Old tree morphology in singleleaf pinyon pine (Pinus monophylla)

Forest Ecology and Management 263 (2012) 67–73
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Forest Ecology and Management
journal homepage: www.elsevier.com/locate/foreco
Old tree morphology in singleleaf pinyon pine (Pinus monophylla)
Peter J. Weisberg a, Dongwook W. Ko b,⇑
a
b
Department of Natural Resources and Environmental Science, University of Nevada, Reno, Mail Stop 186, Reno, NV 89557, USA
Kangwon National University, Institute of Environmental Research, Chuncheon, Kangwon-Do 200-701, South Korea
a r t i c l e
i n f o
Article history:
Received 25 May 2011
Received in revised form 23 August 2011
Accepted 31 August 2011
Available online 21 October 2011
Keywords:
Old growth
Semi-arid woodland
Canopy architecture
Tree morphology
Late-seral attributes
a b s t r a c t
Singleleaf pinyon pine (Pinus monophylla) is a long-lived tree species that dominates montane plant communities over large areas of the arid and semi-arid Intermountain West, USA. Although old-growth forests are widely valued by society, old trees in pinyon-dominated woodlands may be threatened by active
management against woodland expansion on rangelands, particularly in the absence of knowledge concerning old tree morphology and crown architecture. This study, which took place within a 15-km2 area
in central Nevada, used detailed field observations of tree morphology and dendrochronological measurements of tree age, in combination with principal components analysis and multiple linear regression, to
identify the distinctive attributes of old P. monophylla trees that require long time periods to develop.
P. monophylla tree age was most parsimoniously quantified using three linear combinations of fieldmeasured variables, representing overall tree size, crown diminishment with age, and ‘‘stubbiness’’
(i.e. the combination of short stature and wide girth). These composite variables were derived from just
five types of tree measurements: stem diameter, height, diameter of lowest branch, crown area, and an
index of bark texture. The three composite variables have intuitive meaning and do not require precise
quantification to aid researchers and natural resource managers in developing more accurate visual estimations of approximate tree ages in P. monophylla or other cembroid pines characteristic of arid lands.
Old tree attributes identified in this study are likely characteristic of long-lived conifers growing in arid
and semi-arid regions, and are expected to provide important elements of habitat structure and complexity for diverse taxa.
Ó 2011 Elsevier B.V. All rights reserved.
1. Introduction
Singleleaf pinyon pine (Pinus monophylla Torr. and Frem.) codominates the pinyon–juniper woodlands of the Great Basin with
Utah juniper (Juniperus osteosperma (Torr.) Little), and is the dominant tree species in most central Nevada mountain ranges (Bauer
and Weisberg, 2009; Greenwood and Weisberg, 2009). This species
can be extremely long-lived when not killed by fire or other disturbance agents. Maximum ages recorded for P. monophylla and J. osteosperma are 888 and 1350 years, respectively (F. Biondi, Univ. Nevada
Reno, personal communication; Floyd et al., 2003). Old-growth
woodland comprised of these species has been an important component of western North American landscapes over past centuries to
millennia and is commonly associated with less productive sites
characterized by thin soils, talus slopes, rocky outcrops or other
landscape features that limit fuel loads or otherwise act as fire
breaks (Young and Evans, 1981; Jacobs et al., 2008; Weisberg
et al., 2008). However, old-growth woodland may well have covered
greater areas during certain times in the past when climatic condi-
⇑ Corresponding author. Tel.: +82 33 250 7318.
E-mail addresses: [email protected], [email protected] (D.W. Ko).
0378-1127/$ - see front matter Ó 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.foreco.2011.08.048
tions were less conducive to fire ignition and spread. One recent
study suggests that the relationship between site productivity,
apparent fire risk and the current distribution of old-growth woodland is relatively weak (Weisberg et al., 2008).
Old-growth forest and woodland types throughout North
America are widely valued for their role in maintaining structural
complexity and biodiversity at the landscape level (Franklin and
Van Pelt, 2004; Kneeshaw and Gauthier, 2003; Ziegler, 2002). Characteristic old-growth attributes have been extensively studied for
Douglas-fir forests of the Pacific Northwest, and silviculturists of
that region actively manage forests to accelerate development of
old-growth characteristics within younger stands (Franklin and
Van Pelt, 2004; Tappeiner et al., 1997). Key structural attributes
of old-growth Douglas-fir forests include diverse diameter and
height distributions, heterogeneous distribution of vertical foliage,
heterogeneity in horizontal canopy cover (commonly, aggregation
of smaller size classes), and abundant coarse woody debris of varying size and decomposition class (Spies, 1998). Waichler et al.
(2001) identified the following characteristic old-growth attributes
for western juniper (Juniperus occidentalis) woodlands in central
Oregon: large asymmetrical crowns, abundant standing and fallen
large woody debris, lichen cover on dead branches, and open canopies. Similar old-growth attributes have been reported for Pinus
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P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
edulis woodlands (Floyd et al., 2003; Jacobs et al., 2008). As a result
of such structural complexity, old-growth pinyon–juniper woodlands often support a rich diversity of understory plant species,
microbiotic soil crusts, and numerous avian, mammalian, reptilian
and amphibian species (Floyd et al., 2003).
Despite their ecological importance, old-growth pinyon–juniper
communities have been relatively ignored (Waichler et al., 2001;
Floyd et al., 2003, 2008; Jacobs et al., 2008; Weisberg et al.,
2008; Romme et al., 2009), while recent expansion of pinyon–juniper woodlands into other vegetation types has received considerable attention from both scientists and managers (e.g. Blackburn
and Tueller, 1970; Miller and Wigand, 1994; Weisberg et al.,
2007; Bradley and Fleishman, 2008). Since settlement, there has
been an estimated 10-fold increase (from 3 million ha to 30 million
ha) in pinyon–juniper woodland area within the western U.S.
(Miller and Tausch, 2001). This expansion has been associated with
negative ecological and economic effects (Davenport et al., 1998;
Gruell, 1999; Miller and Tausch, 2001; but see Belsky (1996)),
and much resources and labor go towards reducing tree cover
and establishing understory vegetation.
Effective management of conifer establishment at the woodland-sagebrush ecotone requires differentiation of persistent
woodlands from expansion woodlands. It is essential that current
efforts to reduce woodland cover on rangelands by thinning,
burning or otherwise clearing pinyon–juniper are able to discriminate old trees from post-settlement trees. Unfortunately, there is
surprisingly little information on the distribution of old-growth
pinyon–juniper woodland throughout the Great Basin. Old woodlands are difficult to recognize and map using aerial photographs
or satellite imagery. Older pinyon and juniper trees differ little from
younger ones with regard to tree height or crown diameter, and
generally require field visitation to distinguish.
A major limitation for accurate, extensive mapping of oldgrowth distribution is the lack of an objective classification for
determining old-growth structure in the field. Bradshaw and
Reveal (1943) identified four maturity classes of P. monophylla
based on attributes such as tree height, diameter and overall
growth form. However, their broad classification resulted in widely
varying tree morphology within the same maturity class, and
lumped all older trees (>100–175 years) in a single ‘‘Class 4.’’ Use
of increment cores and dendroecological analysis to estimate tree
age is generally most accurate but time consuming and expensive,
and often impossible because of rotten heartwood. An improved
understanding of old tree attributes is needed for P. monophylla
and other cembroid pines (Pinus subsection cembroides) of arid
and semi-arid landscapes. Few studies have quantified old-growth
attributes of pinyon–juniper woodlands at the stand level
(Waichler et al., 2001; Jacobs et al., 2008), and we are aware of
no published studies that have rigorously quantified structural
attributes of individual P. monophylla trees. Our primary goal was
to identify those aspects of P. monophylla tree morphology and
architecture that are distinctive attributes of older trees, and hence
require long time periods to develop. A secondary objective was to
identify the minimal set of field observations needed for distinguishing P. monophylla trees on the basis of old-growth attributes.
2. Methods
2.1. Field and laboratory methods
A total of 50 P. monophylla trees was sampled from within a
15-km2 area of consistent terrain and climate, located within the
Simpson Park Range of central Nevada, USA (longitude 39°220 –
39°340 N, latitude 116°440 –116°530 W. The study area ranges in
elevation from 1980 to 2675 m, and is predominately volcanic in
lithology with extensive Tertiary andesite, interlaced with silicaceous ash-flow tuff formations (Raines et al., 1996). Most precipitation accumulates as winter snowfall, with mean annual values
ranging from 200 to 350 mm. The study area consists of three major vegetation units: a shrub-dominated community at the lower
elevations and adjacent valley flats, a mid-elevation band of pinyon–juniper woodland, and a shrub-dominated community again
at the highest elevations. The lower elevations are dominated by
Wyoming big sagebrush (Artemisia tridentata Nutt. ssp. wyomingensis Beetle & A. Young), planted crested wheatgrass (Agropyron
cristatum (L.) Gaertn.), occasional native bunchgrasses, and abundant cheatgrass (Bromus tectorum L.), an exotic annual grass. The
mid-elevation woodland is a mosaic of tree-dominated and
shrub-dominated patches, with occasional small wetlands surrounding seeps and springs. The arborescent component is dominated by P. monophylla, with J. osteosperma co-dominant on xeric
sites. The high-elevation shrub community is dominated by mountain big sagebrush (A. tridentata Nutt. ssp. vaseyana (Rydb.) Beetle),
snowberry (Symphoricarpos spp. Duham.), and low sagebrush
(Artemisia arbuscula Nutt.).
Sampled trees were selected randomly among strata defined by
10-cm diameter classes from within the mid-elevation woodland,
such that a range of tree ages from 23 to 381 years (dbh range from
4 to 54 cm) was ultimately selected for analysis. Sampling occurred
in 2007 and 2010. Twelve morphological variables were measured
on each tree and used for analysis. Both diameter at breast height
(DBH) and diameter at root crown (DRC) were measured using
diameter tapes and proved highly correlated, so that only DBH
was retained for analysis. Tree height (Height) was measured to
the nearest decimeter using a stadia rod, whereas crown area
(Crown.Area) was estimated as the area of an ellipse using field
measurements of the longest axis and its perpendicular. Crown
eccentricity (Crown.Ecc), or the degree to which an irregular tree
crown deviates from a circular shape, was calculated as:
sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
2
b
e¼ 1
a
where e = crown eccentricity and a and b are the length of the elliptical crown’s major and minor axes, respectively. Crown eccentricity
ranges from 0 (perfect circle) and asymptotically approaches 1 as
the shape eccentricity increases. Crown asymmetry (Crown.Asym)
was measured as the horizontal distance from stem base to the
ground projection of the center of gravity of the tree crown. Percent
dead crown (PC.Dead) was determined by ocular estimate to the
nearest 5% from multiple perspectives around each tree. The number of forks in the main trunk (Fork.Num) was counted. Bark texture
(Bark.Txt) was classified using a categorical scale ranging from 1
(smoothest) to 5 (most deeply furrowed). Several measurements
were taken of the lowest live branch, including height above the
ground (LB.Ht) and diameter at the intersection with the main trunk
(LB.Dia); the number of nodes or vertices where the branch changes
direction (LB.Node); and the angle of the projected line from base to
tip relative to the main trunk (LB.Angle), such that a branch parallel
to the ground is 90° whereas branches angled upwards are greater
than 90°.
Each sampled tree was cored at the base (just above the root
crown) for age determination. Increment cores were processed
using standard dendrochronological techniques (Stokes and
Smiley, 1968). Increment cores were visually crossdated using
marker years to a pinyon reference chronology assembled from
the Shoshone Range and two nearby mountain ranges Ring widths
were measured to 1 lm precision using a Unislide ‘‘TA’’ Velmex
measuring system, and COFECHA software was used to verify
crossdating (Grissino-Mayer, 2001) to the same reference chronology. To estimate tree origin year for cores that did not reach pith,
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P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
we adjusted ages using the concentric circle method (Applequist,
1958) and empirical relationships for pinyon early growth from
Bauer and Weisberg (2009).
2.2. Data analysis
Pearson’s correlation analysis was used to assess the strength of
linear association between tree age and the various tree structural
attributes (Table 1), as well as to assess patterns of inter-correlation among the structural attributes. A principal components
analysis (PCA) was then conducted on the tree structural attributes
(i.e. predictor variables) to reduce the data to a simplified set of
uncorrelated components (PCs) representing underlying, latent
dimensions of variation; the full set of PCs was subsequently regressed against tree age as the response variable (Graham, 2003).
Akaike’s Information Criterion (AIC) was used to rank the effectiveness of alternative covariate models for fitting the data, given the
number of parameters included. For pairs of candidate models with
AIC differing by at least 2, the most parsimonious model was that
with the lower AIC value (Burnham and Anderson, 2002).
Principal components regression analysis has the disadvantage
that it cannot readily be extrapolated to a different data set, for
which a PCA would result in construction of different PCs. Therefore
we used loadings of measured variables with the PCs found to be
important predictors of tree age, to guide construction of meaningful, linear combinations of the original, measured variables
(Ramsey and Schafer, 2002). PCA loadings describe the coefficients
used for the principal components transformation (i.e. the weights
used to construct each PC as a linear combination of input variables). The resulting linear combinations were interpreted as composite variables describing particular, uncorrelated attributes of
tree morphology associated with tree age. Multiple regression analysis was used to predict tree age as a function of the three composite variables found to be important, and visual interpretations of
scatter plots and partial regression plots were used to further interpret the relationship between tree age and tree morphology.
3. Results
3.1. Relationships of structural attributes with tree age
Several of the tree structural attributes were highly correlated
(r P 0.6) (Table 1). Attributes with positive correlations included
DBH, Height, Crown.Area, and Bark.Txt. Lower branch diameter
(LB.Dia) was only moderately correlated with these variables (e.g.
r = 0.51 with DBH), but was highly correlated with LB.Node, Crown.Area, Bark.Txt, and Fork.Num.
Tree age had strong positive correlations with several of the
structural attributes, including LB.Dia (r = 0.65), DBH (r = 0.65),
and Bark.Txt (r = 0.63). Correlations were moderate (0.4 6 r 6 0.6)
with PC.Dead, LB.Node, Crown.Area, Crown.Asym, Height, and
LB.Ht (Table 1). Correlations with tree age were weak or non-significant for Fork.Num and LB.Angle. However, relationships were
typically nonlinear even for structural attributes exhibiting the
highest correlations with tree age (Fig. 1). The relationship
between DBH and tree age showed a strongly saturating response,
where DBH increased linearly with increasing age for young trees,
but then exhibited a flat trend with high variability for trees older
than approximately 200 years (Fig. 1A). Bark.Txt and PC.Dead
showed similar relationships with tree age as DBH, although the
functional relationship did not level off as strongly (Fig. 1B and
C). All trees with smooth bark were less than 140 years old. The
only structural attribute exhibiting a consistently strong, linear
relationship with tree age was LB.Dia (Fig. 1D).
3.2. Composite indices of old tree structural attributes in P. monophylla
Principal components analysis identified 12 components representing uncorrelated dimensions of tree morphology (Table 2).
Model selection procedures identified a parsimonious model that
included three ecologically interpretable principal components
(PCs 1, 11 and 12) and explained approximately 67% of the variance in tree age. PC 1 was positively associated with tree age and
showed moderately positive loadings with all size-related variables (Table 2). PC 11 was positively associated with tree age and
showed positive loadings with LB.Dia and DBH, but negative loadings with Crown Area. PC 12 was negatively associated with tree
age and showed negative loadings with DBH but positive loadings
with tree height.
Composite indices were then constructed to represent PCs 1, 11
and 12 in terms of the original, measured variables after the latter
were zero-centered and normalized to standard deviate units (i.e.
z-standardized). Size Index, as interpreted from PC 1, was constructed as the mean of z-standardized DBH, Height, LB.Dia, Crown.Area, and Bark. Txt. This index represents the tendency for older
trees to achieve rougher bark texture and greater dimensions in
diameter, height, branch thickness, and crown area. Crown Diminishment Index, as interpreted from PC 11, was constructed as the
mean of LB.Dia and DBH, minus Crown.Area. This index represents
the tendency for older trees to lose crown area due to the accumulation of mortality factors over time. Stubbiness Index, as
Table 1
Matrix of pairwise Pearson’s correlation coefficients for tree age and 12 measures of tree morphology. Only significant correlations (a 6 0.1) are shown, and correlations P0.6 are
shown in bold font. Variable abbreviations: Age, tree age; DBH, diameter at breast height; Height, tree height; PC.Dead, percent of dead crown; LB.Ht, height above ground of
lowest branch; LB.Dia, diameter of lowest branch at intersection with the trunk; LB.Angle, angle of the projected line of the lowest branch from base to tip relative to the main
trunk; LB.Node, the number of nodes where the lowest branch changes direction; Crown.Area, projected crown area estimated as the area of an ellipse; Crown.Ecc, crown
eccentricity, or the degree to which an irregular, elliptical crown deviates from a circular shape; Crown.Asym, the horizontal projection distance from stem base to crown center;
Bark.Txt, an ocular estimate of the degree to which bark is smooth vs. furrowed; Fork.Num, the number of forks in the main stem.
Age
DBH
Height
PC.Dead
LB.Ht
LB.Dia
LB.Angle
LB.Node
Crown.Area
Crown.Ecc
Crown.Asym
Bark.Txt
DBH
Height
PC.Dead
LB.Ht
LB.Dia
LB.Angle
LB.Node
0.65
0.45
0.91
0.56
0.47
0.46
0.42
0.34
–
–
0.65
0.51
0.41
0.38
0.36
–
–
–
–
–
–
0.52
0.34
0.28
0.53
–
0.70
–
Crown.Area
0.49
0.81
0.74
0.40
–
0.66
0.24
0.43
Crown.Ecc
Crown.Asym
Bark.Txt
Fork.Num
–
–
–
0.23
0.40
–
–
–
–
0.47
0.38
0.26
–
–
0.45
–
0.34
0.38
–
0.63
0.74
0.69
0.56
0.27
0.69
–
0.51
0.80
–
0.39
0.39
0.38
0.39
–
0.35
0.69
–
0.49
0.50
–
0.25
0.59
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P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
A
B
5
Bark Texture
DBH (cm)
50
20
4
3
2
1
0
100
200
300
400
0
100
200
Age (years)
C
400
300
400
D
0.6
20
LB.Dia (cm)
Percent Dead Crown
300
Age (years)
0.4
0.2
15
10
5
0.0
0
100
200
300
0
400
0
100
200
Age (years)
Age (years)
Fig. 1. Bivariate scatter plots of P. monophylla tree age as a function of selected predictor variables, (A) diameter at breast height (DBH), (B) bark texture (Bark.Txt), (C) percent
dead crown (PC.Dead), (D) diameter of the lowest branch (LB.Dia).
Table 2
Principal component loadings, eigenvalues and cumulative proportion of variance explained (cum. var.) from a principal components analysis of 12 variables indicating tree
morphology. Only loadings exceeding |0.1| are shown, and loadings exceeding |0.5| are shown in bold font. Loadings are the coefficients used in the principal component
transformation; higher values indicate a greater contribution of the measured variable to the principal component.
DBH
Height
PC.Dead
LB.Ht
LB.Dia
LB.Angle
LB.Node
Crown.Area
Crown.Ecc
Crown.Asym
Bark.Txt
Fork.Num
Eigenvalue
Cum. Var.
PC1
PC2
PC3
PC4
PC5
PC6
0.37
0.35
0.27
0.18
0.36
0.21
0.22
0.34
0.22
0.54
0.26
0.28
0.50
0.16
0.19
0.28
0.29
0.39
0.28
0.26
0.23
0.12
0.55
0.15
0.18
0.21
0.58
0.50
0.23
0.15
0.19
0.19
0.12
0.29
0.25
0.23
0.30
0.23
0.19
0.13
0.68
0.12
0.17
0.18
0.75
0.17
0.45
0.14
1.32
0.58
0.33
1.10
0.68
0.28
1.01
0.77
0.36
0.92
0.84
0.22
0.80
0.89
0.29
0.37
0.22
0.39
0.29
2.29
0.44
0.18
0.39
interpreted from PC 12, was constructed as DBH minus Height and
represents the tendency of P. monophylla trees to achieve an upper
limit in stem height within the first 100–200 years of age, while
continuing to grow in diameter. The three indices are summarized
below:
Size ¼ meanðDBH; Height; LB:Dia; Crown:Area; Bark:TxtÞ
Crown Diminishment ¼ meanðLB:Dia; DBHÞ Crown:Area
Stubbiness ¼ DBH Height
The three composite indices from measured variables were
close approximations of the principal components (R2 > 0.90 from
simple linear regressions of index values vs. PCA scores) and provided a model with greater explanatory power for predicting tree
age (R2 = 0.73) than did the model using PCA scores (R2 = 0.67).
The multiple regression model for the combined influence of the
three composite indices (in standard deviate units) is:
PC7
PC8
0.11
0.19
0.57
0.31
0.55
0.18
0.27
0.34
0.63
0.92
0.49
0.34
0.12
0.34
0.34
0.23
0.25
0.52
0.57
0.95
PC9
0.14
0.39
0.21
0.15
0.34
0.17
0.48
0.15
0.10
0.49
0.33
0.51
0.97
PC10
PC11
0.36
0.29
0.49
0.35
0.19
0.10
0.14
0.45
0.15
PC12
0.69
0.65
0.21
0.76
0.10
0.70
0.10
0.41
0.99
0.13
0.30
0.99
0.17
0.26
1.00
Tree Age ¼ 170:86 þ 71:06 ðSizeÞ
þ 62:26 ðCrown DiminishmentÞ þ 73:42 ðStubbinessÞ
Of the three old tree structural indices in the model, the Size
Index and Stubbiness Index were most strongly associated with
tree age, with the former showing the most consistent effects
(Fig. 2). The Size Index is a good predictor of tree age for trees
younger than about 200 years but requires the other two indices
to reliably predict tree age for older trees (compare Fig. 2A and
D). Conversely, the Stubbiness Index does not predict tree age
reliably for younger trees, but does so for older trees (Fig. 2B).
The Crown Diminishment Index is only weakly associated with
tree age in a bivariate sense (Fig. 2C) but is more strongly associated with tree age (R2 = 0.30) after accounting for the variation
explained by the other two indices (Fig 2F). Taken together, these
three components describe independent dimensions of tree morphology that collectively predict tree age for old-growth stands of
P. monophylla.
P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
71
Fig. 2. Bivariate scatter and partial regression plots: (A) Age vs. Size Index; (B) Age vs. Stubbiness Index; (C) Age vs. Crown Diminishment Index; (D) partial residual of Age vs.
Size Index, after accounting for the influences of the Stubbiness and Crown Diminishment indices; (E) partial residual of Age vs. Stubbiness Index, after accounting for the
influences of the Size and Crown Diminishment indices. (F) partial residual of Age vs. Crown Diminishment Index, after accounting for the influences of the Size and
Stubbiness indices, X-axes are in standard deviation units.
4. Discussion
The morphological variables measured in the field were highly
correlated with each other, and several showed nonlinear relationships with tree age. Our analysis defined three composite indices
based on the linear combinations of these variables that collectively
describe attributes of tree morphology (i.e. Size, Crown Diminishment, Stubbiness) that are (1) independent of one another, and (2)
when used in combination, strongly predictive of P. monophylla tree
age across the range of ages sampled (26–384 years). Although P.
monophylla trees can live to more than twice the maximum age of
trees measured in this study, it is unlikely that the observed trends
in old tree attributes would differ strongly had 400–800 year old
trees been included. However, future research should address old
tree morphology in this species across a broader age range.
Old P. monophylla trees are:
1. Large with deeply furrowed bark. However, this generalization
diminishes as tree age begins to exceed 150–200 years.
2. Larger in bole and lower branch dimensions than in crown area.
As portions of the crown die back over time, stem wood continues to accumulate.
3. Stubby in appearance. Old P. monophylla trees thicken with time
as they quickly reach their maximum height potential. Site
potential for height growth in these semi-arid ecosystems is
very low, so height growth soon saturates.
The practical value of our research lies not only in describing
the three composite variables that explain over 70% of the variation
in pinyon tree age, but in identifying the minimal set of field observations needed to distinguish old P. monophylla trees on the basis
of structural attributes: stem diameter, tree height, basal diameter
of the lowest branch, crown area, and bark texture. The three composite variables themselves have intuitive meaning that can aid
researchers and natural resource managers in developing more
accurate visual estimations of relative tree ages. Even in the
absence of precise measurements, managers and ecologists should
be able to distinguish old trees by carefully observing these attributes. The resulting improvement in the ability to detect old trees
should, in turn, limit the likelihood of old trees being inadvertently
removed by landscape restoration treatments implemented to
reduce tree dominance in expansion woodlands.
Attributes of old pinyon trees are similar to those reported for
other, more mesic forest types in that older trees are generally larger in stature and most structural dimensions (Franklin et al., 2002;
D’Amato et al., 2008) and have diminished crown area due to senescence and partial canopy mortality arising from periodic disturbance events (Spies, 2004). However, the relatively early
cessation of height growth results in morphological forms with proportionately thick boles and large lower limbs (i.e. high ‘‘stubbiness
index’’), that are likely characteristic of long-lived conifers growing
under conditions of extreme water limitation in arid and semi-arid
regions of the world. In particular, we expect our results to be
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P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
generalizable to other cembroid pine species in North America (e.g.
P. edulis, Pinus cembroides, and Pinus quadrifolia) that have similar
life history traits. Similar canopy morphology attributes (furrowed
bark, crown mortality) were also reported for old-growth western
juniper (J. occidentalis) woodlands in central Oregon, USA (Waichler
et al., 2001). Further research is needed to determine whether oldtree morphological forms reported here are typical of other Pinus
species in severely water-limited environments (e.g. Pinus halapensis). Representative P. monophylla trees of different ages are shown
in Fig. 3.
There are several ecological implications arising from the structural attributes of old pinyon trees described in this study. Strong
negative effects of P. monophylla canopy cover on cover and abundance of understory species (Tausch et al., 1981; Tausch and
Tueller, 1990) may become ameliorated as trees age, due to thinning of the crown and a concurrent reduction in tree productivity
and use of belowground resources. Old P. monophylla trees are
likely to provide distinctive habitats for arthropods and other invertebrates, in that they have deep, furrowed bark and relatively open
crowns, allowing for a mosaic of high-light and shaded microsites.
Hosting an invertebrate community that differs from that of younger trees will likely favor a distinctive avian community structure.
Cavity nesting species, that tend to be insectivorous, are also likely
to select old trees for nesting that have a greater frequency of
cavities (San Miguel and Colyer, 2003). In general, thick lower
branches and an open crown provide valuable habitat for a range
of arboreal and epiphytic plant and animal taxa (Floyd et al.,
2003). However, the habitat values of old pinyon trees (P. monophylla or P. edulis) have been but little studied.
Old-growth forests are highly valued worldwide from diverse
perspectives including spiritual and esthetic values, biodiversity
conservation, nutrient cycling, carbon sequestration, and a variety
of other ecosystem services (Wirth et al., 2009). In most parts of
the world, old-growth forests are scarce as a result of forest management practices that have emphasized earlier stages of stand
development. Where old-growth forests are especially scarce,
there are efforts to recreate or hasten development of old-growth
attributes through forest preservation or silvicultural treatments
(Bailey and Tappeiner, 1998; Bauhaus et al., 2009). However, information on old-growth attributes that has been developed to date
applies primarily to mesic forests, with little information available
for forests and woodlands in arid and semi-arid landscapes. Studies
of mesic temperate forests emphasize an increase in vertical and
horizontal structural complexity in later stages of stand development (e.g. Spies and Franklin, 1988; Franklin et al., 2002). Our
results support this generalization for singleleaf pinyon pine at
Fig. 3. Representative photographs of Pinus monophylla trees of various ages, that were used in the study. (A) Young tree of 61 years showing a symmetrical, full crown with
little mortality; (B) lower portion of a 140-year old tree that has developed a forked stem and thickened lower branches; (C) a 286-year old tree showing crown dieback and
thick lower branches; (D) a 307-year old tree showing extensive crown dieback, thick lower branches and the ‘‘short but stubby’’ growth form.
P.J. Weisberg, D.W. Ko / Forest Ecology and Management 263 (2012) 67–73
the scale of individual trees, but further research is needed to
quantify structural attributes of old forests in arid lands at stand
and landscape scales. Descriptions of old-growth attributes developed from mesic ecosystems may not apply in severely waterlimited forest types where productivity is low, tree height potential
is greatly limited, tree regeneration is highly episodic, and tree
species diversity may be quite low.
Acknowledgements
Todd Granberry, Julisa Edwards and Walter Weisberg assisted
with field research. Ashley Sparrow contributed valuable comments and ideas. Franco Biondi contributed the master tree-ring
chronology.
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