains would be adequate (0.80 power)
to detect a 35–50% change in population density in 3 years. Although much longer periods are needed to detect
smaller population changes (8–12 years to detect a 10–25% change) (Butler et al. 2007), typically detection of a
25–50% change is desired for management purposes (Healy and Powell 1999). However, feasibility of road-based
surveys may vary depending on time and personnel constraints, availability of roads, and fiscal restraints.
Additionally, traffic conditions may influence encounter rates, but the researchers lacked data to examine this
prospect. Finally, survey protocols may not be applicable to other parts of the wild turkey’s range. Wildlife
managers should develop survey protocols tailored to the conditions of the region in which they work.
Erxleben and colleagues (2010) randomly established 100 16-km transects on county roads or farm–to-market
highways in rural areas. They used ArcMapTM to generate random transect start points on roads. They began
surveys 30 minutes after sunrise and finished surveys 1 hour before sunset. They conducted all surveys on days
with no precipitation or fog, conditions which could reduce flock detectability. Surveys were conducted from a
four-wheel-drive pickup truck with one observer traveling at 16–32 km per hour. The observer was also the
driver of the pickup truck. To maintain independence of sighting events, they recorded each flock, rather than
each bird, as an individual observation.
When the researchers detected a flock, they used a range finder to estimate sighting distance to the center of the
flock. For each observation, they collected a sighting distance, a sighting bearing, and the UTM coordinate on the
transect at the point where they collected the measurements. These measures were used to estimate
perpendicular distance (in meters) to the center of each observed flock. They recorded all measurements to the
location of the flock prior to flushing. Observers usually recorded measurements perpendicular to the flock or
from a location that provided the least obstructed view. They also recorded flock size, flock composition (i.e.,
number by gender and age), and any flushing responses (i.e., none, walked away, ran away, or flew away) for each
observation. To assess vegetative cover for each observation that could potentially obscure flocks from detection,
they classified vegetation as grassland, low-density understory (50% visual obstruction), or high-density
understory (more than 50% visual obstruction). To determine flock encounter rates, they divided data into
surveys conducted during the first half of daylight hours (AM) and surveys conducted during the last half of
daylight hours (PM), and then used DISTANCE 5.0 (Thomas et al. 2005) to calculate AM, PM, and combined
encounter rates for each ecoregion to determine when road-based surveys would be most appropriate. Butler et
al. (2007) found that a sample size of 60–70 flock detections was necessary to detect a 10–25% change in
January 2013
population density in 8–12 years or a 35–50% change in 3 years. Therefore, they used estimated encounter rates to
determine how many kilometers of road were needed to detect 60 flocks within each ecoregion. They did not use
DISTANCE 5.0 to estimate wild turkey densities because of low encounter rates.
Tejon Ranch Research and Conservation Recommendations
Mountain Thinking Conservation Science Collaborative recommends development of a turkey management plan
with objectives indicating management prescriptions for turkey relative to other species, population and harvest
objectives, and monitoring techniques.
Age and sex characteristics and success rate of hunter should be recorded for all turkeys killed. Mountain
Thinking Conservation Science Collaborative recommends testing road-based distance sampling methods for
monitoring turkeys on Tejon Ranch (Rosenstock et al 2002). Transects should be randomly sampled in the best
habitats on the Ranch and driven as recommended above to determine if sample sizes are large enough to allow
use of this method. Spring harvest rates of less than 30% appear appropriate but should be tested on Tejon Ranch
via monitoring.
As turkeys are not native to Tejon Ranch and are very resilient, any habitat management for wildlife on Tejon
Ranch should be consistent first with the needs of native species. Turkeys supply a source of prey for coyotes,
bobcats, and foxes, so any program geared to enhancing turkey survival will likely enhance these predators as
well and should be weighed against the role of these predators and their effects on other wildlife species.
MOUNTAIN Q UAIL (O REORTYX PICTUS )
The mountain quail is the largest quail in the United
States. John Muir described the mountain quail as “the
very handsomest and most interesting of all American
partridges … That he is not so regarded, is because as a
lonely mountaineer he is not half known.” As Gutierrez
and Delehanty (1999) note, more than 100 years later,
Muir’s observation remains largely true. The mountain
quail is a secretive bird inhabiting dense shrub and forest
habitats of the Pacific Coast and western Great Basin of
North America. As further noted by Gutierrez and
Delehanty (1999), despite its occupation of almost every
major mountain range along the American West Coast, its
proximity to major coastal population centers, and the
description of five subspecies, the mountain quail remains
an enigma to avian ecologists. Its sometimes impenetrable
Mountain Quail (© G. Smith 2009)
habitat and secretive nature contribute to the paucity of
life-history information. The few comprehensive studies of
mountain quail provide insights about a bird that appears
to differ from other North American quail in many ways. These differences include its ability to exploit highelevation habitats by making long-distance seasonal movements, and its unusually high degree of herbivory and
ability to exploit temporarily abundant foods.
Brennan and colleagues (1987) found that mountain quail were consistently associated with a microhabitat
configuration consisting of tall and dense shrubs that are in close proximity to drinking water and escape cover.
Although the researchers emphasized the importance of food and water, they could not completely discount the
possibility that other processes, such as predation, climatic stress, or even parasitism may have influenced the
patterns of habitat use observed. Interspecific competition with California quail (Callipepla californica) was largely
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ruled out by Gutiérrez (1980) as a process that has influenced habitat use by mountain quail. The respective
ecologies and biogeographic histories of these two quails are vastly different (Gutiérrez 1980).
Mountain quail spent a great deal of time beneath the perennial vegetation that provides many food resources
(Gutiérrez 1980). The analysis of the relative amounts of shrub species indicated an apparent preference for those
species that are known to provide food (as described in “Diet”). Presumably, large and well-developed shrubs
provide more food than small shrubs. Tall, dense shrubs might also provide more shade and relief from thermal
stress than low, sparse shrubs. Thus, it seems reasonable that this quail should use areas where the shrub height
and canopy coverage is greater that what is generally available. Although Gutiérrez (1980) emphasized the role of
shrubs in their analysis, other variables that showed little difference between the used and available groups (such
as percent herb cover or litter depth) might also be important biologically.
Gutiérrez (1980) provided the only quantitative assessment of habitat use by mountain quail. He reported that a
dense tree canopy and steep slopes were important components of mountain quail habitat in the Coast Ranges of
central California. Because his study was conducted in only one area, a general pattern of habitat use was not
established. Gutiérrez (1980) reported that steep slopes were an important factor in distinguishing between the
habitats used by California and mountain quail. The data of Gutiérrez and colleagues (1987) indicated that
topography alone probably has little value as a component of mountain quail habitat. Rather, it is the
juxtaposition of tall, dense shrubs in proximity to available water that characterizes the general pattern of
habitat use by mountain quail in northern California compared to California quail.
Legumes were the most prominent food consumed by mountain quail in southwestern Oregon (Pope et al. 2002).
California hedge-parsley, manzanita, and hawthorn were frequently used in winter. Mountain quail ate greater
quantities of grasses and green foliage in winter, but berries were consumed more during the fall. In fall and
winter, insects were frequently found in crops, but composed less than 3% of the total volume of the diet.
Mountain quail in southwestern Oregon are opportunistic foragers that shift their diets seasonally to take
advantage of prevailing food abundances.
Population Dynamics
Analyses of both long-term (1966–1991) and short-term (1982–1991) Breeding Bird Survey data found “stable”
populations in California, Oregon, and Washington (Church et al. 1993). Reproduction is strongly linked to
rainfall in arid ranges (Gutierrez and Delehanty 1999).
Brennan and Block (1986) estimated the densities of four populations of mountain quail in northern California
during the breeding season (May–June) using line transect data. Surveyed areas were 500–1,200 ha in size;
elevations ranged from 1,100 m in the Coast Ranges to 2,100 m in the Sierra Nevada. Vegetation in the Coast
Ranges consisted of mixed conifer and broad-leaved forest and stands of mixed brush. The Klamath and Sierra
sites were dominated by stands of mixed conifers and mixed brush. The Modoc area was dominated by Jeffrey
pine (Pinus jeffreyi)-western juniper (Juniperus occidentalis) forest, shrub-steppe, and basalt lava reefs. Estimates of
density were obtained from analyses of perpendicular distance data. Density ranged from 9 to 30 quail per 100 ha,
with associated coefficients of variation less than 20%. In general, mountain quail were behaviorally compatible
with line-transect sampling methodology.
Brennan and Block (1986) collected data for 4–5 days in each area, with total transect length of 10–14 km. Data
were collected using the methods outlined by Burnham and Anderson 1984. All counts were made by a twoperson team. After selecting random starting points, transects were placed at each area along abandoned skid
trails, haul roads, fire breaks, and other linear openings in the vegetation to ensure that quail located on the
transect line would be detected. This also minimized potential observer effects on the quail. The teams walked
along each segment of transect and recorded sighting distance and angle deviation from the transect to each
detected quail. Detection (sighting) distances were measured with a rangefinder; angles were measured with a
compass equipped with a sighting mirror. In the case of calling birds, the teams used a rangefinder to estimate
the distance from the transect line to an object that was considered to be at the same location as the calling quail.
Angles from the transect line to each calling quail were also estimated in this way. The perpendicular distance
January 2013
from the transect line to each detected quail was calculated using the program TRANSECT (Burnham and
Anderson 1984). Teams alternated the starting and ending points to avoid temporal sampling bias (as described
in Grue et al. 1981).
Mountain Thinking recommends development of a quail management plan with objectives indicating
management prescriptions for quail relative to other species, population and harvest objectives, and monitoring
techniques.
Age and sex characteristics and success rate of hunters should be recorded for all quail killed. Similar to turkeys,
Mountain Thinking recommends road-based distance sampling methods for monitoring quail on Tejon Ranch
(Rosenstock et al. 2002). Transects should be randomly sampled in the best habitats (dense shrubs) on the
Ranch and driven or walked, as recommended above, to determine if sample sizes are large enough to allow use of
this method. Because quail population changes are largely driven by precipitation, if Tejon Ranch pursues
relatively high harvest rates, Mountain Thinking recommends adjusting the harvest in relation to annual
precipitation.
Activities that promote shrub cover will be beneficial, including fire and reduced grazing.
Gutiérrez and Delehanty (1999) noted that many areas of mountain quail ecology remain unknown, but this is
understandable because the behavior and habitat of the species present a formidable challenge. Key priorities for
future research are the following:
▪
Population dynamics‒Little is known of the dynamic nature of mountain quail populations, vital rates,
dispersal, or basic life history traits.
▪
Fire-habitat relationships‒The role of fire in creating and maintaining vegetation communities at seral
stages beneficial to quail has tremendous potential for explaining population dynamics and range
expansions and contractions.
C ALIFORNIA QUAIL (C ALLIPEPLA CALIFORNICA )
The California quail is the state bird of California. It is the
subject of A. Starker Leopold’s 1977 classic book, The
California Quail, which combines nearly a century’s worth of
published and unpublished research into a single text.
California quail inhabits scrubby habitat, primarily in
California, Oregon, and Washington. The species does
best in broken habitat, where it has access to cover and to
annual food species, mainly legumes. Given its occurrence
in arid land west of the California deserts, researchers have
been particularly interested in the species’ tolerance of
high temperatures and drought (Calkins et al. 1999).
Population Dynamics
Density
California quail
(Photo by Dave Menke, U.S. Fish and Wildlife Service)
California quail densities vary as a result of climatic factors. Local densities range from no more than 0.02 birds
per hectare (ha) to at least 0.5 birds per ha (Leopold 1977, Koford 1987). Brennan (1993) analyzed Audubon
Society Christmas Bird Count data for 1960–1989 and concluded that populations across surveyed areas had
declined rapidly from 1960 to the 1970s and slightly from the 1970s to 1989. Church and colleagues (1993), using
January 2013
Breeding Bird Survey data (1966–1991), concluded that populations were stable across surveyed areas and
increased 3.2% per year during 1982–1991. Levels of Jan–March rainfall accounted for 76% of the total variance in
reproductive success in an unhunted population on Santa Cruz Island over 25 years (Botsford et al. 1988, Smith et
al. 1988).
Crawford (1978) examined long-term effects of weather and vegetation succession and found that succession was
the only variable related significantly to the population decline of California quail. Rate of harvest did not affect
quail populations from 1958 to 1974. Because of the rapid rate of succession, California quail were closely
associated with early successional stages and open habitat.
Francis (1970) reported that regression of quail productivity on selected weather parameters revealed a close
relationship. Quail productivity seemed to be a function, in order of importance, of (1) soil moisture in late April
calculated from temperature and rainfall data, (2) proportion of breeding females more than 1 year old, and (3)
seasonal rainfall from September to April. Three geographically isolated wild quail populations and one penned
population were observed during two breeding seasons that were very different in productivity. In 1963, quail
produced many young. The breeding period was characterized by intense activity and persistence of breeding
effort extending, in captive birds, to production of second broods. Vegetation that year included many annual
forbs growing vigorously during the breeding season. In 1964, production of quail was very low on all areas. The
birds seemed to lack reproductive drive, and breeding effort terminated early. Forb vegetation that year was
sparse.
Botsford and colleagues (1988) reported that demographic responses of California quail to precipitation-related
variables differed among locations with different mean rainfall. Based on 23 years of data from a California quail
population in a semiarid region, they determined a positive response of reproductive success (juveniles per adult)
to precipitation during the previous winter. Computed correlations with soil moisture content and actual
evapotranspiration were significant but not as high as those with precipitation. Correlations with mean monthly
temperature, days per month below 0ºC, and days per month above 38ºC were not significant. Attempts to
account for possible lower reproductive capability of first-year breeders did not improve statistical relationships.
The number of adults each year was positively correlated with the number of juveniles in the previous year. The
number of juveniles produced each year was correlated with the number of adults in that year only when the
effect of precipitation was removed; then, the relationship was linear. The interannual fluctuations in population
numbers resulted from low adult survival and the influence of precipitation on recruitment through unknown
mechanisms.
Botsford and colleagues (1988) recommended that a juvenile census could be valuable for setting allowable levels
of hunting on an annual basis. If that were not possible or if it were too expensive, prediction on the basis of
precipitation data is also a possibility. Setting allowable hunting levels, once the reproduction rate is known,
depends on better knowledge of population dynamics, specifically the degree of density dependence.
Determining the allowable harvest depends on knowing the effect of the remaining density of birds on future
reproduction. Results obtained for the population studied by Botsford and colleagues (1988) (i.e., the linear
relationship between recruitment and adult density) indicate that leaving higher densities following harvest
would lead to higher recruitment and higher levels of huntable birds in the future. They also found that the
presence of off-road vehicles may adversely affect quail habitat. The results obtained are not conclusive in that
regard, but indicate that further, direct investigation is warranted.
In California, Oregon, Nevada, and Baja California, California quail is found primarily in chaparral, sagebrush
scrub, grassland, and oak, although may inhabit riparian and foothill woodland and disturbed humid forestlands
(Leopold 1977, Calkins et al. 1999). Kilbride et al. (1992), working in mesic habitats of western Oregon, found
that quail numbers and productivity also were related primarily to the abundance of annual forbs (Oates and
Crawford 1983, Blakely 1990). Consequently, management for California quail has focused on habitat
manipulations that increase or maintain these key foods, rather than management of nesting habitat. Breeding
January 2013
densities of one quail per 6 ha for central California (Glading 1938, Emlen 1939) were similar to those for western
Oregon (one quail per 5 ha).
Removal of brush and trees to improve forage production or for firewood can reduce California quail habitat.
Because adult California quail prefer to forage no farther than 15 m into open areas (Sumner 1935), a clearing as
small as 1 ha will remain mostly unused if no brush cover is present. Leaving brush piles in place benefits quail by
replacing some of the natural cover that was removed or by creating cover where none previously existed
(Leopold 1977).
Disking, compared with burning, promoted greater production of key foods for California quail in western
Oregon. Key food production should be targeted for habitats that will be readily used by foraging quail. The
importance of roadsides and areas adjacent to adequate cover (for roosting and escape) was reported in several
studies (Sumner 1935, Emlen and Glading 1945, Klebenow and Stinnett 1986), and these areas often produce the
best variety of key quail foods. Management for increased production of key quail foods should be conducted by
disking strips or meandering paths adjacent to patches of cover. Disking large, contiguous areas should be
avoided because, as stated above, quail typically forage only in areas adjacent to cover (Sumner 1935, Emlen and
Glading 1945). Disking in combination with compaction may be a viable management method. Burning is
recommended when disking is not feasible. In mesic zones, habitat manipulations should be conducted
approximately every 2–3 years to maintain increased production of key foods.
Recommendations for California quail harvest and monitoring are similar to those described above for mountain
quail.
In areas of heavy grazing and agriculture, brome grasses can invade and out-compete preferred forbs.
Furthermore, these grasses are highly flammable and increase both the likelihood and intensity of fires (Leopold
1977). Regular, small fires in chaparral may lead to increases in populations by promoting the growth of annuals
in burned-out spaces. A study by Gorenzel and colleagues (1995) found that California quail preferred larger,
higher brush piles over smaller and lower ones.
In addition, the impacts of feral pigs on quail nesting success could be significant and should be examined (as
described in Section 8, “Feral Pig,” of this wildlife assessment).
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