Fire Ecology 11(3) - Fire Ecology Journal

Transcription

About the cover:
Surface fire in a Pinus douglasiana forest in Sierra de Manantlán, Mexico.
Photo credit: Salvador García.
Fire Ecology is an online publication of the Association for Fire Ecology. The journal
publishes high quality, peer reviewed articles on topics primarily focusing on fire
ecology, as well as letters and responses to each article. Articles that deal with other
fire science or fire management topics must establish a relationship with fire ecology.
New issues of Fire Ecology come out in April, August, and December.
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TABLE OF CONTENTS
Classic Article
Present Studies and History of Burning in Greece,
with an Introduction by Vasilios P. Papanastasis
Author: Leonidas G. Liacos
Pages: 1–13
Research Articles
Lichen Community Response to Prescribed Burning and Thinning in Southern Pine
Forests of the Mid-Atlantic Coastal Plain, USA
Authors: David G. Ray, Jason W. Barton, and James C. Lendemer
Pages: 14–33
Simulating Grassland Prescribed Fires Using Experimental Approaches
Authors: Katherine C. Kral, Ryan F. Limb, Torre J. Hovick, Devan A. McGranahan,
Aaron L. Field, and Peter L. O’Brien
Pages: 34–44
Soil Carbon and Nutrient Recovery after High-Severity Wildfire in Mexico
Authors: Shatya D. Quintero-Gradilla, Felipe García-Oliva, Ramón Cuevas-Guzmán,
Enrique J. Jardel-Peláez, and Angelina Martínez-Yrizar
Pages: 45–61
Variability in Fire Prescriptions to Promote Wildlife Foods in the Longleaf Pine Ecosystem
Authors: Marcus A. Lashley, M. Colter Chitwood, Craig A. Harper, Christopher S. DePerno, and
Christopher E. Moorman
Pages: 62–79
Approximation of Fire-Return Intervals with Point Samples in the Southern Range of the
Coast Redwood Forest, California, USA
Authors: Gregory A. Jones and Will Russell
Pages: 80–94
Recovery of Tall Open Eucalypt Forest in South-Western Australia following Complete
Crown Scorch
Authors: Lachlan McCaw and Ted Middleton
Pages: 95–107
A Case Study Comparison of LANDFIRE Fuel Loading and Emissions Generation on a
Mixed Conifer Forest in Northern Idaho, USA
Authors: Josh Hyde, Eva K. Strand, Andrew T. Hudak, and Dale Hamilton
Pages: 108–127
Review Article
Faunal Responses to Fire in Chaparral and Sage Scrub in California, USA
Authors: Elizabeth F. van Mantgem, Jon E. Keeley, and Marti Witter
Pages: 128–148
Book Review
Current International Perspectives on Wildland Fires, Mankind and the Environment
Author: Ernesto Alvarado
Pages: 149–152
Liacos: Burning in Greece
Page 1
Fire Ecology Volume 11, Issue 3, 2015
doi: 10.4996/fireecology.1103001
Classic Article
INTRODUCTION TO LEONIDAS G. LIACOS’ ARTICLE
Vasilios P. Papanastasis
Faculty of Forestry and Natural Environment, Aristotle University of Thessaloniki,
54 124 Thessaloniki, Greece
Tel.: +30-231-099-6000; e-mail: [email protected]
Leonidas Liacos is a pioneer of fire ecology and management for Greece. He studied forestry in
Greece and in France where he did his Ph.D. on alpine grassland hydrology in the early 1950s. In
1958, he went to Berkeley, California, USA, for post-doctoral studies in range management under
Professor Harold Biswell, who was promoting the use of fire and prescribed burning in forest
management at that time. Liacos was inspired and fully accepted Dr. Biswell’s ideas. When he
returned to Greece in the early 1960s, he started advocating the use of fire in forest management
in Greece, as well as established his first prescribed burning experiments. His article published
here, which was originally presented in the 1974 fire ecology conference of the Tall Timbers Research Station in Tallahassee, Florida, USA, describes most of these experiments, the ideas behind them, and the first results produced.
Liacos’ article is a classic for Greece because it provides the first historical evidence that fire was
part of the natural environment since prehistoric times by citing Homer and other classic writers.
This information had not been recognized in the early 1970s. The information that prescribed fire
can reduce fire risk in forests and rangelands that had started to get devastated by wildfires during
that decade was also new. Indeed, although wildfires in the previous decades were few and small
in size, they started to increase both in numbers and especially in size in the 1970s due to socioeconomic changes that favored increased human activity in the urban-wildland interface (Xanthopoulos 2000).
In the late 1960s, I was appointed as a forester in the North Greece Forest Research Centre, where
Liacos was doing his experiments. As his research assistant, I vividly remember him, standing in
front of his experimental plots, preaching the ecological role of fire to extension foresters and
suggesting prescribed burning as a tool to properly manage the fire-prone coniferous forests consisting of warm-Mediterranean pines such as aleppo (Pinus halepensis Mill.) and brutia (P. brutia
Ten.). He also preached to forestry authorities and university professors, who were preoccupied
by the traditional fire suppression policies.
His experiments were also the first to get established not only in Greece but in the whole Mediterranean region. He was frequently receiving visitors from other Mediterranean countries, to whom
he was presenting his ideas and showing his experiments. Fire suppression policy was the dominant philosophy in these countries, too. As a result, he met a lot of opposition. Having studied in
France, he wrote a relevant article (Liacos 1986) and had several contacts with French foresters,
with whom he carried out very long and hot discussions.
Liacos stresses in his paper the role of fire in decomposing organic matter, a function that is hampered under the Mediterranean climate due to the warm and dry conditions. His innovative idea
Page 2
was that grazing has a similar function. For this reason, he tried to combine prescribed burning
and livestock grazing in his experiments. The methodology he proposed was to apply prescribed
burning to reduce the woody understory in the pine forests, then seed palatable forage species
and, finally, introduce livestock, mainly goats, in order to control the shrub regrowth. This was a
clever idea for Greece and other Mediterranean countries having conflicts between domestic animals and forests because he suggested that livestock be considered as a forest management tool
(Liacos 1980). Given the prevailing conviction at that time that goats were the main factor for
the destruction of the Mediterranean forests (e.g., Thirwood 1981), his ideas were revolutionary
and helped in the reconsideration of the role of goats in these forests (Papanastasis 1986).
Liacos’ paper stirred the stagnant waters of classical forestry inspired by the nineteenth century
Central European ideas of no interference in the forests (no fire, no grazing) and contributed to
the education of a new generation of foresters on the ecological role of fire and grazing in Mediterranean forest management. Unfortunately, however, it did not help institutionalize the use of
prescribed fire by the Greek Forest Service, mainly for two reasons. One was his experimental
results showed that the time period with ideal temperature and moisture conditions to apply prescribed fire in the winter period was relatively limited. The other, more important reason was the
prohibition of using prescribed fire in forest management that required a change in the law on
forest fires in the Greek parliament. That change was not possible given not only the opposition
of the officials in the Forest Service but also of the general public who were already overwhelmed
by the frequent summer wildfires and were not prepared to see smoke coming out from prescribed
fires in the winter period, too. Even legalizing the use of prescribed fire in rangelands to mitigate
the big problem of pastoral wildfires was not possible.
Unfortunately, prescribed fire today is still forbidden and is not even mentioned as a management
tool. On the contrary, livestock grazing is widely perceived as a tool for reducing fire risk and
enhancing tree growth in forest lands (e.g., Papanastasis 2009). I can only hope that the ecological wisdom expressed by Liacos will prevail in the future.
LITERATURE CITED
Liacos, L. 1980. Livestock grazing in Mediterranean forests. Pages 1-20 in: Incontri Internazionali: problemi della Conservazione e Reconstituzione della Copertura Forestali. Colloquio
II, 6-11 Ottobre 1980. Ministerio dell’Agricoltura e delle Foreste, Palermo, Italy.
Liacos, L. 1986. Le pâturage et le feu prescrit, des outils efficaces dans l’ aménagement des
forêts méditerranéennes du groupe Pin d’Alep. Options Mediterraneennes 86: 179-199.
Papanastasis, V.P. 1986. Integrating goats into Mediterranean forests. Unasylva 38: 44-52.
Papanastasis, V.P. 2009. Grazing value of Mediterranean forests. Pages 7-15 in: M. Palahi, Y.
Birot, F. Bravo, and E. Gorriz, editors. Modelling, valuing and managing Mediterranean forest ecosystems for non-timber goods and services. European Forest Institute Proceedings 57,
European Forest Institute, Joensuu, Finland.
Thirgood, J.V. 1981. Man and the Mediterranean forest. A history of resource depletion. Academic Press, New York, New York, USA.
Xanthopoulos, G. 2000. Fire situation in Greece. International Forest Fire News 23:76-84.
Page 3
Classic Article
PRESENT STUDIES AND HISTORY OF BURNING IN GREECE
L.G. Liacos
School of Agriculture and Forestry,
Aristotelion University of Thessaloniki,
Greece
INTRODUCTION
Greece, to those who know it only from archeological books and its ancient architecture,
is associated with rocks, and bare mountains
of white fine-granular marble, decorated by
fine-sculptured temples, all built of white marble. Probably, the small size pine-tree grove,
ideally matched with scattered columnar cypress and olive trees, which commonly constitute the frame that beautifies the ancient Greek
landscape, do not prevent [readers] from wondering whether Greeks, being in an arid country, had no choice in selecting their building
material.
However, all over the Greek territory, the
climate, characterized by more or less long dry
and hot summers (typical Mediterranean climate), is, in general, very favorable for the development of even dense forests.
No doubt, in prehistoric times Greece was
totally covered with thick forests, with the
only exception of the summits of high mountains, rising above the timber line.
The recently discovered bones, found in
excavations near Pikermi a few kilometers east
of Athens, belong to a prehistoric large and
very robust animal, the habitat of which is
confined to extent forest environment. That
gives a very strong evidence that Attica was
covered in unbroken forests.
Greek Mythology, on the other hand, says
that Hercules killed the Kithaeronian Lion and
the Elk of Artemis (Diana) in Peloponessos.
This allows [one] to conclude that Peloponessos was covered with large forests, since lions
and elk require a forest environment over large
areas.
Moreover, Homer in his Odyssey calls the
now bare Mount Noriton in the island of Ithaca “dense leaved” and the island Zakynthos
“forest covered”.
HISTORY OF BURNING
The destruction of the Greek forest largely
began with the invasion of the country by various indo-German races. They started from the
country around the Danube River, at the beginning of the 20th century B.C.
First, the Achains, a race purely nomadic,
following the valley of the Axios River entered
Greece, and arrived in Peloponessos through
central Macedonia, Thessaly, Biotia, and Attica. Using fire mainly, they converted large
forested surfaces to grasslands, in order to secure better feeding for their numerous livestock animals, or to open passages to
grass-covered lands (alpine rangelands).
Second, the Doreans, a mountainous race
entered from western Macedonia, and following the main mountain range went down as far
as Peloponessos. They also converted large
areas of forests to grasslands for the same reason, using the most effective tool, burning.
Naturally started wildfires, also, were a
very common phenomenon all over Greece.
Homer in Iliad (Λ. 155) sings:
And as when consuming fire falls
upon thick woodlands and the whiching wind beareth it everywhither and
the thickets fall utterly as they are assailed by the onrush at the fire.
Thoukidides, also, talking about the unexpected escape of Plataeans, while they were
besieged by Spartans the summer of the third
year of Peloponnisian war (429 B.C.), thanks
to an unusual storm that followed a big fire the
Spartans put all around the city, says:
And a conflagration arose greater
than any one had ever seen up to that
time, kindled, I mean, by the hand of
man; for in times past in the mountains
when dry branches have been rubbed
against each other a forest has caught
fire spontaneously therefrom and produced a conflagration.
Forbes, also, talking about the importance
of fire in ancient technology, says that ancient
man applied burning “to extend the forest fires
to manure the cleared spaces.”
Therefore, burning has greatly contributed
to the present physiognomy of the vegetation
cover and the whole ecosystem of Greece, not
only as a tool in hands of economy making
man, but as an important factor of the natural
environment too.
It is rather certain that maquis and garrigues formations (see Figure 1), occupying at
present about 15 percent of the total land area
of Greece, are mainly a result of wildfires.
Moulopoulos (1935) says that the coastal zone
of the Greek peninsula from Albania to Pelopo-
Page 4
nessos and from Peloponessos to Chalkidiki
was in previous times covered with productive
forests of Pinus halepensis Mill., P. brutia Ten.,
P. pinea L., and Quercus ilex L., interrupted
only by very dense Fluviisilvae and Paludisilvae around the mouth of big riverslike the
Axios River in Macedoniaor by deciduous
oak forests growing in isolated stands. And, he
states, that the main reason of their substitution
by maquis formation was the wildfire, caused,
mainly, by man to improve, primarily, grass and
browse production, and secondarily to expand
his cultivated land (Figure 2).
Figure 2. Gradual substitution of Pinus halepensis
by maquis in Chalkidiki peninsula.
But ancient Greeks very early had seen
that burning had also some beneficial effects.
Homer in Iliad (ø 12), talking about the retreat of Argites after they lost the battle, and
trying to escape, says:
And as when beneath the onrush of
fire locusts take wing to flee on to a river and the unwearied fire burneth them
with its sudden oncoming and they
shrink down into the water.
Virgil, also, in his Georgics (book I,
84−93) says:
Figure 1.
peninsula.
Maquis formation in Chalkidiki
Often, too, it has been useful to fire
barren fields, and burn the light stubble in crac[k]ling flames; whether it be
that the earth derives thence hidden
strength and rich nutriment, or that in
the flame every taint is baked out and
the useless moisture sweats from it, or
that heat opens fresh paths and loosens
hidden pores, by which the sap may
reach the tender blades, or that it rather hardens the soil and narrows the
gaping veins, that so the searching
showers may not harm, or the blazing
sun’s fierce tyranny wither it, or North
wind’s piercing cold.
Vassus Kassianos, too, refers to burning
and its beneficial effects upon the crops and
says in his Geoponica [Beckh 1895]:
The best manure of all for vegetables is ash, and being most fine and
naturally warm, it will kill the fleas and
worms and other small beasts
and also:
some people use instead of nitre
ash to also kill caterpillars.
and further (book I Γ, 10−1):
If you hunt ants and burn them, you
will expel all ants that are left, as experience has taught us.
Letsas (1957) in his three volume Mythology of Agriculture reports that the ancients
used to burn the stubble or the herbage and dry
leaves to manure the fields. In Xenophon’s
Economics (XV III, 2) the famous Greek historian reports:
I imagine that the stubble may be
burnt with advantage to the land, or
thrown on the nature heap to increase
its bulk.
Page 5
PRESENT STATUS OF BURNING
At present, fire still constitutes a very important factor of the Greek wildland ecosystems. Wildfires in forests and rangelands are
very common.
D. Kailidis (1972) reports that from 1956
to 1971 the average number of wildfires registered all over Greece per year amounted to
612, and had destroyed, on average, 10 150 ha
of forest and brushlands, with an estimated
damage of about $7 336 000. This represents
0.14 percent of the total forests and brushlands
of Greece. More than 60 percent of the total
burnt area is coniferous forest of Pinus halepensis and P. brutia of the lower Mediterranean
zone, and maquis and garrigues formations.
The surface burnt and losses from wildfires
would be much greater, if forests in this zone
were not broken in relatively small size stands
by the interval of non-forested land. The author also reports that in more than 60 percent
of the fires the cause was carelessness (cigarettes), or inadequate control of stubble burning in neighboring wheat fields, that spread the
fire over to forest ground fuel (ground fuel in
P. halepensis and P. brutia forests is very flammable) or brushlands.
D. Kailidis and A. Papagiannopoulos
(1972) studying the litter moisture trend under
Pinus brutia stands and in openings in the Forest Park of Thessaloniki-city, found that from
June to October in 1968, and from May to November in 1969, litter moisture content was
less than 25 percent; this marks the critical
point under which fuel burns very easily. In
openings the accumulated grass litter had a
moisture content even lower than that of
pine-needle litter under the stands.
Generally, Pinus halepensis and P. brutia
forests in Greece form relatively open stands,
under the canopy of which grows a luxurious
understory vegetation of evergreen, mainly,
brush species and associated herbaceous
plants, which dry-out during the summer
months.
This understory vegetation, intercepting in
addition through all its depth the falling dead
pine-needles, is very flammable. This creates
a big fire hazard. The fire hazard is particularly high in Pinus halepensis forests, managed
primarily for gum production. Gummed pinetree trunks with their wounds all around and
gum droppings are very easy to burn, for they
rapidly conduct the fire to the tree crown and
to the forest canopy, in general, once started
on the ground (Figure 3).
Figure 3. Pinus halepensis stand used for gum
production in the peninsula of Chalkidiki.
Needless to say that with increasing tourist
traffic and the mass outings of urban people
from the noisy, air-polluted cities for outdoor
recreation, fire danger is going to become
great.
Brushlands, also, suffer big losses from
wildfires every year. During the long rainless
and hot summers the moisture content of their
aerial part drops considerably, and it takes just
a spark to start burning. Liacos and Moulopoulos (1967) report that moisture content of
the browsethe most tender succulent tissues
of the aerial partproduced by one of the
main species of maquis formation, the Kermes
oak (Quercus coccifera L.), drops down to
about 40 percent in late summer. Certainly,
the moisture content of the woody parts of the
species, which constitute the bulk of fuel matter, is at that time much lower.
Page 6
Burning is also used at present as a management tool. Wheat farmers almost all over
Greece consider stubble burning a good technique for increasing wheat production. Livestock operators also in many districts use burning for range improvement. They practice it
because they strongly believe in its beneficial
effects, in spite of the general belief that burning is harmful, especially to the soil.
Farmers have seen that when stubble burning is practiced in autumn or in winter time,
crops are better the following season than
when no burning is applied. They specifically
observed the following after burning:
1. Plowing of the field and soil preparation for reseeding is much easier
and perfect, that secures better germination of seeds and better development of the seedlings.
2. Wheat seedlings show no chlorotic
phenomena in spring, as is the case
when stubble burning is not applied.
3. The season following stubble burning insect and disease attacks are
less, and consequently crop damage reduced to a minimum.
4. Weeds are less abundant the season
after stubble burning.
Agronomists are not in a position yet to
give a definite and dependable answer to the
problem. They experiment now on the various
aspects of the problem. Livestock operators,
on the other hand, of Thesprotia County
(northwestern corner of Greece) use burning
in low elevation rangelands every 4 or 5 years
to control undesirable invaders and weeds.
Weeds dominate in plant cover by the end of
the fourth or fifth years after burning. It must
be noted, here, that grazing in the area is practiced by sheep herders without any range management principle, and without any control as
to the number of animals, the grazing period
etc.
Page 7
Livestock operators have seen that burning
of dry range vegetation late in summer:
1. Secures a satisfactory control of
weeds and other undesirable plants.
2. Stimulates a growth of dormant
plants and provides green forage
although in small quantities, when
vegetation is completely dry.
3. Secures a relatively higher quantity
of forage (grazable) for at least the
next 2 years.
This technique of burning has been authorized even by the responsible state agency, the
Greek Forest Service, under the pressure of the
livestock operators, who live at present in this
area as semi-nomads. However, the plant cover and especially the soil have been deteriorated to a high degree. A backward trend of the
range condition is evident. The very valuable
grass species Andropogon distachyos L. is
greatly decreasing in vigor and density, and
the invasion of the range by a phrygana plant
community (Cystus spp., etc.) is obvious.
Certainly, livestock people do not realize
that burning alone, without the application of a
rational and proper plan for the specific area
management-use and improvement, not only
fails to have the expected results, but besides it
becomes the main cause of heavy degradation
of the main resources of the range ecosystem,
namely the vegetation and the soil (Figure 4).
Livestock operators also use burning, although without permission, for improving
browse production in brushlands. Here again
burning is practiced not properly and not prescribed by a management working plan, with
the result, finally, of a more or less severe degradation of the vegetation cover and the soil
(Figure 5).
PRESENT STUDIES OF BURNING
Fire, as it is easily concluded from the preceding analysis, continues to be an important
Figure 4. Degradation of burnt rangelands in
Thesprotia County is evident.
Figure 5. Progressive degradation of brush vegetation (maquis) and soil because of unwise burning
and uncontrolled grazing.
factor even in the modified now wildland ecosystem that dominates, particularly, in the lower Mediterranean zone of Greece.
Moreover, all activities developed today
for restoration of the wildland vegetation and
the reestablishment of the forest primarily for
protection and recreation purposes (environmental forests), magnify the importance of the
fire factor and render it, I might say, dominant
in the environmental forest ecosystem, under,
especially, the rapidly increasing tourist traffic
and the demand for outdoor recreation.
Upon the basis of these facts and considerations lie our studies on prescribed burning,
inspired and guided by the relative research
and application work done in the USA.
Page 8
We thought that burning might be a very
valuable tool, and an unsubstituted servant in
the management of Greece’s wildlands, if
properly used and manipulated with understanding. After a thorough analysis of the
problem, it was concluded that prescribed
burning might be indicated and valuable in
management of the following three distinctive
ecosystems:
A. In the coniferous forests of Pinus
halepensis and Pinus brutia.
B. In the maquis formation.
C. In the high mountain grasslands,
dominated by hard bunchgrasses.
The specific problems in each of these
three ecosystems, and the experimental work
planned and undertaken arc presented in the
following discussion.
Coniferous Forests
In the coniferous forests of aleppo or brutia pine, naturally existing or artificially created in their natural area by reforestation, two
main categories of stands can be distinguished.
Forests on good site. Growth conditions
allow here the development or the creation and
maintenance of thick stands during at least the
first half of their rotation time.
With the progress in age of the stand one
can see:
1. A number of trees dying-off under
the effect of the severe competition
developed among trees (natural
thinning) having no commercial
value, and thus representing an actual loss for the forest business.
For the same reason all understory
vegetation is gradually dying-out
too (Figure 6).
2. A continuous increase of dead
branches of living trees remaining
Figure 6. Pinus halepensis stand about 30 years
old. Dominated trees and understory brush dying-off under the effect of competition.
in place, decreasing thus the quality, and consequently the value of
the timber produced, even if after
several years that they may be broken, but always in a considerable
distance from the tree-trunks (Figures 7 and 8). Under Mediterranean climate, and particularly in its
lower part, natural pruning, that
constitutes in classical silviculture
one of the reasons justifying thick
stands, seems to be an empty word.
Decomposers, the main agent in
natural pruning, can not be very active, because moisture is insuffi-
Figure 7. Dead branches remaining in place in an
artificially established 30 year old stand of Pinus
brutia.
Figure 7. Artificial stand of Pinus brutia about 35
years old immediately after the first thinning. Notice the broken dead branches in the distance from
trunks.
cient when temperatures are sufficiently high in summer time.
3. An accumulation on the ground of
pine needles in thick undecomposed layers, and a storage of dead
pine needles upon the dead branches of trees or upon understory
woody vegetation (Figure 9). The
decomposition of the litter is very,
very slow for the same reason
mentioned above.
Figure 9. Artificial stand of Pinus brutia 30 years
old with thick layers of undecomposed needles on
the ground and upon dead branches.
4. A large volume of slash left upon
the ground after each thinning of
the stands, once the diametre of the
trees reaches commercial value.
Page 9
5. In the older stage during the second
half of the rotation time the stands
are thinned naturally, for they are
constituted by light tolerant (light
demanding we might say better)
species. The density of the stands
is decreasing as they approach the
end of the rotation time. Under
such relatively open stands a dense
understory of woody and herbaceous vegetation grows (Figure 3),
which in summer time is very
flammable; its moisture content is
then very low. This is one of the
reasons for which P. halepensis and
P. brutia stands are not thinned
properly in early age stages with
the result of a lower value of timber produced.
6. After the final cut of the stand at the
end of the rotation time the understory vegetation grows extremely
vigorous and dense in absence of
any competition from pine trees.
Under such conditions natural regeneration becomes uncertain, or it
completely fails. On the other
hand, artificial regeneration can be
warranted only with high cost.
Forests on poor site. Here the stands grow
more or less open from a very young age. Under such stands an understory brush and/or
herbaceous vegetation is developed, and a
heavy flammable fuel is stored on the ground,
much the same way as that under aged stands
growing on good sites, creating similar problems from the very beginning in each stand.
It is certainly clear after this brief analysis
that the fire hazard in such coniferous forests
of the lower Mediterranean climate is very big.
Obviously, the elimination of the accumulated on the ground highly flammable fuel, and
furthermore the prevention of accumulation of
new fuel on the forest floor is of paramount
importance.
One way to do this is to take away from
the forest any flammable matter every time its
quantity exceeds the security limits. However,
this creates heavy expenses, increasing, finally, very much the cost of the timber and/or
gum produced, and the offered services of protection, recreation and landscape improvement
as well.
Certainly, prescribed burning might be a
suitable and extremely valuable tool, and a
very good solution of the problem, under conditions we knew whether, how, when and
where this technique could be applied in
Greece. And furthermore, if following prescribed burning the establishment and maintenance of an understory vegetation of forage
plants could be easy, then the practice of a
proper grazing by livestock and/or wildlife animals could not only prevent the accumulation
of fuel under the forest canopy, but it would, in
addition, produce a considerable income instead of expenses. Besides, this would minimize the competition of the understory vegetation with trees, as far as soil moisture is concerned that constitutes the main limiting factor
of plant growth in the Mediterranean zone, and
thus greatly benefit the forest and consequently timber production. This would, perhaps,
also encourage silviculturists to thin properly
the stands for maximizing the value of the timber that can be produced in proportion to site
potential, since they would not be annoyed by
an undesirable understory vegetation. In addition, once the understory vegetation could be
easily controlled even with benefit (grazing),
the application of fertilizers for further increase of timber and forage production would
be possible and economically justified.
With this in mind as the basic hypothesis,
and in view of the facts and experience gained
in the USA, a number of experiments were
planned and have been put under way since
1968 in Pinus brutia stands. With this net of
experiments it is hoped and expected to have
valuable results, that properly analysed and interpreted, would answer the general problems
created by the use of prescribed burning in for-
Page 10
ests of Pinus halepensis and Pinus brutia.
More specifically it is expected to answer the
questions which came out of the analysis of
the problem made above, that constitute the
general hypothesis of the study.
Up to date results. Although it is very early to have valuable conclusions, a number of
data and observations could be of interest.
The results of the compiled up-to-date data are
as follows:
1. It is rather certain that Pinus halepensis and Pinus brutia endure quite
well, prescribed burning of brush
understory vegetation at an age of
30 years and thereafter. Their rhydidome is at that age thick enough
to protect the cambium from the
released heat (Figure 10).
Figure 10. Rhytidome of Pinus brutia 30 years
old. One can see the decrease in growth after the
15th year because of the high density of the stand.
Thinnings should begin 10 years earlier at least.
2. The temperature of mineral soil under burnt brush and slash is hardly
affected, when burning is applied in
winter 2 or 3 days after a rain good
enough to soak well under the litter
humus. Measurements made
showed 15 °C after fire ran over it,
while air temperature was 16 °C.
Thus soil was not affected at all.
Page 11
3. Soil nitrogen was found to be higher in burnt than in unburnt plot the
first year after burning. It was
0.189 percent and 0.126 percent respectively.
4. The establishment of seeded orchardgrass (Dactylis glomerata
L.)after burning in intensively
thinned plot was satisfactory. Volunteers, among which were many
legumes, colonised the soil after
burning in satisfactory degree.
Main volunteers: Festuca ovina L.,
Aristella bromides (L.) Bertol., Andropogon ischaemum L., Koeleria
cristata Pers., Phleum spp., Trifolium purpurem Loisel., Trifolium angustifolium L., Trifolium arvense
L., Vicea spp., and Poterium sanguisorba L.
5. In burnt plot, after three consecutive thinnings of the 30 year old
stand, that lowered the tree number
per hectare from 1100 to 450, total
volume (standing and taken by
thinnings) was equal to that of the
plot treated according to conservative silvicultural rules (see Table 1
and Figure 11). Also the increment
of standing trees after thinning was
much higher in the intensively
thinned and burnt plot (Figure 12).
6. Pine regeneration 2 years after last
burning was very good. In the unburnt plots many seedlings were
found from germinated seed during
past fall, but almost none from ger-
Volume (m3)
30
A
B
C
20
10
0
1968 1972
1968 1972
Years
1968 1972
Annual increment of diameter (mm)
Figure 11. Volume of standing (open column) and
thinned-out (cross hatched) trees in Pinus brutia
plots: A. Intensively thinned and burnt, B. Lightly
thinned, C. Control.
16
14
12
A
10
B
C
8
6
4
2
0
1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972
Years
Figure 12. Increase in diameter of Pinus brutia
trees in plots: A. Intensively thinned and burnt, B.
Lightly thinned, C. Control.
minated seeds in previous years.
Table 2 shows the pine seedlings
found in February 1973 in burnt
and unburnt plots.
Table 1.
Volume in
1968
Volume of
thinnings
Volume in
1972
Total
volume
Increments
(%)
Intensive thinningprescribed burning
20.53
12.99
12.36
25.35
23.47
Conservative thinning
19.34
1.52
21.56
23.08
19.33
Control
17.93
18.76
18.76
4.64
Treatments
–
Page 12
Table 2.
Intensive thinning– Conservative thinning
prescribed burning plot
plot
Treatments
Seedlings less than 1 year old
Seedlings older than 1 year
Control
plot
2
17
29
15
–
–
Evergreen Brushlands
Maquis brushlands are now used by browsing animals such as goats and deer mainly.
Their value as browse-land is not very high.
Liacos and Moulopoulos (1967) found that
browse production of this land in good condition does not exceed for the area studied, 750
kg ha-1 air dry. Liacos (unpublished data, University of Thessaloniki, Greece) in a conversion study from brushland to grass by seeding
Dactylis glomerata, Phalaris tuberosa L., and
Trifolium hirtum All. after mechanical clearing
of brush, found that grass forage production
was about 500 kg ha-1 air dry.
With this in mind and the fact that wildfire
hazard is very high in this vegetation type a
comparative research study was started last
year. Prescribed burning is used as the main
tool of conversion, followed by planting of a
mixture of seeds of Lolium multiflorum Lam.
(used as the main competitor against brush
sprouts), Dactylis glomerata, Phalaris tuberosa and Trifolium hirtum. On the other hand,
brush vegetation in the remaining underbrush
covered plots is improved by proper manipulation of brush individuals and the whole community as well, for reaching maximum browse
production (Figure 13).
The purpose of this experiment is to find
out:
(a) Whether brush conversion by prescribed burning constitutes an efficient technique.
(b) How to control brush sprouts after
burning.
(c) What is the production of forage as
compared to browse produced.
Figure 13. Brush vegetation treated for high
browse production.
(d) Which is the technique to follow in
order to insure a good establishment and maintenance of forage
cover.
High Mountain Grasslands
Prescribed burning has been also used in a
research study to improve forage production
of high mountain rangelands, dominated by
hard bunch-grasses, grazed for centuries only
by sheep and goats.
Large quantities of undecomposed litter on
the ground surface prevent the seedlings from
rooting into the mineral soil, and are easily and
regularly uprooted by grazing sheep.
The experiment has been established at an
elevation of 100 m the fall of 1971 in Mount
Phalacron in northern Greece, representing an
area of more than 10 000 ha in this mountain
and manyfold larger area all over upland
Greece.
Burning was applied in fall and in spring
immediately after snow melt in combination
Page 13
with and without chemical fertilization (Figure
14).
The first year results show that burning improved the quality of the forage; it was more
tender and palatable. Its crude protein content
was higher than in unburnt forage, while quantitatively no difference was found thus far.
Reprinted and condensed with permission
from Liacos, L.G., 1974. Present studies and
history of burning in Greece. Tall Timbers
Fire Ecology Conference Proceedings 13: 6595, by Tall Timbers Research Station, Tallahassee, Florida, USA.
Figure 14. Experimental plot in high mountain
bunch-grasslands. Fall and spring burning is
checked in combination with and without mineral
fertilization for forage improvement.
LITERATURE CITED
Beckh, H., editor. 1895. Geoponica sive Cassiani Bassi scholastici de re rustica eclogae. Teubner, Leipzig, Germany. [In Greek.]
Kailidis, D., and A. Papagiannopoulos. 1972. Litter and soil moisture under Pinus brutia stand
and in an opening. Pages 256-287 in: The Year Book of Agriculture and Forestry Department. University of Thessaloniki, Greece. [In Greek.]
Kailidis, D. 1972. Forest and grazing land fires in Greece during 1971. University of Thessaloniki, Greece. [In Greek.]
Letsas, A. 1957. Mythology of agriculture. Volume III. Triantaphylou Sons, Thessaloniki,
Greece. [In Greek.]
Liacos, L.G., and C. Moulopoulos. 1967. Contribution to the identification of some range types
of Quercus coccifera L. Forest Research Center of Northern Greece, Thessaloniki, Greece.
[In Greek.]
Moulopoulos, C. 1935. Observations and research on the regeneration of burnt forests of Pinus
halepensis. Pages 1-24 in: The Year Book of Mathematics and Physics Department. University of Thessaloniki, Greece. [In Greek.]
Ray et al.: Lichen Response to Burning in the Mid-Atlantic Coastal Plain
Page 14
Research Article
LICHEN COMMUNITY RESPONSE TO PRESCRIBED BURNING AND THINNING IN
SOUTHERN PINE FORESTS OF THE MID-ATLANTIC COASTAL PLAIN, USA
David G. Ray1*, Jason W. Barton2, and James C. Lendemer2
1
The Nature Conservancy, Maryland-District of Columbia Chapter
116 South Saratoga Street, Salisbury, Maryland 21804, USA
2
Institute of Systematic Botany, New York Botanical Garden,
2900 Southern Boulevard, Bronx, New York 10458, USA
Corresponding author: Tel.: 1+850-241-6837; e-mail: [email protected]
*
ABSTRACT
RESUMEN
The effects of prescribed burning and
thinning on lichen communities is a
poorly understood aspect of biodiversity conservation, despite the widespread
use of these practices to achieve conservation-oriented land management
goals. To address this knowledge gap
we documented apparent changes in the
diversity and abundance of lichens following 0 to 2 growing-season burns
preceded by 0 to 1 commercial thinnings within nine southern pine dominated stands on the Delmarva Peninsula
of Maryland, USA. Corticolous lichens
growing on the stems and within the
canopies of pines and co-occurring
hardwoods were identified to species
and fractional coverage was estimated;
growth forms and reproductive modes
were also determined. A total of 93 lichen taxa were recorded on the 19 tree
species (4 pines, 15 hardwoods) represented in this study. Burning emerged
as a strong driver of reductions in lichen diversity (P = 0.002), whereas
thinning in the absence of burning did
not (P = 0.279). In general, we found
that lichens growing on tree bases and
lower bole sections were more strongly
impacted by burning, both in terms of
Los efectos de quemas prescriptas y raleos sobre comunidades de líquenes es un aspecto
poco comprendido de la conservación de la
biodiversidad, a pesar del extenso uso de esas
prácticas para lograr metas de manejo orientadas a la conservación. Para llenar este vacío
en el conocimiento, documentamos los cambios aparentes en la diversidad y abundancia
de líquenes de 0 a 2 temporadas de crecimiento después de las quemas y precedidas de 0 a 1
raleo comercial, dentro de nueve rodales dominados por pinos del sur en la península de
Delmarva en Maryland, EEUU. Los líquenes
cortícolas creciendo en tallos y dentro del dosel arbóreo de pinos y latifoliadas circundantes, fueron identificados a nivel de especie y
se estimó la fracción de su cobertura; las formas de crecimiento y modos reproductivos
fueron también determinados. Un total de 93
taxones de líquenes sobre 19 especies de árboles (4 pinos y 15 latifoliadas) fueron registrados en este estudio. Las quemas emergieron
como fuertes conductoras en la reducción de
la diversidad de líquenes (P = 0.002), mientras que los raleos en ausencia de quemas no
tuvieron ningún efecto (P = 0.279). En general, encontramos que los líquenes que crecen
en la base de los árboles y en las porciones bajas del tronco fueron más impactados por las
quemas, tanto en diversidad como en cobertu-
Page 15
diversity and cover, than those residing
in the canopy. The apparent refugia
represented by the canopy was qualified
by the limited overlap in lichen species
composition observed among the various sampling heights. This work calls
attention to an understudied component
of biodiversity that appears to be sensitive to fire management; however, we
suggest that these results need to be interpreted in the context of altered disturbance regimes and the trajectory of
community assembly resulting from
long-term fire exclusion.
ra, que aquellos ubicados en el dosel. El aparente refugio representado por el dosel fue estimado por la limitada superposición en la
composición de especies de líquenes observados entre las distintas alturas de muestreo.
Este estudio llama la atención sobre un aspecto poco estudiado de la biodiversidad que
aparenta ser sensible al manejo del fuego;
desde luego, sugerimos que estos resultados
deben interpretarse en el contexto de regímenes de disturbios alterados y la trayectoria del
ensamble de la comunidad resultante de la
exclusión del fuego por largos períodos de
tiempo.
Keywords: biodiversity, disturbance regime, lichens, prescribed burning, restoration, southern
pines, thinning, woodlands
Citation: Ray, D.G., J.W. Barton, and J.C. Lendemer. 2015. Lichen community response to prescribed burning and thinning in southern pine dominated woodlands of the Mid-Atlantic Coastal
Plain, USA. Fire Ecology 11(3): 14–33. doi: 10.4996/fireecology.1103014
INTRODUCTION
Terrestrial biodiversity has been substantially diminished by anthropogenic factors including land-use change, altered disturbance
regimes, and, increasingly, as a result of global
climate change (IPCC 2013). Contributing to
these trends, substantial areas of mixed-species upland forest in the Mid-Atlantic Coastal
Plain region of the US have been displaced by
agriculture and development or converted to
intensively managed pine plantations (Auch
2000). Contemporary approaches to land
management that seek to re-establish missing
elements of ecosystem composition, structure,
and function in order to enhance biodiversity
and resilience typically embrace approaches
grounded on historic disturbance regimes
(Kohm and Franklin 1997, Seymour et al.
2002, Egan 2005, Mitchell et al. 2006, Wiens
et al. 2012).
Wildland fires, both natural and human
caused, have shaped forest communities and
influenced plant specialization for millennia in
eastern North America (Whitney 1994, Delcourt and Delcourt 1997, Frost 1998, Platt
1999, Ryan et al. 2013). However, European
settlement altered extant fire regimes, culminating in government agency policies that
greatly reduced the number and area of wildland fires throughout the twentieth century
(Pyne 1982, 2010). As a result, historic woodland and savanna systems in eastern North
America have largely been transformed into
closed-canopy forests through the recruitment
of shade-tolerant, fire-sensitive vegetation
(Anderson 1991, Wolf 2004, Bond et al. 2005,
Nowacki and Abrams 2008). It is now widely
accepted that many ecosystems in eastern
North America depend on periodic burning to
maintain plant communities and associated
habitats for native wildlife. Prescribed burns
are increasingly used in an effort to reverse the
detrimental impacts that fire exclusion has had
on these fire-adapted ecosystems (Platt 1999,
Brooks et al. 2004, Agee and Skinner 2005,
Ryan et al. 2013).
Page 16
Similar to fire exclusion, forest management and, more specifically, practices commonly associated with intensive southern pine
silviculture (e.g., site preparation, herbicide release, fertilization, and maintenance of high
stocking) are also widely considered to have
negative impacts on biodiversity. While not
without merit, this view can be overly simplistic, and approaches have been suggested to
mitigate some of the negative impacts of these
practices (Andreu et al. 2008, Hartmann et al.
2010). Coxson and Stevenson (2005) reported
on the short-term impacts of partial harvesting
practices on canopy lichens in mixed conifer
forests of British Columbia, Canada, concluding that, while species exhibiting pendulous
growth forms were susceptible to wind damage, the other groups that they studied appeared relatively unaltered by the treatments.
In contrast to the extensive body of literature describing the response of vascular plants
to prescribed burning, similar resources are
not currently available for lichens (see FEIS
2015). Lichens are symbiotic organisms comprised primarily of a fungus and an alga that
form a single unit in which the fungus tends to
dominate (Brodo et al. 2001). They are recognized as keystone members of terrestrial ecosystems, performing diverse services contributing to nitrogen fixation, animal forage, soil
stabilization, and moisture retention, and hosting diverse and unique communities of bacteria, fungi, and other microorganisms (Brodo et
al. 2001, Arnold et al. 2009, Hodkinson and
Lutzoni 2009, Gauslaa 2014). Despite their
importance, many aspects of lichens, from taxonomy to basic biology, remain understudied
(Brodo et al. 2001, Lendemer and Allen 2014).
Similarly, lichens have demonstrated utility as
indicator species for environmental pollution
and degradation (Nash 1975, Showman 1981,
Muir and McCune 1988, Wolseley 1995, McCune et al. 1997), yet their responses to disturbances and how disturbance regimes shape the
composition and structure of lichen communities has yet to be studied in many ecosystems.
The majority of studies documenting the
relationship between lichens and disturbance
regimes suggest that lichens are highly impacted by burning, both in terms of diversity and
abundance, across a range of habitats (Klein
1982, Antos et al. 1983, Mistry 1998, Reinhart
and Menges 2004, Johansson and Reich 2005).
Reduced lichen cover may persist in burned
areas due to slow growth and colonization
rates, and as the result of unprotected organelles in ground-layer lichens (Antos et al.
1983, Holt and Severns 2005). Nonetheless, a
study of reindeer lichens (Cladonia spp. P.
Browne) in grasslands of Minnesota, USA,
suggests that recovery is largely a factor of fire
intensity and frequency, whereby lichens subjected to low intensity fires are quicker to recover compared to those exposed to higher intensity burns (Johansson and Reich 2005).
Many of the studies detailing lichen community response to fire in North America have focused on soil lichens within grassland habitats
of the West (Bowker et al. 2004, Holt and
Severns 2005, Johansson and Reich 2005), and
therefore provide limited insight to the response of corticolous lichen communities in
forest and woodland settings.
Because prescribed burning and tree density reduction (i.e., thinning) represent the most
widely used management techniques being
employed to restore and promote resiliency
within overly dense, fire-excluded forests, we
sought to better understand the impacts of
these practices on affiliated lichen communities. Here we present the results of an observational study describing the short-term effects of these treatments on corticolous lichens
within southern pine forests of the Mid-Atlantic Coastal Plain. The study was undertaken in
the broader context of a large-scale inventory
of lichens on protected lands throughout the
region, which revealed unexpectedly high levels of diversity, including on the Delmarva
Peninsula (Lendemer and Allen 2014). Discussions undertaken with land managers and
agency officials during the larger project re-
Page 17
vealed that, although these practices were being used to achieve conservation benefits in
this region, the possible impacts of these management actions on lichen communities were
not being considered and were largely unknown.
METHODS
Study Area
This study took place on Nassawango
Creek Preserve located in Wicomico and
Worcester counties, on the Eastern Shore of
Maryland, USA (38° 16’ 09.5” N 75° 28’ 15.2”
W; Figure 1). The ~4050 ha property is owned
and managed by The Nature Conservancy and
was acquired for the purpose of biodiversity
and watershed protection beginning in the late
Figure 1. Map of the Mid-Atlantic Coastal Plain
showing the location of the study area on the lower
Eastern Shore of the Delmarva Peninsula, Maryland, USA
1970s. Floodplain forests dominated by bald
cypress (Taxodium distichum [L.] Rich.), black
gum (Nyssa sylvatica Marshall), and red maple (Acer rubrum L.) predominate across much
of the Preserve. Excessively drained and nutrient-poor upland sites known as inland dunes
(Denny and Owens 1979) account for roughly
10 % of the land base and, by contrast, host a
variety of fire-adapted woodland species. Under historic or pre-European settlement conditions, the inland dunes are thought to have
been vegetated by drought-tolerant tree species including oaks (white oak [Quercus alba
L.], black oak [Q. velutina L.], blackjack oak
[Q. marilandica Münchh.], post oak [Q. stellata Wangenh.]), sand hickory (Carya pallida
[Ashe] Engl. & Graebn.), and southern pines
(loblolly pine [Pinus taeda L.], shortleaf pine
[P. echinata Mill.], Virginia pine [P. virginiana
Mill.]). Understory vegetation on the dunes is
typically characterized by a diversity of pyrogenic herbaceous, grass, and shrub species, at
least when a sufficient canopy openness is
maintained (Harrison 2011, NatureServe
2011).
The region has a complex and lengthy
land-use history, wherein extensive areas of
wetland forests were drained and converted to
productive agriculture and plantation forestry.
Despite the lower productivity of plantations
grown on the inland dunes, the fact that this
ground remains operable by heavy equipment
throughout the year makes it a valuable asset
to the forest industry during periods of wet
weather. As a result, loblolly pine is often the
dominant tree species encountered on these
sites and within adjacent upland ecotones,
where this study took place. Restoration practices, including the re-introduction of fire, reduction of tree stem density, and enrichment
planting with site-adapted species, are being
implemented to enhance the biodiversity and
habitat values of degraded inland dunes and
affiliated uplands across the property.
An observational study design was used to
characterize differences in lichen community
Page 18
response to restoration management practices
while controlling, to the extent possible, for
edaphic setting, stage of stand development,
and tree composition. Study plots were established in middle-aged (20 yr to 40 yr) pine
stands that were previously (1) thinned but not
burned (n = 3 stands; code = 10), (2) thinned
once and burned once (n = 2 stands; code =
11), (3) thinned once and burned twice (n = 2
stands; code = 12), or (4) an unaltered reference (n = 2 stands; code = 00). Thinning to
reduce canopy density was accomplished with
conventional logging equipment and always
occurred at least one year prior to burning.
Pine tree basal areas on the thinned plots were
reduced to between 16.1 m2 ha-1 and 18.4 m2
ha-1 by commercial thinning treatments carried
out between 2007 and 2012. Prescribed burns
were conducted during the early growing season (March through May). Descriptions of the
treatments are presented in Table 1.
Sample Selection
Corticolous lichens were sampled from
trees growing on plots drawn from a nominal 2
ha systematic grid used for forest inventory on
the property. The sample trees were selected
as follows: within a search radius of 15.2 m
from the plot center and in a randomly selected quadrat (i.e., NE, SE, SW, NW), we chose
the closest tree of each species within two diameter-based size classes (2.54 cm dbh to 11.2
cm dbh, and >11.2 cm dbh). One representative of each tree species was sought within
each size class on each plot. Species present
at lower densities were searched for within the
remaining quadrats until the entire plot area
was used (730 m2).
Lichens were inventoried on each of the
selected trees within established sampling
heights based on three height categories: (1)
base (forest floor to 0.3 m up the stem), (2)
bole (0.3 m to 2.4 m, or up to the lowest live
branch within the tree canopy), and (3) canopy
(defined as the lowest live branch, excluding
epicormic sprouts). Measurement of lichens
on the base and bole sections of the stem were
accomplished from the ground, whereas canopy samples were either collected from the
ground with a pole saw or required climbing
equipment to excise the selected branch. Lichen thalli were identified and recorded in the
field within each sampling interval. Voucher
specimens for each species identified on a plot
were collected. Vouchers were later examined
Table 1. Selected attributes of the study plots including the timing of commercial thinning and prescribed
burns (Treatment: 00 = control; 10 = thinned, not burned; 11 = thinned, burned once; 12 = thinned, burned
twice). Means and standard deviations for basal area (BA) and average stand diameter (Dq), and the relative abundance of pines to hardwoods (Pine BA, %). na = not applicable.
Treatment
Stand
name
Plot
(n)
Thinning
Prescribed burn
BA
(m2 ha-1)
Pine BA
(%)
Dq
(cm)
00
Ace
2
na
na
26.5 ± 11.4
55
21.7 ± 1.3
00
Laws
4
na
na
39.7 ± 8.3
81
22.8 ± 3.2
10
Ches/Som
2
2011
na
16.1 ± 13.0
72
23.5 ± 1.6
10
SCI-P2
3
2005
na
23.0 ± 4.0
87
21.7 ± 1.5
10
WIC-5
4
2013
na
16.7 ± 8.3
95
28.5 ± 5.3
11
WIC-2
4
2007
May 2011
27.6 ± 13.9
96
26.6 ± 4.5
11
WOR-1
2
2006
April 2011
16.1 ± 6.5
~100
26.9 ± 3.6
12
WOR-4
4
2005
April 2009, April 2013 19.0 ± 8.3
~100
27.9 ± 2.3
12
WOR-7
2
2007
April 2011, May 2013 13.8 ± 6.5
~100
22.5 ± 0.5
Page 19
in the lab using compound and dissecting microscopes, chemical spot test, and thin layer
chromatography when appropriate. All vouchers were deposited in the New York Botanical
Garden, Bronx, New York, USA. In addition
to abundance (counts for a given species within a sampling height), cover was also visually
estimated in the field for each lichen taxon recorded. Cover was placed into five groups as
follows: 1 (1 % to 5 %), 2 (6 % to 25 %), 3
(26 % to 50 %), 4 (51 % to 75 %), and 5 (76 %
to 100 %). An estimate of total lichen cover
for each sampling interval was also made independent of those for the individual taxa. For
the purposes of assessing growth form and reproductive mode, a table of all species found
during the study was produced and these characters were scored for all taxa using existing
references and standard literature. This resulted in the assignment of a growth form (i.e.,
crustose, foliose, fruticose) and reproductive
mode (asexual vs. sexual) to each taxon.
Statistical Analyses
Estimates of lichen diversity and cover obtained from the individual trees (n = 177) were
treated as sub-samples, and values for the experimental unit, represented by plots (n = 27)
for correlation and stands (n = 9) for Anova,
were arrived at by either summing (for diversity measures) or averaging (for cover) over the
sub-samples. Dependent variables were calculated for each plot or stand and sampling
height (Base = BAS, Bole = BOL, Canopy =
CAN) as follows: (1) lichen diversity (taxa)
was determined as the number of unique taxa
observed across all trees, (2) lichen cover
(cover) as the average of the fractional cover
estimate for each sampling height, (3) lichen
morphology (growth form) as the proportion
of lichens within three categories (crustose, foliose, and foliose) across treatments, and (4)
lichen reproductive strategy (reproductive
mode) as the proportion of lichens exhibiting
either sexual or asexual reproductive struc-
tures (indeterminate samples were discarded
from the analysis) across treatments.
Sørensen similarity values (Sørensen
1948) were used to compare lichen taxa among
sampling heights, (i.e., BAS and BOL, BOL
and CAN, and BAS and CAN). Values were
calculated using EstimateS for Windows v9.10
(Colwell 2013) by tree species group (hardwoods = HW, pines = PI) for each treatment
category. More formal analysis was not possible with this dataset due to a preponderance of
missing values on the burned plots, which resulted in a highly unbalanced dataset. A combination of factors contributed to this occurrence, but it was largely attributable to lichens
having been eliminated from the BAS sampling height of trees in the burn treatments.
The zero values in this analysis correspond to
situations in which lichens were present within
both heights that were being compared, but no
taxa were common to both.
We took an analysis of variance approach
to assessing how lichen communities were impacted by the treatments. Models of the following general form were used to evaluate the
contribution of independent variables:
taxa or cover or growth form or
reproductive mode = treat + cov,
(1)
where the lichen variables were determined in
total or at the different sampling heights, treat
is a class variable describing the combination
of fire and thinning treatments (n = 4, coded
00, 10, 11, 12), and cov is a quantitative covariate representing the number of hardwood
species sampled in each stand. This variable
was included in an attempt to account for
known differences in the morphology and
chemistry of tree bark between pines and hardwoods as they relate to lichen occupancy (Culberson 1955, Schmitt and Slack 1990). Owing
to the small sample size available for this analysis, a limited number of contrasts were chosen a priori for evaluation with post hoc significance tests. Specifically, we compared the
Page 20
burned and unburned (00 + 10 = 11 + 12), and
the thinned and unthinned (00 = 10) treatments. The GLM procedure in SYSTAT 12
(SYSTAT Software, San Jose, California,
USA) was used to carry out all statistical tests.
Quantification of Fire Severity
Methods developed by the Monitoring
Trends in Burn Severity program (MTBS;
http://www.mtbs.gov/index.html) were used to
obtain plot-level estimates of fire impacts on
the vegetation (e.g., Picotte and Robertson
2011). Paired Landsat scenes collected approximately one year before and as soon as
possible following the prescribed burns provided the basis for this assessment. The value
of the fire severity variable (differenced normalized burn ratio, dNBR) determined at each
plot location was paired with lichen taxa and
cover variables. For this analysis, the lichen
taxa variable was given by the cumulative
number of lichen species recorded on each
plot by tree species group (PI and HW), and
lichen cover as the average of the base, bole,
and canopy sampling heights. The highest
value of the dNBR variable recorded for each
plot was used to describe fire severity on the
twice-burned plots (dNBRMAX). Simple correlation analysis was used to assess the
strength of the relationship between fire severity and the lichen variables.
RESULTS
Considering the availability of different
substrates for corticolous lichens, hardwood
tree species were notably more common on
the unburned than burned plots (Table 2), and
large-sized hardwoods were limited to the reference plots. Of the common hardwood species, only sweetgum (Liquidambar styraciflua
L.), southern red oak (Quercus falcata
Michx.), and sassafras (Sassafras albidum
[Nutt.] Nees) were substantially represented
on both the burned and unburned plots. Fur-
thermore, the hardwood species on the burned
plots were typically found in subordinate
crown positions to the pines, within the midstory layer, presumably as a result of past cultural treatments (i.e., broadcast herbicide release to favor the pines). A number of more
mesic and generalist species, including red
maple, American holly (Ilex opaca Aiton), and
water oak (Q. nigra L.), were also well represented on the unburned plots. Pines, and most
notably loblolly pine, were a dominant feature
across all the study plots (Table 2). On average, tree basal areas (BA, m2 ha-1) were highest in the reference areas and lowest in stands
that had been thinned and burned twice, although these values varied considerably
among plots within a treatment (Table 1).
A grand total of 93 lichen species were
found growing on trees sampled in this study.
Among these, 76 were found on trees in the
reference areas (T = 00), 83 in the thinned and
unburned plots (T = 10), 35 in the thinned and
once-burned plots (T = 11), and 8 in the
thinned and twice-burned plots (T = 12).
Trends in tree species diversity paralleled
those for the lichens, with 16 tree species represented in the reference, 13 in the thinned, 5
in the thinned and burned, and 3 in the thinned
and twice-burned stands. Viewed across all
plots and treatments, the relationship between
the number of tree species and lichen diversity
was strong for the hardwoods (r = 0.862, P <
0.001) but not for pines (r = 0.143, P = 0.477).
In contrast, no significant correlations were
found when comparisons were restricted to
plots within the burned and unburned treatments, although the relationship was marginal
for the unburned hardwood category (Figure
2).
While fewer in total number, the lichen
species found on the pines exhibited substantial overlap with those found on the hardwoods
(Table 3). For example, three quarters (75 % ±
10 % mean and SD) of the lichen taxa growing
on the pines were also found on the hardwoods
in all but the twice-burned plots. The higher
Page 21
Table 2. List of tree species on which lichens were sampled, by species group (HW = hardwood, PI =
pine) and treatment (00 = control; 10 = thinned, not burned; 11 = thinned, burned once; 12 = thinned,
burned twice). Values indicate tree frequency (the proportion of plots on which each tree species was
present) by treatment and for the study. Taxa refers to the total number of lichen species found on each
tree species.
Species group
00
Treatment
10
11
Pinus echinata
PI
0.17
0.00
0.00
0.00
0.04
6
Pinus serotina Michx.
PI
0.33
0.00
0.17
0.00
0.11
10
Pinus taeda
PI
0.83
1.00
1.00
1.00
0.96
40
Pinus virginiana
PI
0.33
0.11
0.00
0.00
0.11
17
Acer rubrum
HW
1.00
0.89
0.00
0.00
0.52
56
Carya pallida
HW
0.33
0.00
0.00
0.00
0.07
29
Cornus florida L.
HW
0.33
0.00
0.00
0.00
0.07
21
Diospyros virginiana L.
HW
0.00
0.11
0.00
0.00
0.04
20
Ilex opaca
HW
0.83
0.89
0.00
0.00
0.48
27
Liquidambar styraciflua
HW
0.83
0.89
1.00
0.00
0.70
59
Magnolia virginiana L.
HW
0.17
0.00
0.00
0.00
0.04
9
Nyssa sylvatica
HW
0.50
0.22
0.17
0.00
0.22
36
Quercus alba
HW
0.33
0.11
0.00
0.00
0.11
28
Quercus falcata
HW
0.17
0.67
0.5
0.00
0.37
46
Quercus nigra
HW
0.67
0.22
0.00
0.00
0.22
35
Quercus rubra L.
HW
0.00
0.11
0.00
0.17
0.07
19
Quercus stellata
HW
0.17
0.11
0.00
0.00
0.07
29
Sassafras albidum
HW
0.50
0.89
0.17
0.17
0.48
45
Tree species
diversity of lichens found on the hardwood
trees corresponded to more taxa in common
among sampling heights than for the pines
(Figure 3, top panels). Similarity values were
comparable for the BAS and BOL interval of
hardwoods (0.51 ± 0.01) and pines (0.59 ±
0.09) on the unburned plots, and appeared to
remain stable for the hardwoods, yet declined
for the pines on the burned plots, although reduced sample size due to missing values on
the burned plots makes this comparison less
clear cut (Figure 3, bottom panels). Similarity
values for the BOL and CAN interval were
generally lower than those determined for the
more proximate BAS and BOL interval, and,
when averaged across treatments, values for
12
Total
Taxa
the hardwoods (0.45 ± 0.18) were more than
double those for the pines (0.18 ± 0.01). The
lowest similarity values were obtained for the
most distant BAS and CAN interval.
The Anova model assessing overall lichen
diversity suggested a highly significant treatment effect and, further, that the covariate representing the number of hardwood tree species
was also important to consider (Figure 4, top
panel). The subsequent contrasts revealed that
burning substantially reduced the overall diversity of lichens in stands subject to one or
two fires, where, on average, 36.0 ± 5.2 (least
squares mean and SE) more taxa were represented in the unburned (T = 00 and T = 10)
than burned (T = 11 and T = 12); no effect of
Page 22
Figure 2. Relationship between the number of tree
species and lichen species found growing on hardwood (HW) and pine (PI) tree species for burned
and unburned plots. Pearson correlation coefficients and P-values.
thinning in the absence of burning was indicated (Figure 4). Models evaluating treatment effects on lichen diversity within the base and
bole sampling heights yielded significant results, whereas no difference was apparent
among samples taken from the canopy (Figure
5, top panel). The number of lichen taxa found
on the boles of trees in the unburned stands averaged 39.3 ± 6.1 more than in the burned
stands.
In contrast to the findings for lichen diversity, analysis of overall cover did not yield a
significant result, despite that the ratio of cover
in the unburned to burned stands approaches
3:1 (Figure 4, bottom panel). Findings for the
discrete base and bole sampling heights were
more intuitive, in both cases suggesting that
cover was substantially lower in the burned
plots, by 0.28 ± 0.08 and 0.36 ± 0.9, respectively (Figure 5, bottom panel). Consistent
with the findings from the sampling height
analysis of the diversity variable, lichen cover
within the canopy was apparently unaltered by
burning or thinning.
We were unable to demonstrate differences
in either the proportion of lichens exhibiting
different growth forms (Figure 6, top panel) or
reproductive modes (Figure 6, bottom panel)
in response to the treatments. Lichens exhibiting a crustose growth form were most common across stands 0.72 ± 0.14 (mean and SD),
and appeared to maintain a similar proportion
of that total across treatments. While not supported by the results of any formal statistical
tests, there did appear to be a tendency for the
proportion of lichens with a foliose growth
form to decline, and reciprocally for those
with a fruticose growth form to increase, or
more likely to simply persist within the burned
stands (Figure 6, top panel). Similarly, while
the statistics do not support any shift in the reproductive mode exhibited by the lichens persisting in treated stands, we did note an apparent downward trend in the occurrence of lichens exhibiting a sexual reproductive mode
(Figure 6, bottom panel).
Assessment of the relationship between
plot-level fire severity (dNBRMAX) and lichen
variables was restricted to observations made
Table 3. The number of lichen species found within each sampling height and in total by species group
(HW = hardwood, PI = pine) and treatment (00 = control; 10 = thinned, not burned; 11 = thinned, burned
once; 12 = thinned, burned twice). “Both” indicates the number of lichen taxa in common across the tree
species groups, and na = not applicable.
Base
PI Both
HW
Bole
PI
Both
Canopy
HW
PI Both
Total
HW
PI Both
Treatment
HW
00
34
7
7
57
16
10
42
17
14
71
27
21
10
39
20
12
62
14
12
38
16
12
76
31
26
11
8
3
2
21
6
4
15
8
4
30
14
9
12
1
0
na
4
0
na
1
5
1
4
5
1
Page 23
Figure 3. Similarity of lichen species found growing on hardwood and pine species at different sampling
heights for the various treatments (00 = control; 10 = thinned once, not burned; 11 = thinned once, burned
once; 12 = thinned once, burned twice). Means and standard deviations for the total number of species in
common (top panels) and corresponding Sorensen similarity coefficient (bottom panels).
on pine trees because hardwoods were not well
represented in the burned stands, particularly
those that had been subjected to two fires. The
range of dNBR values determined across the
burn blocks (range = −235 to 621) was considerably wider than for dNBRMAX recorded on
the study plots (range = 175 to 466), and fell
well within the range of possible values indicated for the methodology (approx. −600 to
1200). Similarly, the average dNBR values
determined across all burn blocks (168 ± 140,
mean and SD) was both lower and more variable than the dNBRMAX values (317 ± 84) included in the analysis. Plots that were burned
twice tended to have higher dNBRMAX, values,
but there was some overlap within the central
part of the distribution (Figure 7). A signifi-
cant negative correlation was observed between fire severity and the number of lichen
taxa found on pine trees; however, no relationship was detected for lichen cover. One of the
plots had a substantially higher average cover
value than the others (dNBRMAX = 367, cover =
0.20), an observation that was attributable to
high lichen cover within the crown (0.60), as
opposed to the more exposed base or bole sections of the stem.
DISCUSSION
We acknowledge that findings from this research are tempered by the observational study
design and that the variability in the timeframe
over which the treatments were applied result-
Page 24
Figure 4. Overall trends in lichen diversity and
cover for the different treatments (00 = control; 10
= thinned once, not burned; 11 = thinned once,
burned once; 12 = thinned once, burned twice).
Statistics from the GLM are presented, where PTR,
PCV, PH1, and PH2 are P-values associated with tests
for the effects of the treatment, covariate, and contrasts associated with burning (00 + 10 = 11 + 12)
and thinning (00 = 10), respectively.
ed in different recovery periods when the lichen samples were collected. Also, hardwood
trees in the treated stands tended to be younger
and smaller than the pines, with correspondingly higher vulnerability to fire-induced mortality. However, available evidence suggests
that the variable lag times between treatments
and observations represented here are not likely to have been sufficient for lichen taxa to become reestablished or expand substantially
following these types of disturbances (Jandt
and Meyers 2000, Coxson and Marsh 2001).
The treatments documented in this study,
prescribed burning and thinning, were undertaken to restore aspects of structure and composition that had been diminished through species conversion and long-term fire exclusion
(Andreu et al. 2008, Nowacki and Abrams
2008, Ryan et al. 2013). Historic vegetation
assemblages on these sites straddle the desig-
Figure 5. Trends in lichen diversity and cover by
sampling height for the different treatments (00 =
control; 10 = thinned once, not burned; 11 =
thinned once, burned once; 12 = thinned once,
burned twice). Three discrete heights were analyzed: BAS, BOL, and CAN. Summary statistics
from the GLM are presented, where PTR, PCV, PH1,
and PH2 are P-values associated with tests for the
effects of the treatment, covariate, and contrasts
associated with burning (00 + 10 = 11 + 12) and
thinning (00 = 10), respectively.
nations of Coastal Plain Oak–Loblolly Pine
Forest and Inland Sand Dune and Ridge
Woodland community types in Maryland (Harrison 2011), and these community types are
known to harbor fire tolerant or pyrogenic
vegetation supporting the use of prescribed
burning as a management tool for restoration.
Similarly, fire exclusion has led to tree densification with negative consequences for associated understory vegetation and wildlife (Taft
2009). We viewed the retention of off-site
pines, noting that shortleaf pine would probably be more abundant than loblolly on the inland dune sites, as desirable, at least over the
short term, because the highly flammable needle litter represents an important source of fuel
that facilitates burning (sensu Kirkman et al.
2007).
Page 25
Figure 6. Trends in the proportion of lichen
growth forms and reproductive modes determined
across treatments (00 = control; 10 = thinned once,
not burned; 11 = thinned once, burned once; 12 =
thinned once, burned twice). Summary statistics
from the GLM are presented, where PTR, PCV, PH1,
and PH2 are P-values associated with tests for the
effects of the treatment, covariate, and contrasts associated with burning (00 + 10 = 11 + 12) and thinning (00 = 10), respectively.
In combination, these practices have resulted in substantial increases in understory
plant diversity and structural heterogeneity of
the forest canopy (The Nature Conservancy’s
Nassawango Creek Preserve, Wicomico and
Worcester counties, Maryland, USA, unpublished data), yet relatively little is known about
associated impacts on understudied groups
such as lichens (Lendemer and Allen 2014),
which collectively comprise an overwhelming
proportion of earth’s biodiversity (Hawksworth 1991, Whitman et al. 1998, Mora et al.
2011). Lichens also often function as indicator and keystone organisms in many ecosystems, providing vital services for other members of the community (Brodo et al. 2001, Gianinazzi et al. 2010). Thus, the general lack of
data documenting how management practices
impact these groups represents a risk because
Figure 7. For pine trees only, the relationship between fire severity (dNBR) and a) the total number
of lichen taxa, and b) lichen cover on plots subjected to one or two prescribed burns. Pearson correlation coefficient (r) and P-values. Dashed vertical lines represent the 25th and 75th percentiles of
the dNBR values recorded across the burn blocks
in 2009, 2011, and 2013 when prescribed burns
were carried out.
they are being carried out and evaluated without considering one of the most diverse and
important components of the ecosystem.
Our findings suggest that corticolous lichen communities similar to those present in
the unburned stands reported on in this study
have the potential to be substantially altered
by the reintroduction of fire. Most notable
was the apparent reduction in the diversity of
lichen taxa found in burned stands (Figure 4,
top panel). An explanation for this result may
be traced, at least in part, to the reduced number and smaller stature of the otherwise generally higher lichen diversity supporting hardwood species present on the burned plots (Tables 1 and 2). Moreover, the canopy samples
collected from the hardwoods on burned plots
tended to be in closer proximity to the forest
floor than for the larger pines, suggesting that
exposure of canopy lichens to damage by the
Page 26
fires was also higher. We speculate that if
more large, fire-tolerant hardwoods had been
present in the burned stands, their canopies
would have acted as more of a refugium for
the lichen diversity, similar to that of pines.
However, the extent to which the canopy layer
represents a refugium from fire damage is
tempered by the compositional dissimilarity
among lichens encountered at the various
sampling heights, with possible implications
for post-fire colonization of the lower bole
sections.
While the average number of lichen taxa
found on pines was substantially lower than on
the unburned hardwoods, those values remained fairly stable following the fires (Figure
2). Taken together, these findings support the
idea that hardwoods harbor more diverse lichen communities than pines (Schmitt and
Slack 1990), but this may be countered by a
correspondingly higher vulnerability to damage by fire. A surprising result was that total
lichen cover was not identified as significantly
related to the treatments (Figure 4, bottom
panel). We attribute this counterintuitive finding to two primary issues: first is the small
sample size available for the Anova (n = 9
stands) in conjunction with the relatively high
variability in the cover variable among stands,
and secondly that important differences were
revealed for the base and bole sampling
heights when they were analyzed independent
of the null response of lichen cover in the canopy (Figure 5, bottom panel).
Thin-barked hardwoods are highly vulnerable to damage by fires independent of their
size, a factor that has been used to infer the encroachment of fire-sensitive species across the
landscape (e.g., Kirwan and Shugart 2000,
Nowacki and Abrams 2008). Therefore, any
lichen diversity associated with fire-susceptible hardwood species (e.g., red maple, American holly, American beech) should be assessed
in the context of the broader restoration objectives for these natural areas by recognizing
that mesophication of the tree community re-
sulting from long-term fire exclusion may also
have given rise to uncharacteristic lichen communities. Whether such reductions in lichen
diversity will be offset by other species that
become established on site-adapted hardwood
trees is an open question requiring further
study.
Abiotic factors such as humidity and solar
insulation may represent stronger selective
pressures on lichens than tree species, pushing
lichen taxa to be more generalist in terms of
their use of substrates (Gauslaa 2014). Some
lichen species are known to depend on specific
humidity levels for survival (Kantvilas and
Minchin 1989), a condition that is altered by
the removal of canopy trees as in a thinning.
However, in this study, thinning in the absence
of fire did not appear to result in meaningful
changes in lichen diversity or cover. We speculate that this finding may be due to the relatively short and variable intervals following
thinning (a period spanning over seven years
between 2007 and 2013) when the samples
were collected, in relation to rates of colonization by lichens. Alternatively, the lichen communities encountered in this study may be relatively insensitive to the magnitude of microclimatic changes brought about by the thinning
treatments. Wind damage to pendulous lichens along the edges of harvest gaps was reported by Coxson and Stevenson (2005), but
short-term impacts to lichens with other
growth forms were somewhat ambiguous.
Previous research has documented differences in lichen communities based on the
height gradient within trees, suggesting a level
of discrimination among the base, bole, and
canopy (Lesica et al. 1991, Peck and McCune
1997, Campbell and Coxson 2001, Cleavitt et
al. 2009). While our findings generally support this observation, we also observed some
notable similarities among the lichens on the
bases and boles of hardwoods and pines, particularly on the unburned plots (Figure 3).
Burning tended to eliminate lichens from the
tree base, effectively disallowing the calcula-
Page 27
tion of similarity values for that sampling
height in the burned plots, but values determined on the unburned plots were consistent
with the hypothesis that lichen composition
would become more different with increasing
vertical separation in trees.
Evidence from other studies suggests that
all lichen morphologies (i.e., crustose, foliose,
fruticose) are highly vulnerable to fires (Romangni and Gries 1997, Wolseley and Aguirre-Hudson 1997, Johansson et al. 2012).
While our findings do not provide any solid
evidence contradicting this assertion, we did
note an interesting trend in the data suggesting
that lichens with a fruticose growth form may
be better suited than foliose lichens to persist
in fire adapted systems (Figure 6, top panel),
but this contention will require further study.
Crustose lichens were the dominant growth
form in both the unburned and burned plots,
where their relative abundance was unchanged. Lichens exhibiting the crustose
growth form have relatively lower surface area
exposed to fire compared to those with foliose
and fruticose morphologies, providing a possible explanation for the neutral response of
crustose lichens to fire observed here. In the
case of fruticose lichens, we speculate they
may have an advantage related to either the rapidity with which they can colonize new habitats, or to their ability to occupy microhabitats
on the bark surface that are less exposed to
fire.
Changes in the proportion of lichens with
different reproductive modes following disturbance also has implications for colonization
and persistence under a re-established burning
regime. Previous research has indicated lichen
soredia, which are small vegetative reproductive structures composed of fungal hyphae and
algae (Brodo et al. 2001), are an effective dispersal mechanism for colonizing recently
burned habitats (Eversman and Horton 2004).
Over half of the lichens collected in this study
primarily reproduce asexually through the dispersal of soredia or other specialized vegetative propagules. In contrast, the colonization
of canopy branches by sexual species present
in adjacent forest blocks might be expected
considering the increased dispersal abilities of
small fungal diaspores, such as ascospores,
compared to relatively much larger asexual diaspores (Löbel et al. 2009, Wagner et al. 2006,
Werth et al. 2006, Johansson et al. 2012, Lendemer et al. 2014). Our findings related to
possible changes in the reproductive mode favored by lichens following thinning and burning were ambiguous (Figure 6, bottom panel),
yet trended with the idea that a vegetative dispersal mechanism might dominate, at least
over the short term.
It is reasonable to assert that the variability
of fire effects on vegetation may not be adequately captured by a simple count of the
number of times a stand has been burned. To
address that possible limitation, the once- and
twice-burned class variable used to represent
the treatment in the Anova models was further
explored using the dNBR approach to quantifying fire severity (http://www.mtbs.gov/index.html; e.g., Picotte and Robertson 2011)
(Figure 7). While these results generally supported our use of the simpler class variable approach (i.e., lower values of dNBR were consistently associated with the once-burned plots
and higher values with those that were burned
twice), a considerable range of dNBR values
was also represented within each burn treatment. The study plots were located at higher
and drier than average landscape positions
within the respective burn blocks, and were
consistently associated with higher dNBR values. Anecdotal evidence suggests that the second fires in these areas burned hotter than the
first as the result of abundant dead fuels generated by the initial burn, helping to explain why
the burn count variable performed adequately
in the context of this study. Findings for the
pine trees based on this analysis are entirely
consistent with the overall results presented in
Figure 4, in which a stronger negative relationship is indicated for lichen diversity than for
cover.
Page 28
MANAGEMENT IMPLICATIONS
While burning appears to have reduced the
abundance and diversity of lichens previously
found growing in the study area, we suggest
that this outcome should be interpreted in light
of restoration goals and in the context of an altered disturbance regime brought about by fire
exclusion. From this perspective, it makes
sense that the phenomenon of mesophication
(Nowacki and Abrams 2008) would also extend to organisms for which component trees
act as hosts. Available references suggest that
a relatively frequent and low-intensity fire regime was characteristic of the coastal plain
landscape where this study took place (Frost
1998, Guyette et al. 2012).
It is fairly well established that lichens are
highly vulnerable to damage by fire, yet,
through various avoidance and dispersal type
mechanisms, they are still able to maintain a
presence within fire-adapted systems (Longán
et al. 1999, Eversman and Horton 2004, Johansson 2008). The initial fires in these areas
burned under conditions that led to more intense fire behavior than desired over the long
term (e.g., as a result of heavy fuel loads following thinning and timing in the early growing season), and may have led to greater impacts to the lichen communities. If so, these
factors could be mitigated by initially reintroducing fires under conditions that would give
rise to less active fire behavior while reducing
fuel loads. Other studies have documented
detrimental effects of forest densification on lichens, of the type that occurs in the absence of
fires (Bond et al. 2005, Root et al. 2010), although this could conceivably be addressed
through thinning.
Over time, repeated burning can be expected to act as a filter selecting for fire-tolerant
tree species that will in turn provide stable
substrates for similarly adapted lichens to col-
onize (Bartos and Mueggler 1981, Espelta et
al. 2003). The mature pine component of
these stands is arguably already functioning in
this way, whereas fire adapted hardwood species and associated lichen diversity still need
to be recruited into these areas. For example,
dry-site and fire-adapted oak species (e.g., post
oak and black oak) are being sought as future
overstory components in these areas, but recruitment in the context of a moderately frequent fire regime presents a challenge (see Arthur et al. 2012). Possible approaches to overcoming these limitations include: (1) waiting
to re-introduce fire until repeated thinning of
the pine canopy has released oaks already
present in the understory or midstory and enabled them to grow to sizes (attain a bark
thickness) that will be able to resist damage
from subsequent understory fires, (2) using ignition techniques or other protection measures
(e.g., raking; Williams et al. 2006) to guard selected areas and trees from fire damage within
a burn block, and (3) periodically allowing for
extended fire-free intervals so that new cohorts
can attain sizes that will confer resistance to
damage as in (1).
Recognizing and incorporating biodiversity concerns into forest and restoration management activities benefits from taking a multidisciplinary approach. This observational
study of the impacts of thinning and fire on lichen communities within pine-dominated forests of the Mid-Atlantic Coastal Plain calls attention to a previously overlooked component
of biodiversityone that appears to be responsive to these types of treatments. Additional
study will be required to determine whether a
new equilibrium is established between the lichens and fire-adapted tree community on
these sites where burning was reinstituted to
benefit other more conspicuous aspects of biodiversity.
Page 29
ACKNOWLEDGEMENTS
The participation of J. Barton and J. Lendemer was supported by NSF DEB-1145511 (award
to J. Lendemer and R. Harris). The authors thank B. McCune and R. McMullin for discussion of
aspects of study design. J. Allen, N. Noell, G. Dettmann, and B. Palmer are thanked for their assistance with field sampling and laboratory study. A.M. Ruiz (also supported by NSF DEB1145511) aided significantly in the curation and digitization of voucher specimens generated by
this study.
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Kral et al.: Simulating Prescribed Fires
Page 34
Research Article
SIMULATING GRASSLAND PRESCRIBED FIRES USING
EXPERIMENTAL APPROACHES
Katherine C. Kral*, Ryan F. Limb, Torre J. Hovick, Devan A. McGranahan,
Aaron L. Field, and Peter L. O’Brien
School of Natural Resource Sciences, North Dakota State University,
1402 Albrecht Boulevard, Fargo, North Dakota 58102, USA
Corresponding author: Tel.: +1-701-231-5828; e-mail: [email protected]
*
ABSTRACT
RESUMEN
Small-scale fire approaches, like burn
boxes, burn tables, and propane burners, are often used to facilitate experimental control over fire and allow
greater replication. We compared
characteristics of grassland prescribed
fires to three experimental approaches
to determine if these approaches simulate prescribed fires. We conducted
prescribed fires during the growing
and dormant season to compare with
burn box, burn table, and propane
prong approaches. Burn box and
burn table approaches used additional
timothy (Phleum spp. L.) hay for a
fuel source, while the propane prong
used propane to burn in situ and
greenhouse-grown plants. We collected temperature data with thermocouples to determine time-temperature profiles, maximum temperatures,
heat durations (time above 60 °C),
and heat dosages (the product of time
and temperature above 60 °C). Fires
produced by burn box, burn table, and
prescribed fires had similarly shaped
time-temperature profiles, but propane prong fires produced different
curves with a longer duration near the
maximum temperature. Burn box and
burn table approaches had the highest
heat dosages because timothy hay
Los fuegos experimentales a pequeña escala,
como las quemas en caja, en mesas de quema y
con quemadores de propano, son frecuentemente utilizados para controlar experimentalmente
el fuego y permitir más repeticiones de los mismos. Nosotros comparamos las características
de las quemas prescritas en pastizales realizadas durante las estaciones de crecimiento y de
reposo con tres ensayos experimentales que involucraron quemas en cajas, en mesas de quema y usando clavijas de propano. Para las cajas
y las mesas de quema, se utilizó paja de timote
(Phleum spp. L.) como fuente de combustible,
mientras que para los ensayos con clavijas de
propano se utilizó propano para hacer quemas
in situ y también sobre plantas producidas en
invernaderos. Nosotros tomamos datos de temperaturas con termocuplas para determinar perfiles de temperatura, temperaturas máximas,
duración del calor (duración de las temperaturas por sobre los 60 °C), y de dosis de calor (el
producto de la duración y la temperatura por
encima de los 60 °C). Los fuegos producidos
en las cajas de quema, en las mesas de quema y
en las quemas prescritas presentaron perfiles similares en cuanto a duración y temperatura,
aunque los fuegos realizados con clavijas de
propano produjeron diferentes curvas, con una
duración mayor cerca del máximo de temperatura. Los ensayos en cajas de quema y en mesas de quema tuvieron las dosis más altas de calor porque la paja del timote se quemó comple-
Page 35
burned completely compared to in
situ vegetation in prescribed fires. To
simulate prescribed fires, propane
rates should be regulatedeither increased or decreasedto produce
time-temperature profiles consistent
with prescribed fires. Moreover, approaches using added hay often result
in higher heat dosages and may require decreased fuel loading to match
research objectives.
tamente en comparación con la vegetación in
situ de las quemas prescritas. Para simular quemas prescritas, las tasas de propano deberían
ser reguladasaumentándolas o disminuyéndolaspara producir perfiles de duración y
temperatura consistentes con las propias quemas. Más aún, los ensayos con paja producen a
menudo altas dosis de calor y pueden requerir
menor cantidad de carga de combustible para
que así puedan encuadrarse en los objetivos de
investigación.
Keywords: fire methodology, fuel, grasslands, heat dosage, prescribed burn, rangelands, simulation, time-temperature curve
Citation: Kral, K.C., R.F. Limb, T.J. Hovick, D.A. McGranahan, A.L. Field, and P.L. O’Brien.
2015. Simulating grassland prescribed fires using experimental approaches. Fire Ecology 11(3):
34–44. doi: 10.4996/fireecology.1103034
INTRODUCTION
Climate, fire, and grazing formed and
maintain grasslands in North America (Anderson 2006), but land fragmentation (Higgins
1984) and fire suppression have limited the extent and use of fire since European settlement
(Umbanhowar 1996). Recently, demands for
fire research have increased as managers and
researchers work to restore pre-settlement disturbance regimes and ecological processes
(Fuhlendorf et al. 2009). Although fire research activity has increased in most grassland
biomes, there are still many unanswered questions relating to ecological effects of fire. Fire
is an important ecological process that can be
effectively implemented for management after
the fire regime has been assessed over a wide
range of conditions and landscapes. However,
most research fails to measure fire characteristics and burning conditions, which can contribute to variable results when quantifying
fire effects (Fuhlendorf et al. 2011).
Experimental approaches may be suitable
substitutes to prescribed fires when examining
fire effects on vegetation and soils. However,
there are inherent differences when using
wildfires, prescribed fires, or other approaches
to study fire ecology (Sullivan et al. 2013).
Therefore, one approach may not be suitable
for all research questions. To increase replicates and experimental control, fire ecology
researchers often conduct fires on a smaller
scale compared to wildfires and prescribed
fires (Sullivan et al. 2013). Research plots
typically vary in size from several square meters (Redmann et al. 1993, Waterman and Vermeire 2011) to several hectares (Whisenant
and Uresk 1989, Smart et al. 2013). Researchers make small plots in the field by creating
breaks and barriers with back burns (Biondini
et al. 1989, Belsky 1992) and metal sheeting
(Sharrow and Wright 1977, White and Currie
1983, Whitford and Steinberger 2012). Most
small plots still maintain many of the same
features, such as weather interactions, as larger
prescribed fires. However, weather interactions can be eliminated in the field by using
propane burners made of stainless steel barrels
and installed jets that burn enclosed in situ
vegetation or individual plants (Britton and
Wright 1979).
In addition to the approaches presented
above, several other methods can be used to
simulate fire or heat that move studies from
the field to a laboratory setting. Wind tunnels
Page 36
are commonly used to study fire spread and
heat transfer under different fuel characteristics with controlled wind speeds and temperatures (Rothermel and Anderson 1966, Lui et
al. 2014). Wind tunnels are usually large,
free-standing structures that burn harvested
biomass, unlike field approaches, which consume living plants rooted in a substrate. Fuel
beds or burn tables can also use harvested biomass (Weise et al. 2005, Weir and Limb 2013)
or rooted plants in an open area (Limb et al.
2011). Other approaches, such as furnaces,
use indirect heat to study heat and combustion
effects on seeds (Franzese and Ghermandi
2012, Ruprecht et al. 2013), soils (Hogue and
Inglett 2012), or ash nutrients (Qian et al.
2009) in the absence of field conditions. Each
of these approaches has benefits compared to
prescribed fires, but they lose many of the ecological interactions present in field-based fires.
Our objective was to compare time-temperature profiles, maximum temperatures, heat
durations, and heat dosages of several experimental approachesburn box, burn table, and
propane prongto prescribed fires to determine how closely these approaches simulate
prescribed fires. We chose to compare prescribed fires and experimental approaches using time-temperature curves, maximum temperature, heat duration, and heat dosage because these parameters are commonly reported
in the recent literature and easy to quantify in
prescribed fires and controlled experiments.
Additionally, temperature and heat duration
are used to determine heat dosage, a good predictor of plant mortality (Vermeire and Roth
2011, Strong et al. 2013), an important aspect
of grassland fire ecology. We used approaches
with modified fuelsadditional hay or propanefrom either the tallgrass or mixed-grass
prairie to characterize prescribed fires and experimental approaches.
METHODS
Prescribed Fires
We performed two dormant-season and
two growing-season prescribed burns within
the tallgrass prairie in North Dakota, USA (46°
31’ N, 97° 06’ W) and Oklahoma, USA (36°
06’ N, 97° 23’ W). We conducted one fire for
each season and area combination (n = 4).
Plant communities were dominated by C4
grasses, forbs, and shrubs. Average fuel loads
in growing-season fires were 5545 kg ha˗1 and
5036 kg ha˗1 in dormant-season fires. We ignited prescribed fires using a ring-fire technique incorporating both back and head fires.
We distributed two HOBO® U12 Thermocouple Data Loggers (Onset, Cape Cod, Massachusetts, USA) with 24 AWG (American Wire
Gauge) K-thermocouples with insulated wire
throughout burn units to record temperatures
10 cm above the soil surface. We monitored
weather conditions during fires with a Kestrel
4000® device (Loftopia, LLC, Birmingham,
Michigan, USA) every 1800 sec (Table 1).
Experimental Approaches
We recorded temperatures during experiments using 24 AWG K-thermocouples with
insulated wire and a CR100 data logger
Table 1. Mean temperature, wind speed, and relative humidity during prescribed fires and experimental
approaches in Montana, North Dakota, and Oklahoma, USA, in 2012 through 2014.
Weather measurement Growing season Dormant season Burn table
Mean temp (°C)
Wind speed (km h˗1)
Relative humidity (%)
28
5.0
40
14
8.5
41
24
9.5
53
Burn box Propane prong
23
9.7
47
6
0.0
95
(Campbell Scientific, Logan, Utah, USA), averaging temperatures over 0.5 sec intervals.
We monitored fire weather conditions with a
Kestrel 4000 device before every burn when
applicable (Table 1).
Burn box. We conducted the burn box approach in eastern Montana, USA, on the
Charles M. Russell National Wildlife Refuge
(47° 41’ N, 107° 10’ W) during the growing
season. The mixed-grass prairie and sagebrush (Artemisia spp. L.) landscape was dominated by native C3 graminoids and shrubs. We
constructed burn boxes around in situ vegetation using four 2 m × 2 m aluminum sheets to
form a square burn perimeter. We added timothy (Phleum spp. L.) hay to adjust all fuel
loads to 3000 kg ha˗1, typical of the plant community, and ignited fires using a propane torch.
We recorded time-temperature profiles using
three thermocouples 10 cm above the soil surface during each replicate (n = 5).
Burn table. We grew several native and
non-native grass species in 15 cm plastic pots
with a substrate mixture of sandy loam soil
and commercial sand to conduct the burn table
and propane prong experiments. The burn table approach used a metal burn table, elevated
off the ground, measuring 1.2 m × 2.4 m with
five 16.5 cm diameter circles (Limb et al.
2011). Our burn table did not have sides like
other fuel beds (Weise et al. 2005, Limb et al.
2011). We placed five pots below the table so
that plant crowns were level with the tabletop.
We spread timothy hay at a rate of 3000 kg
ha˗1 on the table and around plant bases with a
10 cm fuel-free border to prevent fuel from
falling off and ignited head fires with a drip
touch. We recorded time-temperature profiles
using three thermocouples 10 cm above the
soil surface during each replicate (n = 5).
Propane prong. The third approach utilized a propane prong constructed from 19 mm
diameter black pipe, a pressure regulator, a
venturi tube for mixing oxygen and fuel, and a
Page 37
standard propane tank. We formed the prong
in a U shape with two 30 cm arms with holes
every 6 mm (Figure 1). We burned five pots
with paired plants for 60 sec between the
prongs with a thermocouple 10 cm above the
soil surface. We conducted all of our burns inside a closed structure with ventilation.
Figure 1. Images for each of the three experimental approaches conducted in Montana and North
Dakota, USA, from 2012 to 2014. The top panel
shows the burn box with one missing sheet to show
the placement of the added biomass with in situ
vegetation. The middle panel shows the burn table
using plants rooted in pots and added timothy hay.
The bottom panel shows the propane prong that
was used inside an enclosed structure to burn
plants rooted in pots.
Fire Measurements and Statistical Analysis
We averaged temperatures over the thermocouples for each fire to create mean
time-temperature curves for each prescribed
fire and experimental approach (Figure 2). We
identified the mean maximum temperature as
the peak from each time-temperature profile.
We determined heat duration as the time (sec)
above 60 °C and heat dosage in degree-seconds (°C · sec) as the sum of the products of
time and temperatures above 60 °C (Russell et
Figure 2. Mean time-temperature profiles for
growing-season and dormant-season prescribed
fires and burn table, burn box, and propane prong
approaches in Montana, North Dakota, and Oklahoma, USA, from 2012 to 2014. The white line
represents the mean and shaded areas (black or
gray) represent 95 % confidence interval for each
curve.
Page 38
al. 2013, Strong et al. 2013). We compared
differences in these three dependent variables
across independent fires (two prescribed fires
and three experimental approaches) using a
univariate generalized linear model with a oneway analysis of variance (Anova) and post-hoc
Tukey tests (α = 0.05) in SPSS version 22.0
(IBM, Armonk, New York, USA).
RESULTS
Prescribed, burn table, and burn box fires
had similarly shaped time-temperature profiles
(Figure 2). Generally, curves increased at a
high rate during warming, reached a short peak
around the maximum temperature, and gradually decreased during cooling. The propane
prong warming and cooling curves were similar to the prescribed fires and other approaches,
but the profile plateaued at a sustained elevated
temperature instead of peaking.
We found a difference in maximum temperature (P ≤ 0.001), heat duration (P ≤ 0.001),
and heat dosage (P ≤ 0.001) between prescribed fires and experimental approaches.
Dormant-season and burn box fires averaged
maximum temperatures 278 °C hotter than the
growing-season, burn table, and propane prong
fires. On average, heat durations were 72 sec
longer in burn table and burn box fires compared to the prescribed and propane prong fires.
Total heat durations were similar between the
prescribed and propane prong fires. However,
there was no difference (P > 0.05) between
prescribed and burn box fires (Figure 3).
Heat dosage also varied between fires, like
heat duration. High maximum temperatures
and longer heat durations led to higher heat
dosages in the burn box and burn table approaches. Heat dosages in the burn box were
almost two times higher than the prescribed
and propane prong fires. Although heat dosages in the burn table approach were almost
twice as much as dormant-season fires, there
was not a statistically significant difference (P
> 0.05) between dormant-season and burn ta-
Page 39
(°C · sec)
DISCUSSION
Figure 3. Mean maximum temperature, total heat
duration, and heat dosage for growing-season (GS)
and dormant-season (DS) prescribed fires and burn
box (BB), burn table (BT), and propane prong (PP)
approaches in Montana, North Dakota, and Oklahoma, USA, from 2012 to 2014. Error bars are
shown for each mean. Different letters correspond
to a difference at α = 0.05 within each measurement across fires from the post-hoc Tukey test.
ble fires. Heat dosages in the burn table approach were approximately 16 000 °C · sec
higher than the growing-season and propane
prong fires (Figure 3).
There are inherent differences between using prescribed fires and experimental approaches to study fire ecology (Sullivan et al.
2013). Experimental approaches can determine effects of temperature (Wright 1971) and
different combinations of disturbance and plant
age (Limb et al. 2011) on individual plant species survival. Generally, experimental approaches are used for finer-scale manipulations
to produce more experimental data over a wide
range of conditions to better apply fire ecology
concepts to larger landscapes. Conversely,
most field studies only use burned or nonburned as treatments (Fuhlendorf et al. 2011).
In our study, the burn table and propane prong
provided the closest simulation to prescribed
fires, but all approaches could successfully be
used to simulate fire. Slight modifications can
be made to fuel loads and propane pressure to
mimic areas of interest depending on region,
study question, and vegetation.
Generally, time-temperature profiles from
the prescribed, burn table, and burn box fires
were similar to curves determined in other
studies with prescribed fires (Engle et al. 1989,
Archibold et al. 1998, Ohrtman et al. 2015).
These time-temperature curves reached a
quick peak and cooled slowly, while the propane prong profile stabilized at hotter temperatures before decreasing. Propane burners produce curves typical of prescribed fires with a
quick peak under certain conditions (Wright
1971, Wright et al. 1976). However, temperatures measured at the soil surface in other propane burners produced similar results as our
propane prong with sustained hotter temperatures (Wright 1971). To create realistic fire
curves with the propane prong, fuel adjustments should be made during the burns. We
only burned at one rate for a certain time frame
as done in other studies (Wright 1971), but it
would be better to slightly increase fuel pressure until the target maximum temperature is
reached and then slowly decrease fuel pressure
to mimic flame fronts and smoldering material. It may also be useful to disconnect the two
sides of the prong and move them closer and
farther away from the plants to increase or decrease heat exposure.
Maximum temperatures for prescribed
fires and experimental approaches were within range of other fires throughout the mixedgrass (Archibold et al. 1998, Vermeire and
Roth 2011, Strong et al. 2013) and tallgrass
(Engle 1989, Ohrtman et al. 2015) prairie but
hotter than maximum temperatures found in
the shortgrass prairie (Augustine et al. 2014).
Maximum temperatures were hotter in dormant-season fires compared to growing-season fires. This temperature trend may be region-dependent for prescribed fires, as growing-season fires can produce hotter (Ansley et
al. 2006) or similar (Strong et al. 2013) maximum temperatures compared to dormant-season fires in other areas. Generally, dormant-season fires have drier fuels, which can
produce hotter maximum temperatures (Bragg
1982). Therefore, moisture content and the
amount of senesced material can be important
factors for explaining differences between
various fire characteristics (Brooks et al.
2004). Even though burn box and burn table
approaches used timothy hay, dormant-season
fires utilized a larger proportion of senesced
vegetation and produced hotter maximum
temperatures.
Because heat can be partially confined in
the burn box, the presence of shrubs could account for increased maximum temperature in
this approach, as shrubs have longer cooling
time-temperature curves due to smoldering
coarse, woody fuels (Archibold et al. 1998).
However, in field-based fires with predominantly smaller shrub species like snowberry
(Symphoricarpos occidentalis Hook), grassland and shrubland fire temperatures are similar (Bailey and Anderson 1980), so it is unlikely that shrubs caused the temperature increase
in the burn box approach. Although high maximum temperatures contribute to plant mortali-
Page 40
ty and can be an important characteristic to determine in fire research, heat duration and heat
dosage have been found to be better predictors
of plant responses to fire (Strong et al. 2013).
Heat durations can be highly variable, even
within the same study (Strong et al. 2013).
Heat durations we observed in our prescribed
fires and experimental approaches were similar to some fires (Vermeire and Roth 2011) but
lower than other studies (Ohrtman et al. 2015)
that measured heat duration as time above
60 °C. The variability in heat duration is most
likely caused by a combination of additional
factors including fuels and weather (Strong et
al. 2013). In the mixed-grass prairie, heat dosages ranged from around 1000 °C · sec to
26 000 °C · sec (Vermeire and Roth 2011,
Strong et al. 2013). Heat dosages in our fires
never reached the lower end calculated in the
above studies. However, dosages in the prescribed and propane prong fires fell within that
range. Although calculated slightly differently, heat dosages in the tallgrass prairie were
approximately 10 000 °C · sec above heat dosages found in this study (Engle et al. 1989).
Heat dosage is an important characteristic
in fire ecology because it can explain plant
mortality by combining temperature, heat duration, and weather conditions instead of just
one of these factors (Augustine et al. 2014).
Overall, heat dosage is considered a better predictor of plant mortality when assessing plant
responses to fire (Vermeire and Roth 2011,
Strong et al. 2013). The burn table and burn
box approaches had higher heat dosages compared to the prescribed fires, so they could
cause plant mortality similar to propane burners used in the field to reduce plant survivability (Britton and Wright 1979).
Methods of fuel manipulation for experimental approaches in our study included adding timothy hay or using propane to burn rooted plants. Adding cellulose or biomass creates
complete burns compared to patchy burns typically found on prescribed fires (Thaxton and
Platt 2006). Small-scale approaches with add-
Page 41
ed fuels burn all available material because
they lack natural fire breaks found on larger-scale prescribed fires that create non-burned
areas. Complete burning increased maximum
temperatures and smoldering, which increased
heat duration and heat dosage in the burn table
and burn box approaches. The fuel loads were
lower in these approaches compared to prescribed fires and still produced higher heat
dosages. To account for differences between
fuel types, studies using cellulose-based fuels
in experimental approaches should consider
using reduced fuel loads to create realistic heat
dosages. This may involve calibrations to understand the relationship between fuel loads
and heat dosage on burn tables and burn boxes
compared to prescribed fires.
Generally, dissimilarities between maximum temperatures, heat durations, and heat
dosages of prescribed fires can be explained
by variable fuel loads, along with plant species
composition and weather conditions (Archibold et al. 1998). In our study, fire characteristic differences between prescribed fires and
experimental approaches were explained by
manipulated fuels. Many previous studies fail
to include fire characteristics like maximum
temperature, heat duration, or heat dosage
even though these parameters can improve the
overall understanding of ecological impacts
and recognize variations between fires (Engle
et al. 1989). Currently, more research is including these parameters to improve interpretation and application of results (Vermeire and
Roth 2011, Russell et al. 2013, Augustine et
al. 2014, Ohrtman et al. 2015), but field studies are still limited by constraints like size and
replication. We suggest using experimental
approaches to increase replication and allow
for more manipulation of specific fire characteristics to determine their implications on
grassland plant and soil responses to fire.
ACKNOWLEDGEMENTS
We would like to acknowledge the staff at the North Dakota State University Agricultural Experiment Station Research Greenhouse Complex for their assistance throughout our study and all
the faculty, staff members, and graduate students who helped conduct fires and collect data. We
would also like to thank two anonymous reviewers for their helpful suggestions and comments.
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Quintero-Gradilla et al.: Carbon and Nutrient Recovery after Fire
Page 45
Research Article
SOIL CARBON AND NUTRIENT RECOVERY AFTER
HIGH-SEVERITY WILDFIRE IN MEXICO
Shatya D. Quintero-Gradilla1*, Felipe García-Oliva2, Ramón Cuevas-Guzmán3,
Enrique J. Jardel-Peláez3, and Angelina Martínez-Yrizar4
Centro Universitario de la Costa Sur, Universidad de Guadalajara,
Avenida Independencia Nacional 151, Autlán de Navarro, Jalisco, México, C.P. 48900
1
Instituto de Investigaciones en Ecosistemas y Sustentabilidad,
Universidad Nacional Autónoma de México,
Antigua Carretera a Pátzcuaro 8701, Morelia, Michoacán, México, C.P. 58190
2
Departamento de Ecología y Recursos Naturales,
Centro Universitario de la Costa Sur, Universidad de Guadalajara,
Avenida Independencia Nacional 151, Autlán de Navarro, Jalisco, México, C.P. 48900
3
Instituto de Ecología, Universidad Nacional Autónoma de México,
Boulevard Colosio sin número, Hermosillo, Sonora, México, C.P. 83000
4
*Corresponding author: +52-317-382 5010, ext. 7158; e-mail: [email protected]
ABSTRACT
RESUMEN
Fire severity can increase above historical levels due to factors such as human-derived fire suppression and climate change. Studies about the effects
of high-severity fires on soil carbon
and nutrients in pine forest at tropical
latitudes are still rare. We analyzed the
changes in carbon (C), nitrogen (N),
and phosphorus (P) contents in the organic layer and the top mineral soil
layer in a post-fire chronosequence of
Pinus douglasiana Martínez-dominated forest stands in central-western
Mexico 8 yr, 28 yr, and 60 yr following
a high-severity fire. We found that fire
significantly affected the total C, N,
and P contents in the organic layer, explained mainly by mass losses. We did
not detect differences in C, N, and P
contents (Mg ha-1) in the mineral soil,
but C and N concentrations (mg g-1) in-
La severidad de los incendios podría aumentar
por encima de los valores históricos como resultado de acciones humanas como la supresión de incendios y el cambio climático. Estudios sobre el efecto de los incendios de alta severidad sobre el carbono y los nutrientes almacenados en suelos de bosques de pino en latitudes tropicales, son escasos. En este estu
dio
analizamos los cambios en los contenidos de
carbono (C), nitrógeno (N) y fósforo (P) almacenados en la capa orgánica del suelo y en la
capa superficial del suelo mineral, en una crono-secuencia post-incendio en bosques dominados por Pinus douglasiana Martínez, en el
centro-occidente de México, 8 años, 28 años, y
60 años después de incendios severos. Los incendios afectaron significativamente los contenidos de C, N y P en la capa orgánica, explicado principalmente por la pérdida de masa. No
hubo diferencias en los contenidos de C, N y P
(Mg ha-1) en el suelo mineral, mientras que la
creased with stand age. This can be
explained by the high levels of tree
mortality that occur during high-severity fires, depleting litter inputs to the
soil. We observed a fast recovery of C,
N, and P, perhaps resulting from the
high capacity of Pinus douglasiana to
regenerate following high-severity
fires. This can be associated with high
metabolic rates of forests in tropical
latitudes, which, given their climate
and soil conditions, favor higher rates
of vegetation growth and, thus, faster
rates of organic C inputs and soil organic C accumulation.
Page 46
concentración de C y N (mg g-1) se incrementó
con la edad del rodal. Esto puede ser explicado por la alta mortalidad de árboles provocada
por los incendios severos, lo que disminuyó la
entrada de materia orgánica al suelo. Se registró una rápida recuperación de los contenidos
de C, N y P probablemente como resultado de
la alta capacidad de Pinus douglasiana para regenerar después de incendios severos. Lo anterior puede estar asociado con las altas tasas
metabólicas de los bosques en latitudes tropicales, dadas las condiciones climáticas y de
suelo que favorecen mayores tasas de crecimiento de la vegetación y de incorporación y
acumulación de C en el suelo.
Keywords: biomass, duff, fire effects, litter, Mexico, nitrogen, phosphorus, pine forests, Sierra de
Manantlán
Citation: Quintero-Gradilla, S.D., F. García-Oliva, R. Cuevas-Guzmán, E.J. Jardel-Peláez, and
A. Martínez-Yrizar. Soil carbon and nutrient recovery after high-severity wildfire in Mexico.
Fire Ecology 11(3): 45–61. doi: 10.4996/fireecology.1103045
INTRODUCTION
Fire affects forests globally (Agee 1993,
Fulé and Covington 1997, Alauzis et al. 2004,
Russell-Smith and Yates 2007, Scott et al.
2014), changing various components of these
ecosystems, such as carbon and nutrient dynamics (Johnson and Curtis 2001, Carter and
Foster 2004). Fire severity can increase with
variations in fuels, topography, and weather
conditions (Agee 1993), and if the time between fires increases due to factors such as human-derived fire suppression, fuels accumulate and high-severity fire can occur (Fulé and
Covington 1997), promoting forest stand replacement processes (Smithwick et al. 2005).
During the nineteenth and most of the
twentieth centuries, fire suppression was a
generalized management approach in fireprone forests worldwide, including Mexico, to
protect timber resources and rural communities (Covington and Moore 1992, Agee 1993,
Jardel et al. 2009, Rodríguez-Trejo et al.
2011). Cessation of frequent low-severity fires
can increase severity in the next fire event, due
to higher biomass accumulation (Agee 1993);
in addition to this, global climate change scenarios predict higher temperatures and more
droughts in some regions of the world, which
may lead to high-severity fire proliferation
(Wotton and Flannigan 1993, Westerling et al.
2006). Thus, studies that generate quantitative
data that help understand the effects of
high-severity fires on soil carbon and nutrients
are critical to improve and validate global carbon cycle models and to provide information
that supports fire management (Badia et al.
2014).
The organic layer and soil surface represent important sources of nutrients in forest
ecosystems (Switzer et al. 1979, Boerner
1982). High-severity fires cause high tree
mortality and reach high temperatures (675 °C)
in the organic layer, consuming most or all of
it (Overby et al. 2003). These fires can transfer considerable heat to the mineral soil, re-
ducing soil carbon (C) and nitrogen (N) stocks
(Johnson and Curtis 2001), as these elements
volatilize at 200 °C (Neary et al. 1999, Certini
2005). Thus, high-severity fires can negatively impact carbon and nutrient stocks (Neary et
al. 1999), decreasing forest productivity (Covington and Moore 1992, Georgiadis 2011,
Bento-Goncalves et al. 2012, Powers et al.
2013).
Studies report losses higher than 75 % of C
and N stocks in the organic layer following
high-severity fires (Baird et al. 1999, Neary et
al. 1999, Murphy et al. 2006, Neary and Overby 2006). Since phosphorus (P) requires temperatures above 770 °C to volatilize (Neary et
al. 2005), only 50 % to 70 % is lost during
combustion in high-severity fires, and the residual P returns to the soil as ash (DeBano and
Conrad 1978, Murphy et al. 2006). However,
residual phosphorus is vulnerable to hydric or
wind erosion, and can be lost rapidly following a fire (Giardina et al. 2000).
Mineral soil layers appear to be less affected by high-severity fire, as only the first 5 cm
of depth generally register a small amount of
the heat generated during the fire, rarely exceeding 200 °C (Neary et al. 1999, Certini
2005). However, losses of up to 50 % of total
C and N content in the top mineral soil layer
have been documented as a direct result of the
combustion of soil organic matter (SOM) in
different forest soils (Kutiel and Naveh 1987,
Fernández et al. 1997, Baird et al. 1999, Murphy et al. 2006, Martín et al. 2012). Furthermore, subsequent losses of C and N may occur
due to increased SOM mineralization and surface soil erosion (Neary et al. 2005). In contrast, total P in soil may increase by 100 % to
300 % (Kutiel and Naveh 1987, Giardina et al.
2000, Martín et al. 2012), mostly due to ash
inputs, organic P mineralization, and solubility
of the occluded P as a result of chemical
changes to the soil solution (Kutiel and Naveh
1987, García-Oliva and Jaramillo 2011).
Fire causes temporary N and P mineralization in soils (Wan et al. 2001, Certini 2005),
Page 47
increasing the availability of these nutrients
for plants and microorganisms (Grove et al.
1986, Kutiel and Naveh 1987, Serrasolsas and
Khanna 1995, Murphy et al. 2006). While this
contributes to vegetation regeneration, decreased availability in the years following the
fire is due to plant assimilation, microbial immobilization, and losses from leaching and
erosion (Kutiel and Naveh 1987, Murphy et al.
2006, García-Oliva and Jaramillo 2011, Chen
and Shrestha 2012, Guénon et al. 2013).
Post-fire recovery of soil C, N, and P relies
on organic matter accumulation, which is tied
to forest productivity. Litter accumulates relatively quickly during stand development,
reaching a maximum, and remaining relatively
constant when inputs equal outputs through
litter decomposition (Switzer et al. 1979, Seedre et al. 2011). Smith and Heath (2002) reported that, for several forests in the USA,
equilibrium is reached 20 to 80 years following a fire event; recovery time depends on bioclimatic conditions, plant productivity, plant
community composition, and post-fire successional dynamics (Switzer et al. 1979, Certini
2005, Smithwick et al. 2005, Gurmesa et
al.2013).
Recovery of C, N, and P in surface mineral
soil layers depends on the quantity of organic
matter produced by the vegetation established
after the fire. Nitrogen recovery can occur at
faster rates, even exceeding pre-fire levels, after the establishment of N-fixing plants (Carter
and Foster 2004, Johnson et al. 2004). In contrast, soil P recovery depends mainly on ion
leaching and occlusion processes within the
mineral soil (Kutiel and Naveh 1987); soil texture is a key factor in this process, as clays
have a higher capacity to form stable compounds with organic molecules and metals
within the soil matrix (Six et al. 2002).
Nonetheless, soil C, N, and P recovery
rates following high-severity fires are variable,
depending on amounts of organic matter input,
which in turn depends on temperature, moisture, soil type, plant species, and nutrient
availability (Post and Kwon 2000). For instance, Baird et al. (1999) reported recoveries
of 70 % of soil organic carbon (SOC), and
32 % of soil N within the first year following a
high-severity fire in a Pinus ponderosa P. Lawson and P. ponderosa C. Lawson forest.
Alauzis et al. (2004) observed that, four years
after a fire in Nothofagus pumilio (Poepp. and
Endl.) Krasser forests, concentrations of C and
N were 52 % and 22 % lower than in soils
without fires. In contrast, LeDuc and Rothstein (2007) observed that in Pinus banksiana
Lamb. forests, SOC recovered to pre-fire levels six years after the fire, while N concentrations were 36 % lower than those in control
stands.
While the immediate effects of high-severity fires on soil properties have been widely
documented, their mid- and long-term effects
must be further investigated (Wan et al. 2001,
Duran et al. 2010). Thus, the objective of this
study was to analyze changes of C, N, and P
contents in the soil organic layer and the top
mineral layer in a chronosequence of Pinus
douglasiana Martinez-dominated forests, 8 yr
and 28 yr following high-severity fires, and in
mature stands without fire for more than 60
years, in central-western Mexico. The hypotheses of this work were as follows: a) C, N, and
P in the organic layer and top mineral soil will
increase with stand age after a high-severity
fire, until they reach values similar to those of
mature stands not affected by high-severity
fires; and b) the recovery of these elements in
the organic layer will be at a faster rate than in
the mineral soil layer.
METHODS
Study Area
The study was conducted in Las Joyas Research Station (LJRS), located in the central-western portion of the Sierra de Manantlán
Biosphere Reserve (SMBR; 19° 14´ 49˝ N to
19° 37´ 30˝ N, and 104° 14´ 49˝ W to 104° 18´
16˝ W). This reserve is a federally protected
Page 48
area located in the state of Jalisco, in central-western Mexico. The station covers 1245
ha, with altitudes that range between 1500 m
and 2242 m. Climatic conditions in the study
area correspond to the lower montane subtropical moist forest of the Holdridge Life Zone
System (Jardel et al. 2004b). Climate in LJRS
is classified as sub-humid temperate with summer rains (June to September). Mean annual
rainfall is 1826 ±94 mm, and the potential
evapotranspiration ratio (potential evapotranspiration:annual precipitation) ranges between
0.5 and 0.6. Mean annual temperature is 15
±2 °C, ranging from 12.8 °C in January, the
coldest month, to 20 °C in May, the warmest
month (Jardel et al. 2004b).
The geological substrate of LJRS consists
of Tertiary extrusive igneous rocks like basaltic porphyries, basalts, andesitic basalts, and
volcanic tuffs. A typical soil catena in the area
is a gradient from Inceptisols in mountaintops
and upper slopes to Alfisols in lower slopes,
and Ultisols in hollows and stream banks
(Martínez et al. 1993, Jardel et al. 2004b).
Vegetation cover in the area is a mosaic of
pine-oak forests associated with convex landforms (mountaintops and upper slopes), mixed
hardwood forests (bosque mesófilo de montaña or cloud forest) in concave landforms
(ravines and hollows), mixed pine-hardwood
forests in intermediate conditions, and secondary scrub in abandoned agriculture fields
(Jardel et al. 2004a). Pinus douglasiana is
the dominant species in pine-oak and
pine-hardwood forests.
The area has a long history of human influence through slash and burn agriculture in
small plots, extensive livestock grazing, and
logging; these activities ended in 1987, following the designation of LJRS as part of one
of the core zones of SMBR (Jardel 1991).
Since biodiversity conservation and restoration are central goals of LJRS, fire suppression is used to encourage the recovery of forest cover through natural regeneration of
mixed hardwood forests and mixed pine-hardwood forests.
Most fires in the SMBR occur between
April and early June, at the end of the dry season. Fires in the area are relatively small
(mean: 189 ha, mode: 50 ha); the most common ignition factors are human-related activities, but fires originated by lightning have also
been recorded (Balcázar 2011). Frequent,
low-severity, surface fires characterize the historical fire regime in the pine-oak forest, with
mean fire intervals ranging from 3 to12 years
(Jardel 1991, Llamas-Casillas 2013, Cerano-Paredes et al. 2015), similar to intervals recorded in northwestern Mexico and the southwestern USA (Stephens and Fulé 2005).
Fire suppression in LJRS has led to decreased fire frequencies and accumulation of
fuels. Organic matter and woody debris loads
for stands without fires in 20 years have been
estimated, respectively, at 37 Mg ha-1 to 58 Mg
ha-1, and 31 Mg ha-1 to 38 Mg ha-1 (Alvarado-Celestino et al. 2008). These conditions
can lead to intense surface fires with high tree
mortality (basal area loss >70 %) and consumption of most or all of the organic soil layer, caused by smoldering combustion and
torching, opening 1 ha to 40 ha patches (as recorded following fires in 1983 and 2003)
where succession is restarted (Jardel 1991,
Llamas-Casillas 2013). For this study, we selected sites that burned at high-severity in the
1983 and 2003 fires.
Sampling Design
To evaluate the effects of stand-replacing
fires on total C, N, and P contained in the soil
organic layer and the top mineral layer, we
compared stands in a post-fire chronosequence, 8 yr and 28 yr following a fire, with
mature stands without high-severity fire for
more than 60 years. These three conditions
are referred to hereafter as 8 yr old, 28 yr old,
and 60 yr old stands, and coincide with three
stand development stages: stand initiation,
stem exclusion, and understory reinitiation, respectively. The 60 yr old stands had not had
Page 49
low-severity fires since the protected area was
established in 1987 and represent late-successional seres in the absence of fire.
Our space-for-time substitution design relies on the assumption that all variation among
sites is due to differences in time since disturbance (Yanai et al. 2003); we use a nested
sampling design to help account for violations
to these assumptions. If sites differed in organic matter and soil C, N, and P due to inherent landscape variability (rather than time after
disturbance), we expected to capture that variability in our sample units (Allen et al. 2010).
We selected three independent stands for each
age group (8 yr old, 28 yr old, and 60 yr old);
within each we established three 500 m2 circular plots (12.62 m radius) with a minimum 50
m separation between their centers. Stands
were ~0.5 km to 2.4 km apart to minimize the
impact of spatial autocorrelation, and we did
not sample stands of the same age class in
close proximity to one another.
To minimize the effect of site conditions,
stands were located in the same altitudinal
range (1950 m to 2150 m), within the same
soil type unit (Alfisols), in the mid-portion of
north-facing slopes dominated by Pinus douglasiana (>70 % basal area) (Table 1). While
mean tree density did not differ among stands,
tree basal area in the 8 yr old stands was four
times lower than in the 28 yr old and 60 yr old
stands, an expected effect of high-severity
fires, which strongly alters the forest structure
(MacKenzie et al. 2004).
Organic Layer and Mineral Soil Sampling
We collected organic and top mineral soil
samples in the dry season, between January
and June 2011, the highest accumulation period for the organic layer in the region (Covaleda 2008). We divided the organic layer into
two sub-layers: litter layer (LL) and duff layer
(DL). The LL is formed of plant residues (excluding woody debris) that keep their structure
and have an identifiable origin, and the DL in-
Page 50
Table 1. Tree density and basal area in 8 yr old, 28 yr old, and 60 yr old stands of Pinus douglasiana following high-severity fires in central-western Mexico. Values represent averages for each stand, with standard error in parentheses; a and b show significant differences between means (P < 0.05) with the post-hoc
Tukey test.
Structural variables
Density (trees ha ≥ 2.5 dbh)
-1
8 yr
1802 (923)
a
Stand age
28 yr
60 yr
820 (114)
1924 (256)a
a
Total basal area (m2 ha-1)
10 (0.73)a
45 (3.2)b
50 (3.2)b
Relative basal area ( %) (p: pines, b: broadleaf)
91 p, 9 b
95 p, 5 b
80 p, 20 b
cludes fragmented and partially decomposed
organic matter that has lost its original structure. To measure the mass of the LL and DL
sub-layers, we set up four radial lines (12.62
m) originating at plot center, following each
cardinal direction (N, E, S, W), and established four sampling points every 3 m (16
points plot-1) where we measured the depth of
LL and DL. To obtain LL and DL bulk density
samples, we selected three random points in
each plot and used a 30 cm × 30 cm metal
frame that was pushed into the organic layer to
collect LL and DL samples (Ottmar and Andreu 2007 modified by Morfín et al. 2012).
We used a soil core (5 cm diameter) to obtain mineral soil samples from the top 10 cm
of this layer, in eight points systematically selected from the 16 points used for LL and DL
sampling. Four of the eight samples were used
to determine soil bulk density.
Sample Processing and Analyses
Organic layer samples were oven dried at
60 °C and weighed. Half-gram subsamples
were ashed in a muffle furnace at 500 °C for 4
h to determine inorganic content; data are reported on an ash-free, 60 °C dry weight basis.
The three subsamples were ground and
passed through a 40 sieve, and then pooled
into one composite sample per plot for chemical analyses.
Mineral soil samples were oven dried at
50 °C. Bulk density samples were weighed
and the bulk density of the <2 mm fraction
was calculated for each plot; the eight subsamples were pooled into one composite sample
per plot, which was then passed through a 100
sieve for all chemical analyses. Soil pH was
determined with a potentiometer in water with
a 1:2 (wt:vol) soil-solution ratio and in a Cl2Ca
0.01 M solution in a 1:5 (wt:vol) soil-solution
ratio. The sand and silt-clay fractions were
separated under running water with a 320
sieve.
The LL, DL, and mineral soil samples
were analyzed for total concentration of C, N,
and P (TC, TN, and TP). The TC was determined by combustion and coulometric detection using an automated CO2 analyzer (UIC
model CM5012, Joliet, Illinois, USA). The
TN was determined after acid digestion by the
macro-Kjendahl method and determined colorimetrically with a 3Bran-Luebbe auto analyzer (SPX, Norderstedt, Germany). The TP was
obtained after acid digestion and reduction
with ascorbic acid and determined colorimetrically in the same autoanalyzer used for TN.
Mass (Mg ha-1) was calculated as the product of depth (cm) and bulk density (Mg ha-1
cm-1). The TC, TN, and TP contents (Mg ha-1)
of the organic and mineral soil layers were calculated as the product of C, N, and P concentration, bulk density, and thickness of the organic and mineral soil layers. Stands were
considered treatment replicates.
Page 51
We tested the normality and homoscedasticity assumptions of all variables with the
Kolmogorov-Smirnov and Levene tests, respectively. Data were log-transformed to meet
assumptions when required (Zar 1999), although they are reported in their original scale
of measurement. We used a nested analysis of
variance to compare the effects of high-severity fires on depth; bulk density; mass; TC, TN,
and TP concentrations and ratios; and TC, TN,
and TP pools in the organic and mineral soil
layers in the three stand ages (8, 28 and 60).
Stand age (8, 28, and 60) was the main fixed
effect, and stands were the nested random effects within each stand age. We compared
means with a Tukey test (P = 0.05); Pearson’s
correlation coefficient was used to estimate
correlations between tree basal area and litter
mass, and between tree basal area and soil C
concentration. We used simple linear regression to relate soil C concentration to stand age.
All statistical analyses were carried out with
SPSS version 15 (SPSS Inc., IBM, Armonk,
New York, USA).
RESULTS
Litter and Duff Mass
The organic layer depth (LL + DL) differed significantly among ages (F2.6 = 55.85, P
< 0.001), with 5.5 cm in the 8 yr old stands,
16.4 cm in the 28 yr old stands, and 14.5 cm in
the 60 yr old stands. The LL was deeper in the
28 yr old stands, while the DL did not show
any differences between the 28 yr old and 60
yr old stands (Table 2). Bulk density of LL
and DL was lower in the 8 yr old than in the
28 yr old and 60 yr old stands (Table 2).
Total mass (LL + DL) in the 8 yr old stands
represented 17 % of that in the 28 yr old and
60 yr old stands (Figure 1). The LL mass was
Table 2. Physical and chemical properties of the litter and duff layers and the top mineral soil in 8 yr old,
28 yr old, and 60 yr old stands of Pinus douglasiana after high-severity fires in central-western Mexico.
Values are average (n = 3) with the standard error in parentheses. Letters indicate significant differences
between means (P < 0.05) with the post-hoc Tukey test.
Property
Depth (cm)
Litter layer (LL)
Stand age (yr)
8
28
60
3.6a
(0.5)
8.2b
(0.5)
7.1c
(0.6)
0.01a
0.03b
0.02b
Bulk density (g cm-3) (0.001) (0.004) (0.001)
Duff layer (DL)
Stand age (yr)
8
28
60
1.9a
(0.4)
8.2 b
(0.5)
7.4b
(0.4)
0.03a
0.05b
0.06b
(0.005) (0.002) (0.007)
Top mineral soil layer
(0 cm to 10 cm)
Stand age (yr)
8
28
60
10
10
10
0.79
0.61
0.67
(0.007) (0.041) (0.077)
C (mg g-1)
471.5
(7.1)
478.7
(2.8)
472.4
(3.5)
444.1
(11.8)
459.5
(1.0)
454.4
(9.3)
57.4 a
(4.3)
72.1 b
(2.6)
85 c
(3.5)
N (mg g-1)
5.5
(0.8)
5.7
(0.2)
6.1
(0.3)
7.5
(0.2)
9.1
(0.8)
8.7
(0.3)
3.7 a
(0.1)
4.0 ab
(0.1)
4.8 b
(0.3)
P (mg g-1)
0.3
(0.05)
0.4
(0.02)
0.4
(0.05)
0.3
(0.08)
0.5
(0.01)
0.5
(0.03)
0.8
(0.03)
1.0
(0.17)
1.4
(0.20)
C:N
91
(11)
84
(4)
79
(49)
61
(1)
52
(5)
53
(3)
16
(2)
19
(1)
18
(1)
N:P
17
(2)
14
(1)
17
(2)
28
(5)
20
(2)
18
(1)
6
(2)
4
(1)
4
(1)
C:P
1553
(280)
1183
(46)
1304
(188)
1738
(323)
1030
(25)
958
(72)
118
(60)
74
(8)
65
(13)
Page 52
The TC, TN, and TP contents in both LL
and DL were different among ages (Table 3).
In the LL, the 8 yr old and 28 yr old stands had
the lowest and the highest TC, TN, and TP
contents, respectively (Figure 2). In the DL,
the 8 yr old stands had lower TC, TN, and TP
contents, but these did not change in the 28 yr
old and 60 yr old stands (Figure 2).
Figure 1. Total organic layer mass (LL + DL), litter layer mass (LL), and duff layer mass (DL)
(mean ±SE) in 8 yr old, 28 yr old, and 60 yr old
stands of Pinus douglasiana after high-severity
fires in central-western Mexico.
4.2 Mg ha in the 8 yr old stands, 18.3 Mg ha
in the 28 yr old stands, and 12.3 Mg ha-1 in the
60 yr old stands (Figure 1). The DL was 6.2
Mg ha-1 in the 8 yr old stands, representing
15 % of that in the 28 yr old and 60 yr old
stands (40.5 Mg ha-1 and 42.5 Mg ha-1, respectively; Figure 1). The masses of LL, DL, and
total organic layer (LL + DF) were positively
related to the basal area of the trees (R2 = 0.35,
P ≤ 0.001; R2 = 0.64, P ≤ 0.001; R2 = 0.64, P ≤
0.001, respectively).
-1
Table 3. Nested analysis of variance (F and P)
with stand nested within stand age for total C, N,
and P (Mg ha-1) in the organic layer and the top
mineral soil in 8 yr old, 28 yr old and 60 yr old
stands of Pinus douglasiana after high-severity
fires in central-western Mexico. Stand age is the
fixed effects factor; stand is the nested stand effect,
within stand age, as random effects factor.
Variation source
Stand age
-1
C, N, and P Contents of the Organic Layer
The TC, TN, and TP concentrations in the
LL and DL were not significantly different
among the three stand ages (Table 2). Average
TC, TN, and TP concentrations in the LL were
474 ±2 mg g-1, 5.8 ±0.2 mg g-1, and 0.38 ±0.02
mg g-1, respectively. Average concentrations
in the DL were 452 ±5 mg g-1, 8.4 ±0.5 mg g-1,
and 0.43 ±0.05 mg g-1, respectively. The C:N,
N:P, and C:P ratios in LL were relatively constant among the three stand ages. The C:N,
N:P, and C:P ratios in DL were not significantly different among the three ages (Table 2).
Parameter
F
P
Stand nested
within stand age
F
P
Litter layer (LL)
C
6.53
0.031
9.530
≤0.001
N
7.24
0.025
10.49
≤0.001
P
8.39
0.018
15.55
≤0.001
Duff layer (DL)
C
31.3
0.001
0.962
0.477
N
42.7
≤0.001
0.477
0.816
P
24.6
0.001
0.631
0.704
Total organic layer (LL + DL)
C
34.9
≤0.001
1.240
0.334
N
38.5
≤0.001
0.762
0.609
P
30.1
0.001
0.802
0.581
Top mineral soil (0 cm to10 cm)
C
4.71
0.059
1.917
0.133
N
2.43
0.168
1.966
0.124
P
1.07
0.400
14.33
≤0.001
Top Mineral Soil Layer
The soil mass was formed of silt and clay
particles (74 % to 78 %) in the three stand ages
Page 53
Figure 2. Contents of total C, N, and P in the litter layer (LL), duff layer (DL), and total organic layer (LL
+ DL) (mean ±SE) in 8 yr old, 28 yr old, and 60 yr old stands of Pinus douglasiana after high-severity
fires in central-western Mexico. Bars with different letters show significant differences between means (P
< 0.05) with the post-hoc Tukey test.
(8, 28, and 60); soil bulk density was similar
among these (Table 2). The pH was moderately acidic (5.3 to 5.6); there were no significant
differences in pH among the three stand ages.
Soil C, N, and P Contents
Soil C concentration increased with stand
age, being higher in the 60 yr old stands (Table
2). The regression between C concentration
and stand age was significant (β = 0.5181, R2 =
0.56, P ≤ 0.001); tree basal area was positively
correlated with soil C concentration (R2 =
0.36, P ≤ 0.001).
Soil N concentration was lower in the 8 yr
old than the 60 yr old stands; while the concentration in the 28 yr old stands did not differ
from the 8 yr old and 60 yr old stands. Soil P
concentrations did not differ among the three
stand ages. The C:N, N:P, and C:P ratios were
relatively constant among the three ages (Table 2).
Soil C contents were not different among
ages (Figure 3), but we observed a trend of
Page 54
higher values in the mature stands with 56.24
Mg ha-1 (F2,6 = 4.7 P = 0.059). The N and P
contents were not significant among the three
stand ages. The nested effect of the site on soil
P content was significant (Table 3).
DISCUSSION
Organic Layer C, N, and P Contents
Figure 3. Contents of total C, N, and P in the top
mineral soil (mean ±SE) in 8 yr old, 28 yr old, and
60 yr old stands of Pinus douglasiana after
high-severity fires in central-western Mexico.
Concentrations (mg g-1) of C, N, and P in
LL and DL were similar after the severe fire in
the study sites, which suggests that the type of
litter inputs to the system did not change
across these successional stages. This was expected, as Pinus douglasiana represents 70 %
or more of tree basal area in the study sites,
and the organic layer was formed mostly of organic compounds produced by this species.
Similar results were found by MacKenzie et
al. (2004) in a chronosequence of low elevation, second growth Pinus ponderosa-Pseudotsuga menziesii (Mirb.) Franco forest in western Montana, USA, and by Switzer et al.
(1979) in a secondary succession of pine forest
in eastern Mississippi, USA.
The low C, N, and P contents in the organic layer in the 8 yr old stands suggest that the
high-severity fire eliminated most of the organic layer mass, and that its accumulation is
slower in the first years following the disturbance. Several studies have reported that organic layer combustion during high-severity
fires causes substantial losses of C, N, and P
soil contents (for instance, see Baird et al.
1999, Murphy et al. 2006, Neary and Overby
2006). While our study did not evaluate the
organic layer loss during fire events, preliminary observations indicate that high-severity
fires in LJRS have drastic effects on the organic layer mass, reducing it by 80 % to 100 %
(E.J. Jardel, Universidad de Guadalajara, Autlán de Navarro, Mexico, unpublished data).
Tree basal area in the 8 yr old stands was
four times lower than in the 28 yr old and 60
yr old standsan expected effect of high-se-
verity fires, which strongly alters the forest
structure (MacKenzie et al. 2004, Kashian et
al. 2006). In our study sites, reduction of tree
mass also decreased tree productivity, depleting organic matter inputs to the system. Additionally, forest canopy opening promotes litter
decomposition by raising organic layer temperatures (Smithwick et al. 2005, Nave et al.
2011). The positive relationship between organic layer mass and tree basal area suggests
that leaf litter production is lower in the
youngest sites (8 yr old stands), and that the
input of new organic matter to the soil is not at
an equilibrium between litterfall production
and litter decomposition, which has been confirmed in previous studies (Buschiazzo et al.
2004, Hu et al. 2013).
In our study sites, 28 years after high-severity fire, forest floor mass was similar to that
of 60 yr old stands (59 Mg ha-1 and 55 Mg ha-1,
respectively), which suggests that litterfall
production and organic layer decomposition
are at equilibrium approximately 28 years following a high-severity fire. The mass of the
organic layer determined through this study is
greater than values reported for several pine
forests of the USA (25 Mg ha-1 and 28 Mg ha-1
30 years and 50 years after high-severity fires,
respectively), but similar to those reported for
50 yr old mixed conifer and broadleaf forests
in North America (60 Mg ha-1) (Smith and
Heath 2002).
Top Mineral Soil C, N, and P Contents
While it has been reported that high-severity fires can strongly alter the properties of
mineral soils (Neary et al. 1999, Certini 2005),
our results show that, 8 years after a high-severity fire, bulk density; pH; soil P concentration; C:N, N:P, and C:P ratios; and soil C, N
and P contents were similar to those of 60 yr
old stands. This suggests that the effect of
high-severity fires is temporary and could even
decrease shortly after fire, as has been shown
by previous studies (Johnson and Curtis 2001,
Page 55
Wan et al. 2001, LeDuc and Rothstein 2007,
Nave et al. 2011, Chen and Shrestha 2012).
Soil C and N concentrations in the 8 yr old
stands were lower than in the 60 yr old stands,
which is consistent with previous studies in
temperate forests worldwide that report reduced soil C and N concentrations due to volatilization during high-severity fires (Kutiel
and Naveh 1987, Fernández et al. 1997, Baird
et al. 1999, Murphy et al. 2006, Rovira et al.
2012). However, recovery times can be different. Alauzis et al. (2004) found that, four
years after a fire in Nothofagus pumilio forests,
C and N soil concentrations were 52 % and
22 %, respectively, lower than in control sites.
Similarly, LeDuc and Rothstein (2007) found
that soil N concentration was 36 % lower six
years after a severe fire than in control stands
in Pinus banksiana-dominated forests.
We detected a positive and statistically significant relationship between tree basal area
and soil C concentration, in which the youngest sites had a lower tree basal area and soil C
concentration than the older stands (28 yr old
and 60 yr old stands), which has also been reported by other studies (Hu et al. 2013,
García-Oliva et al. 2014). These results can
be explained by the high levels of tree mortality that occur during high-severity forest fires,
depleting litter inputs to the mineral soil. Other studies have shown that soil C and N recuperation will depend on increased tree production (Brown and Lugo 1990, Richter et al.
1999).
Soil textures dominated by fine particles
increase the amount of C stored in the soil, as
clays form stable compounds with organic and
metal molecules, favoring C stabilization in
the soil (Six et al. 2002, Lützow et al. 2006).
Since soils in the study area are dominated by
fine particles, we suggest that they play a key
role in SOC accumulation, as has been reported for other pine forests in volcanic soils in
Mexico (Peña-Ramírez et al. 2009). The SOC
yearly accumulation rate (0.52 mg C g-1),
shown in the regression between SOC concen-
Page 56
tration and stand age, reaches concentrations
of 85 mg C g-1 60 years after a fire. This value
is within the range reported by other authors
for conifer forests on volcanic soils in Mexico:
56 mg g-1 to 89 mg g-1 in Pinus montezumae
Lamb. forests (Peña-Ramírez et al. 2009) and
73 mg g-1 to 89 mg g-1 in pine-oak forests in
southeastern Mexico (Mendoza-Vega et al.
2003). These results suggest that, in the study
area, SOC concentrations reach higher values
in mature Pinus douglasiana forests without
severe fires for at least 60 years.
Post-fire recovery of soil organic matter
and nutrient content begins with vegetation regeneration (Certini 2005). Pinus douglasiana
forests in LJRS have a high capacity to regenerate following high-severity fires (Jardel
1991, Llamas-Casillas 2009). Our results suggest a rapid recovery of C, N, and P, which
may be a result of the high metabolic rate (i.e.,
high primary productivity and high transformation rate of soil organic matter) of forest
ecosystems in tropical latitudes. In sub-humid
temperate climates with summer rains, the precipitation corresponds with the growing season, and higher precipitation is associated with
increased vegetation growth, organic C inputs,
and SOC accumulation.
In the context of increased frequency and
severity of wildfire resulting from human-derived fire suppression and climate change,
there is a threat of higher soil carbon and nutrient losses, which will reduce forest productivity (Covington and Moore 1992, Georgiadis
2011). Forest managers must consider these
potential threats when developing fire and forest management plans, to reduce vulnerability
or to enhance forest recovery.
ACKNOWLEDGEMENTS
This study was funded by the Consejo Estatal de Ciencia y Tecnología of the State of Jalisco
through the grant Estructura, diversidad y reservorios de carbono de bosques de cañadas en el
Pacífico Mexicano (PS-2009-664). The first author received financial support from Consejo Nacional de Ciencia y Tecnología (scholarship number 272059/222300). R. Velázquez-Durán
helped with chemical analyses at the Laboratorio de Biogeoquímica de Suelos, Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México. We
thank Dr. C. Cortés Montaño for comments on previous drafts of this manuscript.
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Lashley et al.: Fire Prescriptions for Wildlife Foods
Page 62
Research Article
VARIABILITY IN FIRE PRESCRIPTIONS TO PROMOTE WILDLIFE FOODS IN THE
LONGLEAF PINE ECOSYSTEM
Marcus A. Lashley1*, M. Colter Chitwood2, Craig A. Harper3, Christopher S. DePerno2,
and Christopher E. Moorman2
1
Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University,
Box 9690, Mississippi State, Mississippi 39762, USA
Department of Forestry and Environmental Resources,
Fisheries, Wildlife, and Conservation Biology, North Carolina State University,
110 Brooks Avenue, Raleigh, North Carolina 27607, USA
2
3
Department of Forestry, Wildlife, and Fisheries, University of Tennessee,
2431 Joe Johnson Drive, Knoxville, Tennessee 37996, USA
*Corresponding author: Tel.: +1-662-325-5795; e-mail: [email protected]
ABSTRACT
RESUMEN
Prescribed fire is commonly used to
restore and maintain the longleaf pine
(Pinus palustris Mill.) ecosystem
(LLPE). A key function of the LLPE
is the provisioning of food for wildlife. Despite the plethora of literature
evaluating the effects of fire season
and fire-return interval on plant community dynamics, little attention has
been given to the response of wildlife
foods to fire season or fire-return interval. We measured the availability
of key wildlife foods (fleshy fruit [i.e.,
seed containing a nutritious pericarp]
and understory plant biomass) in upland pine forest following dormant-season (December–February)
and growing-season (April–June) fires
in a chronosequential design. Also,
we quantified the relative contributions of the upland hardwood and bottomland hardwood forest types, which
often are intentionally suppressed in
the LLPE. In 2011 and 2012, we
measured understory leafy biomass,
Las quemas prescriptas son comúnmente usadas para restaurar y mantener el ecosistema de
pino palustre o pino de hoja larga (Pinus palustris Mill.), comúnmente llamado LLPE. Una
función clave del LLPE es el aprovisionamiento de alimento para la fauna silvestre. A pesar
de la profusa literatura que evalúa los efectos de
la estación de fuego y el intervalo en la recurrencia del fuego en la dinámica de las comunidades vegetales, muy poca atención ha sido
brindada a la respuesta de los alimentos para la
fauna a la estación de fuego o a la recurrencia
entre fuegos. Nosotros medimos la disponibilidad de alimentos clave para la fauna (aquellos
frutos carnosos [i.e., semillas que contienen un
pericarpio nutritivo] y plantas del sotobosque)
en un bosque de altura de pino después de fuegos ocurridos en períodos de latencia (diciembre–febrero) y de crecimiento activo (abril–junio) en base a un diseño crono-secuencial.
También cuantificamos las contribuciones relativas de los bosques altos y bajos de latifoliadas, que frecuentemente son intencionalmente
suprimidos en los LLPE. En 2011 y 2012, medimos la biomasa foliar del sotobosque, la bio-
biomass of forages selected by whitetailed deer (Odocoileus virginianus
Zimm.), and soft mast production
chronosequentially in relation to
years-since-fire, fire season, and vegetation type in the LLPE at Fort Bragg
Military Installation, North Carolina,
USA. Understory leafy biomass increased in upland pine and hardwood
forests as years-since-fire increased
until two years post fire. Selected forages decreased in upland pine forest
and increased in upland hardwood
forest as time-since-fire increased. In
upland pine forests burned during the
growing season, 94 % of the fruit was
detected two years after fire, 6 % one
year after fire, and 0 % the same year
as fire. In June, fruit density was
greatest in bottomland hardwood forest; in July, fruit density was greatest
in dormant-season burned upland pine
forest; in August, fruit density was
greatest in upland hardwood forest;
and in September, fruit density was
greatest in upland hardwood and bottomland hardwood forest. Overall
summer fruit density (i.e., the sum of
fruit density detected each month)
was greatest in upland hardwood forest. Understory leafy biomass and
deer-selected forages were stable in
bottomland hardwood forest because
they were not burned, thereby providing a relatively high and stable availability from year to year. Our data
demonstrate the importance of diversity in fire season and frequency, and
diversity in vegetation types to promote key wildlife foods in the LLPE.
Page 63
masa de los forrajes seleccionados por el ciervo
de cola blanca (Odocoileus virginianus Zimm.),
y la producción de frutos blandos de arbustos,
de manera crono-secuencial, en relación a los
años desde el fuego, la estación de fuego, y el
tipo de vegetación en el ecosistema LLPE ubicado en el Fort Bragg Military Installation, Carolina del Norte, EEUU. La biomasa foliar del
sotobosque se incrementó en el bosque alto y
en los bosques de latifoliadas a medida que el
tiempo del post-fuego se incrementó hasta los
dos años posteriores al fuego. Los forrajes seleccionados disminuyeron en el bosque alto de
pino y se incrementaron en el bosque alto de latifoliadas a medida que se incrementó el tiempo
después del fuego. En los bosques altos de pino
quemados durante la estación de crecimiento,
94 % de los frutos fueron detectados dos años
después el fuego, 6 % un año después del fuego,
y 0 % en el mismo año del evento de fuego. En
junio, la densidad de frutos fue mayor en los
bosques bajos de latifoliadas; en julio, la densidad de frutos fue mayor en el período latente en
el bosque de pino de altura; en agosto, la densidad de frutos fue mayor en los bosques altos de
latifoliadas; y en septiembre, la densidad de
frutos fue mayor tanto en los bosques altos
como bajos de latifoliadas. Considerando todo
el verano, la densidad de frutos (i.e., la suma de
la densidad de frutos detectada cada mes) fue
mayor en los bosques altos de latifoliadas. La
biomasa foliar del sotobosque y el forraje seleccionado por el ciervo de cola blanca fue estable
en el sotobosque del bosque bajo de latifoliadas, dado que éste no fue quemado, proveyendo
por lo tanto de una disponibilidad alta y estable
año tras año. Nuestros datos muestran la importancia de la diversidad en la estación y frecuencia de los fuegos y la diversidad en los tipos de vegetación para promover alimentos clave para la fauna en los ecosistemas LLPE.
Page 64
Keywords: biodiversity, diet selection, ecosystem-based management, fire application, fire frequency, fire season, fruit, heterogeneity, microhistological survey, white-tailed deer
Citation: Lashley, M.A., M.C. Chitwood, C.A. Harper, C.S. DePerno, and C.E. Moorman. 2015.
Variability in fire prescriptions to promote wildlife foods in the longleaf pine ecosystem. Fire
Ecology 11(3): 62–79. doi: 10.4996/fireecology.1103062
INTRODUCTION
In the US, the highly threatened longleaf
pine (Pinus palustris Mill.) ecosystem (LLPE)
is commonly targeted for ecological restoration (Landers et al. 1995, Brockway et al.
2005, Fill et al. 2012). Historically, the LLPE
was one of the most extensive ecosystems in
North America and occupied 38 million ha in
the southeastern United States (Frost 1993,
Landers et al. 1995). Currently, ~800 000 ha
remain, representing a 97 % decline across the
natural range (Frost 2006). Restoring the
LLPE may provide several ecosystem services, including improved habitat quality for
wildlife, high-quality longleaf pine timber and
pine straw, recreational opportunities, and
preservation of natural and cultural legacies
(Brockway et al. 2005).
Previous studies suggested developing prescribed fire regimes based on various types of
data for the LLPE (e.g., modeling [Beckage et
al. 2005], historical fire scars [Stambaugh et
al. 2011], plant reproductive allocations [Fill
et al. 2012]). The consensus is that high-frequency growing-season fire regimes (≤3 yr
fire-return interval in May or June; Waldrop et
al. 1992, Streng et al. 1993, Stambaugh et al.
2011, Fill et al. 2012) are keystone processes
and vital to restoring the LLPE (Aschenbach
et al. 2010). However, the LLPE represents
one of the most diverse systems in the temperate zone, and simplified management strategies guided by a few focal flora and fauna may
fail to accurately represent the complexity
within this dynamic ecosystem (Franklin 1993,
Drew et al. 1998). For example, Lashley et al.
(2014a) reported that homogeneous fire applications could simplify forest stand structure
and landscape floral composition even when
prescriptions are based on historical references. Similarly, Beckage et al. (2005) raised
concern for oversimplified inferences of reference conditions in fire-maintained ecosystems.
Because fire frequency, intensity, and seasonality may affect flora and fauna differently
(Van Lear and Harlow 2000), variable fire prescriptions are likely needed to create and
maintain a heterogeneous landscape (Fuhlendorf and Engle 2001, Bond and Archibald
2003, Fuhlendorf et al. 2006).
Previous study of the effects of fire season
and frequency on understory flora and related
forest structural characteristics in the LLPE
showed that variability in fire prescriptions
was needed to maximize biodiversity and ecosystem function with fire (Hiers et al. 2000,
Palik et al. 2002, Ryan et al. 2013). For example, Fill et al. (2012) reported reproductive responses of wiregrass (Aristida stricta Michx.)
were greatest following early growing-season
fires (May to June). Furthermore, Clewell
(1989) reported that wiregrass plants persist
for extended periods without fire. Hence,
wiregrass reproductive responses indicate adaptations to frequent growing-season fires, yet
other characteristics of wiregrass simultaneously indicate adaptations to infrequent growing-season fire. Similarly, Ostertag and Menges (1994) reported that shrub species had differing reproductive allocation strategies to
time-since-fire, and believed that plants likely
did not synchronize strategies because of variability in historical fire-return intervals. Hiers
et al. (2000) reported that fire season did not
affect pollination and reproductive allocations
of legumes in the LLPE; however, Platt et al.
(1988) reported that the season of fire was im-
portant in flowering synchrony in many forb
species. Also, legumes in the LLPE respond
similarly to fire suppression and dormant- and
growing-season fires in terms of nitrogen fixation (Hiers et al. 2003). However, fire frequency may be of particular importance to the
species composition in the understory, with
yearly and biennial fires favoring herbaceous
plants, and longer rotations allowing woody
plants to establish (Glitzenstein et al. 2003).
Despite the plethora of literature concerning the application of fire in LLPE and the effects on floral diversity, reproductive allocations, and plant community structure, we were
able to find only one study reporting on fleshy
fruit (i.e., seed containing a nutritious pericarp; e.g., berry, drupe, etc.) production
(Greenberg et al. 2012) and no studies reporting on leafy biomass or forage production for
white-tailed deer (Odocoileus virginianus
Zimm.; hereafter deer), the native keystone
herbivore (Cote et al. 2004) in the LLPE. Further, Greenberg et al. (2012) did not relate
fleshy fruit production to fire. Moreover, the
relative contributions of vegetation types to
the abundance of these foods in the LLPE are
unknown. Fleshy fruit and leafy biomass are
important to many fauna inhabiting the LLPE.
While wildlife are essential components of
ecosystem function and commonly considered
in management plans, little information about
the interactions of these food sources with fire
season and frequency exists. Therefore, we
measured overall understory leafy biomass,
biomass of selected deer forages, and fleshy
fruit production in relation to years-since-fire,
fire season, and vegetation type. We hypothesized that the wildlife foods that we measured
would respond differently to different fire seasons and frequencies, thus illustrating the importance of variability in fire regimes for promoting wildlife foods throughout the year in
the LLPE.
Page 65
METHODS
Study Area
We sampled leafy biomass and fruit density at Fort Bragg Military Installation (Fort
Bragg) in Cumberland, Harnett, Hoke, and
Moore counties, North Carolina, USA (35o 6′
N, 79o 12′ W). The 73 469 ha property was located in the Sandhills physiographic region in
the northernmost remnants of the LLPE. The
long-term (~50 years) average yearly rainfall
was 120 cm, average yearly snowfall was 7.5
cm, and there were ~175 frost-free days per
year (Sorrie et al. 2006). According to the
State Climate Office of North Carolina, there
was a moderate drought in 2011 followed by a
normal rainfall year in 2012. Primary vegetation types included longleaf pine, upland hardwoods, bottomland hardwoods, and managed
openings (see Sorrie et al. 2006 for detailed
floristic accounts). Fort Bragg Military Installation was considered an important contributor
to the floristic diversity of the LLPE with more
than 1200 plant species, 61 of which were species of conservation concern and 3 of which
were federally endangered (Sorrie et al. 2006).
The LLPE is inhabited by numerous wildlife species that rely on vegetative plant parts
or fleshy fruits for part or all of their diet. For
example, deer, eastern cottontail (Sylvilagus
floridanus Allen), Virginia opossum (Didelphis virginiana Kerr), gray fox (Urocyon cinereoargenteus Schreber), and raccoon (Procyon
lotor L.) occur in the LLPE and consume plant
parts or fleshy fruits. Similarly, numerous
birds, including small passerines (e.g., American robin [Turdus migratorius L.], cedar waxwing [Bombycilla cedrorum Vieillot], hermit
thrush [Catharus guttatus Pallas], gray catbird
[Dumetella carolinensis L.]) and larger gallinaceous birds (e.g., wild turkey [Meleagris
gallopavo L.], northern bobwhite [Colinus virginianus L.]), use fruits or plant parts in their
diet. Also, at least two species of conservation
concern (gopher tortoise [Gopherus poly-
phemus Daudin] and Florida black bear [Ursus
americanus floridanus Pallas]) rely heavily on
the these food items in the LLPE.
Since 1989, the United States Department
of Defense has managed burn units on a 3 yr
growing-season (April to June) fire-return interval, targeting the prevailing longleaf pine
vegetation type (Cantrell et al. 1995). However, upland hardwood and bottomland hardwood stands are interspersed within some burn
units and are subjected to the same fire regime,
although fire behavior may differ based on
moisture and fuels. The fire regime was initiated to maintain structural requirements for
the federally endangered red-cockaded woodpecker (Picoides borealis Vieillot) and to maximize biodiversity of the LLPE (Cantrell et al.
1995). Because of limitations in resources,
manpower, and adequate fire weather, some
units not burned as scheduled were burned the
following dormant season (January to February). However, these units were moved immediately back into the 3 yr growing-season
fire-return interval. Further, some units were
exclusively burned on a dormant-season fire
schedule to buffer sensitive areas such as
buildings and other man-made structures on
the base.
Stand Selection
We characterized three major vegetation
types using a geographic information system
(GIS) overlay map of land cover and firebreaks provided by the US Department of Defense: upland hardwood, bottomland hardwood, and upland pine. We characterized upland hardwood as any upland forest stand
dominated by hardwood species (primarily
turkey oak, Quercus laevis Walt.), bottomland
hardwood as hardwood-dominated forest (primarily blackgum, Nyssa sylvatica biflora
Marsh.) associated with streams, and upland
pine as upland longleaf pine-dominated forest.
We selected 5 or more representative units in
each vegetation type across three separate
Page 66
drainages at Fort Bragg (averaging 7 km apart)
to compare the relative contribution of each
vegetation type to forage and fruit density. We
selected units with similar soil types (Candor
Sands complex) and basal area in upland pine
and upland hardwood to reduce any biases that
could be associated with soil productivity or
overstory coverage. After controlling for soil
type and basal area (45 m2 ha-1 to 60 m2 ha-1),
we selected upland pine units based on the fire
season (i.e., dormant- or growing-season fires;
hereafter, dormant upland pine and growing
upland pine, respectively) and years-since-fire
(0 yr, 1 yr, 2 yr, 3 yr). We selected upland
hardwood stands by years-since-fire (0 yr, 1 yr,
2 yr, 3 yr). Units were selected for dormant
upland pine or growing upland pine only if
they had been burned in the respective season
for three or more consecutive fire rotations
(average 3.2 consecutive rotations for dormant
upland pine and 5 rotations for growing upland pine). Dormant-season fires occurred
from December to February and growing-season fires occurred April to June.
Understory Leafy Biomass
We had two objectives when measuring
understory leafy biomass: 1) compare biomass
among vegetation types within years-sincefire, and 2) compare biomass among yearssince-fire within each vegetation type. Therefore, in January to March 2011 (i.e., in the dormant season), we randomly placed 40 1.2 m ×
1.2 m × 1.2 m woven-wire−panel exclusion
cages in upland hardwood, dormant upland
pine, and growing upland pine burned 0 yr to 3
yr prior (i.e., 10 cages in each year-since-fire
category for each vegetation type). Also, we
placed 40 cages in bottomland hardwood units.
Cages, designed to exclude herbivores, were
used only to control for biases in understory
biomass estimates related to herbivory. For
example, if caged plots had the same biomass
as random uncaged plots, then herbivory was
not affecting understory biomass and all plots
could be pooled for assessing understory biomass response to fire application. Cages were
simply used as a precaution because deer may
affect plant communities negatively at high
densities (Cote et al. 2004). We did not expect
deer at Fort Bragg to negatively affect the
plant community because deer density decreased by as much as 60 % from what was apparently sustained in the 1980s (Lashley et al.
2015a), which likely resulted from high predation rates from coyotes (Canis latrans Say) on
adult and neonatal deer (Chitwood et al. 2014,
2015a, 2015b). From 1 to 14 August 2011, we
collected all leafy biomass (i.e., standing crop)
from woody species and entire herbaceous
plants (excluding fibrous stems) within cages.
Additionally, we sampled an uncaged plot at a
randomly generated distance (10 m to 100 m)
and bearing (0 degrees to 360 degrees) from
the original location of the cage. The uncaged
plot was kept in the same vegetation type with
the same years-since-fire; we replaced the cages in a new area and repeated the sampling
protocol in 2012 (i.e., 160 caged and 160 uncaged plots per year; Lashley et al. 2011). We
separated samples by species, bagged them in
small paper bags, and dried them in an air-flow
dryer at 50 °C (Lashley et al. 2014b). We
weighed dried samples to the nearest 0.01
gram and calculated understory leafy biomass
per hectare by summing plant weights from a
plot and extrapolating to kilograms per hectare. The caged and uncaged plots served as
the experimental unit for subsequent statistical
analyses.
To measure the availability of selected deer
forages, we first determined what flora were
selected by deer on site. To do so, we calculated a selection index (Chesson 1978, 1983),
which provided criteria for determining the
strength of deer selection of a plant and an index cutoff value that represents the point at
which deer are selecting the forage more than
available. The Chesson index requires a measure of plant use by the targeted herbivore.
Therefore, we collected deer fecal samples
Page 67
from May to August in 2011 and 2012 across
Fort Bragg to perform a microhistological survey, which gives the proportion of each plant
species in the diet based on the remaining undigested plant cells excreted in the feces (Vavra
and Holechek 1980). Because one of the years
was a drought, we calculated diet selection in
each year separately to avoid biases in diet selection associated with drought (Lashley and
Harper 2012). We collected at least five fecal
samples per week consisting of at least 10 pellets per sample from 15 May to August in 2011
and 2012, and formed weekly composite samples (mean = 12.2 fecal samples per composite
sample for 30 composite samples). To ensure
that samples were independent of one another,
no two samples were collected within 1 km
(greater than the average summer home range
of adult female deer on the area; Lashley et al.
2015b) of each other during the respective
week. The density of deer at Fort Bragg was
very low (3 km-1 to 5 km-1, Lashley et al.
2015a), making collection of fecal samples difficult; therefore, we did not stratify fecal samples by vegetation type or years-since-fire.
However, because deer are a relatively mobile
species, the fecal sample may consist of dietary
choices from the past several days. As each of
the areas were readily available to deer (Lashley et al. 2015b), we did not suspect any bias in
dietary choice associated with the area in
which the fecal sample was found. Because
plant species may be digested differently by
deer, we used acid detergent fiber (ADF),
which is a measure of indigestible fibers in
plants, to standardize use based on the proportion of the plant that remains distinguishable in
the microhistological survey (Vavra and
Holechek 1980). Simultaneously, we collected
samples of plants (72 genera) representing the
plant-part selectivity of deer, and dried and
submitted them to a National Forage Testing
Association certified laboratory to determine
the acid detergent fiber of each plant during
each month that fecal samples were collected
(Lashley et al. 2014b). After receiving diet
compositions for each composite fecal sample,
we weighted each plant-use percentage by the
respective ADF to correct for differential digestibility of plants (Leslie et al. 1983). After
correcting for differential digestibility, we calculated deer diet selection from the corrected
use and availability (leafy biomass of each
plant available on site). After determining
which plants were selected, we calculated forage availability of selected forages from the
collected leafy biomass estimates.
Fruit Density
We placed 30 25-meter transects in dormant upland pine, growing upland pine, upland hardwood, and bottomland hardwood
units in each of four months (June to September) of 2011 and 2012 (n = 480 yr-1). After
sampling of each transect in each month, the
transect was moved in the next month to another area within the same vegetation type and
years-since-fire when applicable. In growing
upland pine, 10 of the transects each month
were placed in areas 0 yr, 1 yr, and 2 yr since
fire. We used the fruit-count method described
in Lashley et al. (2014c) to measure understory fruit density under 1.2 m height (i.e., understory fruits) and within 0.5 m of each side
along a 25 m transect. Fruits were tallied by
species, month, vegetation type, and year, with
the transect being the experimental unit in subsequent analyses. We extrapolated each transect fruit count into a per-hectare equivalent.
We compared monthly fruit density over two
growing seasons among vegetation types and
time-since-fire (in growing upland pine only).
Initially, we used analysis of variance to
compare understory leafy biomass estimates
between caged and uncaged plots to determine
whether herbivory affected biomass. We used
generalized linear regression, fitting the data
with a Poisson distribution (to account for left
Page 68
truncation), to compare understory leafy biomass (total and deer-selected forages) among
vegetation types with years-since-fire held
constant. We used the same analysis to test for
the effects of years-since-fire within a vegetation type. We assigned the year of collection
and the drainage of the unit sampled as random effects to account for any site-specific or
year-specific effects. Also, we used generalized linear regression to compare understory
fruit density among vegetation types across
months with year as a random effect and
among the three categories of years-since-fire
in growing upland pine with month and year
as random effects. We fit the fruit data with a
zero inflated Poisson distribution to account
for left truncation and zero inflation. We used
JMP 10.0 (SAS Corp., Cary, North Carolina,
USA) for all analyses.
RESULTS
We detected 66 genera of native plants
during the study, 33 of which were selected by
deer and 6 of which produced fruits detected
in the understory (Table 1). Ten genera accounted for the majority of the biomass (i.e.,
~80 %), with Aristida (~34 %) and Quercus
(~20 %) accounting for more than 50 % of the
biomass detected (Table 1). Understory leafy
biomass was not affected by herbivory (P =
0.99), so we combined caged and uncaged
samples for subsequent analyses.
Leafy Biomass
Understory leafy biomass differed among
the vegetation types, with biomass greatest in
bottomland hardwood. Also, biomass was
greater in upland pine than upland hardwood
when holding years-since-fire constant (Table
2). Understory leafy biomass was greater 2 yr
and 3 yr post fire than soon after fire (Table 2,
Figure 1). Deer-selected forages were most
available in bottomland hardwoods. Also, selected biomass was greater in upland hard-
Page 69
Table 1. Genera detected at Fort Bragg Military Installation, North Carolina, USA, from 2011 to 2012.
Genus
Acer L.
Achillea L.
Alnus L.
Ambrosia L.
Andropogon L. a
Aristida L. a,b
Artemisia L.
Arundinaria Michx a
Asclepias L.
Aster L.
Baptisia Vent.
Bidens L.
Carex L.
Carya Nutt.
Centrosema Benth.
Chamaecrista L.
Clethra L. a
Clitoria Baill.
Cnidoscolus Pohl
Coreopsis L.
Cornus L.
Crataegus L.
Cyrilla L.
Desmodium Desv.
Dichanthelium Gould
Dioscorea L.
Diospyros L.
Eupatorium Spreng.
Euphorbia Wheeler
Froelichia Moench
Galactia P. Br.
Gaylussacia Kunth a,c
Gelsemium L.
Selected forages
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Genus
Geranium L.
Helianthus L.
Hypericum L.
Ilex L. a,c
Iris L.
Itea L.
Lespedeza Michx.
Liquidambar L.
Lyonia Nutt.
Magnolia L. a
Morella Lour.
Nyssa L.
Parthenocissus Planch.
Phytolacca L.
Pinus L. a
Pityopsis Nutt.
Potentilla L.
Prunus L.
Quercus L. a,b
Rhus L.
Robinia L.
Rubus L. c
Sassafras Presl.
Silphium L.
Smilax L. c
Solidago L.
Stillingia L.
Symplocos Jacq.
Tephrosia Pers. a
Toxicodendron Mill.
Vaccinium L. c
Viola L.
Vitis L. c
Selected forages
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Genera collectively comprising >80 % of the detected understory biomass.
Genera collectively comprising >50 % of the detected understory biomass.
c
Primary genera detected producing fruit in the understory.
a
b
wood than in dormant-season and growing-season burned upland pine (Table 3, Figure 2). Deer-selected forages increased with
years-since-fire in upland hardwood and decreased with years-since-fire in upland pine
burned during the growing season (Figure 2).
Fruit Density
The sum of fruit densities detected across
the months was two to three times greater in
upland hardwood than in other vegetation
types over the course of the growing season
(Table 4, Figure 3). Fruit density was similar
among vegetation types in June, greatest in
dormant season burned upland pine in July,
greatest in upland hardwood in August, and
greatest in upland and bottomland hardwood
vegetation types in September (Table 4, Figure
3). Moreover, 94 % of the fruit detected in
growing-season burned upland pine occurred
in the last year of the rotation, whereas 6 % oc-
Page 70
Table 2. Parameter estimates of generalized linear regression for understory leafy biomass (kg ha-1) in
major forest types and as related to years-since-fire in growing season burned longleaf pine forests at Fort
Bragg Military Installation, North Carolina, USA, in June to September, 2011 to 2012.
Term
Biomass
Intercept
Bottomland hardwood
840
Dormant upland pine
623
Growing upland pine
562
a
401
Upland hardwood
Same yr as fire
357
1 yr post fire
443
2 yr post fire
636
462
3 yr post firea
Dormant upland pine*same yr as fire
396
Dormant upland pine*1 yr post fire
733
698
566
Growing upland pine*same year as fire
553
Growing upland pine*1 yr post fire
550
722
484
322
Upland hardwood*same year as firea
Upland hardwood*1 yr post firea
345
486
Upland hardwood *2 yr post firea
432
a
Chi square
580 622.56
64.05
116.68
8.79
P value
<0.0001
<0.0001
<0.0001
0.003
Estimate
4.33
1.27
2.71
1.51
SE
0.01
0.16
0.25
0.51
–2.21
–1.52
1.31
0.36
0.43
0.40
37.61
12.59
10.70
<0.0001
0.0004
0.001
3.15
3.77
3.98
3.47
3.66
4.10
3.30
0.65
0.19
0.20
0.26
0.39
0.32
0.45
0.37
0.26
266.21
351.56
243.11
79.61
131.83
83.12
81.61
6.29
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
<0.0001
0.01
Reference group for comparisons.
curred the year after fire, and no fruits were
detected in the same year as fire.
DISCUSSION
Variation in years-since-fire yields heterogeneity in wildlife food availability across the
landscape. For example, we detected no fruits
in the same growing season as fire, very few
the following growing season, and many in the
last year of the three-year prescribed burning
rotation. Therefore, shortening the fire-return
interval to every one or two years across the
landscape may eliminate understory fruit production, which would negatively affect wildlife populations that consume fruits (Woinarski and Legge 2013) or preclude the use of the
areas by mobile species (Buler et al. 2007).
Alternatively, shorter fire-return intervals
yielded more deer-selected forages, although
deer may be negatively affected by the lack of
cover soon after fire (Lashley et al. 2015b).
Additionally, short fire-return intervals maintain grass- and herbaceous-dominated understories by suppressing woody encroachment
(White et al. 1990, Glitzenstein et al. 2003).
Hence, fire-return interval can be adjusted to
encourage the understory structure and composition desired by the landowner (White et al.
1990, Palik et al. 2002, Glitzenstein et al.
2003, Lashley et al. 2014a). On federally
owned properties mandated to take an ecosystem-based management approach (e.g., Fort
Bragg), we suggest that fire frequencies should
be variable. For example, one- to two-year
fire-return intervals could be used in some
units to encourage herbaceous plants, whereas
≥3 yr fire-return intervals could be used in oth-
Page 71
Figure 1. Influence of years-since-fire on understory leafy biomass (kg ha-1; SE) available in the upland
longleaf pine vegetation type following dormant- and growing-season fires and in the upland hardwood
vegetation type following growing-season fires at Fort Bragg Military Installation, North Carolina, USA in
August 2011 and 2012. In each year, 80 plots (40 caged and 40 uncaged) were sampled in each vegetation
type with 20 sampled in each years-since-fire category.
er units to encourage fruit production and increased understory leafy biomass (Ostertag
and Menges 1994).
Similarly, application of fire within only a
single season (e.g., growing season) will fail to
promote the maximum floral diversity and
fleshy fruit production on the landscape (Hiers
et al. 2000, Palik et al. 2002, Ryan et al. 2013).
Fire timing plays a key role in flowering synchrony and duration and differentially affects
leguminous forbs and other flowering plants
with divergent flowering phenologies (Platt et
al. 1988, Howe 1994, Hiers et al. 2000). In
our study, fruit density after growing- and dormant-season fires followed different trends
month to month because of differences in
fruiting phenology of the flora responding to
each season of fire. Furthermore, growing-season fires promoted a grass-dominated
understory (wiregrass in particular), whereas
dormant-season fires promoted other herbaceous and woody flora. Therefore, varying fire
season across an area is necessary to encourage heterogeneity in understory structure and
to provide fruits in every month of the growing season across the landscape (Lashley et al.
2014a).
Although oaks are important for wildlife in
the LLPE (Perkins et al. 2008), aggressive removal of oaks has become a primary manage-
Page 72
Table 3. Parameter estimates of generalized linear regression for selected deer forage (kg ha-1) in major
forest types and as related to years-since-fire in growing season burned longleaf pine forests at Fort Bragg
Military Installation, North Carolina, USA, from June to September, 2011 to 2012.
Term
Biomass
Intercept
Bottomland hardwood
84
Dormant upland pine
23
Growing upland pine
28
44
Upland hardwooda
Same year as fire
22
1 yr post fire
17
2 yr post fire
28
47
3 yr post firea
Dormant upland pine*same year as fire
16
16
33
26
Growing upland pine*same yr as fire
48
25
32
9
2
Upland hardwood*same year as firea
10
17
83
a
Estimate
1.11
11.55
–20.53
−27.61
SE
0.04
0.49
0.78
2.77
Chi square
807.49
559.06
689.25
99.43
P-value
<0.001
<0.001
<0.001
<0.001
−34.69
−19.16
−16.21
2.77
2.00
1.44
157.28
91.61
126.10
<0.001
<0.001
<0.001
1.62
1.15
1.14
1.21E−07
2.29
2.52
1.96
1.47
140.91
67.43
221.64
3.54E+15
198.37
97.71
109.25
2.46
<0.001
<0.001
<0.001
<0.001
<0.001
<0.001
0.1171
<0.001
19.17
9.41
17.00
−7.17
32.23
24.90
20.52
−2.30
ment strategy in the LLPE, with the primary
goal to improve habitat for the Endangered
Species Act-listed red-cockaded woodpecker
(Cantrell et al. 1995, Hiers et al. 2014). Other
studies (i.e., Perkins et al. 2008, Hiers et al.
2014, Lashley et al. 2014a) have outlined the
direct importance of oaks for food and cover
in the LLPE, but our data indicate that hardwoods have an additional indirect benefit
through the promotion of understory fruit and
selected deer forages. In upland hardwood
communities, the sparse distribution of pyrophytic fuels (i.e., wiregrass and longleaf pine
needles) may result in a more heterogeneous
fire mosaic than typically occurs following
prescribed fires in upland pine vegetation
types (Kane 2008, Ellair and Platt 2013). The
meandering fires in upland hardwood vegetation types likely protect some stems of fruiting
understory plants from top-kill, sustaining fruit
production even in the same year of fire. As a
result, upland hardwood vegetation types provided two to three times more fruit than any
other vegetation type during the summer
months. Therefore, upland hardwoods provide
many benefits to wildlife in the LLPE beyond
hard mast production; therefore, removal efforts should be minimized when wildlife habitat is of concern (Perkins et al. 2008, Hiers et
al. 2014, Lashley et al. 2014a).
Like wildlife foods, cover should be considered when managing plant communities
with prescribed fire. Prescribed fire greatly influences understory structure as it relates to
wildlife cover (McCord et al. 2014), which inevitably influences the overall quality of an
area as habitat for a given species. In fact,
cover may be the more important resource in
habitat selection as indicated in two concurrent
studies at Fort Bragg that demonstrated that
Page 73
Figure 2. Influence of years-since-fire on understory leafy biomass (kg ha-1; SE) of plants selected by
white-tailed deer in the upland longleaf pine vegetation type following dormant- and growing-season fires
and in the upland hardwood vegetation type following growing-season fires at Fort Bragg Military Installation, North Carolina, USA, in August 2011 and 2012. In each year, 80 plots (40 caged and 40 uncaged)
were sampled in each vegetation type with 20 sampled in each year-since-fire category.
deer increasingly selected burned areas as
years-since-fire increased (Lashley et al.
2015b) and wild turkeys selected burned areas
following dormant-season fires (Kilburg et al.
2015). Kilburg et al. (2015) and Lashley et al.
(2015b) suggested that cover was the primary
resource (as opposed to food) driving the selection of areas, despite the increased energy
requirements of reproduction during the respective study periods. Our results for understory biomass following fire support this previous work because the biomass likely serves
as a proxy for the availability of cover. Thus,
a matrix of shorter and longer years-since-fire
may be important to ensure adequate availability of food and cover simultaneously.
We suggest that a variety of strategies can
be used to promote fire-influenced heterogeneity in fire-maintained systems. Heterogeneity
can be maintained at the landscape level by
varying fire season, frequency, and intensity
among burn units (Fuhlendorf and Engle 2001,
Fuhlendorf et al. 2006). Within a burn unit,
temporal heterogeneity can be encouraged by
varying the time between fires, the season of
subsequent fires, and the firing techniques and
firing conditions used for each prescribed burn
when possible (Cheney et al. 1993). Addition-
Page 74
Table 4. Parameter estimates of generalized linear regression for summer fruit density (fruits ha-1) in major
forest types and as related to years-since-fire in longleaf pine stands burned during the growing season at
Fort Bragg Military Installation, North Carolina, USA in June to September, 2011 to 2012.
Term
Mean
Intercept
Bottomland hardwood
Dormant upland pine
Growing upland pine
Upland hardwooda
June
July
August
Septembera
Bottomland hardwood*June
Bottomland hardwood*July
Bottomland hardwood*august
Dormant upland pine*June
Dormant upland pine*July
Dormant upland pine*August
Growing upland pine*June
Growing upland pine*July
Growing upland pine*August
Upland hardwood*June
Upland hardwood*July
Upland hardwood*Augusta
Same yr as fire
1 yr post fire
2 yr post firea
2324
3584
2312
5440
548
3988
2572
6548
947
1240
631
448
6712
1080
503
2833
567
307
4813
8027
0
220
3367
a
0.09
0.61
0.74
0.56
Wald
Chi square
258.48
89.43
2.49
87.74
Prob >
Chi square
<0.0001
<0.0001
0.1144
<0.0001
−12.00
−0.46
−2.06
2.06
0.71
0.64
34.05
0.42
10.33
<0.0001
0.5146
0.0013
−0.27
−6.57
−9.94
2.85
1.17
−4.15
0.68
−4.53
−9.07
1.34
0.71
0.93
1.91
0.54
0.78
1.51
0.58
0.83
0.04
85.94
113.89
2.23
4.70
28.50
0.20
61.00
117.97
0.8405
<0.0001
<0.0001
0.1351
0.0302
<0.0001
0.6525
<0.0001
<0.0001
−43.02
−15.68
2.59
2.75
275.58
32.51
<0.0001
<0.0001
Estimate
SE
1.41
−5.79
−5.17
−5.20
ally, in the LLPE, some upland hardwood
should be allowed to persist because of the inherent heterogeneity of post-fire understory
conditions and continuous availability of
fleshy fruit and hard mast that may otherwise
be lost (Hiers et al. 2014, Lashley et al.
2014a). Furthermore, fires allowed to burn
into drainages generally will be suppressed by
high moisture levels; at Fort Bragg, these less
frequently burned drainages contained unique
plant assemblages and abundant fruits early
and late in the growing season. We recommend that managers randomly assign a fire
prescription (i.e., stochastic variability in firing techniques, season, return frequency, fire
intensity, and weather conditions) to each burn
block to maximize structural and floral diversity. In fact, Robbins and Meyers (1992) developed a matrix that managers in the LLPE
could use to select random fire seasons and
frequencies for each burn unit, which they said
was supported by historical accounts of fire
conditions in the LLPE ecosystem (Frost
1993). For example, it is believed that ~70 %
of fires occurred during the growing season
based on the historical distribution of lightning-ignited fires (Fill et al. 2012) and that
fire-return intervals in upland pine forests
ranged from biannual to every 12 years (Stambaugh et al. 2011). Randomly assigning treat-
Page 75
Figure 3. Mean fruit produced (fruits ha-1; SE) during each summer month (symbols) and cumulative fruit
produced (fruits ha-1; bars) in the bottomland hardwood vegetation type, following dormant- and growing-season fires in the upland pine vegetation type, and following growing-season fires in the upland hardwood vegetation type at Fort Bragg Military Installation, North Carolina, USA, in August 2011 and 2012.
In each month of each year, 30 transects were sampled in each vegetation type.
ments with parameters guided by literature and
ongoing research will more likely restore and
maintain the heterogeneous forest structure
and floral and faunal composition of the LLPE
and other fire-maintained forest ecosystems
(Greenberg 2001, Bond and Archibald 2003,
Lashley et al. 2014a).
ACKNOWLEDGEMENTS
We thank the United States Department of Defense and Fort Bragg Military Installation for
financial contributions to this research. We thank A. Schultz, J. Jones, and the Fort Bragg Wildlife Branch for technical and logistical support. Special thanks to J. Thompson for statistical consultation. Also, we thank A. Prince, M. Elfelt, E. Kilburg, B. Sherrill, and M. Broadway for assistance in data collection and entry.
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Jones and Russell: Fire-Return Intervals in the Coast Redwood Forest
Page 80
Research Article
APPROXIMATION OF FIRE-RETURN INTERVALS WITH POINT SAMPLES IN THE
SOUTHERN RANGE OF THE COAST REDWOOD FOREST, CALIFORNIA, USA
Gregory A. Jones1 and Will Russell2*
1
2
*
National Park Service, Golden Gate National Recreation Area,
201 Fort Mason, San Francisco, California 94123, USA
Department of Environmental Studies, San Jose State University,
One Washington Square, San Jose, California 95192, USA
Corresponding author: Tel.: +1-415-505-5800; e-mail: [email protected]
ABSTRACT
RESUMEN
A legacy of past fires is evident in the
form of blackened basal hollows found
throughout the southern range of the
coast redwood (Sequoia sempervirens
[D. Don] Endl.) forest. A deeper look
reveals cambial scars dating back centuries, telling a story of low- to moderate-intensity fires that burned periodically across California’s Central
Coast bioregion. While attempts have
been made to reconstruct the fire history of this forest type, estimates of
the fire-return interval vary widely,
and the relationship of the fire-return
interval to varying cultural influences
is not fully understood. We analyzed
373 fire scars from 70 cross-sections
removed from stumps, downed logs,
and live trees in the coastal Santa Cruz
Mountains of California, USA, in order to estimate fire-return intervals
(FRI) for individual trees, mean FRI
across samples, and seasonality of historical fires. The mean FRI, averaged
across point samples, was 60.6 yr with
a median of 40.1 yr. Fire scars were
most prevalent in the dormant and
latewood portions of annual growth
rings. A sub-sample of 19 cross-sections, for which we were able to deter-
El legado de fuegos pasados es evidente en forma de huecos ennegrecidos en la base de troncos encontrados en los bosques de sequoia roja
(Sequoia sempervirens [D. Don] Endl.) de la
región costera sur. Una mirada más profunda
revela cicatrices en el cambium que datan de
centurias pasadas, contándonos una historia de
fuegos de baja a moderada intensidad que quemaron periódicamente a través de la Bioregión
de la Costa Central de California. Mientras que
varios intentos han sido realizados para reconstruir la historia del fuego en este tipo de bosque, estimaciones del intervalo de retorno varían ampliamente, y la relación entre el intervalo de retorno del fuego con influencias culturales variables no está completamente entendida.
Nosotros analizamos 373 cicatrices de un total
de 70 cortes transversales obtenidas de tocones,
troncos caídos, y árboles vivos en la costa de
las montañas de Santa Cruz en California,
EEUU, para estimar los intervalos de retorno
del fuego (FRI por sus siglas en inglés) para árboles individuales, el FRI promedio entre
muestras, y la estacionalidad de fuegos históricos. El FRI medio, promediado de muestras
puntuales, fue de 60,6 años con una mediana de
40,1 años. Las cicatrices de fuego fueron más
prevalentes en las porciones latentes y de leño
tardío de los anillos anuales de crecimiento.
Una sub-muestra de 19 secciones transversales,
mine approximate fire years, exhibited a high degree of variation between
samples with individual tree FRIs
ranging from 10.4 yr to 128 yr. The
mean FRI of 43.3 yr was marginally
higher for the pre-settlement period
(1352 to 1849) compared to 30.7 yr for
the settlement period (1850 to 1924)
and 32.3 yr for the recent period (1925
to 2013). While our results suggest a
longer estimate of fire-return intervals
than previously documented for this
forest type, high variation within and
between samples clouded distinctions
and illustrates a culturally constructed
fire regime characterized by temporal
and spatial heterogeneity.
Page 81
para las cuales nosotros pudimos determinar
años aproximados de fuegos, exhibió un alto
grado de variación entre muestras, con FRI de
árboles individuales en un rango desde 10,4
hasta 128 años. La media del FRI de 43,3 años
fue marginalmente más alta para el período de
pre-colonización (1352 a 1849) comparado con
30,7 años para el período de colonización
(1850 a 1924) y 32,3 años para el período reciente (1925 a 2013). Mientras que nuestros
resultados sugieren un intervalo de retorno del
fuego más largo que el previamente documentado para este tipo de bosque, una variación
alta dentro y entre las muestras enmascararon
las distinciones e ilustraron un régimen de fuegos construido culturalmente y caracterizado
por una heterogeneidad espacial y temporal.
Keywords: anthropogenic, fire-return interval, historical variation, Sequoia sempervirens
Citation: Jones, G., and W. Russell. 2015. Approximation of fire-return intervals with point
samples in the southern range of the coast redwood forest, California, USA. Fire Ecology 11(3):
80–94. doi: 10.4996/fireecology.1103080
INTRODUCTION
Recent wildfires in California’s Central
Coast bioregion have revived interest in the
fire ecology of coast redwood (Sequoia sempervirens [D. Don] Endl.). The combination
of fire- and rot-resistant properties and resiliency following disturbance (Ramage et al.
2010, Lazzeri-Aerts and Russell 2014) allows
for the accumulation of fire scars in the blackened basal cavities that can persist for centuries (Jacobs et al. 1985, Stephens and Fry
2005). Although there is ample evidence of
fire, estimates of the fire-return interval (FRI)
vary significantly across the coast redwood
range, and in the southern forests in particular
(Davis and Borchert 2006, Lorimer et al.
2009). Relatively short mean FRIs (6.2 yr to
23.0 yr) were found by Finney and Martin
(1992) on individual stumps, and mean FRIs
ranged from 12.4 yr to 16.3 yr in a study by
Stephens and Fry (2005). However, both of
these studies focused on areas where Sequoia
sempervirens tends to grow in isolated groves
and are not necessarily representative of southern coast redwood forest as a whole, as fire
frequencies found in these two studies are
likely influenced by the fire regimes of adjacent grassland or chaparral communities (Stephens and Fry 2005). Brown et al. (1999) also
found relatively short composite mean FRIs
(7.7 yr to 13.0 yr) where coast redwood mixed
with Douglas-fir (Pseudotsuga menziesii [Mirbel] Franco var. menziesii) in Point Reyes National Seashore, while a longer mean FRI of
21.7 yr to 27.1 yr was reported for Muir
Woods National Monument in southwestern
Marin County, where redwood is more contiguous across the landscape (Jacobs et al. 1985).
Greenlee (1983) estimated a composite mean
FRI of 45.4 yr in a more representative coastal
redwood stand in Big Basin Redwoods State
Park, but the estimate was based on scars from
only two stumps.
Page 82
Lightning-ignited fires are rare in coastal
California due to a relatively low frequency of
thunderstorms, as well as moist fuel conditions
during the rainy season (Keeley 2005, Stephens and Fry 2005, Brown 2007, van Wagtendonk and Cayan 2008). As a result, most
fires in the region have resulted from a variety
of anthropogenic origins. To address the issue
of human-induced burning, McBride (1983)
proposed that fire history studies should include a classification of fire regimes based on
land use. The redwood region, in general, supported high human population levels during
the late Holocene (Sawyer et al. 2000), and
Native Americans regularly used fire to manipulate coastal landscapes for a variety of
purposes (Keeley 2002, Stewart 2002, Lightfoot and Parrish 2009). Considering that
pre-colonial population densities on the central
California coast were among the highest in
North America (Milliken et al. 2009), it is
likely that Native American burning practices
altered the natural fire regime of the central
coast (Keeley 2002).
The cultural use of fire during the Spanish
and Mexican periods (1792 to 1848 AD) transitioned from indigenous management practices to fires resulting from logging and burning
to improve livestock forage. Spanish loggers
did not use fire intentionally, but accidental
fires occurred on occasion. An early record of
fire during the Spanish period (circa 1799) describes guards of enslaved “Indian axemen”
who were injured by a fire in the woods
(Brown 1966). There is also evidence that the
Spanish stockmen engaged in intentional burning to extend areas of suitable forage and it is
reasonable to assume that some of these intentionally set fires spread into heavier timber
(Gordon 1996). Interestingly, the Spanish did
engage in fire suppression activities to some
degree as they routinely used military companies from the Presidio and Native American
labor from the missions to suppress the fires
(Brown 1966).
Logging and farming practices may have
resulted in shorter fire-return intervals with the
arrival of large numbers of Anglo-American
homesteaders following the gold rush, which
began in 1848 to the east in the Sierra Nevada.
Homesteaders increased available farming and
grazing acreage by using fire. Loggers set
fires both to ease travel and log yarding, and to
reduce the considerable quantities of slash that
was generated during felling and limbing operations (Adams 1969). General apathy towards the practice of both indiscriminate and
accidental burning eventually waned. Even
before California officially achieved statehood, concerns over destructive fires in the
redwoods were being voiced. Initially, the
California state government avoided any
state-sponsored fire control efforts, since it
perceived fire prevention to be a personal responsibility. In the early part of the twentieth
century, however, a series of subsequent acts
institutionalized the system of fire suppression
under the recently established (circa 1885)
California Department of Forestry (Clar 1959).
A series of fire lookout stations were built
around the state to aid suppression efforts, the
first being erected in the Santa Cruz Mountains on Mount Bielawski in 1922, in close vicinity to our study site (Clar 1959).
Stuart (1987) distinguished land use history for the northern part of the redwood range
into the following periods: pre-settlement (pre1875), settlement (1875 to 1897), and post-settlement (1898 to 1940). California’s central
coast experienced a similar pattern of historical burning regimes originating from a variety
of cultural land use practices. Greenlee and
Langenheim (1990) classified five different
fire regimes for the Santa Cruz Mountains: ancient (up to 11 000 years before the present),
aboriginal (11 000 years before the present to
1792 A.D.), Spanish and Mexican (1792 to
1848), Anglo (1848 to 1929), and recent (1929
to the present). For this study, we used three
cultural periods: pre-settlement (<1849),
which included both the Native American and
Spanish periods; settlement (1849 to 1921),
which included the early Anglo-American settlement and logging period; and recent (1922
Page 83
to 2013), the Anglo-American-dominated period with systematic fire suppression methods in
place.
Our goals in conducting this study were to
add to existing knowledge regarding coast redwood fire history in the southern part of the
range by collecting and analyzing a broad
range of samples from the Santa Cruz Mountains coastal biome. Fire scar analysis was
used to estimate FRI for individual trees (point
samples), approximate seasonality of past
fires, and to estimate fire-return interval between three historical periods.
METHODS
Ring counts were used to approximately
date fire scar samples extracted from live redwood trees, snags, downed logs, and stumps in
the coastal Santa Cruz Mountains, California,
USA. Fire scar records from individual trees
were divided into two data types: 1) floating
fire scar sequencesa decipherable temporal
record without known beginning or end points
(Kelly et al. 1994, Robichaud and Laroque
2008), based on fire interval data gleaned from
ring counts; and 2) approximate chronologiesderived from cross-sections extracted
from live trees and other samples with a
known date of harvest. For the purpose of our
analysis, results were grouped into comprehensive data (including both floating sequences and approximate chronologies) that were
used to estimate the grand mean and median
FRI, and approximate chronology data that
were used to estimate FRI for three historical
periods.
Study Area
We collected samples in the Santa Cruz
Mountains north of Davenport, California, approximately 26 km northwest of Santa Cruz
and 100 km south of San Francisco (Figure 1).
Elevations within the study area range from
sea level at the coast to 800 m, with moderate
to steep slopes ranging from 30 % to 60 %. All
cross-sections were taken within the Central
Coast Hydrologic Basin, as defined by the California Department of Water Resources (2003).
The climate of the area is characterized as
Mediterranean with cool wet winters and dry
summers. Mean precipitation is approximately 107 cm, falling mostly in the winter and
spring in the form of rain with occasional
snow on the higher peaks and ridges. Temperatures are generally mild, ranging from
6.5 °C to 23 °C. Fog tends to moderate the
summer drought (Dawson 1998, Johnstone
and Dawson 2010), and is considered a significant determinant in the distribution and inland
extent of coast redwood (Cooper 1917).
Forest types in the area include stands
dominated by Sequoia sempervirens and
mixed stands with common associates such as
Douglas-fir (Pseudotsuga menziesii), tanoak
(Notholithocarpus densiflorus [Hook. & Arn.]
Manos), coast live oak (Quercus agrifolia
Nee.), Pacific madrone (Arbutus menziesii
Pursh), knobcone pine (Pinus attenuata Lemmon), California nutmeg (Torreya californica
Torrey), and California bay (Umbellularia californica [Hooker & Arnott] Nuttall).
Data were collected on lands owned and
managed by Big Basin Redwoods State Park,
Big Creek Lumber, the Sempervirens Fund,
Skylark Ranch, Swanton Pacific Ranch, and
San Vicente Redwoods (a 3453 ha parcel that
was recently acquired by a consortium of San
Francisco Bay area land conservation organizations). Both Swanton Pacific Ranch and Big
Creek Lumber employ selective harvesting
and uneven-aged forest management practices
on their respective land holdings (Swanton Pacific Ranch 2011). Swanton Pacific Ranch has
conducted small prescribed burns for research
purposes, but all unplanned ignitions in the
area are aggressively suppressed. Big Basin
State Park, adjacent to the study areas, has
conducted modest prescribed fires periodically
since 1978 (Biswell 1989).
Page 84
Figure 1. Fire history study area and sample locations in the Santa Cruz Mountains, California, USA. Inset illustrates the study area location in the context of the entire range of coast redwood (depicted in
green).
Data Collection Procedures
We collected 70 cross-sections that were
deemed suitable for analysis, 11 from living
trees and remainder from stumps, logs, and
snags. A cross-section was considered a viable
sample if it exhibited at least two scars, providing a minimum of one fire interval to be included in the analysis. Fire scar specimens
were identified and sampled on an opportunistic basis in order to obtain an adequate sample
size (Brown and Baxter 2003, Stephens and
Fry 2005). We extracted cross-sections (approximately 5 cm to 8 cm thick) using a chainsaw (Arno and Sneck 1977, McBride 1983).
Less than 10 % of the cross-sectional area of
the boles of snags and live trees were removed,
thus minimizing the potential for mechanical
failure (Heyerdahl and McKay 2008). Both
young and old specimens were selected in order to maximize the length and completeness
of the temporal record (Farris et al. 2010).
Wood exhibiting minimal decay and multiple
externally visible fire scars were initially prioritized for sampling (Speer 2010). Sampling
was extended to trees without visible scars as
careful examination of cross-sections often revealed scars that were completely healed over
and thus were not visible on exterior surfaces
of the wood (Stephens et al. 2004). When
possible, cross-sections were extracted from
basal flutes or buttresses near the ground surface to provide the most complete inventory of
scars (Brown and Swetnam 1994, Norman
2007, Norman et al. 2009).
Page 85
We prepared and analyzed fire-scarred
specimens using dendrochronology techniques
(Stokes and Smiley 1968, Arno and Sneck
1977, Orvis and Grissino-Mayer 2002). Samples were air dried and sanded with progressively finer sandpaper until the cellular structure within each annual growth ring, and the
position of fire scars within the ring series,
could be viewed clearly under a stereomicroscope with 7-45X magnification (Speer 2010).
We identified 373 fire scars in 70 whole or partial cross-sections. Fire scars were identified
by the presence of a gap (often charred) within
the ring and subsequent overlapping curvilinear growth characteristic of the tree’s healing
pattern (McBride 1983). In addition, we used
other fire-associated ring characteristics including traumatic resin ducts, double latewood, and growth releases to confirm the presence of a scar found elsewhere along the circumference of the cross-section (Brown and
Swetnam 1994). We approximated the seasonality of fire occurrence by assessing the position of the scar within the annual growth ring
(Caprio and Swetnam 1995).
Accurate cross-dating of redwoods is notoriously challenging due to the unusual ring
patterns exhibited in coast redwoods such as
missing, partial, and compressed rings (Fritz
1940, Brown and Swetnam 1994, Waring and
O’Hara 2006, Lorimer et al. 2009). In their
paper on growth ring analysis, Waring and
O’Hara (2006) stated that: “[Cross-dating] is
not practical (and perhaps not even possible) .
. . [with] coast redwood.” Recent advances in
dendrochronology techniques may improve
the ability of fire ecologists to cross-date fire
scars (Carroll et al. 2014), but, at present, most
studies rely on approximate fire dates as a
means of characterizing the fire history of
coast redwood forests (Stephens and Fry
2005). The process proved no less difficult in
this case, and cross-dating was not successful.
Consequently, individual trees (point samples)
were used as the basic sample unit throughout
this study and intervals from separate trees
were not composited.
Of the 70 cross-sections that were analyzed, 51 provided floating fire scar sequences
that allowed for analysis of undated interval
data. Nineteen of the cross-sections, either extracted from live trees (n = 11) or with reliable
harvest dates (n = 8), provided approximate
fire dates based on ring counts. All dates were
considered approximate as cross-dating was
not conducted.
Intervals were calculated exclusively from
scar to scar. The period from the tree origination date to the first fire scar was not used in
this analysis (sensu Baker and Ehle 2001), as
this interval cannot necessarily be considered
a true fire interval, particularly for a species
such as coast redwood that is not dependent on
fire for recruitment (Lazzeri-Aerts and Russell
2014). All sampled scars were included in the
analysis regardless of age, as we were relying
on data from point samples rather than on
composite data sets verified by cross-dating,
and therefore early scars had value in describing the fire history of these individual trees.
For each cross-section extracted from recording trees, the point minimum, maximum,
median, mean, and range of fire-return intervals were calculated. The single tree (point)
mean fire-return interval was defined as the
statistical average of all fire intervals in each
individual sample and was calculated by recording the number of annual growth rings between each fire scar, summing the intervals,
and then dividing this result by the total number of intervals. We calculated the grand mean
FRI by taking the average across all individual
tree estimates.
We used FHX2: Fire History Software (a
DOS-based utility) to analyze the samples
with approximate fire dates based on ring
counts, including the calculation of the mean
number of recorder years, as well as the analysis of the seasonality and fire-return interval
data (Grissino-Mayer 2001). A chronology
graph was created in the Graphics Module of
the Fire History Analysis and Exploration System (FHAES) on a JAVA platform (www.
frames.gov/fhaes).
Page 86
Comparisons between the three historical
periods (1352 to 1848, 1849 to 1921, and 1922
to 2013) were conducted using descriptive statistics. In addition, the number of scars by 10year increments was determined and a curvilinear regression analysis was conducted to assess the potential relationship between time
period and the incidence of scarring.
RESULTS
Comprehensive Fire Scar Data
The grand mean fire-return interval (FRI)
across all samples was 60.6 yr with a range
from 7.5 yr to 518 yr (SE 8.90). The median,
which may be a more accurate measure of central tendency, was 40.1 yr. A frequency distribution of the FRI, divided into 10-year increments, illustrated a positive skew toward
shorter return intervals (Figure 2). We found
an equal percentage of intervals in the ≤10year and 11- to 20-year interval classes (1 to
10 = 21.1 %; 11 to 20 = 21.4 %). Thirteen per-
cent of the intervals fell within the 21- to 30year interval class while 11 % of the intervals
fell within the 31- to 40-year interval class.
The longer interval classes encompassed the
remaining 33 % of the intervals. Although the
longest interval class captured all intervals that
exceeded 200 years, there were three intervals
(1.3 %) that exceeded 300 years.
We were able to approximate seasonality
of fire occurrence for 296 of the 373 (79.4 %)
fire scars found in the study area. The majority of fire scars were detected in the latewood
(17.7 %) and dormant (53.4 %) portions of the
annual growth rings, indicating that most fires
took place in the late summer, fall, or early
winter. By contrast, we detected only 8 % of
the fires scars in the earlywood potions of annual growth rings.
Approximately Dated Fire Scar Data
We approximated scar dates from 11 samples that were extracted from live trees and 8
samples with definite harvest dates for a total
Figure 2. Fire-return interval frequency distribution in 10-year increments for coast redwood trees in the
Santa Cruz Mountains, California, USA (n = 303).
Page 87
of 19 samples. For these samples, 110 fires
and 91 fire-return intervals were recorded from
4395 total recorder years. The range of years
for samples was 1182 to 2013. The minimum
FRI was 1 yr and maximum interval was 188
yr. Point mean intervals for individual trees
ranged from 10.4 yr to 128 yr. The earliest fire
scar indicated a fire date of 1352, although we
considered approximations of early dates to be
generally less reliable. The most recent date
was 2009, presumably from the 3163 ha Lockheed Fire that occurred on 12 to 23 August of
that year (Figure 3).
Curvilinear regression analysis on approximately dated samples indicated that the mean
number of fire scars per 10-year time period
began to increase in the 1770s (R2 = 0.3407, P
= 0.0273). This trend continued until circa
1920, when the incidence of scarring peaked.
This apparent increase in fire-return interval
was temporary as scarring decreased after the
1930s (Figure 4).
The mean point FRI varied among the
historical periods, with the pre-settlement period (1352 to 1849) exhibiting a relatively
higher FRI than the other two periods (Table
1). There was no apparent difference between
the number of fires during the settlement period (1849 to 1921) and the recent period (1922
to 2013), however. Distinctions between
these periods were clouded by a high degree
of variation.
DISCUSSION
Results from this study provide estimates
of the fire-return interval for the southern
range of the coast redwood forest that were
generally longer than those found in previous
research. The degree of variation among and
within samples, however, suggests that any
measure of central tendency may have limited
practical use for land management planning.
Figure 3. Chronology for approximately dated ring series and fire scars (1182 to 2013) in the Santa Cruz
Mountains, California, USA (n = 19). Horizontal lines are individual fire scar samples and vertical ticks
indicate fire scars. Null years are indicated by horizontal dotted lines and recorder years by horizontal solid lines.
Page 88
Figure 4. Fire scar frequency per 10-year periods (1600 to 2013) from 19 cross-sections. The gray trend
line indicates a 2-period moving average. The blue trend line displays a cubic polynomial curve for which
the R2 and P-value are displayed.
Table 1. Fire-return interval data for approximately dated fire scars by time period in the Santa Cruz
Mountains, California, USA. SE = standard error of the mean (n = 19).
Time period
Pre-settlement
(1352 to 1849)
Settlement
(1850 to 1921)
Recent
(1922 to 2013)
Fire scars
(n)
Intervals
(n)
Mean FRI
(yr)
SE
Median FRI
(yr)
Range
(yr)
49
44
43.3
6.90
26.5
185 (3 to 188)
36
23
30.7
6.18
23.0
124 (4 to 128)
27
24
32.3
5.93
22.5
123 (1 to 124)
The fire-return intervals estimated from
our data were closest to Greenlee’s (1983)
composite mean FRI of 45.4 years for Big Basin Redwoods State Park, and were furthest
from the 6.2 yr to 23.0 yr and 12.4 yr to 16.3
yr FRIs found by Finney and Martin (1992)
and Stephens and Fry (2005). Differing vege-
tation mosaics, combined with both physiographic and microclimate variation between
aforementioned study sites likely accounts for
many of these discrepancies. Where more mesic conditions exist near the coast, Sequoia
sempervirens tends to grow in continuous
groves, and fires tend to be less frequent and
Page 89
intense due to relatively moist fuel conditions
(Veirs 1985, Martin and Sapsis 1991, Heyerdahl et al. 2001). Seasonality of fire was consistent with the literature, with the prevalence
of fire scars in the latewood, and with the dormant portions of the annual growth rings (Finney and Martin 1992, Brown and Baxter 2003,
Stephens and Fry 2005, Norman 2007).
The historical FRI distribution from our
study exhibited certain similarities to distributions from other fire history studies across the
range of coast redwood. The majority of the
intervals were relatively short, but the results
from our study included a greater number of
long intervals resulting in a longer mean FRI
and more variability in the data set (Figure 5).
The relatively large number of fire scars that
were detected in the recent period was primarily a result of sampling methods, rather than a
reflection of a higher number of fires during
that period. More viable samples were available in the youngest wood, whereas older samples provided progressively less reliable fire
scar data due to degradation.
Unlike many forest types in the western
United States, fires in the coast redwood forests result primarily from anthropogenic, rather than natural, sources (van Wagtendonk and
Cayan 2008). Spanish explorer accounts of
Native American burning, as well as current
research, suggests that indigenous tribes used
fire extensively on the central coast, particularly near the coastline in the vicinity of Point
Año Nuevo (Cuthrell 2013). An initial increase in fire occurrence immediately preceding the advent of non-native settlement of the
region eventually gave way to diminished fire
frequencies, most likely due to the implementation of more effective fire suppression campaigns, as illustrated by results from the settle-
Figure 5. Fire history distributions from this study, Prairie Creek Redwoods State Park (Brown and Swetnam 1994), northeast Santa Cruz Mountains (Stephens and Fry 2005), and Annadel State Park (Finney and
Martin 1992). Figure adapted from Norman et al. (2009).
Page 90
ment and recent periods. It is unlikely that this
increase was a result of naturally ignited fire,
as lightning fires are extremely limited in the
region (Keeley 2005). It is likely that both
pre-colonial and historical land use practices
and burning patterns in this study area were
highly temporally and spatially variable, creating a mosaic of fire regime characteristics dispersed across the landscape (Lightfoot and
Parrish 2009). Greater resolution on the topic
of the influence of cultural burning practices,
combined with more accurate dating than this
study provides, may provide more definitive
fire histories in the future.
Knowledge of the coast redwood fire regime is important in order for resource managers to assess the appropriate role of fire in
modern coast redwood forests. However, it is
challenging for managers who wish to reintroduce fire as a disturbance process into redwood ecosystems to find a useful set of reference fire regime attributes on which to base
restoration objectives. If anthropogenic burning practices affected the landscape by increasing biodiversity and influencing forest
structure and composition, then prescribed
burning could serve as a proxy for both pre-colonial and historical ignitions, now largely ab-
sent from the landscape (Finney and Martin
1989, Brown et al. 1999, Stephens and Fry
2005). This study suggests that managing fire
for regularity based on a mean or median
fire-return interval and subsequent fire-return
interval departure (Caprio et al. 2002) may not
be appropriate, as these metrics are only marginally illustrative of the variability of the redwood fire regime in this area. One restoration
model that may prove useful is the practice of
restoring cultural landscapes in which management activities are centered on incorporating components of traditional resource and environmental management (Fowler and Lepofsky 2011). This model has been successfully
implemented in Redwood National Park, California, where the Bald Hills are burned regularly to maintain the ethnographic landscape
(Underwood et al. 2003). In addition, opportunities for patch mosaic burning should be investigated as a means for maintaining both
spatial and temporal variability of fires in this
biome (Brockett et al. 2001, Stephens and Fry
2005). Resource managers will likely need to
employ a suite of fire management strategies
in coast redwood forests that are firmly
grounded in a context of adaptive management, regardless of the restoration model used.
ACKNOWLEDGEMENTS
We would like to thank Big Basin Redwoods State Park, Big Creek Lumber, the Sempervirens Fund, Skylark Ranch, Swanton Pacific Ranch, and the organizations that jointly manage
the San Vicente Redwoods for allowing us access to their lands for our fieldwork and for sharing
their extensive knowledge of land use history in the area. We also thank C. Striplen from the San
Francisco Estuary Institute for his countless hours spent assisting in the field and in the lab.
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McCaw and Middleton: Fire in Tall Eucalypt Forest
Page 95
Research Article
RECOVERY OF TALL OPEN EUCALYPT FOREST IN SOUTH-WESTERN
AUSTRALIA FOLLOWING COMPLETE CROWN SCORCH
Lachlan McCaw1* and Ted Middleton2
1
Science and Conservation Division, Department of Parks and Wildlife,
Brain Street, Manjimup, Western Australia 6258, Australia
Frankland District, Department of Parks and Wildlife,
South Coast Highway, Walpole, Western Australia 6398, Australia
2
*Corresponding author: Tel: +61-8-9771-7998; e-mail: [email protected]
ABSTRACT
RESUMEN
We investigated the response of
overstorey and mid-storey trees in tall
open forest of Eucalyptus diversicolor F.
Muell., Eucalyptus jacksonii Maiden,
and Corymbia calophylla (Lindl.) K.D.
Hill & L.A.S. Johnson over an eightyear period following complete crown
scorch by high intensity fire in March
2001. More than 90 % of E. diversicolor
and E. jacksonii and 85 % of C.
calophylla remained alive four years
after fire, having replaced their crowns
by re-sprouting from epicormic buds on
the stems and larger branches. Midstorey trees were more severely affected
by fire with almost one third of
Allocasuarina decussata (Benth.) L.A.S.
Johnson stems and all above-ground
stems of Agonis flexuosa (Willd.) Sweet
killed back to ground level. Abundant
seedling regeneration of E. diversicolor
and E. jacksonii developed in the year
following the fire but seedling density
and stocking declined progressively over
subsequent years.
Survival of E.
diversicolor seedlings was higher than
for E. jacksonii seedlings, consistent
with findings of earlier research. For
both species, initial seedling densities
were significantly greater within 25 m of
Nosotros investigamos la respuesta del dosel
superior y medio de árboles en bosques altos
y abiertos de Eucalyptus diversicolor F.
Muell., Eucalyptus jacksonii Maiden, y
Corymbia calophylla (Lindl.) K.D. Hill &
L.A.S. Johnson por un período de ocho años,
después de la quema total del dosel por un
fuego de alta intensidad, ocurrido en marzo
de 2001. Más del 90 % de E. diversicolor y
E. jacksonii, y el 85 % de C. calophylla permaneció vivo cuatro años después del fuego,
habiéndose reemplazado su dosel mediante
el rebrote de brotes epicórmicos del tronco y
de ramas largas. Los árboles con doseles en
el estrato medio fueron severamente afectados por el fuego, con casi un tercio de los tallos de Allocasuarina decussata (Benth.)
L.A.S. Johnson y todos los tallos de Agonis
flexuosa (Willd.) Sweet muertos por el fuego
hasta el nivel del suelo. Una abundante regeneración de E. diversicolor y E. jacksonii
se desarrolló al año siguiente del incendio,
aunque la densidad y el número de plántulas
declinaron progresivamente en los años subsiguientes. La supervivencia de plántulas de
E. diversicolor fue mayor que la de E. jacksonii, consistente con los resultados de investigaciones previas. Para ambas especies,
la densidad inicial de plántulas fue significativamente mayor dentro de los 25 m alrede-
potential seed trees, but seedling density
was otherwise unrelated to the basal
area of surrounding forest. Eight years
after the fire, 38 % of sample quadrats (4
m2) were stocked with one or more
eucalypt saplings, with saplings of E.
diversicolor and E. jacksonii having a
mean height of 5 m.
Saplings
established following the 2001 fire could
add a further age class to the stand
provided that this cohort persists during
subsequent fires. The results of our
study provide further evidence to
support the view that tall open eucalypt
forests in south-west Western Australia
rarely experience complete stand
replacement even following intense
fires, and that multi-aged stands are
common.
Page 96
dor de los potenciales árboles semilleros,
aunque contrariamente, la densidad de plántulas no se relacionó con el área basal del
bosque circundante. Ocho años después del
fuego, el 38 % de los parcelas de muestreo
(de 4 m2) estaban ocupadas por una o más
plántulas de eucaliptus, con plántulas de E.
diversicolor y de E. jacksonii cuya altura media era de 5 m. Las plántulas establecidas
después del incendio de 2001 pueden añadir
una cohorte más al rodal siempre y cuando
esta cohorte persista durante fuegos subsecuentes. Los resultados de nuestro estudio
proveen de nuevas evidencias que respaldan
la idea de que los bosques altos de eucaliptus
en el sudoeste de Australia rara vez experimentan un completo reemplazo de sus rodales aún después de fuegos intensos, y que lo
común en ellos son los rodales multi-etáneos.
Keywords: age structure, crown scorch, epicormic sprouting, eucalyptus forest, regeneration
Citation: McCaw, L., and T. Middleton. 2015. Recovery of tall open eucalypt forest in southwestern Australia following complete crown scorch. Fire Ecology 11(3): 95–107. doi: 10.4996/
fireecology.1103095
INTRODUCTION
Fire has long been recognised as having a
dominant role in the regeneration of tall open
eucalypt forests in southern Australia (Ashton
1981). Tall open eucalypt forests have a
mature height >30 m and canopy cover of
30 % to 70 %, often with a stratum of midstorey trees and a dense understorey of shrubs.
Fire facilitates regeneration by reducing
competition, creating receptive seedbed,
stimulating synchronous seedfall, and
temporarily eliminating seed predators and
seedling pathogens (Jarrett and Petrie 1929,
Gilbert 1959, White and Underwood 1974,
Ashton 1981, Wardell-Johnson 2000). The
effect of past fires is evident in the age class
distribution of tall open forests at the landscape
scale, and in the structure of stands at the local
scale where two or more cohorts of trees
originating from significant regeneration
events may be present (Bradshaw and Rayner
1997, Hickey et al. 1999, Lindenmayer 2009,
Turner et al. 2009, Benyon and Lane 2013).
Tall open forests occupy 190 000 ha in
south-western Australia, mostly within the
Warren region, which is an administrative area
that includes 930 000 ha of public land
managed primarily for conservation, outdoor
recreation, and sustainable timber production
(Figure 1). Characteristic overstorey species
include karri (Eucalyptus diversicolor F.
Muell.); marri (Corymbia calophylla [Lindl.]
K.D. Hill & L.A.S. Johnson); blackbutt
(Eucalyptus patens Benth.); and the red,
yellow, and Rates tingle (Eucalyptus jacksonii
Maiden, E. guilfoylei Maiden, and E.
brevistylis
Brooker,
respectively).
Nomenclature for Western Australian plant
species follows Florabase (florabase.dpaw.wa.
Page 97
Figure 1. Map showing the distribution of tall open forest in south-western Australia and the location of
the study area burnt by the March 2001 bushfire. Inset panel shows the general location of the study area
in Western Australia. Rainfall isohyets (mm) are shown.
gov.au; accessed 30 June 2015). Tall open
forests occur in areas receiving >1000 mm
annual rainfall on a variety of soils (loams,
podsols, sandy gravels, and sands) derived
from Proterozoic granite and gneiss, and in a
mosaic with open forests dominated by jarrah
(Eucalyptus marginata Sm.) on gravelly soils,
and sclerophyll shrublands on highly leached
sands (Bradshaw et al. 1997, Wardell-Johnson
et al. 1997). Tall open forests typically have a
dense understorey of mid-storey trees and
woody shrubs that, if unburnt for several
decades, can attain a height >10 m and
accumulate a substantial loading of leaf litter,
twigs, and small branches that can exceed 70 t
ha-1 (Sneeuwjagt 1971, O’Connell 1987,
McCaw et al. 2002).
South-western
Australia
has
a
mediterranean climate with a distinct summer
drought and, in most years, litter and
understorey fuels in tall open forest are dry
enough to ignite and burn in the period from
December to March (McCaw and Hanstrum
2003). Unplanned bushfires occur every
summer as a result of lightning ignition and
accidental or deliberate actions by people
(Plucinski et al. 2014). Bushfires in tall open
forest can be intense and fast moving,
particularly in late summer and early autumn
when the seasonal drought is at its peak and a
high proportion of fine and coarse woody fuels
are consumed (Hollis et al. 2011). Systematic
fire reports available from the late 1930s
onwards (McCaw et al. 2005) indicate that
large bushfires (>10 000 ha) have burnt tall
open forest in this region in 1937, 1950, 1952,
1969, 1997, 2002, 2012, and 2015. The fire of
February 1937 was the most extensive of these
and, while no reliable maps of the fire
perimeter exist, newspaper reports indicate
that fire activity extended across 150 km in the
southern half of the Warren region (McCaw
and Hanstrum 2003).
The mosaic of
vegetation types at the landscape scale means
that the perimeters of large fires typically
include a mixture of tall open forest, open
forest, and shrubland.
Systematic fire
management in the Warren region began in the
1950s and prescribed fire has been used widely
for fuel reduction, and to achieve a range of
land management objectives including
biodiversity conservation and regeneration
following timber harvesting (Burrows and
McCaw 2013). Boer et al. (2009) identified a
statistically significant inverse relationship
between the area burnt by prescribed fire and
the area burnt by unplanned bushfire over a
52-year study period ending in 2004, with a
lag effect persisting for up to six years
following prescribed burning.
Eucalypts characteristic of tall open forest
in south-western Australia are capable of resprouting from epicormic shoots following
complete scorching of the canopy (WardellJohnson 2000, Burrows and Wardell-Johnson
2003). Their large stature, thick bark, and
ability to re-sprout from dormant buds on the
stems and branches confer considerable
tolerance to fires of moderate to high intensity
(fireline intensity 3000 kW m-1 to 7000 kW
m-1, following Cheney [1981]). Large old
trees are often hollow-butted as a result of
stem damage during past fires, and ignition of
dead wood in the hollow section of the stem
can lead to collapse of the trees. Complete
stand replacement is rare even following high
intensity fires, and previous studies have
concluded that multi-aged stands are common
(Bradshaw and Rayner 1997, Wardell-Johnson
2000). The existence of multiple-age cohorts
Page 98
has been inferred from stand structure and
counting of growth rings on a sample of felled
trees.
We studied the response of overstorey and
mid-storey trees at the stand scale over an
eight year period following complete crown
scorch by fire in March 2001 in order to
quantify (1) changes in stand structure as a
result of the fire, and (2) the extent of
recruitment of a further cohort of eucalypts
from seedlings established following the fire.
METHODS
Study Area
The study was conducted 8 km south-west
of Walpole (35˚ 00′ S, 116˚ 43′ E) in the
Walpole Nornalup National Park, Australia, in
undulating terrain rising to an elevation of 160
m above sea level. Dominant vegetation is tall
open forest of E. diversicolor, E. jacksonii and
C. calophylla up to 50 m in height with a midstorey of Allocasuarina decussata (Benth.)
L.A.S. Johnson, Agonis flexuosa (Willd.)
Sweet and Trymalium odoratissimum subsp.
trifidum (Rye) Kellermann, Rye & K.R.Thiele.
Forest structure maps prepared from air photo
interpretation indicate a crown cover of 50 %
to 80 % (Bradshaw et al. 1997). Prior to 2001,
this area was last burnt by the February 1937
bushfire that defoliated the overstorey across a
widespread area of forest around Walpole
(Bellanger 1980, Fernie and Fernie 1989).
On 7 March 2001, a lightning strike ignited
a fire that burnt for four days under conditions
of moderate to high fire danger at the end of
seasonal summer drought when the entire litter
profile was dry and available for combustion
(Table 1). The Soil Dryness Index (Mount
1972, Burrows 1987), which reflects the
dryness of soil and coarse woody debris, was
at its seasonal peak of 165 mm. Despite
temperature and relative humidity being
relatively mild, the combination of dry fuels
and strong easterly winds on the night of 9
Page 99
Table 1. Weather and fuel moisture content recorded at Walpole during the March 2001 fire. Fuel
moisture contents represent daily minimum values predicted by the Forest Fire Behaviour Tables for
Western Australia (Sneeuwjagt and Peet 1985).
Minimum
Wind direction
Fine fuel
Maximum
relative humidity and speed at moisture content Profile moisture
Date
temperature (°C)
( %)
1500 h (km h-1)
( %)
content ( %)
7 Mar 2001
33
32
SW 24
11
22
8 Mar 2001
22
63
SSW 14
18
22
9 Mar 2001
21
54
SE 26
18
22
10 Mar 2001
23
47
SE 34
20
22
March caused the head fire to spread 5 km
through a mosaic of forest and shrubland with
an average rate of spread of 0.35 km hr-1.
Fireline intensity in the long-unburnt tall forest
was estimated to be in the range 3000 kW m-1
to 7000 kW m-1 with flame heights of up to 10
m. This caused complete crown scorch of tall
forest and widespread defoliation of low forest
and shrubland.
Forest Measurements
In November 2001, we established an 800
m long belt transect in forest on a westerly
facing slope that had been completely crown
scorched by the fire (Figure 2). We chose this
area because of the relative uniformity of the
stand structure, and because it was located in
an area where the fire had burnt unimpeded by
suppression action.
Stand structure was
assessed by recording the species, stem
diameter (dbh), and crown condition of
individual eucalypts, Allocasuarina decussata
and Agonis flexuosa >10 cm dbh, within 25 m
either side of the transect. The location of
each tree was recorded as the distance along
and left or right of the transect. Trees judged
to have been dead at the time of the 2001 fire
were not included, although we did observe
evidence of dead trees that had burnt away
partially or completely. Crown condition was
described using an ordinal scale based on the
location of re-sprouting on the stem and
reflecting the relative severity of damage by
fire as proposed by Lacey and Johnston
(1990). Ratings were (1) crown recovering
from shoots on fine terminal branches, (2)
crown recovering from epicormic shoots on
intermediate branches without extensive resprouting from the stem, (3) crown recovering
from epicormic shoots on large branches and
the stem, (4) crown dead with epicormic
shoots on the stem only, (5) epicormic shoots
only arising from the stem below 1.3 m, and
(6) tree completely dead. Crown condition
was assessed in April 2002 and again in
December 2005, respectively 13 months and
52 months after fire.
Seedling regeneration was monitored at 40
permanently marked points located at 20 m
intervals along the transect. At each point, the
number of eucalypt seedlings was counted
within a circular quadrat of 1.13 m radius (4
m2) and the height of the tallest seedling of
each species recorded.
Counts were
undertaken in December 2001; June 2002; and
in December 2003, 2005, and 2009. Stem
diameter was also recorded for individual
plants once they attained a height of 2 m.
Seedling densities on individual quadrats,
including un-stocked quadrats, were averaged
and converted to a per hectare equivalent. The
number of stocked quadrats containing one or
more live seedlings was used as a measure of
site occupancy, consistent with regeneration
survey practice common in eucalypt forests
(Lutze et al. 2004).
The relationship between forest overstorey
composition and initial seedling density in the
first spring after fire (November 2001) was
Page 100
A
B
Figure 2. (A) Mature forest in the early stages of recovery eight months after being fully crown scorched
by the fire of March 2001. Eucalypt seedlings are visible in the foreground. Large trees that have fallen
since the fire are evident, including a rough barked E. jacksonii (foreground) and a smooth barked E.
diversicolor (right side, rear of photo). (B) Re-sprouting of epicormic shoots on mature E. diversicolor
and E. jacksonii one year after the fire. Dense seedling regeneration of E. diversicolor is visible in the
foreground.
investigated for the two dominant species E.
diversicolor and E. jacksonii. We calculated
the basal area of each species within a 25 m
radius of each seedling quadrat, and the
distance to the nearest potential seed tree of
each species with a diameter of ≥70 cm, up to
a distance of 25 m, which was the full width of
the sample transect. Trees ≤70 cm diameter
were excluded because they were immature
and yet to develop their full crown size and
seed potential (Bradshaw and Rayner 1997).
For each species, seedling density was plotted
against basal area and the relationship tested
by fitting a linear regression. Seedling density
was also compared for quadrats located <25 m
and >25 m from a potential seed tree of each
species using the non-parametric MannWhitney test.
This distance represents
approximately twice the crown radius and half
the height of a mature tree (Rotheram 1983).
RESULTS
Overstorey and Mid-Storey Trees
The forest overstorey was dominated by
mature eucalypts with a density of 45 stems
ha-1 and a basal area of 45.7 m2 ha-1 (Table 2).
Half of the basal area was contributed by E.
diversicolor, with smaller contributions of E.
Page 101
Table 2. Stand characteristics recorded on a 3.9 ha transect.
Species
Corymbia calopylla
Eucalyptus diversicolor
Eucalyptus guilfoylei
Eucalyptus jacksonii
Eucalyptus marginata
Agonis flexuosa
Allocasuarina decussata
Stems ha-1
7
26
1
10
1
9
17
jacksonii and C. calophylla and occasional E.
marginata and E. guilfoylei. The modal
diameter class of overstorey trees was 125 cm
to 149 cm with a secondary peak in the 50 cm
to 74 cm diameter class, and occasional very
large trees with a stem diameter >2 m, which
were mostly E. jacksonii (Figure 3). Midstorey trees were predominantly Allocasuarina
decussata with a mean stem diameter of 40
cm, and a lesser component of Agonis
flexuosa.
Most overstorey trees had begun to resprout from epicormic buds within one year of
the fire (Figure 2).
Re-sprouting from
epicormic buds on the larger branches and
6
Stems ha-1
5
4
3
C. calophylla
E. diversicolor
E. jacksonii
2
1
0
Diameter class (cm)
Figure 3. Stem diameter distribution for the three
dominant overstorey trees on a 3.9 ha belt transect.
Basal area
(m2 ha-1)
7.9
23.6
0.3
13.4
0.5
0.3
2.5
Mean dbh (SE) dbh of largest tree
(cm)
(cm)
111 (10)
199
96 (5)
241
62 (11)
89
112 (11)
345
88 (21)
117
18 (1)
37
40 (2)
70
stems was the most common recovery
mechanism observed on E. diversicolor and E.
jacksonii, while C. calophylla more commonly
re-sprouted from epicormic buds on small and
intermediate branches (Table 3). The small
number of E. marginata and E. guilfoylei
present also re-sprouted from epicormic buds
on the larger branches and stems (data not
shown). Mid-storey trees were more severely
impacted than the overstorey due to their
lower stature, with 7 % of Allocasuarina
decussata dead within the first year and most
surviving trees re-sprouting only from the
stems and larger branches. Two-thirds of
Agonis flexuosa stems were killed back to
ground level and re-sprouted from basal buds.
At 52 months post fire, the proportion of dead
trees had increased to 6 % of E. diversicolor,
9 % of E. jacksonii, and 15 % of C. calophylla
(Table 3). For surviving trees, the proportion
of trees limited to epicormic shoots on the
stems had reduced and re-sprouting on fine
terminal branches and intermediate branches
had increased for all eucalypts.
No E.
marginata or E. guilfoylei died following the
fire, with all trees re-sprouting from epicormic
shoots on terminal and intermediate branches.
By 2005, the number of dead Allocasuarina
decussata had increased four-fold to 29 % of
trees, with a further 6 % re-sprouting only
from the base. All Agonis flexuosa re-sprouted
from basal shoots.
Page 102
Table 3. Crown condition of fully scorched overstorey and mid-storey trees in 2002 and 2005. Crown
condition ratings indicate the predominant location of epicormic shooting on the tree.
Number (%) of sprouts by location
Stems Months Terminal Intermediate Branches
Base below Dead
Species
(n) since fire branches branches and stem Stems
1.3 m
n (%)
13
7 (27)
10 (39)
4 (15)
4 (15)
1 (4)
0 (0)
C. calophylla
26
52
19 (73)
2 (8)
0 (0)
0 (0)
1 (4)
4 (15)
13
31 (31)
5 (5)
46 (46)
16 (16)
0 (0)
3 (3)
E. diversicolor 101
52
31 (31)
21 (21)
30 (30)
11 (11)
2 (2)
6 (6)
13
4 (10)
4 (10)
25 (64)
5 (13)
0 (0)
1 (3)
E. jacksonii
39
52
12 (30)
4 (10)
18 (46)
2 (5)
0 (0)
3 (9)
13
18 (26)
16 (24)
19 (28)
10 (15)
0 (0)
5 (7)
A. decussata
68
52
24 (35)
15 (22)
4 (6)
1 (2)
4 (6)
20 (29)
Seedling Regeneration
Eucalypt seedling densities were highest in
November 2001, the first spring after fire
(Figure 4). Seedling densities of E. jacksonii
were initially twice those of E. diversicolor,
but the percentage of 4 m2 quadrats stocked
with E. jacksonii (53 %) was lower than for E.
diversicolor (73 %), indicating a more clumped
distribution of E. jacksonii seedlings (Figure
5). Few seedlings (<25 ha-1) of other eucalypts
were recorded. The density of E. diversicolor
seedlings was significantly higher at quadrats
located within 25 m radius of a mature tree,
but there was no significant relationship (P >
0.05) between seedling density and basal area
of mature trees in surrounding forest (Table 4,
Figure 6).
The density of E. jacksonii
seedlings was also significantly greater on
quadrats located within 25 m radius of a
mature tree than those located farther away.
Seedling density and basal area of mature trees
100
Seedlings ha-1
1000
800
E. jacksonii
E. diversicolor
600
400
200
0
0 10 20 30 40 50 60 70 80 90 100
Months since f ire
Figure 4. Mean density of seedlings of E.
diversicolor and E. jacksonii recorded at 40
quadrats between November 2001 and December
2009. Bars indicate SE.
Quadrats stocked (%)
1200
80
E. jacksonii
E. diversicolor
Any eucalypt
60
40
20
0
0 10 20 30 40 50 60 70 80 90100
Months since f ire
Figure 5. Percentage of quadrats stocked with one
or more seedlings of E. diversicolor, E. jacksonii,
or any species of eucalypt between November
2001 and December 2009.
Page 103
Species
E. diversicolor
E. jacksonii
<25 m
1.8a (0.4)
4.0a (2.2)
>25 m
0.6b (0.4)
0.6b (0.3)
were significantly related (P < 0.01) for E.
jacksonii, with the relationship influenced
strongly by very high seedling density at a
single quadrat associated with high basal area
(62 m2 ha-1). By the beginning of winter 2002,
15 months after the fire, seedling densities had
reduced by half for E. jacksonii and by 35 %
for E. diversicolor. Stocking and density
declined progressively over the following
seven years and by December 2009, 38 % of 4
m2 quadrats remained stocked with at least one
eucalypt (Figure 5). Densities of surviving E.
diversicolor and E. jacksonii were similar,
respectively 33 stems ha-1 and 34 stems ha-1.
Seedlings of E. diversicolor and E.
jacksonii exhibited similar height growth over
time and, by 2009, the regeneration cohort
consisted of saplings with a mean height of 5
m (Figure 7), and a mean dbhob (dbh outside
bark) of 4 cm (SE = 0.6 cm). The largest and
most vigorous saplings observed in the general
study area were up to 15 m tall and 17 cm
dbhob.
DISCUSSION
The existence of multiple-age cohorts in
tall open eucalypt forest has generally been
inferred from stand structural data including
stem diameter size class distribution, tree
canopy characteristics, and evidence of fire
scarring and charcoal on stems (Bradshaw and
Rayner 1997, Hickey et al. 1999, Turner et al.
E. diversicolor
35
Seedling density (m-2)
40
30
25
20
15
10
5
0
0
40
20
40
60
2
Basal area (m ha-1)
80
E. jacksonii
35
Table 4. Seedling densities of E. diversicolor and
E. jacksonii in November 2001 for quadrats
located <25 m and >25 m distant from a potential
seed tree of either species. Data are means (SE).
Values in each row followed by a different
superscript are significantly different (P < 0.05;
Mann-Whitney test).
30
25
20
15
10
5
0
0
20
40
60
Basal area (m2 ha-1)
80
Figure 6. Density of seedlings of E. diversicolor
and E. jacksonii in November 2001 in relation to
the basal area of that species within 25 m radius of
the quadrat.
2009). Cohort ages have been estimated using
tree ring counts for overstorey and fire
sensitive mid-storey trees, and from fire
records.
We employed a different but
complementary approach by studying
responses at the stand scale over an eight year
period following fire. Benyon and Lane
(2013) used a similar approach to assess
6
Height (m)
5
E. jacksonii
E. diversicolor
4
3
2
1
0
0 10 20 30 40 50 60 70 80 90 100
Months since f ire
Figure 7. Height of E. diversicolor and E.
jacksonii at intervals between November 2001 and
December 2009. Bars indicate SE.
overstorey survival and seedling regeneration
at multiple sites following the extensive 2009
bushfires in Victoria, south-eastern Australia,
although their observations were limited to the
first two years following fire and did not
include quantitative assessments of eucalypt
seedling density.
Monitoring the fate of particular
regeneration cohorts provides scope to better
understand the varied factors that may
determine the pathway from seedling to
mature tree. Seedling densities of E. jacksonii
were twice those of E. diversicolor in the first
spring after fire, but this higher density did not
persist beyond the third spring after fire.
McCaw et al. (2000) reported a similar finding
from a previous study of seedling recruitment
following two low intensity fires in tall open
forest near Walpole, with the higher density of
E. jacksonii seedlings reflecting the relative
dominance of overstorey eucalypts in the two
stands examined in that study. Overstorey
composition does not explain the findings of
the present study in which E. diversicolor was
dominant both in terms of basal area and the
Page 104
number of stems per hectare.
The
opportunistic circumstance of the present
study meant that no information was available
about the size or condition of the seed crop at
the time of the fire. McCaw et al. (2000)
reported little or no persistent recruitment of
E. diversicolor or E. jacksonii following low
intensity fires, attributing this to high levels of
competition from overstorey and mid-storey
trees with intact crowns, and rapid loss of seed
bed receptivity due to heavy post-fire litter fall
from Allocasuarina decussata. In contrast, E.
diversicolor and E. jacksonii saplings
established following the 2001 fire have
remained competitive with the dense post-fire
understorey and have the potential to form an
additional cohort within the stand provided
they survive subsequent fires. In the absence
of a competing overstorey, E. diversicolor
saplings take at least 15 years to develop to a
stage at which they are tolerant of low to
moderate intensity fire (McCaw et al. 1994),
and E. jacksonii is likely to require a similar
period.
Competition from surviving
overstorey trees would be expected to suppress
the further development of some saplings into
more advanced growth stages (Rotheram
1983). The stocking of persistent eucalypt
regeneration following the 2001 fire is low in
comparison with E. diversicolor stands
regenerated using seed tree silviculture
following timber harvesting (McCaw et al.
2002), and much lower than post-fire
regeneration density common in some tall
open forests in south-eastern Australia (Ashton
1976).
The stand examined in this study included
trees of a wide range of size classes with
evidence of several distinct cohorts, including
a low density of very large trees that have
persisted through multiple fire events,
including a previous high intensity fire in
1937. Wood et al. (2015) reported a similar
stand structure from a sample of nine 1 ha
plots established in E. diversicolor and E.
jacksonii forest as part of a continental scale
Page 105
network of plots in tall open eucalypt forest.
More than 85 % of overstorey trees examined
in our study survived complete crown scorch
and replaced their crowns from epicormic
buds on the stems and larger branches,
consistent with the findings of WardellJohnson (2000). The capacity of eucalypts
from tall open forest in south-west Western
Australia to recover from complete crown
scorch appears similar to that of the more firetolerant eucalypts from tall open forests in
south-eastern Australia (Benyon and Lane
2013), including pure stands of E. nitens
(Deane & Maiden) and mixed species stands
of E. obliqua L’Hér, E. baxteri (Benth.)
Maiden & Blakely ex J.M. Black, E.
cypellocarpa L.A.S. Johnson, and E. radiata
Sieber ex DC. Mid-storey trees, particularly
Allocasuarina decussata, are also capable of
surviving fires of moderate to high intensity
and can attain considerable age and stature,
contributing to structural complexity of the
forest that may be important for biodiversity
conservation (Lindenmayer 2009).
It is important to recognise that our
findings and those of Wardell-Johnson (2000)
relate to fires within the lowest decile of
potential fire intensity recorded in tall eucalypt
forest (Cruz et al. 2012). More intense fires,
which can potentially include crowning fires,
could impact severely on stand structure
through increased mortality and accelerated
loss of hollow-butted trees.
ACKNOWLEDGEMENTS
We thank J. Neal, R. Smth, R. Robinson, R. Wittkuhn, and T. Hamilton for assisting with field
measurements. J. Bradshaw, G. Wardell-Johnson, and two anonymous referees provided
constructive comments on earlier versions of the manuscript.
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Hyde et al.: Fuel Layer Comparisons
Page 108
Research Article
A CASE STUDY COMPARISON OF LANDFIRE FUEL LOADING AND
EMISSIONS GENERATION ON A MIXED CONIFER FOREST IN
NORTHERN IDAHO, USA
Josh Hyde1*, Eva K. Strand1, Andrew T. Hudak2, and Dale Hamilton3
University of Idaho College of Natural Resources
Department of Forest, Rangeland, and Fire Sciences,
975 West 6th Street, Moscow, Idaho 83844, USA
1
2
3
USDA Forest Service, Rocky Mountain Research Station,
1221 South Main Street, Moscow, Idaho 83843, USA
Northwest Nazarene University, Mathematics and Computer Science Department,
623 South University Boulevard, Nampa, Idaho 83686, USA
Corresponding author: Tel.: +1-206-473-1979 e-mail: [email protected]
*
ABSTRACT
RESUMEN
The use of fire as a land management
tool is well recognized for its ecological benefits in many natural systems.
To continue to use fire while complying with air quality regulations, land
managers are often tasked with modeling emissions from fire during the
planning process. To populate such
models, the Landscape Fire and Resource Management Planning Tools
(LANDFIRE) program has developed raster layers representing vegetation and fuels throughout the United States; however, there are limited
studies available comparing LANDFIRE spatially distributed fuel loading data with measured fuel loading
data. This study helps address that
knowledge gap by evaluating two
LANDFIRE fuel loading raster optionsFuels Characteristic Classification System (LANDFIRE-FCCS)
and Fuel Loading Model (LANDFIRE-FLM) layerswith measured
fuel loadings for a 20 000 ha mixed
El uso del fuego como herramienta de manejo
de tierras es bien reconocido por sus beneficios
ecológicos en varios ecosistemas naturales.
Para continuar con el uso del fuego y a su vez
cumplir con las regulaciones referidas a la calidad del aire, los gestores de tierras deben frecuentemente cumplir con tareas de modelado
de emisiones durante el proceso de planificación de las quemas. Para alimentar tales modelos, el programa denominado Landscape Fire
and Resource Management Planning Tools
(LANDFIRE) ha desarrollado capas raster, que
representan vegetación y combustibles a lo largo de todos los EEUU; desde luego, son limitados los estudios disponibles que puedan comparar los datos de carga de combustibles espacialmente distribuidos derivados del LANDFIRE,
con datos similares producto de mediciones de
carga de combustible en el terreno. Este estudio ayuda a dilucidar este vacío en el conocimiento mediante la evaluación de carga de
combustible usando dos opciones del programa
LANDFIREel Fuels Characteristic Classification System (LANDFIRE-FCCS) y el Fuel
Loading Model (LANDFIRE-FLM) layers
conifer study area in northern Idaho,
USA. Fuel loadings are compared,
and then placed into two emissions
modelsthe First Order Fire Effects
Model (FOFEM) and Consumefor
a subsequent comparison of consumption and emissions results. The
LANDFIRE-FCCS layer showed
300 % higher duff loadings relative
to measured loadings. These led to
23 % higher total mean total fuel
consumption and emissions when
modeled in FOFEM. The LANDFIRE-FLM layer showed lower
loadings for total surface fuels relative to measured data, especially in
the case of coarse woody debris,
which in turn led to 51 % lower
mean total consumption and emissions when modeled in FOFEM.
When the comparison was repeated
using Consume model outputs,
LANDFIRE-FLM consumption was
59 % lower relative to that on the
measured plots, with 58 % lower
modeled emissions. Although both
LANDFIRE and measured fuel loadings fell within the ranges observed
by other researchers in US mixed conifer ecosystems, variation within
the fuel loadings for all sources was
high, and the differences in fuel
loadings led to significant differences in consumption and emissions depending upon the data and model
chosen. The results of this case
study are consistent with those of
other researchers, and indicate that
supplementing LANDFIRE-represented data with locally measured
data, especially for duff and coarse
woody debris, will produce more accurate emissions results relative to
using unaltered LANDFIRE-FCCS
or LANDFIRE-FLM fuel loadings.
Accurate emissions models will aid
Page 109
comparados con la medición de la carga para
20 000 ha de un área de bosques mixtos de coníferas en el norte de Idaho, EEUU. Las cargas
de combustibles fueron comparadas, y luego
ubicadas dentro de dos modelosel First Order
Fire Effects Model (FOFEM) y el Consumepara su subsecuente comparación de los
resultados del consumo de combustibles y sus
emisiones. El LANDFIRE-FCCS mostró una
estimación 300 % superior en la carga del mantillo comparado con la carga medida a campo.
Esto llevó a un valor 23 % más alto en la media
total de consumo y emisiones del combustible
cuando fue modelado mediante el modelo FOFEM. El modelo LANDFIRE-FLM layer mostró menores cargas para combustibles de superficie relativo a datos medidos a campo, especialmente en el caso de restos de combustible
leñoso grueso (coarse woody debris), que a su
vez llevó a un 51 % menos en el consumo y
emisiones promedio cuando fueron modeladas
por el modelo FOFEM. Cuando la comparación
fue repetida usado el Consume model outputs,
el consumo estimado por el LANDFIRE-FLM
fue un 59 % menor en relación a lo determinado
en las parcelas medidas, con un 58 % menos que
las emisiones modeladas. Aunque ambos modelos de LANDFIRE y las cargas efectivamente
medidas se ubican dentro de los rangos observados por otros investigadores en los ecosistemas
mixtos de coníferas de los EEUU, la variación
dentro de las cargas de combustible determinadas por las distintas fuentes fue alta, y las diferencias en carga de combustible llevan a diferencias significativas en consumo y emisiones,
dependiendo éstos del modelo elegido. Los resultados de este estudio de caso son consistentes
con aquellos obtenidos por otros investigadores,
e indican que suplementando datos de LANDFIRE con datos locales obtenidos de mediciones a campo, especialmente para el mantillo y
restos de combustible leñoso grueso, producirá
resultados de consumo y emisiones más precisos que aquellos que usan solamente datos de
carga provistos por LANDFIRE-FCCS o LANDFIRE-FLM. Los modelos de emisiones preci-
Page 110
in representing emissions and complying with air quality regulations,
thus ensuring the continued use of
fire in wildland management.
sos ayudarán a representar emisiones y a cumplir con las regulaciones sobre la calidad del
aire, de manera de asegurar el uso continuado
del fuego en el manejo de áreas naturales.
Keywords: coarse woody debris, duff, fire effects, fuel loading models, Fuels Characterization
Classification System, LANDFIRE
Citation: Hyde, J., E.K. Strand, A.T. Hudak, and D. Hamilton. 2015 A case study comparison of
LANDFIRE fuel loading and emissions generation on a mixed conifer forest in northern Idaho,
USA. Fire Ecology 11(3): 108–127. doi: 10.4996/fireecology.1103108
INTRODUCTION
The use of fire as a land management tool
is widely recognized for its ecological benefits, and as a historic disturbance that has driven succession across many ecosystems (Agee
1996, Hardy and Arno 1996, Rothman 2005).
While fire science and policy has advanced in
the last 50 years to better allow for the use of
fire in managing wildlands (van Wagtendonk
2007), increasingly stringent air quality regulations (US EPA 1990, Hardy et al. 2001, US
EPA 2015,) and an increased awareness of the
health impacts from smoke (Liu et al. 2015)
can make the use of fire as a management tool
difficult. In a recent United States survey, prescribed fire practitioners expressed that smoke
and air quality issues are the third greatest impediment to prescribed burning, following low
work capacity and unfavorable weather conditions (Melvin 2012). To continue using fire as
a management tool, land managers must plan
to meet management objectives, while also
limiting the impact of smoke on public health
and keeping smoke levels within regulatory
thresholds (NWCG 2014). Such planning may
often require the use of models to determine
the quantity of emissions generated by fire;
these models require many pieces of information, including expected fire size, fuel loading
characteristics, and fuel consumption. Of
these, fuel loading has been identified as the
most critical step in obtaining accurate smoke
predictions (Drury et al. 2014). Unfortunately,
in many areas there may be little or no measured data on fuel loading; this creates a major
difficulty in estimating fuel consumed and
emissions produced.
To address the lack of fuel loading information in planning, geospatial Fire Effects
Fuel Model (FEFM) layers developed by the
Landscape Fire and Resource Management
Planning Tools (LANDFIRE) program are often used. LANDFIRE data layers were developed for the contiguous United States, Alaska,
and Hawaii to provide consistent geospatial
data describing the vegetation type, structure,
fuel loading, and disturbances, regardless of
land ownership boundaries (Rollins 2009).
LANDFIRE is principally intended to inform
management and planning decisions made by
land management agencies in the United
States. It is also the only resource available
that provides the geospatial information outlined above across as wide an area as the continental US. To populate models for smoke
production, LANDFIRE FEFMs describe fuel
loading for duff, litter, woody fuels from
timelag size classes ranging from one hour
(≤0.6 cm) to 1000 hours (≥7.62 cm), and live
herb and shrub loading. Currently, there are
two FEFM choices available through LANDFIRE: one represents fuel loading based on the
Fuel Loading Model (FLM) categories developed by Lutes et al. (2009), and the other
based on Fuels Characteristics Classification
System (FCCS) categories developed by Ottmar et al. (2007). Both methods are derived
from extensive measured datasets; however,
FCCS is stratified to represent fuel loading by
vegetation type (Ottmar et al. 2007), while
FLM is stratified to represent fuel loadings by
their potential fire effects (Lutes et al. 2009).
The two LANDFIRE FEFMs are different not
only in how they stratify fuels, but also in their
reported fuel loadings.
There have been few studies that detail the
differences between these two LANDFIRE
FEFMs. One study evaluated their mapping
performance across the western United States
(Keane et al. 2013), and another compared
their loadings and resulting emissions as part
of a broader comparison of factors affecting
smoke predictions in Washington, USA (Drury
et al. 2014). When Keane et al. (2013) compared fuel loading and mapping accuracy of
FCCS and FLM LANDFIRE layers throughout the western United States to data from the
Forest Inventory and Analysis (FIA) program,
they found poor correlations between FIA and
LANDFIRE represented loadings, mainly due
to the high variability in fuel loadings. Drury
et al. (2014) compared FLM and FCCS FEFM
data with other local datasets and found the
landscape fuel loadings to range from 2.7 million Mg to 8.8 million Mg for their research
area in Washington, USA, depending on which
fuel loading dataset they used.
Studies such as these are extremely valuable for documenting the complexity and variation within fuel loading data, and identifying
the importance and challenges of applying
FEFM fuels data to model emissions. Our
study builds on the few evaluations of LANDFIRE FEFMs to date by comparing FEFM surface fuel loading with measured fuel loadings,
and using these loadings in two popular consumption and emissions modelsthe First Order Fire Effects Model (FOFEM) and Consumeto compare the resulting differences in
fuel consumption and emissions production,
while holding the site and environmental conditions constant. This provides insight into
the degree of fuel loading differences possible
Page 111
at smaller scales relative to the national or
sub-regional scales that LANDFIRE was developed to represent. Yet this 20 000 ha area is
large enough to fall within the range of fire
management units that land managers are
tasked to manage (USDI NPS 2005, USDA FS
2008). We compared duff, litter, herb, shrub,
and woody fuel loadings measured in forest
inventory plots to those shown on both LANDFIRE Fuel Loading Models (LANDFIRE-FLM) and LANDFIRE Fuels Characterization Classification System (LANDFIRE-FCCS) maps. Subsequent differences in
modeled consumption and emissions using
FOFEM and Consume are reported.
METHODS
Study Area
To evaluate potential differences in predicted fuel loadings and fire effects, we selected a 20 000 ha study area centered on Moscow
Mountain in Latah County, Idaho, USA (Figure 1). The mountain lies in the Palouse
Range of northern Idaho, with elevations ranging from 770 m to 1516 m. Moscow Mountain is dominated by mixed conifer forest tree
species including ponderosa pine (Pinus ponderosa C. Lawson var. scopulorum Engelm.),
Douglas-fir (Pseudotsuga menziesii [Mirb.]
Franco var. glauca [Beissn.] Franco), grand fir
(Abies grandis [Douglas ex D. Don] Lindl.),
western red cedar (Thuja plicata Donn ex D.
Don), western hemlock (Tsuga heterophylla
[Raf.] Sarg.), and western larch (Larix occidentalis Nutt.). Ponderosa pine and Douglas-fir habitat types occur on the xeric southern
and western aspects, grand fir and cedar-hemlock habitat types occur on the mesic northern
and eastern aspects (Cooper et al. 1991). The
majority of the land is owned by private timber companies, private non-commercial landowners, and public land holdings. Recent disturbances recorded between 2003 and 2009
were predominantly the result of forest man-
Page 112
Figure 1. 2009 orthoimagery of the Moscow Mountain, Idaho, USA, study area (outlined) from the United States Geological Survey. The white dot in the inset is the study area. Plot locations are indicated with
black dots.
agement practices including thinning, timber
harvesting, and prescribed burning (Hudak et
al. 2012). These activities have resulted in a
forest with varying stand ages and structures
that occur over a variety of biophysical settings (Falkowski et al. 2009, Martinuzzi et al.
2009, Hudak et al. 2012).
Plot Fuel Loadings
Plot data used in this study were collected
in 2009, with information on plot placement
and methodologies described in detail in Hudak et al. (2012). Following a stratified random sampling design of the study area, 0.04
ha fixed-radius field plots were placed ran-
domly within strata based on elevation, slope,
aspect, and percent forest cover. Plots that
randomly fell within agricultural areas were
subsequently excluded, leaving 87 forested
plots for this analysis. Within each plot, duff;
litter; coarse woody debris (CWD) in the
≥1000 hour (≥7.62 cm) size class; and fine
woody debris in one hour (<0.635 cm), ten
hour (0.635 cm to 2.54 cm), and 100 hour
(2.54 cm to 7.62 cm) size classes were measured and loading was determined as described by Hudak et al. (2009), briefly summarized as follows: fuel loading was determined
using two parallel 15 m Brown’s transects
(Brown 1974) centered 2.5 m upslope and
downslope from plot center. On each transect,
one hour and ten hour fuels were tallied over a
1.8 m segment, 100 h fuels over a 4.6 m segment, and 1000 h fuels over the entire length
of both transects. Shrub and herbaceous cover
were estimated ocularly and translated to loadings using equations from Brown (1981) and
Smith and Brand (1983). Duff and litter
depths were measured once at a set distance
along each transect (Brown 1981), and loading
was derived from relationships presented in
Brown et al. (1982) with bulk densities from
Woodall and Monleon (2008).
LANDFIRE Fire Effects Fuel Model Loadings
LANDFIRE FEFM map layers are available for both FCCS and FLM fuel classification systems. The FCCS system is composed
of fuel loading data organized by vegetation
type; each vegetation type is represented by
loadings derived from field data collected from
that vegetation type (Ottmar et al. 2007).
FLM fuel loadings are the result of several
field-collected datasets, which are grouped
into statistically distinct groups based on fuel
loading and modeled fire effects (i.e., emissions and soil heating; Lutes et al. 2009). Indepth comparisons of these approaches have
been addressed by Keane (2013).
For this study, we compared LANDFIRE
Refresh 2008 FEFMs to measured fuel loadings.
LANDFIRE-FCCS and LANDFIRE-FLM layers were generated using different methodologies. LANDFIRE-FCCS layers
were derived by matching FCCS fuelbeds to
LANDFIRE vegetation communities (Comer
et al. 2003) and vegetation type (McKenzie et
al. 2012, LANDFIRE Team 2014a). LANDFIRE-FLMs were derived by a series of database queries that matched LANDFIRE data to
the appropriate FLMs (Hann et al. 2012).
More specifically, Forest Inventory and Analysis (FIA) data (Woudenberg et al. 2010) were
keyed to FLMs (Lutes et al. 2009) and these
FLMs were systematically matched to LANDFIRE vegetation types and cover. We should
Page 113
note that the scope of our study focuses on the
surface fuel loadings represented in LANDFIRE map layers, not the FCCS and FLM fuel
classification systems that the layers are intended to represent.
Generating Emissions within
FOFEM and Consume
Consumption and emissions were generated using two common fire effects models:
Consume version 4.2 (FERA Team 2014) and
the Fire Order Fire Effects Model (FOFEM)
version 6.0 (Lutes 2012). Consume calculates
consumption and emissions based on empirical algorithms from many studies (Prichard et
al. 2005). The FOFEM model generates consumption based on equations from the BURNUP model (Albini and Reinhardt 1997) and
emission factors from Ward et al. (1993).
Evaluating results in both models is important
as FOFEM and Consume are both commonly
used in fire management and are integrated
into planning tools such as the Interagency Fuels Treatment Decision Support System (IFTDSS 2015). Consume is also integrated into
the BlueSky Framework that is used for emissions calculations (AirFire 2015). For this
study, we included the major compounds emitted by wildland fire that could be of concern
for reasons of human health effects, regulatory
impacts, or greenhouse gas emissions: carbon
dioxide (CO2), carbon monoxide (CO), methane (CH4), and particulate matter 2.5 μm and
10 μm (PM2.5 and PM10). Nitrogen oxides
(NOx) and sulfur dioxide (SO2) were also modeled using only FOFEM, and non-methane hydrocarbons (NMHC) were modeled using only
Consume as these options are specific to each
model. To parameterize these models we used
the values in Table 1 to simulate summer fire
conditions under which past fires in the region
have ignited (McDonough 2003).
Page 114
Table 1. Environmental parameters used to populate FOFEM and Consume under default ‘Low’
moisture conditions to simulate an early summer
fire.
Parameter
Moistures
Duff
10 hour
CWD
Soil
Fuel type
Region
Season
Input
40 %
10 %
15 %
10 %
Natural
Interior West
Summer
Statistical Comparison of Fuel Loadings
All analyses were conducted using R Statistical Software (R-Project 2013). We initially tested fuel loading differences using Bartlett’s test for equal variance (Bartlett 1937).
This indicated that the data did not meet the
assumption of homoscedasticity required for
parametric regression analysis. Therefore, we
used non-parametric statistical methods. Analysis of variance was chosen and performed using the Anova test from the “car” package
(Fox et al. 2014) as this version implemented
the test using heteroscedasticity-corrected coefficient covariance matrices. If a significant
difference was detected, further analysis was
conducted with the Dunnett-Tukey-Kramer
pairwise multiple comparison test adjusted for
unequal variances and unequal sample sizes
(Dunnet 1980) using the DTK package (Lau
2013) at the alpha = 0.05 significance level.
This method was used to compare fuel loadings, consumption, and emissions. To examine the influence of different fuels on the total
emissions produced, we used Hoffman and
Gardner’s Importance Index, a ratio of variances between total emissions generated and
each individual fuel component (Hoffman and
Gardner 1983 , Hamby 1994). Values close to
one indicate higher significance than values
closer to zero.
RESULTS
Fuel Loadings
In comparing LANDFIRE fuel loadings
with measured fuel loadings, all fuel components differed at the alpha = 0.05 significance
level with the exception of shrubs (Table 2,
Figure 2).
LANDFIRE-FCCS loadings
over-represented duff and herbs; under-represented litter, 10 h, and 100 h fuels; and did not
differ for 1 h fuels or CWD. LANDFIRE-FLM
under-represented duff, litter, fine (1 h, 10 h,
and 100 h), and CWD fuel loadings; over-represented herb loadings; but duff loading did not
Table 2. Mean fuel loads (Mg ha-1 and SD in parentheses) on measured plots and as modeled by LANDFIRE-FCCS and LANDFIRE-FLM. Asterisks indicate statistically significant difference relative to measured loading data at the P < 0.05 significance level.
Fuel
Duff
Litter
1h
10 h
100 h
CWD
Herb
Shrub
Total fuel
Measured
10.55 (10.20)
5.86 (4.13)
0.65 (0.47)
2.57 (2.19)
4.98 (5.20)
20.087 (23.33)
0.46 (0.28)
1.179 (3.08)
46.26 (32.49)
Mean plot loading
LANDFIRE-FCCS
31.89 (17.80)*
4.199 (1.37)*
0.81 (0.46)
1.85 (1.11)*
2.47 (3.41)*
18.45 (16.38)
0.68 (0.76)*
1.36 (1.51)
61.63 (34.81)*
LANDFIRE-FLM
7.76 (12.19)
3.66 (3.40)*
0.50 (0.32)*
1.65 (1.13)*
1.94 (1.66)*
2.75 (4.04)*
0.73 (0.76)*
3.65 (10.60)
22.64 (21.16)*
Page 115
Figure 2. Differences in fuel loading for measured plots, LANDFIRE-FLM, and LANDFIRE-FCCS
products. Bold horizontal lines indicate median values, asterisks represent significant differences relative
to measured loadings. Circles indicate outliers, and whiskers indicate the region between the first and
third quartiles.
differ. Duff and CWD fuel components
showed the most pronounced difference in
loadings, with LANDFIRE-FCCS duff loadings 200 % higher than measured loadings, and
300 % higher than LANDFIRE-FLM loadings.
LANDFIRE-FLM CWD loading was 9 times
lower than measured or LANDFIRE-FCCS
loadings.
When comparing LANDFIRE
FEFMs to each other, only duff, CWD, and 1 h
fuel loadings differed, with LANDFIRE-FCCS
having the greater loadings.
Modeled Consumption and
Emissions in FOFEM
The statistical relationships for fuel consumption mirrored those for fuel loading (Figures 2 and 3, Tables 2 and 3). Relative to measured consumption, the mean total surface
consumption from LANDFIRE-FCCS was
23 % higher, and LANDFIRE-FLM was 51 %
lower. It is apparent that the high LANDFIRE-FCCS duff loading led to the higher
Page 116
Figure 3. Differences in modeled consumption for measured, LANDFIRE-FLM, and LANDFIRE-FCCS
fuel loadings. Bold horizontal lines indicate median values, asterisks represent significant differences relative to results derived from measured loadings.
Table 3. Mean fuel consumption (Mg ha-1 with SD in parentheses) under fixed environmental conditions
or measured plots, and as modeled by LANDFIRE-FCCS and LANDFIRE-FLM, using FOFEM and Consume. Asterisks indicate statistically significant difference relative to estimates based on measured loading at the P < 0.05 significance level.
Fuel
Duff
Litter
1h
10 h
100 h
CWD
Herb
Shrub
Total fuel
Mean plot consumption in FOFEM
LANDFIRE- LANDFIREMeasured
FCCS
FLM
6.98 (6.84)
20.64 (11.66)*
5.35 (8.38)
5.83 (4.16)
4.14 (1.21)*
3.68 (3.23)*
0.65 (0.49)
0.76 (0.44)
0.49 (0.29)*
2.58 (2.19)
1.77 (1.17)*
1.62 (1.19)*
4.56 (5.29)
2.32 (3.46)*
1.47 (1.25)*
10.59 (16.88)
8.60 (10.84)
0.53 (0.67)*
0.45 (0.28)
0.66 (0.61)*
0.70 (0.70)*
0.70 (1.85)
0.99 (1.20)
1.99 (5.87)
32.35 (25.46) 39.89 (23.40) 15.83 (14.30)
overall consumption, and that the low CWD
loading in the LANDFIRE-FLM contributed
to less consumption. This in turn had a direct
effect on the emissions modeled. All modeled
emissions, with the exception of NOx, were
significantly higher when modeled using
LANDFIRE-FCCS loadings, and lower when
Mean plot consumption in Consume
FCCS
FLM
3.36 (6.48)
5.67 (8.48)
2.31(10.83)
4.45 (3.98)
3.11 (1.66)*
2.32 (1.71)*
0.65 (0.49)
0.75 (0.44)
0.49 (0.29)*
2.24 (1.89)
1.53 (1.00)*
1.44 (0.98)*
3.93 (4.06)
1.84 (2.70)*
1.55 (1.30)*
17.06 (19.41) 14.20 (14.17)
1.84 (1.56)*
0.42 (0.26)
0.61 (0.57)*
0.64 (0.65)*
1.02 (2.88)
1.41 (1.74)
3.10 (9.48)
33.12 (25.90) 29.13 (18.61) 13.69 (16.08)*
using LANDFIRE-FLM loadings, while emissions derived from measured fuel loadings fell
in between (Table 4, Figure 4).
The relative importance of CWD and duff
to total emissions was reaffirmed and quantified using the importance index (Table 5).
Duff and CWD stood out as the primary con-
Page 117
Table 4. Mean modeled emissions (Mg ha-1 with SD in parentheses) calculated using FOFEM and Consume for measured plots, LANDFIRE-FCCS, and LANDFIRE-FLM. Asterisks indicate statistically significant difference relative to estimates based on measured loading at the P < 0.05 significance level.
Effect
CH4
CO
CO2
PM2.5
PM10
SO2
NOx
NMHC
Plot-level values FOFEM
FCCS
FLM
0.32 (0.30)
0.46 (0.30)* 0.13 (0.14)*
6.83 (6.56) 10.00 (6.64)* 2.67 (3.00)*
45.20 (34.09) 52.81 (29.57) 23.39 (21.90)*
0.53 (0.50)
0.76 (0.50)* 0.22 (0.23)*
0.63 (0.59)
0.90 (0.59)* 0.25 (0.27)*
0.03 (0.03)
0.04 (0.02)
0.02 (0.01)*
0.03 (0.03)
0.02 (0.01)*
0.02 (0.03)
tributors to total emissions in all cases, with
the exception of LANDFIRE-FLM data, in
which duff and shrub loadings were the primary contributors. Although shrub loadings did
not statistically different in our study, shrub
loadings tended to be higher in LANDFIRE-FLMs compared to other sources.
Modeled Consumption and
Emissions in Consume
With the exception of duff, the relationships between fuel loading and modeled consumption when using Consume remained the
same as with FOFEM; modeled duff consumption was much lower when using Consume (Table 3). Duff consumption using
LANDFIRE-FCCS loadings did not significantly differ from consumption generated
from measured loadings. Because of this, the
overall modeled fuel consumption from
LANDFIRE-FCCS did not significantly differ
from the fuel consumption generated by measured loadings. However, the modeled consumption from LANDFIRE-FLM was significantly lower than consumption from measured
loadings, with mean total surface fuel consumption 59 % less than that derived from
measured fuel loadings.
The importance index for the consumption
and total emissions in Consume was similar
Plot-level values Consume
FCCS
FLM
0.19 (0.18)
0.19 (0.14)
0.06 (0.11)*
3.67 (3.38)
3.65 (2.65)
1.20 (2.02)*
51.90 (39.72) 44.82 (28.11) 22.08 (25.22)*
0.29 (0.25)
0.27 (0.19)
0.11 (0.15)*
0.33 (0.28)
0.30 (0.21)
0.12 (0.16)*
0.16 (0.14)
0.15 (0.11)
0.05 (0.08)*
to the FOFEM emissions importance index
(Table 5). Duff consumption was still an important component with regard to emissions
production, even though it did not statistically
differ between measured and modeled fuel
datasets when modeled with Consume. When
emissions were evaluated, the LANDFIRE-FLM generated emissions were significantly lower than those generated using measured fuel loadings. Emissions generated using LANDFIRE-FCCS and measured fuel
loadings did not differ from each other (Table
4).
DISCUSSION
Measured Versus Modeled Fuel Loading
Duff and CWD led to the most significant
differences in modeled consumption and emissions. LANDFIRE-FLMs contained higher
shrub loadings, although this number did not
result in a statistically significant difference,
nor was it great enough to influence the total
surface fuel loading when consumption and
emissions were modeled. While the cause for
these LANDFIRE-FLM shrub values to be so
much higher is not known, the FLM system itself was developed with very little available
shrub data (Lutes et al. 2009). This likely influenced which FLMs were available to assign
Page 118
Figure 4. Differences in modeled emissions for measured, LANDFIRE-FLM, and LANDFIRE-FCCS
fuel loadings. Bold horizontal lines indicate median values, asterisks represent significant differences relative to results derived from measured loadings.
Page 119
Table 5. Hoffman and Gardner Importance Index for each FEFM and each fuel type shows that the fuel
of relative importance to the total emissions produced varied depending by FEFM. Emissions from measured data and FCCS fuelbeds were most influenced by CWD and duff, and FLM by duff and shrubs, respectively. Highest values are indicated in bold.
Fuel
Duff
Litter
1h
10 h
100 h
CWD
Herb
Shrub
Importance Index FOFEM
FCCS
FLM
0.012
0.043
0.053
0.002
0.000
0.004
<0.001
<0.001
<0.001
0.001
<0.001
<0.001
0.003
0.002
0.001
0.063
0.048
0.001
<0.001
<0.001
<0.001
0.032
0.001
0.001
to LANDFIRE maps when the LANDFIRE-FLM was created. Because the scope of
this study focused on a mixed conifer ecosystem, our shrub data were somewhat limited
and probably provided little insight in
shrub-dominated ecosystems where shrubs are
a large fuel component. Further investigation
of these LANDFIRE layers in shrub-dominated systems and further fuel loading data from
shrub ecosystems would be beneficial to further refining FLMs and the resulting LANDFIRE-FLM data for shrub ecosystems.
When comparing each fuel component for
measured and LANDFIRE-represented loadings with those of other mixed conifer systems, all three of our fuel loading sets fell
within the ranges observed by other researchers (Table 6). Focusing on duff and coarse
woody debris, we found LANDFIRE-FCCS
mean duff loading exceeded our measured values, but more closely resembled the ranges
found in other mixed conifer forests. Thus, it
is possible that our study area may have had
less duff loading than other mixed conifer forests. When evaluating mean CWD loadings,
we found the wide range noted in other studies, from 0.5 Mg ha-1 to 37 Mg ha-1; LANDFIRE-FLM mean CWD loadings were at the
low end of this range averaging 0.53 Mg ha-1,
while our measured data and LAND-
Importance Index Consume
FCCS
FLM
0.022
0.073
0.0156
0.008
0.003
0.004
<0.001
<0.001
<0.001
0.002
0.001
0.001
0.009
0.007
0.002
0.196
0.204
0.003
<0.001
<0.001
0.001
0.119
0.004
0.003
FIRE-FCCS were 10.6 Mg ha-1 and 8.6 Mg
ha- 1, respectively.
Our results support a broader evaluation of
the importance of various steps in the emissions modeling process in which Drury et al.
(2014) compared LANDFIRE-represented
loadings to a custom loading map based on
measured data. Like our results, their duff
loading was higher for LANDFIRE-FCCS relative to loadings represented using measured
data, while in our study the LANDFIRE-FCCS
total loadings were greater. Drury et al. found
a wide range in possible fuel loadings depending upon the method chosen, as did we, and
concluded that custom fuel loading layers derived from measured data produced the most
reliable emissions estimates. Of the two
LANDFIRE fuel layers, Drury et al. found the
LANDFIRE-FCCS layer produced results
closer to the custom loading layers. We found
this to be true in our study when modeling
emissions with Consume, but still found
LANDFIRE-FCCS to produce higher emissions values when modeled using FOFEM.
In another study that compared classification, mapping accuracy, and fuel loadings of
LANDFIRE-FCCS and LANDFIRE-FLM to
Forest Inventory and Analysis (FIA) plot data
across the western US, Keane et al. (2013)
found poor performance in both LAND-
Page 120
Table 6. Fuel loading for other mixed conifer forests in the western United States compared with mean
fuel loading from this study (in Mg ha-1). Standard deviations, when present, are indicated in parentheses.
Values from this study are indicated in bold in the last three rows.
Source
Hille and
Stephens
2005
Sikkink and
Keane 2008
Sikkink and
Keane 2008
Sikkink and
Keane 2008
Sikkink and
Keane 2008
Sikkink and
Keane 2008
Youngblood
et al. 2008
Youngblood
et al. 2008
Raymond
and Peterson
2005
Raymond
and Peterson
2005
Kobziar et
al. 2006
Kobziar et
al. 2006
Kobziar et
al. 2006
Reinhard et
al.1991
Reinhard et
al. 1991
1
10
100 1000 h 1000 h
Duff Litter hour hour hour sound rotten Herb
17.8 17.8 2.0
(3.6) (3.6) (0.2)
6.3
(0.7)
5.8
(1.6)
0.019 1.649 0.513
0.012 1.297 0.671
0.107 0.709 1.105
1.155 4.390 5.682
2.586 5.567 7.849
22.27 5.9 0.94 1.56
(7.52) (0.97) (0.2) (0.33)
25.48 3.74 0.37 0.64
(7.03) (0.44) (0.12) (0.21)
52
(1.3)
48.4
(1.6)
4.16
(0.59)
3.04
(0.67)
6.0
(3.3)
15.8
(4.3)
0.683 (sound
and rotten)
0.549 (sound
and rotten)
0.937 (sound
and rotten)
0.600 (sound
and rotten)
0.863 (sound
and rotten)
9.63 7.31
(3.46) (2.5)
8.88 7.97
(4.26) (0.61)
Elevation
(m)
North-central Sierra 1200 to
Nevada, California
1500
0.545
NW Rockies*
0.659
NW Rockies
0.581
NW Rockies
0.615
NW Rockies
0.636
NW Rockies
Blue Mountain
Region, Oregon
Blue Mountain
Region, Oregon
730 to
2130
730 to
2130
730 to
2130
730 to
2130
730 to
2130
1040 to
1480
1040 to
1480
1.2
4.1
4.8
1.2 Oregon Coast Range
670 to
850
4.4
6.8
8.7
1.2 Oregon Coast Range
670 to
850
1.25
(0.87)
1.13
(1.04)
0.9
(0.71)
4.53 9.93 7.52 14.18
(3.23) (8.18) (16.82) (23.31)
5.53 6.17 7.91 29.02
(4.97) (7.15) (17.04) (40.86)
2.9
4.25 2.57 26.62
(2.3) (4.12) (5.36) (65.62)
Other values are logging slash,
not natural fuels
Other values are logging slash,
not natural fuels
10.55 5.86 0.65 2.57 4.98 20.09 (23.33)
(10.20) (4.13) (0.47) (2.19) (5.20) (sound and
rotten)
2.75
(4.04)
LANDFIRE- 7.76 3.66 0.50 1.65 2.47
(sound
and
FLM
(12.19) (3.40) (0.32) (1.13) (3.41)
rotten)
LANDFIRE- 31.89 4.19 0.81 1.85 1.94 18.45 (16.38)
FCCS
(17.8) (1.37) (0.46) (1.11) (1.66) (sound and
rotten)
Measured
*
-
Location
NW Rockies includes parts of Idaho and Montana, USA.
Nevada, California
1410
Nevada, California
1410
Nevada, California
1410
900
to
NW Rockies
1200
900 to
NW Rockies
1200
0.46
(0.28)
NW Rockies
770 to
1516
0.73
(0.76)
NW Rockies
770 to
1516
0.68
(0.76)
NW Rockies
770 to
1516
Page 121
FIRE-represented FEFMs. LANDFIRE-FLM
tended to under-predict loadings while LANDFIRE-FCCS tended toward over prediction.
However, LANDFIRE-FLM loadings had
lower root mean squared errors (Keane et al.
2013). Our findings here support the work of
Keane et al. (2013) and Drury et al. (2014) in
describing the tendency of LANDFIRE-FCCS
to have higher loadings relative to LANDFIRE-FLMs.
tion with both fire effects models, but the lower duff consumption in Consume, relative to
FOFEM, led to emissions outputs in which
LANDFIRE-FCCS derived emissions did not
differ from those derived from measured loadings. This difference in duff consumption is
due to the fact that Consume and FOFEM calculate the consumption of duff using different
equations, derived from different data sets
(Reinhardt 2003, Prichard et al. 2005).
Modeled Consumption and Emissions
Using FOFEM
Research Implications
Relative differences in consumption values
when modeled with FOFEM mirrored those of
the loading values. High LANDFIRE-FCCS
duff and low LANDFIRE-FLM CWD loading
and consumption contributed to the total modeled emissions being highest when using
LANDFIRE-FCCS inputs, and lowest when
using LANDFIRE-FLM inputs. In examining
the fuel loading data (Table 2), there is high
variance in all fuel loading categories. This
supports the work by Keane et al. (2013), who
noted the high variance inherent in all categories of fuel loading, and the difficulties caused
by spatial variation when trying to represent
fuel loadings across large landscapes. Consumption followed the pattern of the total fuel
loading values for the landscape, with LANDFIRE-FCCS being the highest, FLM being the
lowest, and measured values in the middle.
This in turn produced higher emissions from
LANDFIRE-FCCS and lower emissions from
LANDFIRE-FLM, highlighting the differences in emissions outcomes depending upon the
choices made to represent fuel loadings.
Modeled Consumption and Emissions
Using Consume
In comparing consumption and emissions
from Consume, the choice of model has an effect on emissions generated. In this study,
there were similar trends in modeled consump-
In modeling emissions, fuel loadings have
been identified as the most crucial variables
(Drury et al. 2014), yet they represent one of
the greatest uncertainties in modeling emissions (French et al. 2011). In a detailed discussion on the topic, Keane et al. (2013) identified several factors creating difficulties in
quantifying fuel loadings. These include lack
of data to develop thorough loading maps; the
use of classification systems that were developed from discrete plot locations but then applied to large, national-scale areas; and the inherent difficulty of classifying fuels into categories such as hourly size classes and duff,
when each of these size classes may have different degrees of variation at different spatial
scales (Keane et al. 2012, 2013). If existing
fuel loading classification maps are to be improved, more data are necessary. The results
of our study indicate that data on CWD and
duff should be priorities, due to the relative
importance of these fuels to overall emissions
in mixed conifer forests (Table 5). While consumption didn’t statistically differ for the specific case of shrubs, shrub loading accounted
for a great deal of variability in emissions from
LANDFIRE-FLMs (Table 5), a classification
that was developed with little available shrub
data (Lutes et al. 2009). For the case of
LANDFIRE-FLMs, having additional data on
shrub loadings would be beneficial.
Despite being represented at a 30 m resolution, LANDFIRE data layers are intended to
Page 122
be used at larger, sub-regional to national
scales (LANDFIRE Team 2014b). Data from
fuel loading maps may work for finer scales;
however, there will likely be greater need to
supplement that data with local knowledge.
Based on our findings in a 20 000 ha area, using measured data, especially for duff and
CWD loadings, is preferable relative to unaltered LANDFIRE layers. However, we understand that measured data are often unavailable,
may be incomplete, or limited in availability.
Management Implications
If monitoring resources are available,
emission estimates will be improved by having more information on duff loading, as differences in duff loading lead to the greatest
differences in emissions, followed by CWD.
For coarse woody debris, the planar intercept
sampling methods have been most commonly
used in forests such as in this study, although
the Photoload (Keane and Dickinson 2007 )
method has also performed well (Sikkink and
Keane 2008). Duff sampling is often performed via sampling points along a planar intercept to gather both loading and depth
(Brown 1974). The fuel photoseries guides
available for many ecosystems provide estimates of duff loading (Ottmar et al. 2003), but
there are few studies comparing their performance relative to the traditional method. If
measured data are not available, one could
model with both the LANDFIRE-FLM and
LANDFIRE-FCCS derived fuel loadings, and
then average the two sets of results.
The use of systems such as the Wildland
Fire Decision Support System (WFDSS) and
the Interagency Fuels Treatment Decision
Support System (IFTDSS) also hold potential
for obtaining measured fuel loading information (IFTDSS 2015, WFDSS 2015). These
systems provide online access to several models to represent fire behavior and effects (including emissions), but they also provide an
easy platform from which data can be shared
from user to user. In the future, it would be
ideal to see a searchable database of user-provided fuel loadings within these decision support systems, similar to the searchable data
available through the Fire Research and Management Exchange System (FRAMES) Resource Catalog (FRAMES 2015).
This study has characterized the potential
differences in LANDFIRE-represented fuel
loadings in a mixed conifer case study area,
and their impact on the emissions modeling.
While using measured data provides the most
reliable outcome, either by itself or to help
supplement the LANDFIRE data, this is not
always possible. Web-based systems can aid
in finding and sharing data; however, a search
for the keywords “duff” and “coarse woody
debris” in FRAMES returned 34 and 3 results,
respectively. While online systems can be
powerful sources of information, there is clearly a need for additional data with which tools
such as the LANDFIRE map layers could be
strengthened. In the interim, information on
the relative differences in fuel loadings from
LANDFIRE-represented data may be useful to
managers who are tasked with quantifying
emissions for fire management planning. Using all of these resources will aid in generating
more accurate emissions estimates in a climate
where regulatory pressure and the need to accurately represent potential emissions from
fire are increasing.
ACKNOWLEDGEMENTS
The authors would like to thank the National Wildfire Coordinating Group’s Fuels Committee
for providing funding to the National Interagency Fuels Technology Transfer, which made this
research possible. Additional thanks go to the USDA Forest Service for providing measured fuel
loading, and to forestry technician P. Fekety for data preparation.
Page 123
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van Mantgem et al.: Faunal Response to Fire in California
Page 128
Review Article
FAUNAL RESPONSES TO FIRE IN CHAPARRAL AND SAGE SCRUB
IN CALIFORNIA, USA
Elizabeth F. van Mantgem1, Jon E. Keeley1*, 2, and Marti Witter3
US Geological Survey, Western Ecological Research Center,
Sequoia-Kings Canyon Field Station,
47050 Generals Highway, Three Rivers, California 93271-9651, USA
1
2
Department of Ecology and Evolutionary Biology, University of California,
612 Charles E. Young Drive South, Los Angeles, California 90095, USA
3
National Park Service, Santa Monica Mountains National Recreation Area,
401 West Hillcrest Drive, Thousand Oaks, California 91360, USA
*Corresponding author: Tel.: +1-559-565-3170; e-mail: [email protected]
ABSTRACT
RESUMEN
Impact of fire on California shrublands has been well studied but nearly
all of this work has focused on plant
communities. Impact on and recovery of the chaparral fauna has received only scattered attention; this
paper synthesizes what is known in
this regard for the diversity of animal
taxa associated with California shrublands and outlines the primary differences between plant and animal responses to fire. We evaluated the primary faunal modes of resisting fire
effects in three categories: 1) endogenous survival in a diapause or diapause-like stage, 2) sheltering in
place within unburned refugia, or 3)
fleeing and recolonizing. Utilizing
these patterns in chaparral and sage
scrub, as well as some studies on animals in other mediterranean-climate
ecosystems, we derived generalizations about how plants and animals
differ in their responses to fire impacts and their postfire recovery. One
consequence of these differences is
El impacto del fuego sobre los arbustales de California ha sido muy bien estudiado, aunque casi
todos esos estudios se han enfocado sobre comunidades vegetales. El impacto sobre, y la recuperación de, la fauna del chaparral, ha recibido
sólo una escasa atención; este trabajo sintetiza lo
conocido al respecto sobre la diversidad de los
taxones animales asociados con los arbustales de
California y delinea las diferencias primarias entre las respuestas al fuego de plantas y animales.
Evaluamos los modos primarios de la fauna de
resistir los efectos del fuego en tres categorías:
1) supervivencia endógena en estado de diapausa o similar, 2) cubriéndose en el lugar dentro de
refugios no quemados, o 3) huyendo y recolonizando. Usando esos patrones en el chaparral y
en el matorral de California, como así también
algunos estudios sobre plantas y animales de
otros ecosistemas con clima mediterráneo, derivamos generalizaciones sobre cómo plantas y
animales difieren en sus respuestas al impacto
del fuego y su recuperación post-fuego. Una
consecuencia de esas diferencias es que la variación en el comportamiento del fuego tiene un
mayor potencial de afectar animales que plantas.
Por ejemplo, las plantas se recuperan del fuego
Page 129
that variation in fire behavior has a
much greater potential to affect animals than plants. For example, plants
recover from fire endogenously from
soil-stored seeds and resprouts, so fire
size plays a limited role in determining recovery patterns. However, animals that depend on recolonization of
burned sites from metapopulations
may be greatly affected by fire size.
Animal recolonization may also be
greatly affected by regional land use
patterns that affect colonization corridors, whereas such regional factors
play a minimal role in plant community recovery. Fire characteristics such
as rate of spread and fire intensity do
not appear to play an important role in
determining patterns of chaparral and
sage scrub plant recovery after fire.
However, these fire behavior characteristics may have a profound role in
determining survivorship of some animal populations as slow-moving,
smoldering combustion may limit survivorship of animals in burrows,
whereas fast-moving, high intensity
fires may affect survivorship of animals in aboveground refugia or those
attempting to flee. Thus, fire regime
characteristics may have a much greater effect on postfire recovery of animal
communities than plant communities
in these shrubland ecosystems.
de manera endógena mediante la germinación
de semillas o el rebrote de tallos preservados en
el suelo, de manera que el tamaño del incendio
juega un rol muy limitado en determinar los patrones de recuperación. Por supuesto, los animales que dependen de la recolonización de
áreas quemadas provenientes de metapoblaciones pueden ser muy afectados por el tamaño del
incendio. La recolonización animal también
puede ser muy afectada por el patrón de uso regional de la tierra, que afecta los corredores de
colonización, mientras que esos patrones regionales juegan un rol muy menor en la recuperación de las comunidades vegetales. Las características del fuego como velocidad de avance e
intensidad no parecen tener un rol importante
en determinar los patrones de recuperación de
los chaparrales y matorrales después de un incendio. Sin embargo, esas características del
comportamiento del fuego pueden tener un rol
muy importante para determinar la supervivencia de algunas poblaciones de animales, dado
que los fuegos que se desplazan y arden lentamente pueden limitar la supervivencia de animales en cuevas o madrigueras. Por otro lado,
los fuegos que se desplazan rápidamente y de
alta intensidad pueden afectar la supervivencia
de animales en refugios que están sobre el suelo o de aquellos que intentan huir del fuego.
Por esas razones y en ecosistemas de arbustales, las características del régimen de fuego
puede tener un efecto más pronunciado en la
recuperación post-fuego en comunidades animales que en las vegetales.
Keywords: chaparral, endogenous postfire recovery, fauna, fire behavior, recolonization, refugia,
sage scrub
Citation: van Mantgem, E.F., J.E. Keeley, and M. Witter. 2015. Faunal responses to fire in
chaparral and sage scrub in California, USA. Fire Ecology 11(3): 128–148. doi: 10.4996/
fireecology.1103128
INTRODUCTION
Chaparral and sage scrub shrublands in
California, USA, are two of the highest diversity plant communities in the world (Richer-
son and Lum 1980). Although climate and
soil interactions have long been considered responsible for this extraordinary diversity, it is
apparent that fire has played a significant role
in shaping these communities. Here, as in
many fire-prone ecosystems, fire is a natural
ecosystem process, and artificial perturbations
to the fire regime are viewed as ecosystem disturbances. Decades of field studies have laid
the framework for understanding vegetation
responses to fire; however, animal responses
have received far less attention. The purpose
of this paper is to review the literature on California’s wildlife responses to shrubland fires,
and then outline our current understanding of
the main differences in plant and animal responses to fire in these ecosystems.
In many ways, wildlife recovery following
fire is profoundly different from plant recovery. Most of California’s shrubland plant species regenerate endogenously, meaning that
they germinate from a seedbank or resprout
from vegetative parts already in place, and exogenous sources that might recolonize the site
are relatively unimportant (Keeley et al.
2005a). In contrast, the recovery of animal
populations after a shrubland wildfire is more
variable. We suggest that the diversity of animal responses to fire can be conveniently categorized into one of three types: 1) insect diapause stages such as eggs and pupae are dormant in the soil at the time of fire and lead to
rapid postfire regeneration much the way plant
seed banks germinate after fire; 2) animals
may seek refuge in burrows, rock outcrops,
randomly unburned patches, or fire-resistant
riparian areas (in essence, they shelter in
place); or 3) they either flee the fire or succumb to it and must recolonize from outside
the burn perimeter. It is recognized at the outset that populations of some species may fall
into more than one of these categories.
We began our synthesis by reviewing published literature on postfire responses of all
fauna in chaparral and sage scrub ecosystems
(J. Keeley, US Geological Survey, Three Rivers, California, USA, unpublished data).
Where instructive, we have included a limited
amount of literature on postfire animal responses from other mediterranean-climate
shrublands. Our goal was to develop general-
Page 130
izations about how fire impacts different faunal components, how fire behavior characteristics may differentially impact these three functional types, and how postfire recovery varies
between these types.
FIRE IMPACTS AND FAUNAL
RESPONSES IN CALIFORNIA
SHRUBLANDS
In reviewing the available research on the
range of animal groups considered here, we
addressed two issues: how fire impacts populations and how populations recover following
fire. These two issues are sometimes viewed
as either direct or indirect fire responses (Bradstock et al. 2005, Engstrom 2010, Robinson et
al. 2013). Direct responses are the immediate,
short-term, proximate behaviors by animals
during a fire, such as running and hiding, or
succumbing to the heat, smoke, and flames.
Often there is little research describing these
behaviors, and the evidence of fire mortality is
typically captured by postfire population
spikes or troughs (Quinn 1979, Stromberg
1997, Underwood and Quinn 2010, Driscoll et
al. 2012).
Indirect responses concern the means of
recovery in the altered postfire environment
over time. These responses are influenced by
both temporal and spatial variation, including
the past history of fire regimes on the site and
the pattern and scale of vegetation mosaics
present at the time of fire, along with any accompanying faunal metapopulation dynamics
(Bradstock et al. 2005, Robinson et al. 2013).
In describing both the direct and indirect
responses of animals to fire, we have stratified
each taxon into vertical zones that include:
subterranean, ground-dwelling, arboreal or aerial, and amphibious fauna (Sugihara et al.
2006). At the outset, we need to recognize that
both direct and indirect responses have not
been studied for all groups; however, we have
tried to capture the level of information available for different groups.
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Arthropods
ther leading to complexity in predicting fire effects on these organisms.
Ground-dwelling. As with other arthropod
groups, studies of the direct effects of fire on
ants and spiders are not available in shrubland
habitat. However, in a postfire study from adjacent oak woodland following a prescribed
fire in California, all ants and spiders recovered within a year (Underwood and Quinn
2010). The slowest were two spiders (Class
Arachnida, Order Araneae): diurnal ambush
spiders (Family Thomisidae) and night running spiders (Family Gnaphosidae), whose
populations remained suppressed for up to
nine months after fire. Immediate postfire
population spikes were observed, but the authors attributed this to sampling bias, measuring a change in animal activity after the fire of
normally cryptic species, rather than measuring a true change in animal numbers. A fiveyear grassland study showed similar results after fire, with an immediate increase in cryptic
ant species 14 days after fire, but these recovered to normal abundance one year later (Underwood and Christian 2009). In contrast,
seed harvester ant species in this grassland
study were initially unaffected at 14 days after
fire, increasing significantly by the end of the
first year.
Indirect studies show that California native
shrubland ant species are only minimally impacted by wildfire, with the exception of the
seed-eating harvester ant, Messor andrei Mayr,
(Class Insecta, Order Hymenoptera). One
postfire study compared several ant species in
pre-fire samples to postfire samples collected
three years later in coastal sage scrub, chaparral, grassland, and riparian woodland (Matsuda et al. 2011). Populations of only two of the
eight ant species changed significantly. These
were in coastal sage scrub and had opposite responses: Crematogaster californica Wheeler
numbers decreased from 21 % to 2 %, while
the harvester ant (M. andrei) increased from
<1 % in pre-fire vegetation to 32 % after fire.
It follows that these two species may be spe-
Subterranean. The scorpions and solifugids (Class: Arachnida, Order Solifugae) of
California’s shrublands seem to be largely unaffected by fire, either directly or indirectly
(Brown et al. 2010). They are large-bodied,
nocturnal generalists that hide in insulated soil
and rock burrows during the day, meaning that
they do not require the shade of a mature, prefire shrub canopy. Further, they can go without food, hidden away in their burrows for
long periods of time, because of a unique
physiology allowing them to store energy. Because these animals live insulated underground
with caloric reserves, a short-term, crown fire
front that is relatively quick, cool, and smokeless is likely harmless to this group of subterranean arthropods. Other fire behaviors such
as slow-moving smoldering fires may impact
these organisms but there is limited information on these impacts.
In contrast, other mediterranean-climate
regions have reported significant differences in
soil-arthropod assemblages in burned plots
compared to control plots within the first two
years after burning (Pryke and Samways 2012,
Radea and Arianoutsou 2012, Pitzalis et al.
2013). Interestingly, in Italy, while species
composition changed significantly, there was
no significant difference in soil-arthropod diversity or evenness between burned and unburned pine forests (Pitzalis et al. 2013). Apparently, species evenness and diversity are affected by fire in independent ways that can
lead to an altered soil-arthropod composition,
illustrating the complexity of multivariate phenomena. Di Castri (1973) pointed out that, in
mediterranean-climate ecosystems, soil animals are heavily influenced by soil humus,
which is a function of aboveground vegetation
and stand age. The variability in aboveground
vegetation and stand age undoubtedly contributes to very different fire behavior patterns
with respect to fire regime parameters such as
soil humus combustion and rate of spread, fur-
cialized species as evidenced by their response
to changes in the habitat structure that resulted
from the fire.
The increase in harvester ant numbers also
seemed to cause an ant specialist, the horned
lizard (Phrynosoma coronatum Blainville), to
increase in number, but this observation was
not formally quantified (Matsuda et al. 2011).
Complicated trophic effects such as this would
likely diminish with close proximity to human
habitation as fewer harvester ants were found
in postfire urban fragments (Suarez et al.
1998). In this case, it was thought that the decreases in native ants might be a result of competition and predation by invasive, irrigation-dependent Argentine ants. In contrast to
the decreasing harvester ant numbers, postfire
spider and carabid beetle numbers, two other
predator groups, were positively correlated
with Argentine ant abundance (Bolger et al.
2000).
The Mediterranean omnivorous ant,
Aphaenogaster gibbosa Latreille, responded to
the changes in temperature and food sources
of the postfire environment by altering foraging behavior and diet preferences. This behavioral plasticity was considered key to its survivorship in a diversity of postfire habitats
(Lazaro-Gonzalez et al. 2013).
In California chaparral, six ixodid and argasid shrubland tick species were unaffected
after a prescribed fire (Class Arachnida, Order
Parasitiformes: Ixodes pacificus Cooley &
Kohls, Ixodes jellisoni Cooley & Kohls, I.
spinipalpis Hadwen & Nuttall, I. woodi Bishop, Dermacentor occidentalis Marx, and D.
parumapertus Neumann), as was the
soil-dwelling tick Ornithodoros coriaceus
Koch. It was concluded that all of the tick
species were sheltered in soil refugia during
the fire (Padgett et al. 2009).
Arboreal or aerial. Arboreal and aerial insects may survive fire during diapause with
below-ground eggs or pupae. For example,
the normally arboreal, wingless walking sticks
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(Timema cristinae Law & Crespi, Class Insecta, Order Phasmatoptera) survived the heat of
naturally occurring summer and fall chaparral
wildfires as diaspores insulated underground
from May to December. Diapause is the tough
egg stage in the walking stick’s lifecycle that
lies in the soil, akin to a seed in a plant soil
seedbank. If a fire occurs out of season, in the
winter or spring, mortality would greatly increase for the unprotected and vulnerable arboreal stages of an active walking stick population, including the larvae, nymphs, and
adults that feed or rest on chaparral foliage
(Sandoval 2000).
The mutualist pollinating yucca moth
(Tegeticula maculata Riley, Class Insecta, Order Lepidoptera) may similarly be partially
protected from fires by soil diapause. After
pollinating, ovipositing, and feeding on the
seeds of its host yucca plant, Hesperoyucca
whipplei (Torr.) Blake (formerly Yucca whipplei), the moth larvae emerge from the seeds
and drop to the ground to overwinter in a pupal stage underground. Following the October
2003 Cedar Fire in San Diego, California, T.
maculata experienced a population crash on a
long-term monitoring plot at the Elliot Chaparral Reserve, despite the fact that 90 % of the
moth’s host yucca plant survived and subsequently flowered normally. As a result of the
decline in T. maculata, there was low fruit set
and low seed viability in the first year after the
fire (D. Udovic, D. Bronstein, and M. Barnes;
Institute of Ecology and Evolution, University
of Oregon, Eugene, USA, unpublished data).
Despite the low population numbers, there was
a sufficient reservoir of pupae in the soil to repopulate the area in subsequent years. The
yucca moth population gradually recovered
over the next two years and yucca fruit production similarly increased (D. Udovic and J.
Bronstein, Institute of Ecology and Evolution,
University of Oregon, Eugene, USA, unpublished data). The authors pointed out that in a
mutualistic system dependent on insect pollination, slow recovery of pollinators could lead
to a delayed decline in the plant population despite high initial plant survivorship (D. Udovic
and J. Bronstein, unpublished data).
The population of a non-pollinating genus
of yucca moth, Prodoxus Riley spp., was also
significantly reduced after the Cedar Fire, although it was not monitored in the same systematic way as T. maculata. The difference
between the two species is that Prodoxus spp.
oviposit in the stalks and fleshy tissue surrounding fruits but then pupate there as well,
making them a completely arboreal and aerial
insect (Darwell et al. 2014). Because all of
the yucca stalks were burned in the fire, Prodoxus spp., lacking reservoir soil populations,
will likely take longer than T. maculata to recover (D. Udovic, Institute of Ecology and
Evolution, University of Oregon, Eugene,
USA, personal communication). Instead of
benefitting from endogenous survival, this genus may only recolonize from unburned yucca
stalk refugia.
One of the more phenomenal animal fire
responses is that representative of the fire beetle genus Melanophila Eschscholtz (Class Insecta, Order Coleoptera, Family Buprestidae).
It finds fires that are still hot via uniquely specialized heat receptors that detect infrared radiation. Even as wood smolders around it, this
genus will both breed and then lay eggs in any
newly dead wood. But the eggs do not hatch
for at least one year. So far in California, this
phenomenon has only been documented in conifer forests (Hart 1998) and it remains to be
seen if similar species are attracted to chaparral fires.
Winged insect communities are conspicuous between one and four years after a fire.
Specifically, they increase in richness and diversity, especially as sunny gaps in the overstory and smoky chemicals encourage fire annuals and herbaceous perennials to grow and
flower (Force 1981, 1982, 1990; Potts et al.
2003). In contrast, phytophagous and parasitic
hymenopterans only become common after
four years postfire, and biting flies, which are
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quite scarce directly postfire, are only common
in mature chaparral (Force 1982, 1990). It is
unclear whether this lag time is due to a requirement for changes in resources or a result
of long colonization times.
One rare California butterfly is negatively
impacted by fire (Marschalek and Deutschman
2008, Marschalek and Klein 2010). The Hermes copper (Lycaena [Hermelycaena] hermes
Edwards: Family Lycaenidae) lives in mature
coastal sage scrub and chaparral ecosystems in
and around San Diego. The butterfly never
travels far from its larval host plant, redberry
(Rhamnus crocea Nuttall) and adults feed
largely on the nectar of California buckwheat,
(Eriogonum fasciculatum Bentham), but it will
also feed on chamise (Adenostoma fasciculatum Hooker & Arnott) and tarplant (Deinandra
spp. Greene) nectar. The adults emerge from
mid-May to early June, to a fairly sessile and
territorial life. On average, they only disperse
11 m to 26 m in a single flight, but flights as
long as 1132 m have been recorded.
Genetic data suggest that the Hermes copper metapopulation around San Diego has
been historically well-linked, despite these
short range dispersal patterns. There is concern that urbanization and subsequent habitat
fragmentation, particularly in the face of recent large fire events, could result in localized
extirpation of some populations in the future
(Strahm et al. 2012).
Fruit flies (Family Drosophilidae) were
found to be quite resilient to fire, based on
postfire surveys of the large 1974 Soboba Fire
from an area of previous population surveys in
the 1930s and 1940s (Moore et al. 1979). The
flies found in the adjacent unburned area reappeared in burned plots almost immediately
through recolonization. Sampling in the first
season postfire (May to September 1975)
showed that species composition remained
constant and was similar to that observed nearly 40 years earlier. The only difference was
that the 1979 species list included two new
species of the obscura group (Drosophila per-
similis Dobzhansky & Epling and D. Miranda
Dobzhansky) when, previously, D. pseudoobscura Frolova was the only species recorded.
Although comprehensive studies of postfire faunal succession of aerial or arboreal arthropods are lacking for chaparral, such studies in Mediterranean Basin shrublands showed
that the community composition of bee pollinators changed as the structural diversity of
floral resources changed from herbaceous to
woody vegetation (Potts et al. 2003). This
suggests that, as California shrubland plant diversity declines after fire (Keeley et al. 2005b),
aerial pollinator species richness will follow
suit.
At present, we lack sufficient studies to
draw conclusions about how invertebrate strata vary in their response to fire. However,
there is reason to expect differences among the
functional groups. One Australian invertebrate
study concluded that surface arthropod assemblages were more resilient to fire than aerial
arthropod assemblages, the first recovering in
one year and the other in three years, respectively (Pryke and Samways 2012).
Reptiles and Amphibians
Terrestrial. There is limited data on the direct effects of fire on reptile and amphibian
species. Adult western fence lizards (Sceloporus occidentalis Baird & Girard) are known to
survive in insulated refugia, although the juvenile lizards seemed to be negatively impacted
by fire (Kahn 1960). Populations of this species also increased significantly after fire
(Rochester et al. 2010b), and Kahn (1960)
found that chaparral fire had little impact on
their food preferences or on female egg laying.
Rochester et al. (2010b) reported that both
chaparral and coastal sage scrub herpetofaunal
community diversity and composition changed
after the large 2003 southern California wildfires. There were increases in some taxa and
decreases in others but, overall, these communities remained simplified two years after fire.
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They found that the coastal whiptail (Aspidoscelis tigris Baird & Girard), coast horned lizard (Phrynosoma coronatum Blainville), common side-blotched lizard (Uta stansburiana
Blainville), and orange-throated whiptail (Aspidoscelis hyperythra Cope) populations increased after fire. In contrast, the California
toad (Anaxyrus boreas halophilus Camp) decreased, as was the case for the southern alligator lizard (Elgaria multicarinata Blainville),
garden slender salamander (Batrachoseps major Camp), and several snake species (yellow-bellied racer, Coluber constrictor Linnaeus; California kingsnake, Lampropeltis californiae Blainville; gophersnake, Pituophis
catenifer Blainville; and striped racer, Masticophis lateralis Hallowell). It was apparently
unclear how much of these community differences were due to patterns of survivorship versus ability to adapt to postfire conditions of
cover, soil moisture, and food resources.
However, the authors suspect that the more
open conditions after fire were largely responsible for the decreased herpetofaunal diversity
and that, with repeated fires, these sites might
be type converted to grass-shrub mosaics with
a depauperate fauna. This is consistent with
Lillywhite’s (1977) observation of a simplification of the animal community when the
shrubland was mechanically and chemically
type converted to be more like grassland.
Where there is minimal postfire habitat
change or small fire size, the impact of fire can
be minimal. In northern California scrub, the
effects of a small prescribed burn (65 ha) on
western yellow-bellied racers (Coluber constrictor mormon [Baird & Girard]) were indistinguishable between burned and unburned
plots (Thompson et al. 2013). This is consistent with the southern California findings of
persistent Coluber populations in grassland
and riparian habitat, but reduced populations
in more drastically altered postfire shrublands
(Rochester et al. 2010b).
Postfire studies in other mediterranean-climate areas provide rich data sources of the
long-term, indirect responses of herpetofauna
to fire (McDonald et al. 2012, Smith et al.
2014). Several Australian studies (Driscoll et
al. 2012, Valentine et al. 2012, Elzer et al.
2013, Nimmo et al. 2013, Smith et al. 2013)
and two French studies (Santos and Cheylan
2013, Couturier et al. 2014) support the idea
that fire response in reptiles and amphibians is
species specific rather than consistent across a
community (Rochester et al. 2010b, Thompson et al. 2013). Most herpetofauna are successional stage specialists, and the preservation of old-growth habitat is essential for reptile community conservation. For example,
the Australian chronosequence study by Nimmo et al.(2013) showed that even 100 years
postfire, the shrubland reptile community still
did not have a full, pre-burn species composition. Smith et al. (2013) suggested that nocturnal and burrowing animals tended to be
“early succession-early postfire” recovery animals, while leaf-litter dwellers tend to be late
successional animals.
Amphibious. California newt populations
survive fire and their postfire population sizes
are similar to prefire levels (Gamradt and Kats
1997). Stromberg (1997) witnessed an example of how individual California newts (Taricha torosa Rathke, in Eschscholtz) might occasionally survive the direct effects of fire.
During a prescribed burn in chamise-live oak
vegetation, he described two newts who were
moving rapidly (~5 cm sec-1) directly into a 5
cm to 10 cm flame front. The slime covering
their bodies foamed up, resembling egg meringue. Within 20 to 30 seconds, they were
through the flames and on the cooler, black
ashes of the litter. Upon close examination,
the now crusty white coating easily wiped off
their wet bodies. He did not observe any skin
blister and the skin color looked normal.
Stromberg’s conclusion was that foaming of
the skin secretions would dissipate heat and
could be a mechanism used by this species to
survive wildland fires. This protective coating
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was in some respects like the foam used on
homes to prevent their burning. Otherwise,
amphibious species are assumed to survive fire
by sheltering in place in aquatic or riparian
stream habitat, as suggested by the observation
of minimal impact of fire on herpetofaunal diversity in riparian habitats (Rochester et al.
2010b).
The most significant threat to amphibious
species following large wildfires is loss of
aquatic habitat from changes like increased
water temperatures, changes in terrestrial food
inputs, or from increased postfire erosion, debris flows, and other sedimentation processes.
Preferred aquatic habitat of the California
newt (pools and runs) was reduced from 37 %
to 16 % after a major wildfire in 1993 in the
Santa Monica Mountains. While adult population density remained stable, total egg masses
were reduced along with the decline in aquatic
habitat area (Gamradt and Kats 1997). Interestingly, as the amount of preferred breeding
habitat declined, selective pressure on larvae
was reduced as food preferences shifted from
cannibalism of conspecific larvae to earthworms that increased as a food source from
streambank erosion in the first several years
postfire (Kerby and Kats 1998).
Some amphibious species, such as the yellow-legged frog (Rana muscosa Camp) and
California red-legged frog (Rana draytonii
Baird & Girard), are more vulnerable to sedimentation impacts, which can drastically reduce or locally extirpate populations (Richmond et al. 2013, Backlin et al. 2015). Such
fire effects are of special concern for populations at their range boundaries because they
threaten the persistence of such species. The
red-legged frogs show no evidence that recent
fire events have left a genetic imprint in the
population, but there was evidence of a 75- to
100-year old genetic bottleneck that was potentially due to large disturbance events in the
past (Richmond et al. 2013).
Birds
Although birds can be stratified into
ground-dwelling versus aerial species, many
species in chaparral overlap in habitat usage,
so we will not attempt to sort out these different functional types. In general, birds are likely to survive the direct effects of fire because
of their mobility. The exceptions to this are
the eggs and nestlings that would be killed in
fires that burn in the spring during nesting season. Several recent examples of spring fires,
notably the 2009 Jesusita Fire in Santa Barbara, the 2013 Springs Fire in the Santa Monica
Mountains, and the May 2014 fires in northern
San Diego County, were the result of severe
winter droughts.
There are no reported observations of birds
sheltering in place in burned shrublands, so recovery is from recolonization of unburned islands or riparian corridors or outside of the
burn perimeter. Recolonization is a function
of fire size and available metapopulations outside the burn perimeter as well as habitat availability inside the burn perimeter. For example,
the special-status California gnatcatcher (Polioptila californica Brewster) prefers old growth
coastal sage scrub, with a mix of Artemisia
californica Lessing and Eriogonum fasciculatum Bentham, and at least 50 % canopy cover
(Beyers and Wirtz II 1995, Akçakaya and Atwood 1997, Atwood et al. 2002). Recovery is
a function of the rate of shrub recovery and
available habitat outside the burn perimeter.
The gnatcatcher is extremely sensitive to fragmentation of the coastal sage scrub vegetation
community, leaving it vulnerable to local extinction as the scrub itself is lost (Chase et al.
2000).
Another fragmentation study similarly
demonstrates that shrubland obligate birds will
become locally extinct over time as increased
fire and other disturbances cause the loss of
habitat corridors and connectedness within a
species’ metapopulation (Soule et al. 1988).
San Diego County’s cactus wren (Campylo-
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rhynchus brunneicapillus Lafresnaye) is another species at risk of extirpation because of
diminishing habitat area and quality. This sedentary species is declining because of habitat
loss, fragmentation edge effects in the form of
over-predation by Cooper’s hawks (Accipiter
cooperii Bonaparte), and drought combined
with increased fire frequency. According to
the Nature Reserve of Orange County, cactus
wren populations declined by over 80 % in the
last two decades, initially because of catastrophic wildfires (Preston and Kamada 2012).
In contrast to these unique fragmentation
studies, Mendelsohn et al. (2008) found that
low-elevation coastal sage scrub bird diversity
increased after fire, and that the bird community structure changed significantly for both
low-elevation chaparral and low-elevation
coastal sage scrub, but not for high-elevation
shrubland. The shift in community structure
for these two low-elevation plant communities
was attributed to increases in lazuli buntings
(Passerina amoena Say) and spotted towhees
(Pipilo maculatus Swainson) in burned chaparral, and postfire decreases of Anna’s hummingbirds (Calypte anna Lesson) in chaparral,
and wrentits (Chamaea fasciata Gambell) and
bushtits (Psaltriparus minimus Townsend) in
coastal sage scrub. Additionally, but in contrast to the results in the chaparral, spotted towhee numbers decreased in the burned coastal
sage scrub. Wirtz II (1979) reported similarly
mixed findings for chaparral birds. With differing study designs, Stanton (1986) and
Morearty et al. (1985) had conflicting results
with Mendelsohn et al. (2008), reporting decreased bird species richness for burned coastal sage scrub. Stanton (1986) concluded that
unburned habitat provided more habitat requirements for more individuals and species of
birds throughout the year than the burned areas. Nonresident, migratory species used
highly seasonal food sources that were little
used by resident species.
At the wildland-urban interface, where
there is a human use disturbance gradient (e.g.,
fire, farming, development, recreation, etc.)
from wildlands to urban neighborhoods, highest avian diversity occurs with moderate human disturbance in rural or exurban and suburban locations. However, the assortment of
avian species in these moderately human-managed sites also comprise widespread generalist
species and lack some of the unique localized
taxa like the California gnatcatcher, wrentit,
bushtit, and cactus wren (Soule 1991; Blair
1996; Sauvajot et al. 1998; Blair 2001a,
2001b; Mitrovich and Hamilton 2007; Preston
and Kamada 2012).
In Australia, a 100-year chronosequence
study by Watson et al. (2012) showed that
mid- and late-succession vegetation (>20 yr)
was critical for the recovery of Australian
shrubland bird communities. Likewise, Taylor
et al. (2012) found that avian species richness
was positively associated with increasing
amounts of older vegetation in landscapes, but
not with the proportion of recently burned
vegetation in landscapes. This was verified
with a more general small-vertebrate study
that included birds: Kelly et al. (2014) warned
that maximizing pyrodiversity does not maximize wildlife biodiversity. On the contrary,
old-growth vegetation was found to be disproportionately important to wildlife conservation. Robinson et al. (2014) agreed that naturally protected, old-growth refugia are essential for the long-term recovery and stabilization of avian communities after fire. Among
Australian researchers, only Sitters et al.
(2014) could support the commonly held idea
that age class pyrodiversity begets biodiversity
for birds, but they recommended increasing
the diversity in fire age classes for optimal bird
conservation by including both young and oldgrowth vegetation. Faivre et al. (2011) called
this “landscape pyrodiversity.”
Small Mammals
In direct response to fire, small mammals
must also attempt to either flee or shelter in
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place. According to Quinn (1979, 1990), animals that perished as a direct result of fire
were sometimes burned and sometimes unburned. Typically, animal corpses are found in
groups along roads and trails, in small clearings, or in small depressions in the ground,
suggesting unsuccessful attempts at sheltering
in place or an inability to outrun the fire. The
worst of the immediate fire casualties were the
dusky-footed woodrats (Neotoma fuscipes
Baird), California mice (Peromyscus californicus Gambel), brush rabbits (Sylvilagus bachmani Waterhouse), and California ground
squirrels (Spermophilus beecheyi Richardson)
(Quinn 1979, 1990).
In contrast, Stephens’ kangaroo rats (Dipodomys stephensi Merriam) in grassland and
coastal sage scrub (Price and Waser 1984, Magle et al. 2012) were not significantly impacted by fires, perhaps due to sheltering in burrows, coupled with the lower fire intensities in
these types of fuels.
The change in habitat after fire favors
some small mammals but not others. Increased open habitat favors deer mice, Peromyscus spp., and kangaroo rats, Dipodomys
spp., but taxa requiring more closed habitat
will recover more slowly, (e.g., the San Diego
pocket mouse, Chaetodipus fallax Merriam;
desert woodrat, Neotoma lepida Thomas; and
brush mouse, Peromyscus boylii Baird) (Lillywhite 1977, Padgett et al. 2009, Brehme et al.
2011). Not surprisingly, as the vegetation recovers, the animal community composition
changes with it, and this may be an on-going
process for a decade or more. Generalizations
at this stage are few; for example, one study
showed that even as the initially inflated deer
mouse population decreased with plant succession, the postfire abundance of the open-habitat-specialist kangaroo rat continued to rise,
doubling from 24 to 43 months after the 2003
Cedar Fire in southern California (Diffendorfer et al. 2012). More recently, Borchert and
Borchert (2013) observed that, even 10 years
after fire, small animal succession remained in
flux. It was hypothesized that recolonization
might be more successful along the perimeter
of a large burn than within the interior
(Schwilk and Keeley 1998); however, due to
species-specific differences and refugia within
burn perimeters, this phenomenon is not easily
demonstrated. Indeed, potential safe sites
during a fire such as presence of riparian habitat and prevalence of rocky substrate will affect recovery in species-specific ways (Diffendorfer et al. 2012).
In the case of bats, Rochester et al. (2010a)
found this extremely mobile taxon to be resilient to large fire events. Despite significant regional variation in community composition,
they found no difference in species composition between burned and unburned sites within
a community.
They concluded that the
wide-ranging nature of bats may eliminate local effects within the community.
Although most small mammal species
seem to be able to find refugia within burned
areas and thus are fairly resilient to natural
fire, one notable exception is the Point Reyes
mountain beaver (Aplodontia rufa phaea Rafinesque). This species showed little or no recovery five years after the 1995 Vision Fire
(Fellers et al. 2004). Based on a <2 % survival
rate (only 19 surviving beavers), the species
was found to have been almost eradicated
within the fire perimeter, with very little immigration from unburned areas. It was unclear
whether this failure to repopulate the burned
areas was a result of limited reproductive success in the following years or just unsuitable
resources within the burn perimeter (Fellers et
al. 2004, Forrestel et al. 2011).
Large Mammals
Large mammals either survive fire by fleeing ahead of the fire front or succumb to fast
moving fires. Recovery requires recolonization from metapopulations outside the fire perimeter. It has long been known that browsing
animals such as deer respond favorably to fire
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with increased populations due the increase in
available, more nutritious forage (Gibbens and
Schultz 1963, Scrivner et al. 1988, Klinger et
al. 1989). Indeed, studies of deer populations
that have flocked to new shrub growth on recently burned sites have perpetuated the myth
of chaparral senescence in older stands when,
in fact, new growth in the older stands is simply produced too high on tall shrubs, beyond
the reach of the deer (Keeley and Fotheringham 2001). This same observation has more
recently been made for the desert bighorn
sheep, Ovis canadensis nelson Merriam, which
apparently prefers chaparral that is no more
than 15 years old (Bleich et al. 2008, Holl et
al. 2012).
Recolonization even after very large fire
events does not seem to be an unsurmountable
task for many large herbivores and carnivores.
Turschak et al. (2010) observed 11 native species after large fire events in 2003 in San Diego County and concluded that mule deer
(Odocoileus hemionus Rafinesque), along with
carnivores and omnivores such as the mountain lion (Puma concolor Linnaeus), coyote
(Canis latrans Say), bobcat (Felis rufus Schreber), badger (Taxidea taxus Schreber), gray
fox (Urocyon cinereoargenteus Schreber), raccoon (Procyon lotor Linnaeus), striped skunk
(Mephitis mephitis Schreber), spotted skunk
(Spilogale gracilis Merriam), opossum (Didelphis virginiana Kerr), and long-tailed weasel
(Mustela frenata Lichtenstein) all recovered
within three years following a very large wildfire. For most of these species, there was little
evidence that relative abundance had changed
from the pre-fire levels. Turschak and colleagues suggested that the mobility of these
large mammals played a significant role in the
ability to recover after large fire events.
More recently, Schuette et al. (2014) reported results similar to Turschak et al. (2010).
They observed postfire carnivore numbers
from 27 to 43 months after the massive 2003
Cedar Fire in San Diego County and were unable to detect significant differences in occu-
pancy between unburned and burned plots in
gray fox, striped skunk, and bobcat. Only
coyotes showed an increase in the burned area,
peaking at 34 months after the fire. In this
study, as in others, the lag time between the
fire and the initiation of postfire wildlife monitoring limited the ability to evaluate how the
rate and spatial pattern of recolonization contributed to the observed population changes.
Population recovery was attributed to their
mobility and behavioral plasticity with respect
to habitat structure and diet.
Recolonization of burned sites is dependent on metapopulation dynamics outside the
burn perimeter. In high human density landscapes such as southern California, this is a
particular challenge because habitat fragmentation may eliminate parts of some metapopulations and disrupt corridors for recolonization. Crooks and Soule (1999) documented
how small, isolated shrubland fragments, disconnected by large areas of urbanization, lost
their larger carnivore species over time. The
fragments that were isolated from larger core
areas of habitat the longest were no longer
visited by any native carnivores, even though
research shows that coyote populations can
thrive in close proximity to humans (Fedriani
et al. 2001, Gehrt and Riley 2010). The difference here may be that the enhanced coyote
population was still connected to the coyote
metapopulation; however, more recent research shows a more variable response by
coyotes to humans and fire in a rural environment (Schuette et al. 2014). In the Crooks
and Soule (1999) study, within the most disturbed of the disconnected urban fragments,
the last remaining hunter was always the human subsidized super-predator, the ubiquitous
house cat, which has a cascading effect on
bird and mammal populations. This study illustrates that, as habitat fragments deteriorate
over time, the resilience of large mammals to
fire is further impaired.
Page 139
DISCUSSION
The literature reviewed here is summarized
in Table 1, along with our understanding of
how each of the taxa fit our hypothesized categories of fire response: 1) endogenous regeneration from diapause or diapause-like stages in
the soil, 2) sheltering in place within unburned
refugia, or 3) fleeing and recolonization.
In general, many soil- and ground-dwelling arthropods survive fire endogenously from
dormant soil-stored stages, much like plants.
For example, insects like walking sticks and
yucca moths seem to endure seasonal shrubland fires as resistant diapause structures.
There is little direct evidence for this fire survival strategy in other arthropod species; however, based on life histories, it is likely that it
applies to many others. Because endogenous
survival (of both plants and animals) is also a
useful survival strategy for the summer and
fall drought of the mediterranean-type climate,
it is perhaps best viewed as an ecosystem adaptation to seasonality rather than a fire-specific response (Keeley et al. 2011).
Animals that shelter in place in unburned
refugia such as burrows, rocks, riparian areas,
or unburned patches include many small vertebrates (reptiles, amphibians, and small mammals) and arthropods. While some refugia
such as burrows, rocks, and riparian areas are
predictable refugia, other unburned islands
within the fire perimeter will depend on fire
behavior, and thus their spatial distribution
will be unpredictable. These patches are
known as stochastic refugia and don’t have
any inherent qualities making them fire resistant (Robinson et al. 2013, New 2014).
The larger or more mobile animals that flee
a fire need to find adequate shelter outside the
fire perimeter until conditions are suitable for
recolonization. Thus, regional patterns of land
use and extent of habitat fragmentation will be
particularly important to these species. Recolonizing burned areas will depend on the distribution of metapopulations and patterns of suitable corridors.
Page 140
Table 1. Summary of animal responses to fire keyed to the literature within our three hypothesized functional categories.
Arthropods
Subterranean
Scorpions and solifugids
Ground-dwelling
Spiders
Ticks
Ants
Arboreal or aerial
Walking sticks
Yucca moths
Fire beetles
Pollinators, parasites,
and biting flies
Hermes copper
Drosophila
Other aerial insects
Reptiles and amphibians
Terrestrial
Amphibians
Birds
Small mammals
Large mammals
Literature
Endogenous
regeneration
1
XXX
2
3
4, 5, 6, 7
XXX
XXX
XXX
8
9, 10, 11
12
XXX
XXX
13, 14, 15, 16
XXX
XXX
17, 18, 19
20
21,2 2
XXX
XXX
XXX
XXX
XXX
XXX
23–35
36–39
40–59
3, 25, 60–69
70–77
1 = Brown et al. 2010
2 = Underwood and Quinn 2010
3 = Padgett et al. 2009
4 = Matsuda et al. 2011
5 = Suarez et al. 1998
6 = Bolger et al. 2000
7 = Lazaro-Gonzalez et al. 2013
8 = Sandoval 2000
9 = D. Udovic, Institute of Ecology and
Evolution, University of Oregon, Eugene, USA, personal communication
10 = D. Udovic D. Bronstein, and M.
Barnes; Institute of Ecology and
Evolution, University of Oregon,
Eugene, USA, unpublished data
11 = D. Udovic and J. Bronstein, Institute of
Ecology and Evolution, University of
Oregon, Eugene, USA, unpublished data
12 = Hart 1998
13 = Force 1981
14 =Force 1982
15 = Force 1990
16 = Potts et al. 2003
17 = Marschalek and Deutschman 2008
18 = Marschalek and Klein 2010
19 = Strahm et al. 2012
20 = Moore et al. 1979
21 = Keeley et al. 2005a,b
22 = Pryke and Samways 2012
23 = Kahn 1960
24 = Rochester et al. 2010b
25 = Lillywhite 1977
26 = Thompson et al. 2013
27 = Driscoll et al. 2012
28 =McDonald et al. 2012
29 = Valentine et al. 2012
30 = Elzer et al. 2013
31 = Nimmo et al. 2013
32 = Smith et al. 2013
33 = Smith et al. 2014
34 = Santos and Cheylan 2013
35 = Couturier et al. 2014
36 = Stromberg 1997
37 = Gamradt and Kats 1997
38 = Kerby and Kats 1998
39 = Richmond et al. 2013
40 = Beyers and Wirtz II 1995
41 = Akçakaya and Atwood 1997
42 = Atwood et al. 2002
43 = Chase et al. 2000
44 = Soule et al. 1988
45 = Preston and Kamada 2012
46 = Mendelsohn et al. 2008
47 = Wirtz II 1979
48 = Stanton 1986
49 = Morearty et al. 1985
Shelter
in refugia
Recolonization
XXX
XXX
XXX
XXX
XXX
XXX
XXX
XXX
50 = Soule 1991
51 = Blair 1996
52 = Sauvajot et al. 1998
53 = Blair 2001a,b
54 = Mitrovich and Hamilton 2007
55 = Preston and Kamada 2012
56 = Watson et al. 2012
57 = Taylor et al. 2012
58 = Robinson et al. 2014
59 = Sitters et al. 2014
60 = Quinn 1979
61 = Quinn 1990
62 = Price and Waser 1984
63 = Magle et al. 2012
64 = Brehme et al. 2011
65 = Diffendorfer et al. 2012
66 = Borchert and Borchert 2013
67 = Schwilk and Keeley 1998
68 = Rochester et al. 2010a
69 = Fellers et al. 2004
70 = Gibbens and Schultz 1963
71 = Keeley and Fotheringham 2001
72 = Bleich et al. 2008
73 = Holl et al. 2012
74 = Turschak et al. 2010
75 = Schuette et al. 2014
76 = Crooks and Soule 1999
77 = Fedriani et al. 2001
Page 141
There are good reasons for believing that
these animal functional types differ markedly
from plants in their response to fire regime
characteristics (Table 2). The primary parameter that drives different plant responses is fire
frequency (Keeley et al. 2012). Although
plants in this ecosystem can tolerate very long
fire return intervals, and this includes postfire
specialist annuals, much of the flora is poorly
adapted to frequent fires. However, a change
in fire frequency likely affects animals indirectly as the habitat changes.
For our three wildlife functional groups,
the other four fire regime characteristics: size,
rate of spread, intensity, and season, seem immediately significant during a fire, particularly
for the animals that shelter in place. Changing
fire’s speed or intensity may overheat soil-insulated animals. An increase in fire size or
speed may make escape or recolonization impossible for large- or medium-sized animals.
Possibly the most damaging, a change in fire
season may affect vulnerable stages of nest
building, offspring rearing, or juvenile survival for all three wildlife functional groups.
Depending on a species’ ability to utilize
the fire-transformed landscape, recolonization
back into the burned area will be rapid or slow
as the vegetation follows its successional pathway (Figure 1). Early seral stage specialists
and generalists will appear within a burn area
immediately, while others may take years to
recover. Colonizers also include those species
that do not escape, but experience complete
mortality and only re-establish in the burn area
by recolonization from unburned metapopulations. For the aerial insects that seem to take
the longest to repopulate a burned area (e.g.,
biting flies, butterflies, and non-pollinating
yucca moth species), escape in combination
with recolonization may be their primary fire
survival strategy.
It follows that no single fire regime will
generate highest biodiversity as different taxa
peak at different times after fire. Instead of
managing for a single fire regime, sustainability of total biodiversity in California shrublands
will require a landscape that, in both space and
time, includes different lengths of time since
fire and, especially, adequate cover of oldgrowth chaparral and coastal sage scrub
(Faivre et al. 2011, Robinson et al. 2013, Kelly et al. 2014). As mentioned previously,
Faivre et al. (2011) call this “landscape pyrodiversity.” For California shrublands, determining the right balance between old-growth
ecosystems and younger, seral stage shrublands to maximize biodiversity should be an
important focus of future research (Kelly et al.
2014).
Table 2. Fire regime characteristics that are significant to plant and animal survival and recovery.
Animals
Shelter in refugia
Flee and recolonize
Size or patchiness
X
X
Rate of spread
X
X
Fire regime
parameter
Frequency
Plants
X
Intensity
Season
Endogenous diapause
X
X
X
X
X
X
Page 142
Old-growth
shrubland
Regenerating
shrubland
Maturing shrubland
Old-growth
shrubland
Population size
Old-growth
specialists
Habitat
generalists
Seral stage
specialists
0 years
Years since the fire
30-150 years
Figure 1. With disturbances such as fire, different species recover at different rates over time. Overall,
generalists such as edge and open-site species will initially thrive with the disturbance and then decline.
In contrast, specialists such as understory and old-growth species will do the opposite, taking a much longer time to recover to pre-fire population numbers.
ACKNOWLEDGEMENTS
This work was supported in part by the California Fire Science Consortium, funded through
the Joint Fire Sciences Program. It was also supported by the US Geological Survey and the National Park Service. Special thanks go to P. van Mantgem, E. Boydston, R. Blair, D. Udovic, M.
Price, M. Mendelsohn, M. Mitrovich, W. Spencer, C. Rochester, and M. Jennings for providing
useful information, citations, review, and comments.
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Alvarado: Current International Perspectives
Page 149
Book Review
Current International Perspectives on Wildland
Fires, Mankind and the Environment. 2015.
Edited by Brigitte Leblon and Martin E. Alexander. Nova Science Publishers Inc., Hauppauge, New York, USA. 271 pp. Hardcover.
US$166.50. ISBN: 978-1-63463-682-7.
Wildfires are a global issue. This year’s
fire season in North America and Asia emphasizes the need for fire sciences that can be applied by the international fire community. Fire
science is being developed mainly in a few
countries. It is heartening to see that Leblon
and Alexander have embarked on the quest to
disseminate some of that knowledge through
their book, Current International Perspectives
on Wildland Fires, Mankind and the Environment. The title of this work is ambitious and
creates high expectations. Does the book live
up to them?
Before the book arrived, I was hopeful that
this could be an affordable one-stop source for
learning about some of the human dimensions
faced by the global fire community across the
world, especially in the tropics. I received the
book before summer, when I was preparing for
several professional trips to the Caribbean,
Mexico, and Portugal, and to Brazil and Bolivia for discussion with research collaborators.
While I was gone, large wildfires occurred on
the Indian reservations where I had planned
summer work in my home state of Washington, USA. I am not surprised that the fires in
Canada and the western US were being covered by the international media in almost real
time. My colleagues in the countries I was
visiting had trouble understanding why countries such as the US, with its good fire science
and fire fighting resources, continue to have
these large and destructive fires. The questions always led to what lessons can be learned
from the North American fires that can be applied to other countries with less developed
fire sciences and minuscule resources.
I started reading the book between my trips
and began searching for answers in it that
could help my colleagues from the global fire
community, where wildfires are mostly human
caused, to increase their readiness for current
and future fire seasons. Most of these countries are signatories of international climate
change agreements and, therefore, their CO2
emissions from wildfires are taken into account. They also see an upcoming climate
change meeting in Paris as an opportunity to
bring fire management to the international
stage. This is the scenario I posed to myself as
I read. Does this book provide that help?
My first impression upon receiving the
book was disappointment with the hardcover
price, which makes it too costly for the intended global audience. Over the years, I have
seen many fire-related books that have been
published but have a small international distribution. I am afraid this book will run the same
course and miss being read by the intended audience. Additionally, for the cost, I expected
higher quality graphics. The graphics are so
fuzzy that one cannot see what the authors intended to convey. In this area, I give the book
2.5 out of 5 stars.
In Current Perspectives, Leblon and Alexander have brought together several authors for
a “smorgasbord” approach from the Americas,
Australia, and Africa. The nine chapters have
no unified theme (in contrast to the majority of
recent fire books), nor does the book take a
comprehensive textbook approach. Instead,
the chapters cover a wide array of topics written by authors with a range of different levels
of experience, from veteran researchers to
emerging scientists. The topics are discrete but
organized in a way that the reader can start at
any chapter of the book depending on interest.
In the first chapter, Dale Wade and others
remind us that the concept of fire regime is applicable to all the world’s ecosystems. They
use an early publication by The Nature Conservancy to discuss the distribution of fire regimes in global ecosystems. One might think
that the most common classification of fire regimes in the United States (low, mixed, and
high severity) is perhaps too western US-centric. Nevertheless, for most ecosystems, this
system works fine. The framework used by
Wade and colleagues in this chapter is applied
to ecosystems beyond the western US. The
authors take us on a fire regime tour of North
America, but restrict the fire regime discussion
mostly to the US and pre- and post-European
settlement in the West. They present an interesting discussion of fire regimes influenced by
Native Americans, but fail to acknowledge
that major drivers of fire regime change were
the Indian treaties that practically removed
Native Americans from most US landscapes
during the mid-nineteenth century. The cessation of Indian burning and the ensuing Euro-American settlement in the West initiated
Page 150
the decline of forest health in most of the region. The chapter’s main focus is on the
southern US and Australia. Undoubtedly,
there is no one better than Dale Wade to discuss fire in the southern US, where he was a
pioneer of fire research. His understanding
and experience of the region is well expressed
in this chapter.
The Australian fire story is similar to the
United States. It starts with a European settler’s misunderstanding of the fire culture and
traditions of Aborigines, a policy of fire exclusion, a wildland-urban interface fire crisis, and
the restructuring of fire policies. The authors
present their ideas for a path forward in the US
and their views on how to increase or restore
fire regimes in the landscapes, and they introduce the reader to a successful case of
multi-stakeholder collaboration in southern
Florida to reintroduce fire.
Chapter 2 on remote sensing is written by
authors from three countries; the common unifier is satellite technology. Leblon and colleagues review the use of satellite technology
for monitoring pre- and post-fire conditions.
Satellite technology has been seen as a panacea for monitoring wildfires, but this technology has only slowly made it to mainstream
wildfire applications. The chapter concentrates on the North American and European
experiences of using optical, thermal infrared,
and radar images. It is unfortunate that the remote sensing science developed by Brazil was
not a part of the review. Brazil’s satellite technology is being applied in tropical systems,
where it is more challenging to develop similar tools than in temperate systems. The chapter emphasizes fuel moisture detection, weather conditions, fuel types, and topography for
monitoring pre-fire conditions based mainly
on the use of optical and thermal infrared imagery and, more recently, radar. Most of the
contribution of satellites to fire management
has been for fire detection. Several systems
have been implemented by many countries using technology based on detection of hot spots.
Many of the initial problems have been
worked out and the technology is reaching maturity. Multiple satellite sensors are used for
burnt area mapping. Post-fire mapping is a
pressing need in fire management, assessment
of environmental effects, and ecosystem restoration. Certainly, the remote sensing community has made tremendous progress from the
early days of three decades ago. The authors
recognize that ground validation appears to be
the most important challenge that needs to be
addressed before remote sensing is fully embraced by fire managers.
In Chapter 3, M.C. Dentoni and colleagues
present the case of adoption of the Canadian
Forest Fire Danger Rating System (CFFDRS)
as a fire management tool for Argentina. The
need for a system of fire danger rating has
been expressed in several international conferences. The major systems in the world are
based on the US National Fire Danger Rating
System, the Canadian CFFDRS, the Australian
MacArthur Index, and the Russian Nesterov
Index. One way or another, all these systems
are pursuing the same goal. In this chapter, I
find interesting the experience that Argentina
went through with their adoption and adaptation of the CFFDRS to a country with such diversityfrom the Andes, to the Equator, and
to the colder systems in Patagonia and Tierra
del Fuego. The adjustments, implementation,
pilot testing, and extrapolation to larger areas
are worth examining. After 15 years of initial
work, the system is used in almost two thirds
of the country. This chapter is worth reading
by managers of countries interested in having
their own fire danger rating system. The Argentinian experience tells us a story of many
challenges faced by scientists and managers
when developing a fire danger system.
In Chapter 4, Martin Alexander and William Thorburn introduce an “A” to the acronym LCES (Lookout-Communications-Escape
Routes-Safety Zones), a standard in the US
federal government fire agencies: adding Anchor Points (A). This stems from a proposal
Page 151
from the province of Alberta, Canada, because
of a serious injury in 1995. The chapter reviews the background of LCES, in addition to
the 10 standard orders and the 18 watch-out
situations in fire fighting. The authors suggest
that adding the “A” will improve the safety of
fire fighters.
After approximately 100+ years of organized fire fighting in the world, we still rely on
human labor for fire fighting. Nevertheless,
the work of fire fighters is made easier when
appropriate technology is incorporated in fire
management tools. In Chapter 5, Cassandra
Hansen and colleagues present to the reader
the use of geographical information systems
(GIS) and the more recent cloud-based GIS to
support fire management. A case study of the
Silver Fire in California, USA, is used to make
the point of the importance of GIS in fire suppression. Undoubtedly, more and better information is expected to improve the efficiency
of fire management. Geographical information systems have become the tools that the
new generation of fire managers must have,
along with remote sensing. Fire fighting will
continue to depend on people to fight fires, but
they will be safer and better equipped to do
their job if new and appropriate technology is
incorporated by fire managers. Personally, I
feel that this chapter is too short and so
case-driven that it is difficult to follow.
In Chapter 6, Gavriil Xanthopoulos writes
on fire fighter safety issues in Greece. He
presents a review of fatalities in wildfires in
Greece, the lessons learned, and how to improve safety of fire fighters. Most of the fatalities reported in this chapter occurred from
1977 to 2013. According to Xanthopoulos,
fire prevention and better training are the keys
to avoiding fatalities. Greece’s case is not
unique, though, and the chapter needed to
make a stronger call for a professional fire
fighting cadre that will be adequately trained.
Unfortunately, countries that depend on civilian volunteers will continue experiencing accidents and fatalities.
Chapters 7 and 8 are my favorites in the
book. Guillermo Defossé and colleagues present a nice review of fire ecology and management in Patagonia. I am glad that these authors have taken a leadership role in fire ecology and management in this richly biodiverse
region. The chapter takes the reader on a historical tour of fire from Triassic to modern
times. Their description of ecology and fires
sparks the reader’s interest in visiting the region and learning more about fire ecology.
Chapter 8, by Carlos Kunst and others, covers
the fire ecology and management of the Argentine Chaco, although the Gran Chaco covers
an extensive area from Argentina through Bolivia, Paraguay, and Brazil. The description of
the Chaco’s ecosystems, fire regimes, ecological effects, and fire management can be applicable to the other regions in South America.
This type of information is missing for most of
Bolivia and Paraguay, and only Brazil has invested in studying this important ecosystem.
The shortness of this chapter reflects the many
knowledge gaps for fires in the Gran Chaco. I
hope that this young group of academics and
scientists can become leaders in fire ecology in
South America.
The book closes with Chapter 9, which is a
recapitulation of fire-related casualties in
South Africa. This chapter has many things in
common with Chapter 6; perhaps they should
have been one chapter, or put in sequence.
Cornelis De Ronde presents a historical review
of the casualties and causes since 1994. In
South Africa, the Incident Command System
has been introduced in fire management. As
Page 152
with the Greek case, fire fighter training is key
to improving fire fighting safety.
This book has important lessons to teach.
One is that, after someone retires from a productive professional life, there is much knowledge that can be shared. The fire science community should recognize the effort that Alexander and Wade have invested in editing the
book and authoring two chapters. We should
appreciate their selflessness in sharing their
experience and knowledge since retiring.
The book itself has several inconsistencies.
Some chapters are deeper than others. The
book presents unbalanced treatments of some
important topics that are only occasionally
mentioned. I wish some chapters were consecutive, for instance Greece and South Africa, or
perhaps they should have been merged to avoid
repetition and enrich the discussion by comparing and contrasting their experiences.
At the end, some questions still linger.
What about tropical fires? There is a huge gap
of knowledge regarding tropical fires that
would improve the understanding and management of fires in Indonesia, Brazil, Central
America, and other tropical countries. I find
also that discussion of human dimensions is
shortchanged in the book. My overall rating
for the book is 3.5 stars out 5. The book is
worth reading, but one can always wait for the
paperback version.
Ernesto Alvarado, School of Environmental
and Forest Sciences, University of Washington,
Seattle, Washington 98195, USA. alvarado@
uw.edu

Fire Ecology 11(3) - Fire Ecology Journal

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