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Using trait and phylogenetic diversity to evaluate the generality of the stress-dominance hypothesis in Eastern North American tree communities


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The stress-dominance hypothesis (SDH) is a model of community assembly predicting that the relative importance ofenvironmental filtering increases and competition decreases along a gradient of increasing environmental stress. Tests of the SDH at limited spatial scales have thus far demonstrated equivocal support and no prior study has assessed the generality of the SDH at continental scales. We examined over 53000 tree communities spanning the eastern United States to determine whether functional trait variation and phylogenetic diversity support the SDH for gradients of water and soil nutrient availability. This analysis incorporated two complementary datasets, those of the U.S. Forest Service Forest Inventory and Analysis National program and the Carolina Vegetation Survey, and was based on three ecologically important traits: leaf nitrogen, seed mass, and wood density. We found that mean trait values were weakly correlated with water and soil nutrient availability, but that trait diversity did not vary consistently along either gradient. Th is did not conform to trait variation expected under the SDH and instead suggested that environmental filters structure tree communities throughout both gradients, without evidence for an increased role of competition in less stressful environments. Phylogenetic diversity of communities was principally driven by the ratio of angiosperms to gymnosperms and therefore did not exhibit the pattern of variation along stress gradients expected under the SDH. We conclude that the SDH is not a general paradigm for all eastern North American tree communities, although it may operate in certain contexts.
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Using trait and phylogenetic diversity to evaluate the generality of
the stress-dominance hypothesis in eastern North American tree
Jessica R. Coyle, Fletcher W. Halliday, Bianca E. Lopez, Kyle A. Palmquist, Peter A. Wilfahrt
and Allen H. Hurlbert
J. R. Coyle (, F. W. Halliday and A. H. Hurlbert, Dept of Biology, Univ. of North Carolina at Chapel Hill, Chapel Hill,
NC 27599-3280, USA. – B. E. Lopez, K. A. Palmquist, P. A. Wilfahrt and AHH, Curriculum for the Environment and Ecology, Univ. of
North Carolina at Chapel Hill, Chapel Hill, NC 27599-3275, USA.
e stress-dominance hypothesis (SDH) is a model of community assembly predicting that the relative importance of
environmental filtering increases and competition decreases along a gradient of increasing environmental stress. Tests
of the SDH at limited spatial scales have thus far demonstrated equivocal support and no prior study has assessed the
generality of the SDH at continental scales. We examined over 53 000 tree communities spanning the eastern United
States to determine whether functional trait variation and phylogenetic diversity support the SDH for gradients of
water and soil nutrient availability. is analysis incorporated two complementary datasets, those of the U.S. Forest
Service Forest Inventory and Analysis National program and the Carolina Vegetation Survey, and was based on three
ecologically important traits: leaf nitrogen, seed mass, and wood density. We found that mean trait values were weakly
correlated with water and soil nutrient availability, but that trait diversity did not vary consistently along either gradient.
is did not conform to trait variation expected under the SDH and instead suggested that environmental filters
structure tree communities throughout both gradients, without evidence for an increased role of competition in less
stressful environments. Phylogenetic diversity of communities was principally driven by the ratio of angiosperms to
gymnosperms and therefore did not exhibit the pattern of variation along stress gradients expected under the SDH. We
conclude that the SDH is not a general paradigm for all eastern North American tree communities, although it may
operate in certain contexts.
Ecological communities are expected to be structured by a
variety of stochastic and deterministic processes. Two deter-
ministic processes thought to play a strong role in determin-
ing the coexistence of species in the same trophic level are
interspecific competition and environmental filtering, where
species are excluded from a community due to an inability to
survive and reproduce in a given physical environment.
General rules for predicting the relative importance of these
processes in different contexts are still largely unresolved
(HilleRisLambers et al. 2012). One compelling community
assembly model predicts that environmental filtering will be
more important in structuring communities in stressful
environments, while competitive interactions will be more
important in benign environments (depicted in Weiher and
Keddy 1995). is hypothesis, which we refer to as the
stress-dominance hypothesis (terminology adapted from
Swenson and Enquist 2007), derives from the expectation
that the importance of competition in plant communities
declines with increasing environmental stress (Grime 1977)
and is consistent with modern theory predicting that fitness
differences change along abiotic gradients (HilleRisLambers
et al. 2012).
Testing the generality of the stress-dominance hypothesis
(SDH) is difficult. e experiments required to identify
competition and environmental filtering are infeasible in
many types of communities (for example, among long-lived
organisms) and rarely cover a sufficiently broad geographic
extent to confirm that the hypothesis is generalizable. Large-
scale observational studies provide a unique opportunity to
evaluate the generality of the SDH because 1) the number of
communities that can be analyzed may be several orders of
magnitude larger than in traditional field studies, 2) large-
scale studies tend to span broader environmental gradients
related to the processes of interest, and 3) the occurrence of
strong relationships amidst the ecological heterogeneity of a
large observational data set provides more persuasive evi-
dence of generality. Nevertheless, parsing ecological pro-
cesses in a non-experimental setting is notoriously difficult,
especially when making inferences from patterns of species
diversity and community composition (Gotelli and Graves
Ecography 37: 814–826, 2014
doi: 10.1111/ecog.00473
© 2014 e Authors. Ecography © 2014. Nordic Society Oikos
Subject Editor: Dominique Gravel. Accepted 12 January 2014
1996). Ecologists are increasingly using information about
species traits and phylogenetic relationships to strengthen
observational pattern-based inference of the mechanisms of
community assembly (Webb et al. 2002, Emerson and
Gillespie 2008, Kraft et al. 2008, Cavender-Bares et al. 2009,
Spasojevic and Suding 2012). e variation of certain traits
within a community can indicate the relative strength of
processes such as competition and environmental filtering
since traits differentially mediate an organisms ability to use
and obtain resources and to tolerate environmental stressors
(Keddy 1992, Tilman 2004). Where trait information has
been unavailable, the phylogenetic structure of communi-
ties has frequently been used as a proxy for functional struc-
ture (Bryant et al. 2008, Cadotte et al. 2008, Graham and
Fine 2008).
Functional and phylogenetic diversity have recently
been used to elucidate processes structuring a wide range of
communities (Ricotta and Moretti 2011), and several stud-
ies have found patterns consistent with the SDH (Swenson
and Enquist 2007, Kluge and Kessler 2011, Machac et al.
2011, Graham et al. 2012, Mason et al. 2012, Spasojevic
and Suding 2012). However, most studies encompass a
relatively small geographic extent and focus on a single
community or habitat type. While this allows researchers
to collect detailed data on traits within communities, it is
unclear how general these findings are. Several major efforts
to accumulate and coordinate extensive trait and phyloge-
netic information (e.g. Phylocom, Webb et al. 2008; TRY,
Kattge et al. 2011) have expanded the potential geographic
scope of trait-based ecology, leading to a number of recent
studies of continental to global scale variation in traits,
functional and phylogenetic diversity (Reich and Oleksyn
2004, Wright et al. 2004, Ordoñez et al. 2009, Safi et al.
2011, Huang et al. 2012, Swenson et al. 2012b). e
next step is to use these broad-scale patterns to evaluate the
generality of community-scale ecological theory. Doing
so requires a dataset encompassing a wide variety of species,
communities, and processes that influence these communi-
ties. It is uncertain if the inherent heterogeneity of such a
dataset will obscure any general signals, or whether hypo-
thesized ‘rules’, such as the SDH, are strong enough to be
observed regardless (Lawton 1999).
Here we test whether patterns of phylogenetic and trait
diversity in 53 439 tree communities in the eastern United
States are consistent with shifts from environmental filter-
ing to competition predicted by the SDH. In doing so, we
assess the general applicability of this hypothesis to eastern
North American forests and evaluate the utility of broad-
scale trait diversity patterns for understanding processes that
structure communities. By using a data set with a small spa-
tial grain and large spatial extent we can examine whether
community-level processes are general across continental to
regional scales.
Phylogenetic diversity and multivariate metrics of func-
tional diversity integrate over many different organismal
attributes, and are potentially influenced by many different
processes in addition to competition and environmental fil-
tering, including dispersal limitation, positive interactions,
and predation or parasitism (Cavender-Bares et al. 2009,
Pavoine and Bonsall 2011, Spasojevic and Suding 2012). As
such, examining functional diversity based on single traits
that are directly related to an organisms competitive or
stress tolerance abilities may provide less ambiguous infor-
mation about the importance of the two processes of inter-
est (Weiher et al. 1998, Swenson and Enquist 2009,
Spasojevic and Suding 2012). e expected response of a
trait depends on the trait’s ecological role (Fig. 1). In the
context of the SDH, environmental filtering acts on traits
that are important for stress tolerance, favoring convergence
to an optimal trait value. is lowers within-community
trait variation, which we refer to as ‘trait diversity’.
Competition can have opposite effects on traits related to
niche differences versus traits related to competitive ability
(Mayfield and Levine 2010). It is expected to increase the
diversity of traits involved in resource partitioning, but
lower the diversity of traits conferring competitive domi-
nance by favoring convergence on the trait value that leads
to greatest competitive ability (Kunstler et al. 2012).
Competition can occur throughout forest development,
and competitive pressures at different successional stages
may select for different phenotypes (Huston and Smith
1987). Given that the majority of eastern U.S. forests are
young (Pan et al. 2011) due to logging and extensive aban-
donment of agricultural lands in the last century (Abrams
1992, Smith et al. 2009), competitive processes operating at
the early successional phases are most likely to dominate the
trait distributions of current forests.
To assess whether the variation of phylogenetic and trait
diversity in tree communities is consistent with the stress
dominance hypothesis, we developed and tested a set of
hypotheses (Table 1) for changes in community mean trait
values, trait diversity, and phylogenetic diversity along two
stress gradients (soil nutrient availability and water avail-
ability). Our hypotheses are based on competition favoring
a fast-growth, low resource-use efficiency strategy in benign
environments. However, this may not be realistic in older
Figure 1. Expected shifts in trait diversity of different trait types
under the stress-dominance hypothesis. Competition and environ-
mental filtering can have different effects on the within-community
dispersion of different types of traits. Consequently, if the relative
strength of these processes varies along a stress gradients as pre-
dicted by the SDH, the diversity of different trait types will exhibit
different correlations with particular environmental stressors. For
example, traits related to niche differences (resource-use traits) are
expected to exhibit high diversity in highly competitive environ-
ments due to limiting similarity, whereas traits conferring greater
competitive ability will be filtered and exhibit low diversity.
Traits mediating a tradeoff between competitive ability and stress-
tolerance may be filtered at both ends of the gradient and reach
maximum diversity in moderate environments.
Table 1. Expected shifts in phylogenetic diversity, trait values and trait diversity along a stress gradient under the stress-dominance hypothesis.
Predictions assume that environmental filters dominate community assembly in stressful environments and that competitive filters dominate
in benign environments. Solid blue lines depict expected shifts in the mean trait value across communities. Red dashed lines depict expected
shifts in trait diversity across communities.
Low stress
(strong competition)
High stress
(strong environmental filtering)
Phylogenetic diversity
*These expectations hold only
when the phenotypes
governing plants’
environmental tolerances and
niche relations are
phylogenetically conserved, so
that phylogenetic distance
measures functional
Phylogenetic diversity will be
high due to competitive
exclusion of species with
similar phenotypes and the
coexistence of
phylogenetically dissimilar
Phylogenetic diversity should be low in
the most stressful environments
because only certain clades have
evolved the adaptations necessary to
tolerate these conditions.*
Seed mass
Sources differ on how seed size
should be affected by stress
gradients because seed mass is
typically thought to reflect a
tradeoff between viability and
dispersal (Kitajima 2007).
Large seeds are advantageous
under strong competition
(see references in Leishman
et al. 2000). Therefore, mean
seed mass will be high and
seed mass diversity will be
low due to competitive
Both small and large seeds can be
advantageous in stressful
environments (Leishman 2001,
Moles and Westoby 2004). Seed
mass diversity will be high.
Leaf nitrogen content
Leaf nitrogen content reflects a
tradeoff between stress
tolerance and competitive
dominance (Wright et al. 2004)
Competition favors faster
growth rates, leading to high
leaf nitrogen content due to
lower resource-use
efficiency. Leaf nitrogen
diversity will be low due to
competitive filtering.
Stressful environments favor high
resource use efficiency and should
lead to low leaf nitrogen content.
Leaf nitrogen diversity will be low
due to environmental filtering.
Wood density
Wood density reflects a tradeoff
between stress tolerance and
competitive dominance (e.g.
the wood economics spectrum;
Chave et al. 2009).
Competition favors fast growth
and consequently low wood
density. Wood density
diversity will be low due to
competitive filtering.
Low water and nutrient availability in
stressful environments favors high
resource use efficiency and
resistance to embolism, leading to
high wood density (Hacke et al.
2001, Martínez-Cabrera et al. 2009).
Since the xylem architecture of
conifers allows them to persist in
stressful conditions despite low wood
density relative to angiosperms
(Hacke et al. 2001), this increase in
mean wood density may not be very
pronounced. Wood density diversity
will be high because high-density
angiosperms co-occur with lower
density conifers.
forests where competitive exclusion has selected for trees
with a shade-tolerant phenotype, or in disturbance regu-
lated forests that do not follow a traditional successional
trajectory. We considered three physiologically important
traits that represent ecological trade-offs: seed mass, leaf
nitrogen content, and wood density. Previous work has
examined geographic variation in these traits (Swenson
and Weiser 2010, Siefert et al. 2012) as well as temporal
and spatial variation in phylogenetic diversity (Potter and
Woodall 2012, Hawkins et al. 2014) in eastern U.S. for-
ests, but has not evaluated whether this variation reflects
changes in community assembly processes along environ-
mental gradients.
Tree community data
is study was conducted using two complementary data-
bases of vegetation plots in the eastern United States: the
U.S. Forest Service Forest Inventory and Analysis National
program (FIA; Gray et al. 2012) and the Carolina Vegetation
Survey (CVS; Peet et al. 2012) (Fig. 2). We used data from
FIA forest plots spanning all states east of the Great Plains
(approximately 96°W longitude). e CVS data set is smaller
in extent and contains plots in North Carolina, South
Carolina, Georgia, and Florida. Although both programs
for each trait in each plot by averaging the species-level trait
values for all species present in the plot, weighted by their
relative abundance (Garnier et al. 2004, Ricotta and Moretti
2011). For CVS, relative abundance was based on percent
cover and for FIA, relative abundance was based on basal area.
We constructed a phylogeny for each data set using the
Phylomatic online software ver. 2 (Webb et al. 2008),
which provides a dendrogram resolved to the genus level
based on the Angiosperm Phylogeny Group III (Stevens
2012). Branch lengths were assigned using the BladJ
function of the Phylocom software, which assigned nodal
ages down to the family-level based on (Wikström et al.
2001). Where node ages were unavailable, the software
split known distances evenly between ageless nodes and
branch tips occurring between or after known nodes. e
Phylomatic online software provided the topology for
gymnosperms, although no nodal ages were available
so branch lengths were split evenly between each node in
the gymnosperm clade. Similar phylogenies have been
useful in evaluating ecological hypotheses about the
phylogenetic relationships among species in communities
(Cavender-Bares et al. 2006, Kembel and Hubbell 2006,
Kraft and Ackerly 2010).
Trait and phylogenetic diversity
We measured trait and phylogenetic diversity using the
abundance-weighted mean pairwise distance among
species in a plot (MPD; Clarke and Warwick 1998, Webb
2000). is is equivalent to Rao’s quadratic entropy
(Botta-Dukát 2005) which has been shown to discriminate
between community assembly processes in simulated data
(Mouchet et al. 2010) and empirical data (Ricotta and
Moretti 2011). MPD is suitable for this analysis because it is
mathematically independent of richness and robust to imbal-
anced phylogenies when detecting overdispersed and clus-
tered community assembly processes (Vellend et al. 2011).
Figure 2. Geographic distribution of plots in the FIA and CVS datasets. Plots are colored by mean annual climatic water deficit.
measure all tree species occurring on plots of fairly equiva-
lent size (FIA – 672 m2; CVS – 1000 m2), the two programs
differ in their sampling ideology and methodology. e goal
of the FIA program is to assess the state of United States for-
est land by surveying randomly located plots. In contrast,
CVS aims to record naturally occurring plant communities
in the southeastern U.S. and chooses plot locations that
maximize homogeneity within plots and exclude potentially
human-introduced elements. We used only the most
recent survey data from each plot and excluded FIA plots
with evidence of tree planting or cutting and CVS plots
labeled as early successional plots. We conducted parallel
analyses on the two datasets separately, since differences in
sampling methodology may impact ecological inference.
Criteria used to select plots and specific methods of
plot sampling are described in Supplementary material
Appendix 1. Our final data set consisted of 51 051 FIA plots
sampled during 1997–2010 and 2388 CVS plots sampled
during 1988–2010. Data available from the Dryad Digital
Repository: , 7d ..
Trait data
We compiled species-level mean trait data for 269 species for
three traits from primary literature sources and publicly
available trait databases (Supplementary material
Appendix 2): seed mass (average mass of 1 seed, 0.055–
16 200 mg), wood density (oven dry mass divided by green
volume, 0.24–0.89 g cm23), and leaf nitrogen content as a
percent of dry weight (0.32–3.54%). Both the CVS and
FIA datasets contained some trees that were identified
only to the genus level (26 taxa) as well as some species for
which we were unable to obtain trait data (41 species:
20 missing all three traits, of which 15 are Crataegus species);
for these cases, we used genus-level average trait values,
calculated from the species that were present in our datasets
(Supplementary material Appendix 2). Fourteen species
retained missing values due to a lack of information at the
genus level. Seed mass spanned five orders of magnitude
and was therefore log10-transformed prior to all calculations.
We calculated the community-weighted mean trait values
calendar year. D is an effective measure of overall water
stress to plants because it represents the potential additional
evaporative demand not met by available water based on
energy input and precipitation (Stephenson 1998, Lutz
et al. 2010). It has also been shown to better correlate with
tree distributions than water supply measures, such as
annual precipitation (Piedallu et al. 2013). We calculated
D for each plot by intersecting plot geographic coordinates
with 30-arc-second resolution maps of long-term average
annual PET and AET (CGIAR-CSI’s Global Aridity and
PET Database and Global High-Resolution Soil-Water
Balance database, (Trabucco and Zomer 2009, 2010)),
which were generated using WorldClim temperature and
precipitation data (Hijmans et al. 2005) under the
Hargreaves model. irty-one plots (27 FIA, 6 CVS)
were excluded as probable outliers and 118 CVS plots
were excluded from D models due to missing geographic
coordinates. A subset of FIA plots (44 394 plots) were clas-
sified as ‘xeric’ or ‘mesic’ within the FIA database according
to topographic position and water availability as perceived
by the survey crew. We used these classes as a local-scale
alternate measure of water stress and used a Mann–Whitney
U-test to compare mean trait values and trait diversity
between these two groups of plots.
Soil nutrient availability was calculated for CVS
plots using principle components analysis (PCA) of 23 soil
characteristics measured at each plot (Supplementary
material Appendix 1). Correlations of individual soil vari-
ables with the first principle component indicated that it
represents a gradient from acidic, low nutrient, stressful
conditions to benign high nutrient, basic conditions (Peet
et al. 2014). We were unable to calculate soil nutrient avail-
ability for 301 CVS plots due to missing data. We did not
calculate soil nutrient availability for FIA plots because
only a small subset had associated soil data.
We tested for monotonic relationships between mean
trait values and the two stress gradients by fitting two mod-
els: a simple linear regression and a power function of the
form y axb using non-linear least-squares (chosen over lin-
ear regression on log-transformed data so that models could
be compared using AIC). We used the same models to test
for a monotonic relationship between PD and the stress gra-
dients. However, for trait diversity we had hypothesized
hump-shaped relationships so we also tested a linear model
with a quadratic term. Models of trait and phylogenetic
diversity used z-scores as the response variable. All models
were fit in R ver. 2.14. e model with the lowest AIC is
reported, unless the difference in AIC was less than 2, in
which case the simpler model was used (Supplementary
material Appendix 4, Table A4.1). Because of the large
number of plots included in the analysis, all slopes differed
from zero with p , 0.001, so we only report relationships
explaining at least 5% of the total variation (r2 . 0.05).
Phylogenetic diversity
CVS phylogenetic diversity (PD) was negatively correlated
with soil nutrient availability (r 20.44; Fig. 3), the
For trait diversity, traits were standardized by their mean
and standard deviations across species and then distances
among species were computed as the Euclidean distance
between these values. Species with missing trait values
were omitted from calculations involving the missing trait
(affecting 728 plots, but with only 2.3% of the total cover
in these plots omitted). For phylogenetic diversity, the dis-
tance between species is the total branch length between
them on the phylogeny. Calculations were performed in R
ver. 2.14.0 (R Core Team) using the FD (Laliberté and
Shipley 2011) and picante (Kembel et al. 2010) packages.
Inference of environmental filtering and competition is
usually based on the deviation (z-score) of a community’s
functional diversity from the diversity value expected under
a null model that simulates random assembly (Cornwell
et al. 2006, Mouillot et al. 2007, Swenson and Enquist
2007). In addition, z-scores allow diversity to be compared
among communities that differ in species number, since
MPD can be correlated with species richness due to sam-
pling effects (Weiher 2011). We generated trait diversity
null distributions for each plot by randomly shuffling
trait values across the entire species pool in each data set
1000 times and recalculating trait diversity each time
(Swenson and Weiser 2010). We then calculated trait diver-
sity z-scores by subtracting the mean of the null distribution
from the observed trait diversity and dividing by the stan-
dard deviation of the null distribution. Plots falling in the
95th or higher percentile of the null distribution were
considered ‘overdispersed’, exhibiting higher diversity than
expected by random assembly, and plots in the 5th or lower
percentile were considered ‘underdispersed’, exhibiting
lower diversity than expected under random assembly
(Swenson et al. 2012a). A similar model was used to
generate null distributions of phylogenetic diversity for each
plot, except in this case, species were shuffled across the
tips of the phylogeny. Because our phylogeny had an
unbalanced, decelerating topology resulting from the initial
gymnosperm-angiosperm bifurcation, we also calculated
MPD using only angiosperm taxa in order to examine
potential inconsistencies. We also evaluated the mean near-
est taxon distance (MNTD) which may be less sensitive to
the angiosperm-gymnosperm split (Supplementary material
Appendix 3). Because unconstrained null models can be
biased toward identifying underdispersion (de Bello et al.
2012), we also calculated z-scores using null models in
which the species at each site were randomly drawn from
the set of species with environmental niches spanning the
environmental conditions found at that site. Results based
on this constrained null model were qualitatively similar
and are addressed in the Discussion section.
Environmental data and models
We chose to examine two of the most important environ-
mental variables known to structure plant communities
worldwide: soil nutrient availability and water availability
(Archibold 1995). To represent water stress, we used aver-
age annual climatic water deficit (D) (Stephenson 1990),
defined as the difference between potential evapotrans-
piration (PET) and actual evapotranspiration (AET) over a
Figure 3. Phylogenetic diversity in CVS and FIA plots along water deficit and soil nutrient availability gradients. Phylogenetic diversity is
measured as the mean pair-wise phylogenetic distance between taxa in a community. Positive z-score values indicate higher diversity
and negative values indicate lower diversity relative to a null model of random community assembly with respect to phylogenetic relation-
ships. Opaque points are above the 95th or below the 5th percentile of the null distribution and points are colored by the proportion of
the community that is comprised of angiosperm taxa. Regression lines are shown for relationships with r2
. 0.05. Horizontal bands of
color indicate that phylogenetic diversity of a community is largely driven by the relative abundance of gymnosperms versus angiosperms
in a community which results from the deep initial split between these clades.
opposite of our prediction that fertile sites should exhibit
phylogenetic overdispersion due to stronger competition
and weak environmental filtering. PD was not correlated
with water deficit in either data set (Table 2). For both CVS
and FIA, PD was strongly influenced by the presence of
gymnosperms, increasing as the proportion of gymnosperms
in the community increased (Fig. 3). PD changed dramati-
cally when only angiosperm taxa were included in the analy-
sis, eliminating the previously observed negative correlation
between soil nutrient availability and PD (Supplementary
material Appendix 3, Fig. A3.2). Other diversity metrics
performed similarly (Supplementary material Appendix 3).
Community-weighted mean trait values
Mean leaf nitrogen content and wood density responded as
predicted to the stress gradients. However mean seed
mass increased with environmental stress, the opposite of
our initial hypothesis (Fig. 4 and 5, Table 2). Most relation-
ships were weak, explaining less than 10% of the total varia-
tion in mean trait values. e strongest relationship was in
CVS plots between mean leaf nitrogen and soil nutrient
availability (r2
0.38), where leaf nitrogen content initially
increased with soil nutrient availability and reached a plateau
at high levels (Fig. 5). Other model results are in Table 2.
Analysis of mean traits using the local-scale xeric-mesic cat-
egorization yielded trends consistent with the water deficit
models. Xeric sites had significantly higher wood density
and seed mass and lower leaf nitrogen content than mesic
sites (Supplementary material Appendix 5, Fig. A5.1).
Trait diversity
Trait diversity showed no clear relationship (r² , 0.05) with
either stress gradient, with two exceptions (Fig. 4, 5). We
found a moderately weak, negative relationship between seed
mass diversity and water deficit in CVS plots (r² 0.09). We
also detected a weak quadratic relationship between wood
density diversity and soil nutrient availability (Fig. 5) with
diversity reaching a minimum in the middle of the gradient.
Trait diversity was higher in xeric than in mesic FIA plots for
seed mass and wood density (p , 0.001), however, these dif-
ferences were small (Supplementary material Appendix 5,
Fig. A5.1) and may not be biologically meaningful.
We found very little overdispersion of trait diversity in
CVS and FIA plots (Table 3) and this may have decreased
our ability to detect the hypothesized shifts in trait diversity
along stress gradients. Although in several cases peak
diversity appears to occur in the middle of the stress gradient
(Fig. 4, 5), permutation tests revealed that the distribution
Table 2. Models relating mean traits, trait diversity and phylogenetic diversity to water and soil nutrient availability. Models in bold highlight
AIC supported models explaining at least 5% of the variation. r2 for non-linear power models were calculated using the residual sum of
squares (deviance) according to 1 2 (SSresidual/SStotal) (Kvålseth 1985). The estimate reported is the slope parameter for linear models, the
quadratic parameter for quadratic models, and the exponential parameter for power models. N is the number of plots used in each model.
Predictor Response Dataset Form r2Estimate Std. Err. tp N
Water deficit Seed mass FIA linear 0.10 3.54E-03 4.68E-05 75.6 0.00E 00 51023
CVS linear 0.03 7.27E-04 9.24E-05 7.9 5.76E-15 2264
Wood density FIA linear 0.07 2.38E-04 3.77E-06 63.2 0.00E 00 51023
CVS linear 0.08 1.53E-04 1.06E-05 14.5 2.31E-45 2264
Nitrogen % FIA linear 0.01 23.49E-04 1.61E-05 221.6 1.95E-103 51023
CVS linear 0.09 29.99E-04 6.63E-05 215.1 5.96E-49 2264
Seed mass diversity FIA quadratic 0.01 28.95E-06 3.61E-07 224.8 2.79E-135 50501
CVS quadratic 0.09 3.35E-06 1.33E-06 2.5 1.18E-02 2256
Wood density diversity FIA quadratic 0.02 21.43E-06 2.66E-07 25.4 7.99E-08 50501
CVS quadratic 0.03 4.61E-06 9.17E-07 5.0 5.39E-07 2256
Nitrogen % diversity FIA quadratic 0.02 2.00E-06 2.66E-07 7.5 5.34E-14 50501
CVS linear 0.02 9.65E-04 1.27E-04 7.6 5.53E-14 2257
Phylogenetic diversity FIA power 0.00 5.78E-01 2.61E-01 2.2 2.67E-02 50501
CVS power 0.02 3.41E-01 8.58E-02 4.0 7.15E-05 2257
Soil nutrient
Seed mass CVS power 0.00 23.16E-02 1.21E-02 22.6 9.18E-03 2087
Wood density CVS power 0.07 26.88E-02 5.32E-03 212.9 7.77E-37 2087
Nitrogen % CVS power 0.38 3.53E-01 1.04E-02 34.1 1.40E-202 2087
Seed mass diversity CVS quadratic 0.03 21.49E-01 1.92E-02 27.7 1.61E-14 2079
Wood density diversity CVS quadratic 0.05 8.77E-02 1.29E-02 6.8 1.20E-11 2079
Nitrogen % diversity CVS quadratic 0.04 9.11E-02 1.36E-02 6.7 2.51E-11 2080
Phylogenetic diversity CVS linear 0.19 25.57E-01 2.51E-02 222.2 3.34E-98 2080
of overdispersed plots along the stress gradient did not
differ from the distribution of non-overdispersed plots.
Overdispersed plots appear to occur in the middle of the
gradient simply because most plots occur in the middle of
the gradient.
Phylogenetic diversity
Our analysis of phylogenetic diversity clearly demonstrates
the importance of taxonomic scale for interpreting phyloge-
netic overdispersion. Analyzing communities containing
both angiosperms and gymnosperms necessitates a deep ini-
tial bifurcation in any phylogeny which leads to phylo-
genetic diversity being chiefly driven by the ratio of
angiosperm and gymnosperm taxa. Because these two groups
are not as functionally and ecologically distinct as this bifur-
cation would imply, phylogenetic diversity is a poor proxy
for functional diversity. is dependence of phylogenetic
diversity on taxonomic breadth of the phylogeny is well-
known (Cavender-Bares et al. 2006, Vellend et al. 2011),
and our work suggests that measures of phylogenetic diver-
sity are difficult to interpret in a functional context when a
community includes both angiosperms and gymnosperms.
However, we chose not to interpret phylogenetic diversity
from only the angiosperm portion of the community because
doing so eliminates a functionally non-random subset and
could mis-represent the process of community assembly.
Mean trait values
Weak shifts in community-weighted mean trait values
along the two stress gradients provide some evidence that
filters act to shape tree communities along these gradients.
Sites with high water deficit, where potential evaporative
demand is much higher than water availability, tended to
have species with lower nitrogen content in their leaves,
denser wood, and larger seeds. From the SDH, we predicted
all but the last relationship, hypothesizing that higher stress
environments with lower resource availability favor plants
with higher resource-use efficiency, whereas if low stress
environments are structured by competition, plants with
lower resource-use efficiency, but faster growth will be
e strongest relationship we observed was between soil
nutrient availability and leaf nitrogen content, which is con-
sistent with previous studies (Ordoñez et al. 2009). Because
we observe a response in literature-based species-level
mean traits, our analysis provides evidence of an environ-
mental filter rather than a plastic response of individuals to
local conditions or soil enrichment by decomposition of
high nitrogen-content leaf litter. e decrease in leaf
nitrogen content with increasing water stress that we
observed in CVS plots was consistent with our hypothesis
that greater resource use efficiency would be promoted in
stressful environments. is is contrary to studies showing
increased leaf nitrogen in arid environments, as an adapta-
tion to prevent water loss by allowing stomata to remain
closed for longer periods of time (Wright et al. 2001, 2005).
However, these studies included sites which were more
arid than the climate of eastern North America.
Among the three traits we examined, seed mass showed
the least response to both stress gradients. is may reflect
the fact that seed mass is tied to dispersal strategy (Leishman
2001, Kitajima 2007), which we do not expect to be strongly
influenced by either of the two stress gradients. e notable
positive relationship between seed mass and water deficit
runs counter to our initial prediction that large seeds would
Figure 4. Effect of water stress on community-weighted mean trait values and trait diversity in FIA and CVS plots. Water deficit is plotted on the x-axis with higher water deficit corresponding
to higher water stress. Panel (A) shows mean trait values while panel (B) show trait diversity z-scores. Positive z-score values indicate high diversity and negative values indicate low diversity compared
to a null model of random community assembly with respect to traits. Black points are above the 95th or below the 5th percentile of the null distribution, whereas grey points are between these
percentiles. Lines show the best fit models and only included if r2 . 0.05 (Table 2 and Supplementary material Appendix 4, Table A4.1).
Figure 5. Effect of soil nutrient availability on community-weighted mean trait values and trait diversity in CVS plots. e x-axis is the first
principle component of a PCA of 23 soil variables and represents a soil nutrient availability gradient ranging from acidic, stressful
conditions (negative values) to basic, benign conditions (positive values). e first column shows mean trait values and the second
column shows trait diversity z-scores, as described in Fig. 4. Black points are above the 95th or below the 5th percentile of the null distribu-
tion, whereas grey points are between these percentiles. Lines show the best-fit models and are only included if r2 . 0.05 (Table 2 and
Supplementary material Appendix 4, Table A4.1).
be competitively superior in low stress environments.
Instead it seems to support experimental evidence that large
seeds are advantageous in drier soil because they confer
greater seedling survival (see references in Leishman et al.
2000). Given the slight trend toward lower seed mass diver-
sity at higher water deficit, our data suggest that the rela-
tionship between seed mass and water availability may be
driven by filtering for larger seeds at drier sites. We find
no evidence for competitive filters on seed mass in benign
e observed shifts in mean trait values differ from
those reported previously in Forest Inventory and Analysis
plots, in which annual precipitation was positively corre-
lated with seed mass and wood density and negatively
correlated with leaf nitrogen content (Swenson and
Weiser 2010). is apparent disagreement can be resolved
by recognizing that annual precipitation measures water
supply whereas water deficit measures evaporative demand.
In fact, annual precipitation and water deficit were weakly
positively correlated along our stress gradient (r 0.20),
measured (Leishman et al. 2000, Sungpalee et al. 2009,
Albert et al. 2010, Auger and Shipley 2013). However, a
study examining community-scale processes, regardless of
spatial extent, may still need to account for local variation in
traits (Albert et al. 2011).
e trait-diversity z-scores that we analyzed are known
to be susceptible to the formulation of the null model
(Mouchet et al. 2010, de Bello 2012). Unconstrained
null models like ours are biased toward detecting underdis-
persion because regional species pools may differ in their
trait distributions. Our null model implicitly assumed that
any species could colonize any site. If certain geographic
areas do not contain species with trait values covering the
entire range of trait values found in the total species pool,
then our null model would bias sites in those areas toward
underdispersion. However, we checked the range of trait
values that occurred within equal-area grid cells across our
study region and found no geographic bias in these trait
ranges. Unconstrained null models are also biased toward
underdispersion because environmental filters operate prior
to biotic interactions so that observed communities will
typically have lower trait diversity than expected of a com-
munity randomly assembled from species across different
environments or habitats (de Bello et al. 2012). One solu-
tion is to attempt to remove abiotic environmental filters by
comparing communities to a null expectation acquired
only from species that could potentially tolerate a site’s envi-
ronment (Peres-Neto et al. 2001, de Bello et al. 2012).
While this approach does not allow us to compare the rela-
tive influence of environmental filtering and competition,
which is crucial for testing the SDH, we wanted to affirm
that the underdispersion and lack of systematic variation
that we observed was not an artifact of an unconstrained
null model. We re-calculated trait diversity z-scores for
CVS plots and a subset of southeastern FIA plots using
environmentally constrained null models that only permit-
ted shuffling of species among sites that fell within species’
environmental niches. Although this resulted in a small
increase in the number of plots exhibiting trait diversity
overdispersion, there was no change in the lack of observed
relationships between trait diversity and environmental
gradients (Supplementary material Appendix 6). Analytical
approaches that separate the effects of competition from
environmental filtering (de Bello et al. 2012) are especially
useful when these processes are predicted to filter traits
toward similar values. In our case, competitive and environ-
mental filters were expected to select for different trait
e overall lack of plots exhibiting trait overdispersion
limited our ability to discern shifts in trait diversity
along the gradients. Yet, the pervasiveness of trait diversity
underdispersion may be ecologically meaningful. Several
other studies have found consistent underdispersion in
plant communities along environmental gradients. De Bello
et al. (2009) attributed underdispersion in specific leaf
area throughout a moisture gradient to environmental fil-
tering. Savage and Cavender-Bares (2012) also found that
environmental filtering was important for willow tree
communities along the length of a hydrologic gradient,
with trees at the dry end exhibiting traits associated with
drought tolerance and trees at the wet end exhibiting traits
with highest water deficit occurring in locations with
moderate annual precipitation.
Trait diversity
Trait diversity did not notably respond to either of the stress
gradients we examined. is can be interpreted in several
ways: 1) our data set did not encompass a wide enough envi-
ronmental range to capture both stressful and benign condi-
tions, 2) the traits we examined are not influenced by
the environmental gradients measured, 3) the species-level
mean trait values we used masked local trait–environment
relationships, 4) our metrics did not accurately capture exist-
ing trait convergence or divergence, or 5) our hypotheses
about processes structuring tree communities along stress
gradients are not generally true across eastern North
It is unlikely our dataset failed to encompass a viable
stress gradient or that the traits we examined were not influ-
enced by it, because we do observe shifts in mean trait
values along both environmental gradients, as have others
(Wright et al. 2005, Swenson and Weiser 2010). Combined
with the significant trait underdispersion that we observe in
many plots, this suggests that both gradients encompass con-
ditions stressful enough to impose filters (albeit weak) on
community membership.
It is possible that our metrics did not accurately
capture existing patterns of trait diversity, either by ignoring
intraspecific variation or by our choice of diversity metric
and null model. Using species-level mean traits may have
masked local mechanisms whereby trait plasticity among
individuals allows coexistence through niche partitioning
(Clark 2010, Burns and Strauss 2012). Several studies have
found trait divergence in local communities when account-
ing for intraspecific trait variation (Jung et al. 2010, de Bello
et al. 2011, Paine et al. 2011). e necessity of including
intraspecific trait variation in large-scale studies has been
debated, since for many traits, variation between species is
usually greater than variation within species when enough
species are included. is is likely true for the three traits we
Table 3. Proportion of FIA and CVS plots with significantly overdis-
persed or underdispersed trait diversity. Overdispersed plots have
trait diversity above the 95th percentile of the null distribution,
underdispersed plots are below the 5th percentile, and random
plots are between the 5th and 95th percentiles. More plots are
under dispersed than overdispersed, but in general most plots have
a level of trait diversity that does not differ from random assembly.
FIA wood density
1.33 75.42 23.25
CVS wood density
0.93 70.41 28.67
FIA leaf nitrogen
1.35 82.69 15.96
CVS leaf nitrogen
2.03 85.82 12.15
FIA seed mass
3.18 81.71 15.10
CVS seed mass
7.95 88.43 3.62
communities, although it may operate in more restricted
e broad geographic extent and large number of com-
munities in our analysis spanned a variety of climates, habi-
tat types, successional stages, and disturbance regimes.
is heterogeneity of environmental contexts is a necessary
condition for testing the generality of a theory in commu-
nity ecology, but it also could have obscured patterns result-
ing from the SDH if this hypothesis only applies under
certain circumstances. e majority of the plots that we
analyzed were embedded in a human-modified landscape
and occurred at a range of successional stages. is may
have masked trait–environment relationships, given that
the importance of dispersal limitation, abiotic filters,
and biotic interactions are known to shift throughout forest
succession as are the traits that are affected by these pro-
cesses (Prach et al. 1997, Douma et al. 2012, Kröber
et al. 2012 and references therein). Additionally, the SDH
may not apply across forests experiencing different levels of
disturbance, since disturbance-related filters on tree traits
can vary across disturbance regimes (Loehle 2000). Future
studies could assess whether SDH-related trait variation is
more evident when restricting analyses to particular eco-
logical contexts. Given the contingent nature of many eco-
logical systems, this approach could aid the search for
general principles in a time of increasing data availability
and integration.
Acknowledgements – is work resulted from a Dimensions of
Biodiversity Distributed Graduate Seminar at the Univ. of North
Carolina at Chapel Hill and we thank the participants for compil-
ing the trait data and initiating the idea for project: K. Becraft,
C. Fieseler, C. Hakkenberg, C. Mitchell, C. Payne, K. Peck,
D. Tarasi, and C. Urbanowicz. We also thank the entire DBDGS
community for their support. is project would not be possible
without the individuals who collected the FIA and CVS data
and made it available. Special thanks to Robert Peet and Nathan
Swenson for the use of their data and to four reviewers and the
subject editor whose comments significantly improved the manu-
script. is work was funded by NSF grant #DEB-1050680 to the
Univ. of Washington (J. Parrish and S. Andelman, PIs) through a
subcontract to the Univ. of North Carolina at Chapel Hill (AHH,
C. Mitchell and R. Peet, PIs). All authors contributed equally to
this research.
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Supplementary material (Appendix ECOG-00473 at
, Appendix 1–6.
... Revealing how trait dispersions vary with environmental gradients is important to advance the predictive ability of functional ecology (Muscarella & Uriarte, 2016). A widely used explanatory proposition for the relationships between trait dispersions and environmental gradients is the stress-dominance hypothesis (SDH), which predicts that environmental filtering plays a major role in stressful environments, yielding a clustered pattern of trait dispersion, whereas biotic interactions determine community assembly in benign environments, favoring an overdispersed pattern of trait dispersion (Coyle et al., 2014;Swenson & Enquist, 2007;Weiher & Keddy, 1995). Therefore, an increasing trait dispersion pattern from stressful to benign environments should be expected (Costa et al., 2017;Spasojevic & Suding, 2012;Wang et al., 2018). ...
... Therefore, an increasing trait dispersion pattern from stressful to benign environments should be expected (Costa et al., 2017;Spasojevic & Suding, 2012;Wang et al., 2018). Although many studies have tested the universality of the SDH in forest communities, empirical supports are still contradictory (Coyle et al., 2014;Lhotsky et al., 2016;Spasojevic & Suding, 2012;Wang et al., 2018). ...
... Additionally, previous studies also found that the relative importance of environmental variables to community assembly increased with increasing spatial scales (Chase, 2014;Legendre et al., 2009). Thus, multiple spatial scale analysis is helpful to evaluate the relationships between trait dispersions and environmental gradients, since a large number of quadrats represent a wide range of spatial variability in soil resource availability and species composition (Coyle et al., 2014). ...
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Identifying patterns and drivers of plant community assembly has long been a central issue in ecology. Many studies have explored the above questions using a trait‐based approach; however, there are still unknowns around how patterns of plant functional traits vary with environmental gradients. In this study, the responses of individual and multivariate trait dispersions of 134 species to soil resource availability were examined based on correlational analysis and torus‐translation tests across four spatial scales in a subtropical forest, China. Results indicated that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource (available phosphorus) showed negative relationships with trait dispersions, non‐limited resource (available potassium) showed positive relationships with trait dispersions, and saturated resource (available nitrogen) had no effect on trait dispersions. Moreover, compared with the stem (wood density) and architectural trait (maximum height), we found that leaf functional traits can well reflect the response of plants to nutrient gradients. Lastly, the spatial scale only affected the magnitude but not the direction of the correlations between trait dispersions and environmental gradients. Overall, the results highlight the importance of soil resource availability and spatial scale in understanding how plant functional traits respond to environmental gradients. In this study, the responses of individual and multivariate trait dispersions of 134 species in Dinghushan plot, China, to soil resource availability were examined. Results showed that different degrees of soil resource availability had different effects on trait dispersions. Specifically, limited resource mainly showed negative relationships with trait dispersions, non‐limited resource mainly showed positive relationships with trait dispersions, and saturated resource had no effect on trait dispersions.
... Environmental filtering can screen some species which can survive in a specific environment (Cui et al., 2022), especially in harsh environmental conditions (Botta-Dukát and Czúcz, 2016), and make their growth and abundance have convergent characteristics (Shipley et al., 2016). For example, under coastal environmental conditions, due to the influence of periodic tidal flooding, the leaf stomatal characteristics and photosynthetic function of plants up the tidal line showed convergent adaptation, while the leaf stomatal and morphological traits of plants below the tidal line showed coevolution (Coyle et al., 2014). Besides, different plants have different levels of adaptation. ...
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Elucidating the relationship between the variation of plant leaf functional traits and the environment is necessary for understanding the adaptation mechanism of plants and predicting changes in ecosystem structure. In this study, the leaf traits of desert plants in Ebinur Lake National Wetland Nature Reserve in Xinjiang, China were studied from the aspects of plant life forms (annuals, perennials and shrubs), phylogenetic signals, and relation to soil properties, using the principal component analysis, variance decomposition, and one-way analysis of variance. The results showed that: (1) There were significant differences in leaf carbon concentration (annuals>shrubs>perennials), leaf nitrogen concentration (shrubs ≥ perennials ≥ annuals), and leaf moisture content (perennials ≥ annuals ≥ shrubs) among the life forms, but there was no significant difference in leaf phosphorus concentration. Besides, soil nitrogen and phosphorus were significantly positively correlated with leaf carbon concentration and leaf nitrogen concentration. (2) There were significant differences in leaf carbon concentration, leaf nitrogen concentration, specific leaf area, and leaf moisture content between C3 and C4 plants, while the differences in P and leaf dry matter content were not significant. Besides, there were significant differences in leaf carbon concentration, leaf nitrogen concentration, specific leaf area, and leaf moisture content between leguminous and non-leguminous plants. Leguminous plants had higher leaf carbon concentration, leaf nitrogen concentration, and specific leaf area than non-leguminous plants, while non-leguminous plants had higher leaf moisture content than leguminous plants. (3) One way ANOVA analysis showed that taxonomy had a more significant effects on leaf carbon concentration, leaf nitrogen concentration, specific leaf area, and leaf moisture content than soil properties, and the coefficient of variation of leaf carbon concentration was greater than 50%. The phylogenetically independent contrasts analysis showed that the phylogenetic signal of all leaf traits was detected in all species and low (K value < 1, p > 0.05), indicating that the functional traits were weakly affected by phylogenetics. Therefore, desert plants in the Ebinur Lake Basin evolved to adapt to arid environments, and leaf traits showed convergent variation.
... Recent studies of individual mountain gradients further provide initial support for this hypothesis. Taxonomic, functional, and phylogenetic diversity of rodents decreased with elevation on the wet tropical slopes of the Peruvian Andes (Dreiss et al., 2015), which conforms to the widely held expectation that functional and phylogenetic diversity should be highest in lowlands, because of weak environmental filters and strong competition and niche partitioning (Coyle et al., 2014;Hanz et al., 2019;Kluge & Kessler, 2011). In contrast, however, functional and phylogenetic diversity of small mammals increased with elevation on three dry, temperate mountains in the Great Basin Desert in North America . ...
Patterns of species richness along elevation gradients vary with geographic and environmental factors but evidence for similar variation in functional and phylogenetic diversity remains scarce. Here, we provide the most comprehensive evaluation to date of elevational gradients in taxonomic, functional, and phylogenetic diversity of rodents – one of the most ecologically diverse groups of mammals – and test the effects of latitude and aridity on their variation for the first time. Forty‐nine mountains on five continents. Contemporary. Rodents (Rodentia). We compiled elevational distributions of 374 rodent species across 49 elevational gradients. For each gradient, we quantified – in 100‐m elevational bins – rodent species richness and functional and phylogenetic richness, evenness, and dispersion, and their species richness‐corrected equivalents. To assess how rodent diversity varies with elevation, we fitted a series of models that included elevation, average latitude, and aridity of each mountain system while accounting for variation in study design and sampling effort. A common mid‐elevational peak in species richness among mountains contrasts with functional and phylogenetic diversity pattern variation (model shape and slope) explained by the aridity at a mountain's base. Specifically, we find that functional and phylogenetic richness and dispersion decline with elevation in wet mountain systems but increase with elevation in arid mountains. In this first comparative analysis of mammal functional and phylogenetic elevational gradients, we find that the decoupling of each from species richness is particularly pronounced in arid regions. Wet‐mountain lowlands and arid‐mountain highlands harbour the most functionally and phylogenetically diverse rodent communities, indicating that water availability is a strong environmental filter in structuring diversity of small mammals on mountain gradients. High regularity of species distances within assemblages supports a constant role for competition across all elevations and niche expansion in elevations with greater species richness.
... Mechanisms of species maintenance can be divided into deterministic processes based on niche theory (i.e., environmental filtering and interspecific competition) (Webb et al., 2002;Dante et al., 2013) and stochastic processes based on neutral theory (e.g., dispersal limitation) (Hubbell, 2001;Vellend, 2010), both of which jointly shape diversity patterns in variable formats (Adler et al., 2007;Wennekes et al., 2012). While environmental filtering has been found to be more important for community assembly in a stressful habitat, competitive exclusion is generally more crucial in ecologically healthy conditions (Coyle et al., 2014). By including information about community phylogeny and species functional traits, researchers can verify biodiversity pattern hypotheses from the perspective of evolutionary history and ecological adaptation, which is helpful to understand the imprints of long-term processes on community assembly and species coexistence (Swenson and Enquist, 2009;Purschke et al., 2013). ...
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The contributions and interaction of biotic and abiotic processes in community assembly are crucial for understanding the elevational patterns of biodiversity. The combined analyses of taxonomic, phylogenetic, and functional diversity are necessary to resolve this issue. By investigating vegetation in 24 transects sampled on Hongla Snow Mountain, in the central Hengduan Mountain Ranges in Southwest China, we delineated the elevational vegetation spectrum on the eastern and western slopes, analyzed the elevational variation in taxonomic, phylogenetic, and functional diversity of woody plant species, and compared the community structure of phylogeny and function in the low-elevational shrublands, mid-elevational forests, and alpine shrubs and meadows. The species richness, phylogenetic diversity, and functional diversity of woody plants showed nonstandard hump-shaped patterns with two peaks along the elevational gradient. The community structure of phylogeny and function (including tree height, leaf area, specific leaf area, leaf thickness, bark thickness, and wood density) clustered in the low-elevation shrub communities, being random and over-dispersed in mid-elevational forests. The phylogenic structure was over-dispersed in alpine communities, whereas the functional structure was clustered. Elevational patterns in taxonomic, phylogenetic, and functional diversity, together with the mean and variation in woody plant functional traits, suggested drought stress and freeze stress as environmental filters dominating the assembly of low and high elevation non-forest communities, and a conspicuous effect of biotic facilitation was also suggested for alpine habitats. By contrast, interspecific competition dominated the community assembly of forests at mid-elevations. The difference in biodiversity indices between the west and east slopes reflected the effects of the Indian Monsoon on the geomorphic patterns of ecosystem structure. These results increased our understanding of biodiversity patterns and underlying mechanisms in the Hengduan Mountains of Southwest China and highlighted the priorities for biodiversity conservation in this region.
... However, there are several general ecological hypotheses that predict changes in the relative importance of community assembly processes along resource, disturbance, and/or stress gradients. One of them is the Stress-Dominance Hypothesis (SDH; Coyle et al. 2014, adapted from Swenson & Enquist 2007, which predicts that in a harsh environment, habitat filtering is the major driver of community composition, resulting in strong trait convergence, while in less stressful habitats limiting similarity is more important, resulting in trait divergence (Weiher & Keddy 1995). ...
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Background and aims – The research aim was to investigate the relation between large-scale geographic factors and the functional structure of the herbaceous layer of calcareous beech forests in the Apennines, managed as high forest. Material and methods – We selected 163 plots (20 × 20 m), ranging from Central to South Italy, using a random stratified sampling design. We correlated the effect sizes of traits’ community-weighted means, functional richness, evenness, divergence, dispersion, and Rao’s quadratic entropy, with the main axes of variation in species composition. Key results – The geographical range played a weak role in shaping the species composition of the herbaceous layer. However, we found evidence of functional convergence towards the northern sectors of the study area, where traits linked to resource retention strategies and vegetative spread are filtered. We did not find any evidence of convergence northwards for leaf phenology and pollination types. Conclusion – The increase of the intensity in the environmental stress was associated with a decrease of diversity for traits related to resource conservation strategies and vegetative propagation. On the contrary, the lower cold stress intensity southwards fostered a better niche partitioning, ensuring the coexistence of species with different modalities of resource acquisition and conservation.
... Due to the highly selective pressure by cold temperatures on the species occurrence on the Qiangtang Plateau (Figure 3a), we expected phylogenetically clustered structures of species assemblages based on the stress dominance hypothesis (Coyle et al., 2014;Graham et al., 2009). Species assemblages for mammals changed from phylogenetic clustering on the Qiangtang Plateau to overdispersion in the Hengduan Mountains (Figure 4(a)). ...
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Mountains harbour a rich and non‐random cluster of species, yet knowledge of the species' biological attributes that support their coexistence in the montane community is limited. Here, we investigated the association of species occurrence on the Tibetan Plateau with their morphological, ecological or evolutionary constraints. Tibetan Plateau (TP). Mammals and birds. We tested whether species occurrence on the TP correlates with morphological, ecological or evolutionary constraints using the spatial distribution, phylogeny, dispersal ability and thermal niche property data for 1353 terrestrial vertebrates (383 mammals and 970 birds). We used standard (non‐phylogenetic) and phylogenetic logistic regressions to elucidate the relative contributions of these attributes of species to explaining their occurrence on the TP. We assessed the geographical patterns of the community structures on the TP and fitted linear mixed models to explore the underlying eco‐evolutionary forces. The TP species exhibited a higher cold tolerance, wider thermal niche breadth and higher rate of niche evolution than non‐TP species. We supported the assumption that the TP species were not a random subset from the species pool, but were structured jointly by environmental filtering and dispersal limitation. While dispersal and ecological processes underlying species assemblages varied spatially and among taxa, we found that species in stressful environments were limited by environmental filtering, whereas dispersal limitation was more pronounced under favourable climatic conditions. Our study finds that environmental filtering and dispersal limitation jointly shape the species assemblage on the TP. These findings provide significant insights into community assembly processes on the TP and other montane ecosystems on Earth, especially those that are sensitive to global warming.
Background Assessing functional diversity to identify its spatial patterns and drivers is an important step towards understanding the adaptive capacity of ecosystems to environmental change. However, until now, these mechanisms were poorly understood in the temperate forests of northeastern China, which prevented the development of new management methods aimed at increasing functional trait diversity and thus ecological resilience. Methods In this study, we mapped functional diversity distributions using a Kriging Interpolation Method. A specific random forest model approach was adopted to test the importance ranking of 18 variables in explaining the spatial variation of functional diversity. Three piecewise structural equation models (pSEMs) with forest types as random effects were constructed for testing the direct effects of climate, and the indirect effects of stand structure on functional diversity across the large study region. Specific causal relationships in each forest type were also examined using 15 linear structural equation models. Results Although environmental filtering by climate is important, stand structure explains most of the functional variation of the forest ecosystems in northeastern China. Our study thus only partially supports the stress-dominance hypothesis. Several abundant species determine most of the functional diversity, which supports the mass ratio hypothesis. Conclusions Our results suggest that forest management aimed at increasing structural complexity can contribute to increased functional diversity, especially regarding the mixing of coniferous and broad-leaved tree species.
Peatlands have accumulated enormous amounts of carbon over millennia, and climate changes threatens the release of this carbon into the atmosphere. Fungi are crucial drivers of global carbon cycling because they are the principal decomposer of organic matter in peatlands. However, the fungal community composition and ecological preferences in peat remain unclear, which restricts our ability to evaluate the role of the fungal community in peat biogeochemical functions. We investigated 54 soils from 6 low-temperature peatlands across China to fill this knowledge gap. The peat was divided into above-water table (AWT) and below-water table (BWT) layers based on the water table fluctuation. We investigated fungal community assembly processes and drivers for each peat layer. The results showed that fungal communities differed significantly among peat layers. The relative abundance of symbiotrophs was significantly higher in the AWT (17.4%) than in the BWT (9.0%), while the abundances of yeast and litter saprotrophs were obviously lower in the AWT than in the BWT. Our results revealed that the assemblage of both fungal taxonomic and phylogenetic communities was mainly governed by stochastic processes in both AWT (87.8%) and BWT (58.6%) layers. However, in the BWT, the relative importance of deterministic processes (28.4%) significantly increased, indicating a potential deterministic environmental selection induced by permanently anaerobic condition. Mean annual precipitation and mean annual temperature were the most critical drives for the assemblage of the fungal community in the BWT. These observations collectively indicate that fungal community assembly is depth-dependent, implying different community assembly mechanisms and ecological functions along the peat profile. These findings highlight the importance of climate driven deep peat fungal community composition assemblages and suggest the potential to project the changes in fungal diversity with ongoing climate change.
1. Despite the recognition of positive interactions as an important driver of species coexistence and community structure, the underlying mechanism of how facilitation affects assembly processes along stress gradients is poorly explored. Understanding the responses of functional diversity to benefactor species at the extreme end of the stress gradient could provide valuable insight about facilitation‐involved assembly mechanisms and contribute to the predictions of species coexistence under climate change. 2. In the drought‐stressed community in the Badain‐Jaran Desert, the responses of the local community to the nurse shrub species Calligonum mongolicum Turcz. were evaluated using hierarchical Bayesian models. For the 3‐year experiment, summer rainfall in each year formed a natural gradient of drought stress. To evaluate the shrub’s effects on the assembly process along that gradient, individual samples were collected in pairwise under‐shrub and open habitats, and four traits related to stress tolerance and resource acquisition were measured simultaneously. 3. Under moderate drought stress, we observed shifting community‐weighted means, broadening ranges and reducing overlaps of functional traits under shrubs. These effects were partly driven by a distinct microenvironment created by shrub plants, in particular the improvement and heterogeneity of soil moisture conditions. However, this influence on trait distributions was strongly dependent on the environmental context, and generally disappeared as drought stress shifted toward its driest end, almost in line with the decreased positive interaction assessed by plant density and species diversity. 4. This study focused on water‐limited community that lies at the driest end of drought gradient and confirmed that facilitation can drive the assembly process through both environmental filtering and niche differentiation. More importantly, these assembly mechanisms are proven to become less efficient under extreme drought stress, which may suggest the occasionally disappearing role of benefactor plants on community assembly and an increasing risk of biodiversity loss in the context of climate change.
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Aims One of the determinants of water availability in drylands, groundwater plays a fundamental role in regulating plant traits, phylogeny, and community assemblage. However, considerable uncertainties exist regarding how groundwater depth influences the relative importance of community assembly process in plant communities, as well as how the influence differs among the above- and belowground components. Methods By using the leaf and root functional traits, in addition to associated environmental factors in 230 plant communities in the lower reaches of an arid inland river basin, we attempted to uncover how the pattern of the community assembly process varied along a depth gradient of groundwater and the key drivers of this variation. Results (1) Across all study sites, we found that the standard effect size of Rao’s quadratic entropy (SES.RaoQ) of leaf and root functional diversity determined using the plant individual species, mean functional traits and phylogenetic information was significantly less than zero. Functional clustering was pervasive among plant communities (90% of the traits). (2) Groundwater depth and soil variables together explained 13%-39% and 14%-48% of the variation in SES.RaoQ determined using leaf and root traits, respectively, and groundwater depth individually explained 13%-22% and 14%-36% of the variation. (3) The SES.RaoQ determined using leaf and root traits decreased as mean groundwater depth decreased, but it increased with increased groundwater depth seasonality. Root traits showed a faster shift in SES.RaoQ along groundwater depth gradients than leaf traits. Conclusion Plant communities in an arid inland river basin are primarily affected by deterministic processes, which supports the niche theory. Most plant communities exhibited functional clustering. Groundwater depth is the key factor determining the relative importance of the community assembly process of plant communities. With the decrease of groundwater depths, the functional structure changes from a pattern of mostly overdispersion to a pattern of clustering. The variation in aboveground functional structure along groundwater gradients is highly consistent with that of the belowground functional structure, but the belowground component of plant communities may be more sensitive to changes in groundwater depth.
This striking book provides a handy summary of the ecology of the world's vegetation. The introductory chapters provide a basic back-drop to the subject. The subsequent chapters examine sequentially the form and function of each major biome throughout the world.
Because of the correlation expected between the phylogenetic relatedness of two taxa and their net ecological similarity, a measure of the overall phylogenetic relatedness of a community of interacting organisms can be used to investigate the contemporary ecological processes that structure community composition. I describe two indices that use the number of nodes that separate taxa on a phylogeny as a measure of their phylogenetic relatedness. As an example of the use of these indices in community analysis, I compared the mean observed net relatedness of trees (≥10 cm diameter at breast height) in each of 28 plots (each 0.16 ha) in a Bornean rain forest with the net relatedness expected if species were drawn randomly from the species pool (of the 324 species in the 28 plots), using a supertree that I assembled from published sources. I found that the species in plots were more phylogenetically related than expected by chance, a result that was insensitive to various modifications to the basic methodology. I tentatively infer that variation in habitat among plots causes ecologically more similar species to co‐occur within plots. Finally, I suggest a range of applications for phylogenetic relatedness measures in community analysis.
Biological Diversity provides an up-to-date, authoritative review of the methods of measuring and assessing biological diversity, together with their application. The book's emphasis is on quantifying the variety, abundance, and occurrence of taxa, and on providing objective and clear guidance for both scientists and managers. This is a fast-moving field and one that is the focus of intense research interest. However the rapid development of new methods, the inconsistent and sometimes confusing application of old ones, and the lack of consensus in the literature about the best approach, means that there is a real need for a current synthesis. Biological Diversity covers fundamental measurement issues such as sampling, re-examines familiar diversity metrics (including species richness, diversity statistics, and estimates of spatial and temporal turnover), discusses species abundance distributions and how best to fit them, explores species occurrence and the spatial structure of biodiversity, and investigates alternative approaches used to assess trait, phylogenetic, and genetic diversity. The final section of the book turns to a selection of contemporary challenges such as measuring microbial diversity, evaluating the impact of disturbance, assessing biodiversity in managed landscapes, measuring diversity in the imperfect fossil record, and using species density estimates in management and conservation.