Download Phylogenetic turnover patterns consistent with niche conservatism in

Journal of Ecology
doi: 10.1111/1365-2745.12385
Phylogenetic turnover patterns consistent with niche
conservatism in montane plant species
e Fortin1
Lanna S. Jin1*, Marc W. Cadotte1,2 and Marie-Jose
1
Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, ON, Canada; and 2Department of
Biological Sciences, University of Toronto at Scarborough, Scarborough, ON, Canada
Summary
1. A fundamental aim in community ecology is to elucidate the processes structuring communities. The key to
understanding community patterns is to account for species differences and similarities in how they respond to
large-scale environmental gradients and partition local resources. Using phylogenetic relationships as a representation of species’ ecological differences, we use phylogenetic beta-diversity (PBD) to examine how patterns of
community relatedness change across space.
2. Specifically, we examine how PBD informs our understanding of the processes (spatial or environmental)
directing species assembly along montane environmental gradients – in particular, whether patterns are consistent with niche conservatism. Also, we examine the depth of phylogenetic turnover to see where in evolutionary
history shared environmental tolerances appear conserved.
3. For angiosperm communities situated to the east and west of the Continental Divide (CD) in the Rocky
Mountain National Park in CO, USA, we compare nine beta-diversity indices (taxonomic, TBD: Jaccard,
Bray–Curtis and Gower; PBD: PhyloSor, UniFrac, Dnn, Dpw, Rao’s D and Rao’s H) to changes in space, environment and environment controlling for space with the partial PROTEST method.
4. We find that PBD differs from taxonomic beta-diversity and some PBD metrics were redundant with one
another (i.e. Rao’s D & Dpw and UniFrac & PhyloSor). The indices’ different sensitivities to evolutionary depth
affected their responses to environmental and spatial gradients: TBD consistently associated greater with all
factors (space, environment and environment controlled for space) than PBD metrics; PBD metrics more sensitive to recent changes were more highly correlated with all factors than those metrics sensitive to turnover
deeper in the phylogeny. Generally, beta-diversity associated strongest with environment and least with space.
5. Synthesis. Taxonomic and phylogenetic beta-diversity complements each other to provide an enhanced perspective of the process governing community structure. Together, they depict patterns expected under niche
conservatism for the Rocky Mountain angiosperm communities, that is, species’ names change faster than their
evolutionary relationships across space.
Key-words: angiosperms, beta-diversity, community ecology, community phylogenetics, determinants of plant community diversity and structure, diversity, niche conservatism, phylogenetic betadiversity, Procrustes Superimposition, PROTEST
Introduction
Community ecology seeks to explain species diversity, not
only within communities, but also at broader spatial scales.
Of the three scales at which ecologists measure species diversity (at a site, among sites and regionally), beta-diversity links
local (alpha) patterns of diversity to regional (gamma) patterns (Whittaker 1960). Beta-diversity captures species variation from community-to-community and can explain whether
an ecological process (e.g. competition or environmental filtering) contributes to changes in species diversity patterns.
For instance, an environmental filter might drive species
diversity patterns when a gradient (e.g. moisture or elevation)
*Correspondence author. E-mail: [email protected]
that is meant to capture the process is tied to the loss or gain
of species in local communities. Due to the vast diversity in
species present today and because the unique traits they possess arise through evolution, we know that evolutionary processes (e.g. speciation and extinction; niche conservatism and
limiting similarity) also drive species assembly patterns. Yet
conventional measures of beta-diversity that only measure
nominal changes in species taxonomy (taxonomic beta-diversity) ignore the profound impact species’ ancestral lineages
may have on species’ current ecological distributions. In this
paper, we demonstrate how the signals from both ecological
and evolutionary processes are visible through evaluating
phylogenetic measures of beta-diversity on ecological data.
Phylogenetic beta-diversity (‘phylobetadiversity’; hereafter,
‘PBD’) incorporates information on species’ evolutionary
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society
2 L. S. Jin, M. W. Cadotte & M.-J. Fortin
relationships with beta-diversity metrics. Analogous to concepts in taxonomic beta-diversity, PBD measures shifts in
phylogenetic diversity among communities (Graham & Fine
2008), where phylogenetic diversity represents the total
amount of evolution contained within a community (as measured in phylogenetic branch lengths). When species’ lineages
retain traits pertinent to species’ niches over evolutionary time
(niche conservatism; Wiens et al. 2010), phylogenetic diversity is thought to correspond to niche diversity (as defined by
total niche space) (Mouquet et al. 2012; Srivastava et al.
2012) and has been shown to capture a community’s functional diversity (i.e. total functional trait diversity) beyond
taxonomic measures of diversity (Cadotte et al. 2009, 2010;
Devictor et al. 2010; Srivastava et al. 2012; however, see
Kraft, Valencia & Ackerly 2008; Graham, Parra & Tinoco
2012). When paired with gradients, PBD reveals species’
niche responses to changes along a gradient – for instance,
changes in environmental conditions may drive not only species’ identity, but also the presence of lineages of species. To
this end, PBD supplements taxonomic beta-diversity with the
amount of species’ evolutionary history in assemblages (Devictor et al. 2010; Meynard et al. 2011).
PBD also provides insight into the ecological and evolutionary drivers of community assembly beyond the capacity of
Webb et al. (2002)’s ecophylogenetic framework. Darwin’s
competition-relatedness hypothesis (coined by Cahill et al.
2008) states that closely related species are more ecologically
similar and therefore require a similar set of environmental
conditions to persist; relatives consequently compete more
intensely for the same resources, thus limiting coexistence and
driving niche and trait differences (Darwin 1859). Webb et al.
(2002)’s framework abstracts the concepts from Darwin’s
hypothesis to then infer processes acting at the community
level, where phylogenetic patterns of relatedness are used as
proxy for niche or trait differences. Patterns of close-relatedness (‘phylogenetic clustering’) indicate abiotic factors over
time resulting in niche conservatism; whereas the converse pattern of distant-relatedness (‘over-dispersion’ or ‘evenness’)
indicates competitive interactions between species lead to limiting similarity over time (Webb et al. 2002). This ecophylogenetic framework, however, attributes only a single process for
a given pattern; when in actuality multiple processes from past
and present likely interact (and counteract) to assemble present
communities. And each process’ separate and individual effect
on community patterns is indistinguishable under Webb et al.
(2002)’s framework (Graham & Fine 2008; Cavender-Bares
et al. 2009). A phylogenetic signal from the aforementioned
framework therefore neither supports a specific assembly process unambiguously (Mayfield & Levine 2010); nor identifies
patterns that may result from environmental filtering, such as
phylogenetic niche conservation (Losos 2008).
Conversely, PBD can discern between the different processes in communities at various spatial scales and along
environmental gradients; moreover, distinguish the lineages
driving turnover (Graham & Fine 2008). We are able to
detect the evolutionary (temporal) depth and phylogenetic
(cladal) scale at which changes occur across space, because
PBD measures differ in their sensitivities to the depth of
phylogenetic turnover (Fig. 1). While taxonomic measures
are blind to evolutionary depth (Fig. 1a), terminal metrics
(‘t-PBD’) are sensitive to turnover among recently diverged
lineages (Fig. 1b). Conversely, basal metrics (‘b-PBD’) are
able to detect turnover deep within the phylogeny (Fig. 1c)
(Swenson 2011). According to Losos (2008), we can detect
phylogenetic niche conservatism when the distribution of
ecological traits match both species’ distribution and evolutionary relationships. We can thereby capture patterns consistent with phylogenetic niche conservatism by examining
PBD with changes in the environmental conditions where
species occur.
Environmental filtering, dispersal limitation and the degree
of environmental spatial structure (spatial autocorrelation)
are all factors that influence the distribution of species’ traits
within a community. For instance, under a strong regional
environmental filter, selective pressures may favour traits
expressed within certain phylogenetic lineages. For communities situated along environmental gradients, turnover deep
within the phylogeny, for instance among monophyletic
clades, suggests niches (or entire clades) track environmental
conditions (Fig. 2c and 2d). However, greater phylogenetic
turnover at the tips of branches (turnover of species within
clades) than turnover at deeper levels (Fig. 2b; t-PBD > bPBD), suggests selective pressures promote divergence into
habitats, and thus modern species likely occupy different
environmental regimes than their ancestors. Beta-diversity
(a)
(b)
(c)
Fig. 1. Conceptualization of Beta-diversity Sensitivities to Phylogenetic Depth. Red colours depict how the beta-diversities view species’
evolutionary relationships. (a) Taxonomic turnover is blind to phylogenetic depth. Because all species are equal in their phylogenetic histories, the phylogeny can be perceived as a star phylogeny. (b)
Terminal phylobetadiversity is focused at the tips, where it is sensitive to turnover among recently diverged lineages within clades. (c)
Basal phylobetadiversity is sensitive to cladal turnover deep within a
phylogeny, among clades.
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology
Phylogenetic turnover in montane plants 3
associations with environmental change may also reflect limitations in niche evolution that lead to adaptive selection
(Ackerly, Schwilk & Webb 2006; Eiserhardt et al. 2013).
Conversely, associations with spatial distance may reflect
dispersal limitation that results in allopatric speciation (Eiserhardt et al. 2013). Stegen & Hurlbert (2011) also suggested
that dispersal limitation can be the only explanation of species’ trait distribution across a landscape in the absence of
spatial structure in the environment.
Given that rapid changes in environmental conditions occur
over short distances in montane ecosystems, such ecosystems
are ideal systems for testing hypotheses on both species’ evolutionary adaptations and community structure at various spatial scales (K€orner 2000). Here, we investigate PBD patterns
for montane angiosperm communities and ask whether there is
evidence of niche conservatism for our system. Using both
PBD and TBD metrics for our analyses, we also investigate
how much more novel information is actually captured by
PBD over taxonomic beta-diversity and, amongst the different
PBD metrics, how sensitivities to the depth of evolutionary
change affect our analyses. Specifically, we ask (i) which processes, spatial and/or environmental, affect community assembly across our angiosperm communities in the Rocky
Mountain National Park (Colorado, USA), on both sides of
the mountain ranges (i.e. the Continental Divide); and if so,
(ii), when and (iii) where within phylogenetic clades do we
observe its influence. We expect beta-diversity associations
with space to reflect dispersal limitations, while associations
with environment reflect a regional environmental filter. If
environment acts on conserved traits (niche conservatism), we
expect to obtain greater TBD than PBD. Greater t-PBD than
b-PBD may reflect recent evolutionary radiations tracking
environmental changes, while the converse scenario indicates
species possess low niche lability.
(a)
(c)
(b)
(d)
Fig. 2. Phylogenetic Beta-Diversity Scenarios. The phylogenetic
changes from one community (red minuses) to another (blue pluses)
as captured by basal (rows) and terminal (columns) PBD metrics. Red
and blue branches represent the unique branches found in, respectively, the red and blue communities; purple branches represent the
branches shared between communities. Turnover can be (a) low for
both terminal and basal PBD; high only for (b) terminal or (c) basal
PBD; or (d) high for both terminal and basal PBD. When basal turnover is high (c & d), niches likely track environmental conditions.
However, when only terminal PBD is high (b), selective pressures
may promote divergence into habitats, where modern species likely
occupy different environmental regimes than their ancestors.
Materials and methods
STUDY AREA & DATA
We used plant community data collected in summer 2002 under the
Vegetation Characterization Program, a product of the United States
Geological Survey and the National Park Service Inventory & Monitoring Vegetation Mapping Program (Salas, Stevens & Schulz 2005).
This data set consisted of the presence/absence data for 661 angiosperm species structured across 569 plots ranging in elevation from
2195 to 3872 metres in the Rocky Mountain National Park, in Colorado (40°200 00″ N 105°420 3″ W; approximately 670 km2). Plots were
approximately 400 m2 in area and selected through the Stratified Random Gradsect Sampling approach (Austin & Heyligers 1991), which
optimally selects sampling plots while encompassing the full spectrum
of vegetation types. We also included individuals identifiable only to
the genus level.
For our analyses, we excluded rare species from our data set
because they are too stochastic to contribute any meaningful signals
(without rare species: 449 species in 565 plots). Rare species are
those that are not abundant in their distribution and possess constrained geographic ranges – for example species found in ten or less
plots and covering 10% or less of the study area’s elevational
expanse. As the Continental Divide (CD) bisects the region into two
different climatic regimes with influence on species abundance and
distribution, we also separately analysed the community data and corresponding phylogenetic trees for plots East/West of the CD – 394
species in 391 plots East of the CD; and 220 species in 173 plots
West of the CD (See Fig. S1). The West (orographic precipitation)
receives approximately 5 inches more annual precipitation than the
East (precipitation shadow) (Beidleman, Beidleman & Willard 2000).
While a combination of different variables may capture environment, we used elevation as a proxy for environment as it correlated
with key environmental variables such as precipitation and temperature within the study area (Peet 1981). Space was represented by the
location of the sampling plots’ x–y geographic coordinates. We converted both variables into Euclidean distance matrices for statistical
analyses.
PHYLOGENETIC TREE CONSTRUCTION
For sampled species, we collected four sequences commonly used in
published angiosperm phylogenies from the GenBank data base (Benson et al. 2005) – rbcl, matK, 5.8s and ITS1. Our collection also
included sequences for two out-group species, Magnolia officinalis
Rehder & Wilson and Amborella trichopoda Ballion, which represent
two early diverging angiosperm lineages useful for rooting molecular
trees. For species with sequences not found in GenBank (hereon
referred to as ‘missing species’), congeneric sequences formed the
genus-level node at which missing species were later inserted. ClustalX aligned the sequences concatenated into a super matrix of species’ sequences by FASconCAT (Larkin et al. 2007; K€uck &
Meusemann 2010). Of 88 possible models, CAT + GTR was the Akaike information criterion’s best-fit nucleotide substitution model for
both individually aligned sequences and the super matrix of
sequences (Posada 2008).
The Bayesian Monte Carlo Markov Chain (MCMC) sampler, PhyloBayes 3.0, estimated our molecular phylogeny (Lartillot, Lepage &
Blanquart 2009) – we ran two independent MCMC chains (100 000
cycles each) started from a Phylomatic Angiosperm Phylogeny Group
III (APG III) supertree (Webb & Donoghue 2005; Bremer, Bremer &
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology
4 L. S. Jin, M. W. Cadotte & M.-J. Fortin
Chase 2009). Next, we visualized and rooted the consensus tree in
the program Archaeopteryx (Zmasek & Eddy 2001); identified any
problematic sequences by running them against the BLAST data base
and replaced sequences as necessary (Altschul et al. 1990); and reiterated the process for arriving at a Bayesian MCMC phylogeny until
we eliminated all problematic sequences. We inserted missing species
at the genus-level node in Archaeopteryx and removed species not in
the species pool (i.e. missing species’ congenerics and the two outgroup species) using library ape, in R-2.15.0 (Paradis, Claude &
Strimmer 2004; R Development Core Team 2011).
Finally to obtain an ultrametric tree, we estimated divergence times
using Sanderson’s (2002) penalized likelihood method with the R2.15.0 function, chronopl (Paradis, Claude & Strimmer 2004; R
Development Core Team 2011). From a cross-validation of different
lambda values, a zero lambda parameter value corresponded to the
cross-validation criterion minima (Paradis 2011).
PHYLOBETADIVERSITY METRICS
In our analyses, we used the presence/absence metrics for three taxonomical beta-diversity (‘TBD’; Jaccard, Bray–Curtis and Gower) and
six phylogenetic beta-diversity (‘PBD’, PhyloSor, UniFrac, Dnn, Dpw,
Rao’s D and Rao’s H; Fig. S5) indices presented in Swenson (2011).
The three TBD indices are a means of comparison to PBD metrics.
Swenson (2011) categorized these PBD metrics as either terminal (tPBD) or basal (b-PBD), based on the depth of phylogenetic change
detected between communities. For instance, t-PBD (PhyloSor, UniFrac and Dnn) are sensitive to recent evolutionary changes (i.e. turnover among nearest neighbour distances), while b-PBD (Dpw, Rao’s
D and Rao’s H) detect changes that occur deeper within evolutionary
history.
These indices have known sensitivities to differences in species/
phylogenetic richness (Koleff, Gaston & Lennon 2003). While we
found no relationship for elevation with species richness (r = 0.07,
P = 0.0841, d.f. = 563), elevation did have a significant relationship
with phylogenetic diversity (r = 0.0849, P = 0.0437, d.f. = 563),
although the R2 value only captures 0.07% of the variation and the
sample size was relatively large (Type II error).
In R-2.15.0, we calculated TBD metrics with vegan; and PBD metrics with picante (Oksanen et al. 2007; Kembel 2009; R Development
Core Team 2011). Measures of similarity were converted into dissimilarities.
partial PROTEST for beta-diversity and environment, controlling for
space. When there are both significant spatial and environmental associations with beta-diversity, the partial PROTEST can determine
whether environment itself is significantly associated with beta-diversity by controlling for the effects of space. 10 000 permutations of
species composition determined significance for all tests.
For PROTEST, each beta-diversity was ordinated using principal
coordinate analysis (PCoA). PCoA directly uses distance matrices
and does not assume normality, an assumption violated by species
distributed along environmental gradients (Kent 2011). PCoAs on
non-Euclidean distances do however yield negative eigenvalues,
where objects’ relationships are distorted by the existence of imaginary dimensions (Gower & Legendre 1986). The PCoA can still
retain realistic relationships between objects when positive eigenvalues far outweigh negative eigenvalues, and when only PCoA
dimensions with positive eigenvalues are used (Krzanowski & Marriott 1994; however, see McArdle & Anderson 2001). A broken stick
plot and relative eigenvalue contribution plot revealed that negative
eigenvalues were significantly smaller in their variance explained
contribution than positive eigenvalues (Figs S1–S3); also that at least
50% of the variance can be explained by the first five PCoA axes
for over half the distance matrices. Given that PROTEST requires
equal dimensionality, the number of axes used was limited to the
first three. PCoA ordinations were also run on the spatial distance
matrix and elevation distance matrix for later use in the partial PROTEST analysis.
We followed Peres-Neto & Jackson (2001)’s procedure for the partial PROTEST. To control for space, first, (i) the PCoAs of each
beta-diversity indices was regressed against the PCoA of space using
a linear model; likewise, (ii) the PCoAs of elevational distance was
also regressed against the PCoA of space using a linear model.
Finally, a Procrustes superimposition was then run on the residuals
from (i) and (ii). Both PROTEST and partial PROTEST methods
were tested against a null model based on 10 000 permutations using
function ‘protest’ in package vegan in R. All statistical analyses were
run within the R environment.
PROTEST’s value of matrix association, m12, captures the minimized sum-of-squares between objects, such that low values indicate
high association and higher values indicate low association. To facilitate comparisons between the metrics in a meaningful way, we use rp
as the PROTEST associative value, where rp = 1 m12.
Comparing beta-diversities
STATISTICAL METHODS
Space vs. environment in species compositional change
We assessed the relationship between space, environment and changes
in species composition using three TBD (Jaccard, Bray–Curtis and
Gower) and six PBD presence/absence metrics (Phylogenetic Sørensen’s: PhyloSor; unique fraction of shared branches: UniFrac; Nearest
Neighbour Distance: Dnn; Mean Pairwise Distance: Dpw; Rao’s quadratic entropy: Rao’s D; and Rao’s quadratic entropy, standardized
for alpha diversity: Rao’s H) presented in Swenson (2011). For each
community composition subset (CD), each beta-diversity metric was
expressed as pairwise differences between sites; x–y geographic coordinates converted to into spatial distance matrices; and the elevation
differences between sites used as environmental distance between
sites. To assess the matrix association between beta-diversity and (i)
space and (ii) environment, we used the PROTEST method, and
Following Swenson’s (2011) methodology, we used a Pearson’s correlation to capture the beta-diversity metrics’ relationships in univariate space (Table 1). To capture the multivariate relationship between
the metrics, we ran a Procrustes superimposition with an integrated
permutation process for all the PCoA ordinations with function ‘protest’ in package vegan in R. The m12 values indicating the degree of
association between matrices were then combined into a triangular
distance matrix, from which we then used PCoA ordination methods
to obtain a graphical representation of how similar the methods were
to each other (Fig. 3).
We also ran a principal components analysis (PCA) on a matrix
comprised of all the standardized distance matrices of the beta-diversity indices, where the variables of interest were the beta-diversity
metric (Fig. S5). The PCA does, however, transform the metrics’ relationships; and, given that the PCoA illustrates similar relationships as
in the PCA, we only present PCoA.
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology
0.396
0.229
0.241
0.54
0.495
0.888
0.584
0.584
–
0.161
0.118
0.122
0.139
0.132
0.395
1
–
0.58–0.587
Fig. 3. Principal Coordinates Analysis ordination of all possible Procrustes superimpositions. Axis 1 and Axis 2 have, respectively,
61.7% and 16.0% relative eigenvalue contribution. Asterisks indicate
large overlap in two indices: * Dpw and Rao’s D; and, ** Jaccard
and Bray–Curtis.
Results
BETA-DIVERSITIES
Upper triangle is the correlation statistic, while the lower triangle is the 95% confidence interval.
0.161
0.118
0.122
0.139
0.132
0.395
–
1–1
0.58–0.587
0.358
0.404
0.418
0.782
0.742
–
0.391–0.399
0.391–0.399
0.887–0.889
0.138
0.687
0.688
0.993
–
0.74–0.744
0.127–0.137
0.127–0.137
0.491–0.499
0.186
–
0.994–0.995
0.637–0.643
0.684–0.69
0.4–0.408
0.113–0.123
0.113–0.123
0.225–0.234
Gower
Jaccard
Bray–Curtis
PhyloSor
UniFrac
Dnn
Dpw
Rao’s D
Rao’s H
–
0.182–0.191
0.164–0.173
0.0985–0.108
0.133–0.143
0.362 to 0.354
0.165 to 0.156
0.165 to 0.156
0.4 to 0.392
0.168
0.994
–
0.642–0.648
0.685–0.69
0.414–0.422
0.117–0.127
0.117–0.127
0.237–0.246
0.103
0.64
0.645
–
0.993–0.993
0.78–0.784
0.134–0.143
0.134–0.143
0.537–0.544
Dpw
Dnn
Jaccard
Gower
Table 1. Pearson Correlation of beta-diversity measures
Bray–Curtis
PhyloSor
UniFrac
Rao’s D
Rao’s H
Phylogenetic turnover in montane plants 5
Both the results of the PCoA (Fig. 3) and Pearson’s correlation (Table 1) distinguish the beta-diversity metrics based on
their respective temporal sensitivities. There is high overlap in
the PCoA and high R2-values from the Pearson’s correlation,
with some metrics being virtually identical: Rao’s D and Dpw
(R2 = 1); Jaccard and Bray–Curtis (R2 = 0.994); and, UniFrac and PhyloSor (R2 = 0.993). The Pearson correlations
match the metric behaviour on the PCoA’s first axis: where
TBD metrics and t-PBD metrics are most correlated to each
other, but b-PBD metrics more correlated with t-PBD than
TBD metrics. Exceptions to these patterns include Dnn, Rao’s
H and Gower.
Similarly, the PCoA reveals that the three different betadiversity types were closest to their own types, with exception
to Dnn and Gower (Fig. 3). b-PBD and TBD were most dissimilar to each other on Axis 1, but most similar to another
on Axis 2 (Fig. 3). On Axis 1, Dnn loaded closer to the bPBD metrics than the terminal PBD metrics, with the other tPBD closer to the TBD; conversely on Axis 2, Dnn was closest to the other t-PBD metrics.
ASSOCIATIONS
In general, PROTEST found the greatest significant associations for TBD and t-PBD with environment, followed by
associations with environment controlling for space were larger than those with space. Dnn was the only main exception
to these patterns, where space had the greatest significant
associations, followed by environment, then environment
controlling for space (Fig. 4, Table S3). While b-PBD also
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology
6 L. S. Jin, M. W. Cadotte & M.-J. Fortin
(a)
(b)
(c)
Fig. 4. PROTEST
matrix
association
between nine beta-diversity metrics with
space (a) and environment (b); (c) compares
beta-diversity indices to environment with
removed spatial effects from the partial
PROTEST. Colours and shapes correspond to
the continental divide; and fill density,
significance based on 10 000 randomizations.
had the greatest significant associations with environment, it
associated more with space than environment controlling for
space; and in the case of communities to the west of the CD,
only had significant relationships with environment, controlling for space.
For overall associations (e.g. with space, environment, and
environment controlled for by space), TBD consistently had
the highest significant associations, followed by t-PBD, then
b-PBD.
Discussion
As a nascent avenue for examining species assemblages
across space, PBD methods provide novel views of how
diversity is distributed spatially and across environmental
gradients. Using angiosperm communities to the east and
west of the Continental Divide, we asked whether space
and/or environment played a crucial role in species assemblage across environmental gradients, and whether certain
clades were particularly affected by these gradients. Specifically, we evaluated the novel contribution of phylogenetic
over taxonomic measures of beta-diversity; and how the
PBD metrics’ different sensitivities to evolutionary depth
influence our understanding of the processes acting on communities.
COMMUNITY PROCESSES
Abiotic factors clearly impact angiosperm community assembly within the Rocky Mountain National Park. We found patterns to be consistent with expectations under niche
conservatism, since not only was environment similar
between neighbouring sites, environment also associated better with phylogenetic turnover than space. Species within sites
were more closely related to their neighbours than we would
otherwise expect (Appendix S1: MPD vs. Elevation, Fig. S6:
line for observed MPD lower than line for null expectation;
Student’s t-test: MPDobserved < MPDnull model). While this provides evidence of niche conservatism at the regional scale, it
does not tell us at what phylogenetic depth niches are conserved. The methods we used, however, indicate there is
greater turnover within clades (t-PBD) relative to among
clades (b-PBD) even though both are significantly correlated
with environment, which we infer to mean that the environmental requirements are relatively conserved deeper within
the phylogeny. Species taxonomic beta-diversity is devoid of
evolutionary relationships between species and only captures
nominal changes; therefore, lower phylogenetic than taxonomic turnover indicates shifts in species lineages are not
nearly as drastic as nominal changes. Moreover, turnover
occurs more often amongst species within clades rather than
among clades. The impact of environmental changes on community assemblage is also clearly greater in communities east
of the Continental Divide than those on the west (where conditions are uniformly drier), when controlling for spatial
effects on environment highlights the prominence of phylogenetic information on assemblage patterns.
While spatial processes overall affect turnover across communities, its influence is much weaker than changes in the
abiotic environment (Fig. 4a). Spatial processes also fail to
discriminate between taxonomic and phylogenetic turnover to
the same extent as environmental processes. Space therefore
minimally reflects evolutionary relationships, and only to the
same degree as taxonomic relationships.
BETA-DIVERSITIES
In the PCoA of the beta-diversity indices, the first axis perceivably captures a metrics’ sensitivity to phylogenetic
depth and the second axis its ‘tippiness’, or sensitivity to
depth at the tips. TBD metrics are devoid of evolutionary
history; however, t-PBD detects recent/shallow, and b-PBD
deep ancestral, phylogenetic shifts. b-PBD and TBD may
be similarly tippy, as taxonomic species’ relationships can
be represented as a polytomous star-like phylogenetic tree
(Helmus et al. 2007; Tucker & Cadotte 2013). Among the
PBD indices, our results concurred with Swenson’s (2011)
findings that some metrics were redundant, when ignoring
species abundance and when employing an ultrametric tree
for Rao’s D (Rao’s quadratric entropy), Dpw (Mean Pairwise Distance) and Rao’s D are computationally equivalent;
moreover, both PhyloSor (Phylogenetic Sørensen’s) and
UniFrac (Unique fraction of shared branches) account for
branch lengths as a fraction of either shared phylogenetic
branches (PhyloSor) or unique branches (UniFrac) in two
communities. Dnn (Nearest Neighbour Distance) was distinct
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology
Phylogenetic turnover in montane plants 7
from all other metrics, as it measures the mean nearest
(phylogenetic) neighbour distance between two communities
– it does not consider all possible species relationships in
two communities, and consequently lacks information on
the overall phylogenetic relationships between two communities. Other aspects beyond sensitivity to phylogenetic
depth or ‘tippyness’ may additionally affect the metrics’
relationships – Tucker & Cadotte (2013) found phylogenetic diversity sensitive to the balance of information across
clades and time, species pool size and spatial autocorrelation. When information is balanced across clades, basal and
terminal phylogenetic metrics may converge in similarity.
Moreover, other unexplored factors may augment the subtle
differences between ‘redundant’ metrics, for example PhyloSor and UniFrac. A simulation analysing the metrics under
various scenarios sensu Tucker & Cadotte (2013) may
therefore elucidate the metrics’ sensitivities to different factors/scenarios, for example Dnn is foreseeably sensitive to
recent radiations (e.g. imbalanced trees).
IMPLICATIONS & FUTURE DIRECTIONS
Traditional taxonomic beta-diversity metrics indicate that abiotic processes influence species diversity for our study system/region; but phylogenetic information further supplements
the narrative with the evolutionary implications of a strong
regional environmental filter: it provides the case for strong
niche/trait conservatism within certain clades, where turnover
mostly reflects recent speciation events. While environmental
filtering has a clear regional influence on species, its influence
is greatest for communities east of the Continental Divide.
When evaluating phylogenetic metrics of turnover, we found
some metrics highly correlated; however, it is necessary to
understand how and when metrics diverge based on their specific sensitivities to tree topology (e.g. balance of information
across clades and time), species pool size and spatial autocorrelation (Tucker & Cadotte 2013). Identifying how the interplay of different factors affect PBD metrics can reveal when a
given metric is more appropriate than another, and also begin
define a systematic approach to deciphering PBD patterns
from a community assemblage perspective.
Acknowledgements
We thank Donald A. Jackson and Stephen C. Walker for strengthening the methodological aspects of this paper; C.M. Tucker, A.J. Parker, S.W. Livingstone and
G.W. Stegeman for helping to improve our paper; and the United States Geological Service and National Park Service for publicly providing the data used in our
analyses. This work was funded by grants from the Natural Sciences and Engineering Research Council of Canada (#386151) to MWC and (#208300) to MJF.
Further, MWC wishes to acknowledge support from the endowed TD Chair of
Urban Forest Conservation and Biology.
Data accessibility
Sampling Data: U.S. Geological Survey & National Park Service Inventory &
Monitoring Vegetation Characterization Program Data: http://science.nature.
nps.gov/im/inventory/veg/project.cfm?ReferenceCode=1047727.
Phylogenetic Data: TreeBASE Study accession no. S17093.
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Received 18 March 2014; accepted 11 February 2015
Handling Editor: Nathan Swenson
Supporting Information
Additional Supporting Information may be found in the online version of this article:
Appendix S1. Description of Phylogenetic Beta-diversity metrics.
Appendix S2. Mean Pairwise Distance vs. Elevation.
Figure S1. Principal Components Analysis of the community data.
Figure S2. A broken stick plot (red line) and relative eigenvalue contribution (black line) plot for each beta-diversity metric (no CD subsetting).
Figure S3. A broken stick plot (red line) and relative eigenvalue contribution (black line) plot for each beta-diversity metric (East of CD).
Figure S4. A broken stick plot (red line) and relative eigenvalue contribution (black line) plot for each beta-diversity metric (West of CD).
Figure S5. Principal Components Analysis of on a matrix comprised of
all the standardized distance matrices of the beta-diversity indices.
Figure S6. Mean Pairwise Phylogenetic Distance (MPD) vs. Elevation.
Table S1. PROTEST matrix association values for each beta-diversity
metric with space, environment, and environment with space controlled.
© 2015 The Authors. Journal of Ecology © 2015 British Ecological Society, Journal of Ecology