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Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
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Perspectives in Plant Ecology, Evolution and Systematics
journal homepage: www.elsevier.com/locate/ppees
Research article
Conservatism of responses to environmental change is rare under
natural conditions in a native grassland
Jonathan A. Bennett ∗ , James F. Cahill Jr.
Department of Biological Sciences, University of Alberta, Edmonton, AB T6G 2E9, Canada
a r t i c l e
i n f o
Article history:
Received 27 April 2013
Received in revised form
23 September 2013
Accepted 16 October 2013
Available online 24 October 2013
Keywords:
Phylogenetic community ecology
Phylogenetic signal
Phylogenetic niche conservatism
Belowground ecology
Grazing
Mycorrhizae
a b s t r a c t
Whether or not niche conservatism is common is widely debated. Despite this uncertainty, closely related
species are often assumed to be ecologically similar. This principle has led to the proposed use of phylogenetic information in forecasting species responses to environmental change. Tests of niche conservatism
often focus on ‘functional traits’ and environmental tolerances, but there have been limited tests for conservatism in species’ responses to changes in the environment, especially in the field. The prevalence
of functional convergence and the likelihood of functional trade-offs in a heterogeneous environment
suggest that conservatism of the response niche is unlikely to be detectable under natural conditions. To
test the relevance of evolutionary information in predicting ecological responses, we tested for conservatism (measured as phylogenetic signal) of grassland plant population responses to 14 treatments (e.g.
light, nutrients, water, enemies, mutualists), each manipulated for 2–3 years, and 4 treatment categories
(aboveground, belowground, resource, and herbivory) at a single site. Individual treatment responses
showed limited evidence of conservatism, with only weak conservatism in plant responses to mycorrhizae and grazing. Aspects of the response niche were conserved among monocots both aboveground and
belowground, although the pattern varied. Conservatism was limited to grazing aboveground, but belowground responses were conserved as a group, suggesting fundamental differences in how selection has
led to niche conservatism in aboveground and belowground environments. Overall, our results suggest
that conservatism of the response niche is not common, but is actually rare. As such, evolutionary relationships are likely to be of limited relevance for predicting species responses under field conditions, at
least over the short time scales used in this study.
© 2013 Elsevier GmbH. All rights reserved.
Introduction
Plant populations often respond idiosyncratically to changes in
their environment (Tilman, 1987; Turkington et al., 2002). Efforts
have been made to identify species characteristics that can be
used to develop a predictive framework for changes in the relative
abundance of plant populations (e.g. Grime, 1977; Westoby, 1998).
Based upon the idea that related species are more ecologically
similar (Darwin, 1859), hypothesized patterns of descent (e.g. a
phylogeny) have been used with some success in determining how
species respond to both biotic (Burns and Strauss, 2011; Reinhart
et al., 2012) and abiotic (Niinemets and Valladares, 2006; Prinzing,
2001; Willis et al., 2008) elements of their environments. Further,
∗ Corresponding author at: B715 Biological Sciences Building, University of
Alberta, Edmonton, AB T6G 2E9, Canada. Tel.: +1 780 492 1577;
fax: +1 780 492 9234.
E-mail address: [email protected] (J.A. Bennett).
1433-8319/$ – see front matter © 2013 Elsevier GmbH. All rights reserved.
http://dx.doi.org/10.1016/j.ppees.2013.10.001
many ecological factors differentially affect certain lineages within
the community, causing phylogenetic clustering (Helmus et al.,
2010; Verdú and Pausas, 2007). This suggests that phylogeny can be
used as a tool to predict species responses to changes in their environment, but for phylogeny to be a useful predictor of ecological
responses, the niche must be conserved. However, the prevalence
of niche conservatism has been questioned (Knouft et al., 2006;
Lavergne et al., 2010; Losos, 2008; Silvertown et al., 2006b).
Niche conservatism can have multiple definitions. Here, we
define niche conservatism broadly as the tendency of related
species to respond similarly to abiotic or biotic environmental
conditions (Wiens et al., 2010; Wiens and Graham, 2005). This definition is more liberal than other definitions that consider niche
conservatism to require species being more similar than expected
under a model of Brownian evolution (Losos, 2008). While phylogenetic relatedness is often considered an integrative measure
of functional similarity (Mouquet et al., 2012; Webb et al., 2002),
for plants, ecologically relevant traits are often labile (CavenderBares et al., 2006; Grime, 2006) or environmentally plastic (Berg
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
and Ellers, 2010; Burns and Strauss, 2012). Further, there are many
ways to respond to different aspects of the environment. For example, defensive compounds are produced using different pathways,
but all reduce herbivory (Howe and Jander, 2008) and competitive
response is associated with many traits representing different ways
of coping with reduced resource availability (Wang et al., 2010).
Additionally, traits may be associated with multiple functions, yet
multiple traits may determine a species’ functional response to a
given factor. High volumes of fine roots can increase both nitrogen
and water uptake (Craine et al., 2003), but periodic drought tolerance also requires that the plant be able to store water for later
use, which is not an adaptation related to nitrogen uptake (Craine,
2009). This suggests that conservatism of a trait does not mean
that a plant’s response to one factor related to that trait can predict
its response to other related factors. Many of the traits necessary
to respond to environmental conditions also involve functional
trade-offs, such as those between shade and drought tolerance
(Niinemets and Valladares, 2006). As a consequence, plant species
may be suited to cope with certain environmental conditions, but
not others. Thus, for many reasons, ecological responses are often
less conserved than morphological or physiological traits (Losos,
2008; Prinzing, 2001). This suggests that evolutionary information may be of limited use for predicting how species respond to
environmental conditions in nature.
When suites of traits appear to confer specific functioning, they
have often been grouped into plant functional strategies (Reich
et al., 2003; Westoby, 1998). Most commonly, plant strategies are
associated with responses to resource availability and disturbance,
where some species are adapted to quick growth and rapid resource
acquisition, while others are adapted to disturbances such as herbivory (Craine, 2009; Grime, 1977; Reich et al., 2003). Responses to
both resources and herbivory are often consistent within broad,
phylogenetically distinct functional groups (Coughenour, 1985;
Lavorel et al., 1997; Niinemets and Valladares, 2006; Turkington
et al., 2002), yet the evidence for conservatism of traits representing these plant strategies is mixed (Brunbjerg et al., 2012; Diaz
et al., 2004). While there are a few experimental tests for conservatism of plant strategies, to our knowledge, no studies have tested
whether population responses to multiple treatments related to
these strategies are conserved.
Plant strategies require coordinated responses to multiple environmental factors, both above- and belowground. This requires
that root and shoot traits co-vary. There is evidence for such
covariance (Craine et al., 2001, 2002), although root and shoot
traits may have evolved independently (Kembel and Cahill, 2011).
Individual root and shoot traits show varying degrees of conservatism (Anderson et al., 2011; Comas et al., 2012; Diaz et al.,
2004; Grime and Mackey, 2002; Kembel and Cahill, 2005, 2011),
as do plant responses to various above- and belowground factors
(Niinemets and Valladares, 2006; Prinzing, 2001; Silvertown et al.,
2006b). However, it is unclear whether plant responses to either
aboveground or belowground factors as groups would be phylogenetically conserved and there are no experimental tests of this
concept.
To test whether related species responded similarly to changes
in their environment, and thus if response niches were conserved,
we synthesized the results of six short-term (2–3 years) experiments conducted in a single grassland system within the Aspen
Parkland eco-region of Canada. In total, 14 abiotic and biotic treatments were manipulated: aboveground insecticide; belowground
insecticide; contact fungicide; drought; fixed interval watering;
high intensity clipping; litter removal; low intensity clipping;
nitrogen addition; nitrogen, phosphorus and potassium (NPK)
addition; shading; systemic fungicide; variable interval watering;
and warming. From population responses to these treatments, we
329
tested for niche conservatism (as measured by phylogenetic signal) in responses to each individual treatment and in responses
to four categories of ecological treatments representing resource,
herbivory, aboveground, and belowground treatment groupings.
Materials and methods
Site description
All experiments occurred at the approximately 5000 ha University of Alberta research ranch at Kinsella, Alberta, Canada (53◦ 05 N,
111◦ 33 W). Research occurred in three fields located in two separate sections of the ranch totalling 100 ha. Field 1 was located
in the northern part of the ranch, whereas fields 2 and 3 are in
the southern part of the ranch, with the two sites separated by
approximately 6 km. The fields used are unseeded and unbroken
and represent a savannah habitat with mixed grass prairie (primarily Hesperostipa curtiseta (Hitchc.) Barkworth, Poa pratensis L.
and Festuca hallii (Vasey) Piper) interspersed with stands of aspen
(Populus tremuloides Michx.). Though historically lightly grazed by
cattle, grazing was halted for the duration of each experiment.
As is true for many grasslands (Foster et al., 2004; Silvertown
et al., 2006c; Tilman, 1996), plant community structure and function varies spatially and temporally. Soils at the site have a thin
topsoil layer over glacial till (Lamb, 2008), but are spatially variable in texture, chemistry, and topography (Bennett et al., 2013).
The site has an average annual temperature of 2.8 ◦ C and receives
approximately 430 mm of precipitation in an average year, but is
subject to periodic drought (Cahill, 2003). Fig. 1 shows the variability in species richness, productivity, and phylogenetic diversity
over the duration of the experiments. These data were taken from
un-manipulated plots at the field site, with species richness and
phylogenetic diversity data derived from cover estimates (0.25 m2 )
and productivity estimates from live biomass clipped in small plots
(0.10 m2 ), dried, and weighed. Phylogenetic diversity was calculated using the constructed phylogeny (see below) as abundance
weighted mean phylogenetic distance (Webb et al., 2002) using the
independent swap null model (Gotelli, 2000) in the picante package
in R (Kembel et al., 2010). Species richness and productivity were
variable among years and across fields, with field 1 having higher
species richness and productivity than fields 2 and 3. Phylogenetic diversity was much more consistent across fields, with limited
interannual variation (Fig. 1), suggesting greater consistency in the
phylogenetic structure of the community.
Data selection
Data were taken from six separate multi-year multi-factorial
experiments, containing a total of 14 treatments (Table 1). Within
each independent experiment, interactions among the treatments
were included in the original study. However, we do not have data
testing the interactive effects of all treatments, so we limit our analyses to main effects, though we recognize complex interactions
among this number of treatments can occur. For each treatment,
we only used plots where a single treatment was applied and
compared those treatment plots to a control plot with no treatments applied within the same block. Grazing was simulated by
clipping plants at either low intensity (7 cm stubble height) or
high intensity (3 cm stubble height; White et al., 2012). Fertilizers
were applied either as ammonium nitrate (5.4 g N/m2 ) for nitrogen only (Lamb, 2008) or as a slow-release fertilizer for NPK at
5.2 g NPK/m2 (applied as 14:14:14 Osmocote® Classic, Scotts, Bennett et al., in preparation). Fixed interval watering increased total
precipitation by 50% through weekly water addition (Lamb, 2008).
Drought treatments decreased precipitation by 60% using rainout
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J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
Fig. 1. Inter-annual variability in (B) species richness, (C) phylogenetic diversity,
calculated as abundance weighted mean phylogenetic distance, and (D) standing
biomass over the course of the 14 experimental manipulations. Panel A shows the
time frame over which each of the manipulations was conducted. In panels B–D,
empty circles show conditions in field 1, grey circles in field 2, and black circles
in field 3. Experimental manipulations abbreviated as follows: AI – aboveground
insecticide, BI – belowground insecticide, CF – contact fungicide, D – drought, FW –
fixed interval watering, HC – high intensity clipping, LC – low intensity clipping, LR
– litter removal, N – nitrogen addition, NPK – NPK addition, S – shade, SF – systemic
fungicide, VW – variable interval watering, and W – warming. Error bars in panels
B–D represent standard error.
shelters (White et al., 2012). This water was collected and added to
plots within 24 h following rainfall for the variable interval watering treatment (White et al., 2012). Shade cloth was used to reduce
light by 73% (Lamb, 2008), open-top chambers were used to warm
plots by approximately 3 ◦ C (White et al., 2012), and litter was
removed by raking (Bennett et al., in preparation). Insects were
suppressed using chlorpyrifos with LorsbanTM 4E (Dow) used for
aboveground insects and LorsbanTM 5G (Dow) for belowground
insects (Clark et al., 2012; Coupe et al., 2009). Fungi were suppressed using both a systemic fungicide (Benomyl, Dupont Inc.;
Cahill et al., 2008a) and a contact fungicide (Rovral® , Bayer; Bennett et al., in preparation). As with all pesticides, each of the
pesticides used has non-target effects. Chlorpyrifos is known to
decrease nutrient availability (Sardar and Kole, 2005) and can
be harmful to other organisms (vandenBrink et al., 1996). Benomyl is commonly used to suppress arbuscular mycorrhizal fungi
(e.g. Hartnett and Wilson, 1999), but it also has effects on nontarget organisms and can increase available nitrogen (Allison et al.,
2007). Rovral® has also been used to suppress mycorrhizal fungi
(Gange et al., 1990), but has fewer documented effects on nontarget organisms (Ganade and Brown, 1997) and no detectable
effects on soil nutrient availability (J.A. Bennett, unpublished data).
Detailed methods for each treatment can be found in the original manuscripts. Additional methods details for the unpublished
experiment are found in Table 1.
Relative abundance was estimated as percent vegetative cover,
a commonly used method to assess relative change within herbaceous plant communities (Lamb and Cahill, 2008; Tilman, 1987).
Most experiments were 2–3 years long, but some experiments ran
for longer than 3 years and only percent cover estimates were collected in the interim as destructive harvesting was unfeasible. To
minimize the variation in experimental duration, we chose to limit
experimental duration to 3 years. Across all experiments, we calculated the responses of 54 different species to at least one treatment,
with an additional six species included when calculating aggregate
responses to treatment categories (see below). For most species,
we were able to calculate responses to approximately half of the 14
treatments (mean 7.1, standard deviation 4.19), although species
did vary in how often we were able to calculate responses (see
Figure A1). Our abundance estimates were the mean of three cover
estimates taken over the growing season (late spring, mid-summer,
and late summer) from 0.25 m2 sub-plots within each larger control or treatment plot. Changes in relative abundance for each
species were calculated as the log response ratio of abundances
(ln(treatment/control)) for each pair of treatment and control plots.
The log response ratio was used instead of percent change to normalize responses (Hedges et al., 1999). As many experiments were
multi-factorial, control plots within a given block were used in
the calculation of responses to multiple treatments. For example, when calculating responses to aboveground and belowground
insect suppression, the control plot where no treatments were
applied was used to calculate responses to both aboveground insect
suppression and belowground insect suppression. However, plots
where insects were suppressed above- and belowground were not
included in any calculations. From these measurements, we calculated the average response of a species to each treatment and the
standard error of that estimate. By using the average response of
a species, we ignore the potential variation in how individuals of
a given species respond to a treatment due to neighbour composition or local environmental conditions. Given that we are testing
the generality of niche conservatism and the utility of evolutionary
information for informing ecology under natural conditions, the
particular set of conditions under which related species respond
similarly is not of interest in the current study.
For each treatment, the mean change in abundance across
populations and its 95% confidence intervals were estimated
using the average response of each species to each treatment in a
mixed model in SPSS (v. 19.0). We only included species for which
we could calculate the standard error for a given treatment and
weighted species responses by the inverse of that standard error.
We also attempted to account for additional sources of variation by
including a number of random factors, including year of data collection and experimental duration. As experiments at the site were
spatially distinct, we included experimental identity to account for
spatial variability among and within fields, but nested it within year
as data from multiple experiments was collected in most years.
Species identity was also included as a random factor to account
for differences in species pool across factors. Thus, we included
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
331
Table 1
Meta data for each treatment included in the analysis.
Treatmenta
Categoryb
Harvested
Length (years)
Field
Speciesc
Nd
Dir.e
Methods
Aboveground insecticide
Belowground insecticide
Contact fungicide
Drought
Fixed watering
High clipping
Litter
Low clipping
Nitrogen
NPK
Shading
Systemic fungicide
Variable watering
Warming
A,H
B,H
U,U
B,R
B,R
A,H
A,U
A,H
B,R
B,R
U,U
U,U
B,R
U,U
2003, 2005
2005
2010
2010
2005
2010
2010
2010
2005
2010
2005
2005
2010
2010
2, 3
3
3
3
3
3
2
3
3
2
3
3
3
3
1, 2
1
1
3
1
3
1
3
1
1
1
1
3
3
48
41
41
10
46
15
41
15
45
41
45
38
12
16
22
10
20
5
22
5
20
5
22
20
22
20
5
5
+
+
?
−
+
−
?
−
+
+
−
?
+
?
Clark et al. (2012) and Coupe et al. (2009)
Coupe et al. (2009)
Bennett et al. (in preparation)f
White et al. (2012)
Lamb (2008)
White et al. (2012)
Bennett et al. (in preparation)f
White et al. (2012)
Lamb (2008)
Bennett et al. (in preparation)f
Lamb (2008)
Cahill et al. (2008a)
White et al. (2012)
White et al. (2012)
a
b
High and low refer to the intensity of clipping; above and below refer to aboveground and belowground; fixed and variable refer to the interval of watering.
Treatments are classified as aboveground (A) or belowground (B) and herbivory (H) or resource-based (R). Treatments we could not classify are categorized as unknown
(U).
c
Species refers to the number of species for which we could calculate the standard error of their response to that treatment, allowing us to estimate their response to that
treatment.
d
N refers to the number of paired treatment and control plots in the experiment where the treatment was applied.
e
Treatments were classified as having a positive (+), negative (−) or unknown (?) hypothesized direction of effect.
f
Rovral® (Bayer) was applied to half the plots at a rate of 0.36 g/m2 active ingredient (iprodione) every two weeks. Litter was raked each spring in all plots, replaced in
control plots and disposed of in litter removal plots. Fertilizer was added as 3- to 4-month slow release 14:14:14 nutrient pellets (Osmocote® , Scotts) each spring at a rate
of 5.22 g NPK/m2 .
treatment as a fixed effect and the calendar year the data was
collected, the duration of the experiment, experiment identity
nested within year and species identity as random effects in the
model. In the final model, we retained only species identity among
the random effects as the other random effects explained no
additional variation, resulting in a Hessian matrix that was not
positive definite.
Given that there is spatial and temporal heterogeneity in local
community processes (Fig. 1), we explored the amount of variation
explained by year and experimental identity relative to the treatments to evaluate our decision to exclude them from the model. We
ran a mixed model with year, experimental identity nested within
year, and treatment identity nested within experimental identity
within year as fixed factors. As in the previous model, species
identity was included as a random effect and species responses
were weighted by the inverse of the standard error. Only treatment identity (F9,421 = 2.73, P = 0.004) and not experiment identity
(F3,450 = 1.34, P = 0.261) or year (F2,456 = 1.45, P = 0.236) explained
significant variation in species responses, supporting our decision
to remove these random factors. We recognize that this does not
account for potential differences in how species may respond to
treatments in different years, but given the nature of the data such
a test is not feasible.
Phylogenetic information
Phylogenetic information was extracted from the molecular phylogeny outlined in Bennett et al. (2013) that sampled
146 species across 35 families found at the study site (see
Fig. A2). The phylogeny was based on a 1400 bp section of the
ribulose-biphosphate carboxylase gene (rbcL) and constructed
using standard techniques. Although the phylogeny only sampled
one gene, sequence variation in rbcL was sufficient to resolve relationships with strong support. Deeper branching patterns were
consistent with published angiosperm phylogenies based on multiple genes (Bremer et al., 2009; Soltis et al., 2011) and topology
within families were largely consistent with published phylogenies for the Poaceae (Döring et al., 2007), Asteraceae (Selliah and
Brouillet, 2008), Rosaceae (Dobeš and Paule, 2010), and Brassicaceae (Beilstein et al., 2008). In addition, few polytomies are
present except amongst close relatives within Poaceae and Asteraceae (Fig. A1). Polytomies at the tips of a phylogenetic tree are
unlikely to influence analyses of phylogenetic signal (Münkemüller
et al., 2012; Swenson, 2009).
Niche conservatism
Our definition of niche conservatism – related species respond
similarly to ecological factors – is broad and our approach is holistic in its focus on population outcomes, rather than trait-focused
measures of plant morphology or physiology. We used three separate methods to test for phylogenetic signal as a proxy for niche
conservatism: Blomberg’s K (Blomberg et al., 2003), Pagel’s (Pagel,
1999), and the decomposition of trait variation (Pavoine et al.,
2010). The first two methods assess whether the distribution of
traits (or in this case population responses) among species follows a Brownian motion model of evolution. The third method
assesses response diversity among all the species descending from
each branch of each node of the phylogenetic tree, measured as
quadratic entropy (Rao, 1982). This information is used to generate both a visual display of where divergence occurred along
the tree and uses randomization procedures to determine if there
is significant phylogenetic signal. The randomization tests for the
response decomposition analyses indicate whether response variation is skewed towards a single node, a few nodes, the root, or the
tips (Pavoine et al., 2010). Variation skewed towards the root or
towards one or few nodes can be used to infer niche conservatism or
at least differentiation, whereas variation skewed towards the tips
suggests convergence. However, careful examination of how variation in responses is distributed across the nodes of the phylogeny
is required to infer patterns of niche conservatism.
Before quantifying phylogenetic signal, we created separate
phylogenetic trees for each experimental treatment, for a total of
14 trees. Each tree was created by pruning the full phylogenetic
tree to include only species for which we had a response value
with an associated error measurement in that treatment. We calculated both K and and tested their significance using the phylosig
function in the GEIGER package in R (Harmon et al., 2008). To
decompose trait variation, we used an updated version of the R
scripts from Pavoine et al. (2010) provided by the author in the
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J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
Fig. 2. Average change in relative abundance following manipulation of various individual treatments (above heavy solid line) and treatment categories (below solid line)
applied to a native grassland. Treatment and treatment category effects are arranged in descending order of the absolute value of the average response. Dots represent the
estimated marginal mean of the log response ratio with error bars showing the 95% confidence intervals of that estimate. Numbers following treatment names represent
the number of species measured followed by the number of replicates for individual treatments and the number of species measured for treatment categories.
ade4 package in R (Chessel et al., 2004). Responses were considered
to be conserved if the tests for phylogenetic signal indicated that
there was significant variation at one or a few nodes that represent
deep branches within the phylogeny. A more thorough explanation
of these methods can be found in the online Appendix. Each test for
phylogenetic signal was conducted for each individual factor with
both ultrametric and non-ultrametric trees. The results were similar, and thus we only present those using the non-ultrametric tree.
In addition to assessing niche conservatism in response to each
individual treatment, we also assessed conservatism of responses
to broad categories of treatments (Table 1). The first set of categories represent plant strategies for responding to resource
availability and herbivory responses (Grime, 1977; Reich et al.,
2003), while the second set of categories test whether the phylogenetic conservatism seen for many root and shoot traits (Anderson
et al., 2011; Cahill et al., 2008b; Comas et al., 2012; Kembel and
Cahill, 2005, 2011) resulted in conservatism in species responses
to aboveground and belowground treatments. Before estimating
responses to treatment categories, we standardized the direction
of effect such that each treatment was expected to negatively affect
population growth (Table 1). For example, the effects of water addition were made negative, whereas drought was left as is. We used
these adjusted species responses to the individual treatments to
estimate species responses to each of the treatment categories. For
Table 2
Phylogenetic signal in individual treatments and treatment categories.
Treatment typed
# Speciese
Significance of skewness (P)*
Aboveground insecticide
Belowground insecticide
Contact fungicide
Drought
Fixed interval watering
High intensity clipping
Litter removal
Low intensity clipping
Nitrogen addition
NPK addition
Shading
Systemic fungicide
Variable interval watering
Warming
Aboveground (agg)
Belowground (agg)
Herbivory (agg)
Resource (agg)
40
35
33
9
41
12
34
13
42
33
39
34
10
10
54
53
49
50
Pagel’s Blomberg’s K
Single node
Few nodes
Root/tip
K
P
P
0.53
0.506
0.788
0.056
0.918
0.913
0.952
0.635
0.679
0.521
0.650
0.033
0.968
0.884
0.149
0.029
0.099
0.188
0.397
0.934
0.621
0.14
0.987
0.894
0.445
0.042
0.112
0.737
0.882
0.668
0.906
0.989
0.592
0.628
0.456
0.244
0.278
0.229
0.469
0.248
0.412
0.847
0.553
0.278
0.566
0.508
0.679
0.591
0.309
0.254
0.435
0.292
0.359
0.590
0.109
0.024
0.132
0.443
0.137
0.349
0.160
0.366
0.058
0.136
0.158
0.146
0.433
0.253
0.107
0.110
0.061
0.091
0.597
0.985
0.651
0.407
0.301
0.169
0.170
0.181
0.801
0.649
0.114
0.355
0.168
0.771
0.379
0.415
0.801
0.567
6.61E−05
6.61E−05
6.61E−05
6.61E−05
6.61E−05
0.010
6.61E−05
0.093
6.61E−05
6.61E−05
6.61E−05
6.61E−05
0.407
6.61E−05
6.61E−05
0.214
6.61E−05
0.100
1.000
1.000
1.000
1.000
1.000
0.976
1.000
0.723
1.000
1.000
1.000
1.000
0.373
1.000
1.000
0.055
1.000
0.319
a
b
c
Values significant at ˛ = 0.05 are bolded.
Single node skewness refers to situations where a single node (branching point) on the phylogenetic tree accounts for most of the variation in plant responses.
Similarly, few nodes skewness refers to situations where a small number of nodes can explain variation in plant responses.
c
Root/tip skewness occurs when most of the variation in plant responses can be explained by either deep branches in the tree or by variation among the tips of the tree.
d
Responses to aggregated categories of treatments are denoted by (agg) and represent model estimated mean responses by individual species to all treatments that fit in
that category (Table 1).
e
The number of species represents the number of species included in that analysis of phylogenetic signal and is limited to the species for which we could calculate a mean
response to that treatment or treatment category.
*
a
b
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333
this estimation, we used mixed models, one for each set of treatment categories, with only species with at least three response
values in a category included in the models. Within these models,
we also included a number of random effects to account for other
potential sources of variation. We initially included treatment category and species identity as fixed effects with treatment identity
nested within treatment category, experimental duration, calendar year of harvest, and experiment identity included as random
effects. However, we only retained one random effect in both final
models, treatment identity nested within treatment category, as it
was the only random effect that explained any variation. From the
models, we estimated (as marginal means) both the mean response
to the treatment categories across species and the response of
the individual species to the same treatment categories. These
species-specific category means were then used in our phylogenetic analyses, following the same methods as described for the
individual treatments.
Results
As expected, species varied in their responses to the individual treatments, with only high intensity clipping and shading
causing significant net change across populations (Fig. 2). Population responses to individual treatments were generally not
conserved (Table 2). We found no evidence of conservatism for
individual treatments as measured using Blomberg’s K or Pagel’s
, but population responses to 2 of 14 treatments (systemic fungicide application and low intensity clipping (Fig. 3 and Table 2))
were similar among related species according to the skewness
tests. Variation in plant responses to systemic fungicide application was skewed towards a single node differentiating Asterids,
which mostly responded negatively, from the other core eudicots,
which generally showed positive responses (Fig. 3A). Conversely,
variation in responses to low intensity clipping was skewed
towards multiple nodes representing variation within the Asteraceae, within the Poaceae, and between monocots and eudicots,
where monocots increased following clipping and eudicots were on
average neutral (Fig. 3B). This weak evidence of niche conservatism
suggests that evolutionary history does little to predict how species
respond to environmental conditions under natural conditions.
Similar to the individual treatments, there was no evidence of
conservatism in species’ responses to the factor groupings when
measuring Blomberg’s K, but there was some evidence of conservatism using Pagel’s and the skewness tests. Specifically, we
found evidence for niche conservatism in population responses
to the group of belowground treatments, but not to groups of
aboveground, top-down, or bottom-up treatments (Table 2 and
Fig. 4A). Variation in species responses to belowground treatments
was significantly skewed towards a single node corresponding to
a split between monocots and eudicots (Fig. 4B), where monocots
declined strongly in response to belowground stresses and eudicot
responses were variable, but on average positive.
Discussion
Plant species varied in their population responses to the different individual treatments, but these responses showed only
occasional and weak evidence of niche conservatism. The results
of previous studies on ecological responses and environmental
niches have been inconsistent as well, with some studies showing strong conservatism (Burns and Strauss, 2011; Prinzing, 2001;
Reinhart et al., 2012; Willis et al., 2008), others weak conservatism
(Niinemets and Valladares, 2006; Thuiller et al., 2011), mixed conservatism (Cahill et al., 2008b), or no conservatism (Cavender-Bares
Fig. 3. Phylogenetic signal in plant species’ responses to (A) contact fungicide application and (B) low intensity clipping depicted graphically as response diversity
decomposed across a community phylogeny. TQE is the total quadratic entropy
(response diversity) and the size of the circle at a given node represents the proportion of entropy concentrated at that node, which corresponds to the amount
of divergence at that node. The bar graphs on the right of each panel show the
response of species at that tip location to that treatment, with monocots and eudicots separated by the bar on the left and the major plant families in boxes of each
panel.
et al., 2004; Silvertown et al., 2006b). Some of this variability in
niche conservatism may be due to the spatial scale at which niche
conservatism is measured. Local scale niches (˛ niches) are thought
to be more labile than habitat niches (ˇ niches) (Silvertown et al.,
2006a), and empirical findings suggest that ˛ niches are often
poorly conserved (Prinzing et al., 2008; Silvertown et al., 2006a,b).
However, for our study region, trait conservatism is stronger within
sites (˛ traits) than among sites (ˇ traits) (Kembel and Cahill,
2011). This suggests that other factors, besides scale, have led to
a lack of response niche conservatism at the site. Further, for sites
where niches are not conserved at local scales (Prinzing et al., 2008;
Silvertown et al., 2006a), responses to environmental change are
even less likely to be conserved. There are many reasons for niche
334
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
Fig. 4. Phylogenetic signal in plant species’ responses to (A) aboveground and (B) belowground treatments. The size of the circle at a given node represents the contribution
of that node to total diversity in responses. The bar graphs show the average response of the species at that tip location on the tree to either aboveground or belowground
stresses and disturbances. Monocots and eudicots are shown along the left hand side of panel A and the major grassland plant families are enclosed within boxes.
conservatism to be variable, including the niche axis considered,
its relationship to local environmental conditions, the nature of
the species pool, and the need to adapt to a diverse set of selective
forces (Grime, 2006; Losos, 2008; Prinzing et al., 2008). We suggest
that functional convergence needs to also be considered. There are
many ways to accomplish different ecological tasks (e.g. mycorrhizae or root traits for nutrient acquisition (Lambers et al., 2008)),
and thus there is a high likelihood of functional convergence even
if different sets of traits are conserved among lineages. Our finding
of limited conservatism of responses, despite morphological trait
conservatism at the site (Kembel and Cahill, 2011) supports this
concept.
In the current study, when evolutionary history explained any
of the variation in species responses, it was primarily related
to differences between monocots and eudicots. This result is
consistent with the large differences between monocots and
eudicots in belowground traits and root foraging (Grime and
Mackey, 2002; Kembel and Cahill, 2005) and responses to herbivory (Coughenour, 1985). Further, it is consistent with broad
differences between monocot and eudicot crop species in how
they respond to belowground resources and stresses (Richmond
and Sussman, 2003; Sadras and Milroy, 1996). However, monocot, but not eudicot, responses to the treatments were conserved;
monocots decreased in abundance when experiencing belowground stresses, but increased following simulated herbivory. This
response conservatism fits with the general conservatism of traits
related to gathering soil resources (e.g. adventitious root growth
and high root allocation) and regrowth following grazing (e.g. basal
meristem and high root allocation) across graminoids and many
monocots (Chase, 2004; Coughenour, 1985). However, it is interesting that belowground responses were conserved as a group,
but only grazing responses were conserved aboveground. In this
system, belowground insect suppression had minimal effect, causing belowground responses to be driven by belowground resource
responses. Having a large root system already in place is going to be
advantageous following resource pulses, regardless of the nature of
the resource. Given that we saw no evidence for conservatism in
species responses to individual belowground treatments, it suggests that niche differentiation among monocots may come from
species abilities to take up different resources. Conversely, both
shading and clipping had large effects on population abundances
and there are known trade-offs between shade and herbivory tolerance (McGuire and Agrawal, 2005), which could limit a species
ability to be respond to multiple aboveground treatments. This suggests that there may be different modes of selection influencing
how species are able to respond to aboveground and belowground
treatments.
Despite differences in conservatism of responses among monocots in how they responded to belowground treatments and
grazing, we did not find a similar pattern for resource and herbivory
responses. Selective forces related to resource capture are expected
to cause convergent evolution (Grime, 2006) and there are known
trade-offs between belowground resource capture (high root allocation) and shade tolerance (high shoot allocation) (Valladares
and Niinemets, 2008). Both mechanisms could limit the conservatism of resource responses. However, trade-offs alone could
have limited conservatism of herbivory responses. There are also
resource allocation trade-offs between herbivory tolerance and
resistance (Agrawal and Fishbein, 2006) which could limit conservatism of responses to herbivory in general. Further, insect
herbivory is variable in its form (Crawley, 1989) and although
grasses may be adapted to grazing (Coughenour, 1985), it seems
unlikely that any species would be well adapted to all forms of herbivory. However, more evidence is necessary before we can draw
any firm conclusions.
Of the treatment responses which showed evidence of conservatism, only systemic fungicide, which suppressed mycorrhizae
(Cahill et al., 2008a), was conserved among groups other than
the monocots. Here, we found that Asterids generally decreased
following mycorrhizal suppression, whereas other core eudicots
mostly increased. Other recent studies found variation among grass
tribes in how they responded to mycorrhizae (Reinhart et al., 2012),
but there were differences in both methodology (e.g. inoculation
vs. suppression, greenhouse vs. field) and species pool between
the two studies that make comparison difficult without further
work. However, it does suggest that there are phylogenetic functional groups in mycorrhizal response, but that these groups vary
contextually.
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
If niche conservatism is truly common (Wiens et al., 2010),
then there should be an emergent pattern in how related species
respond to certain conditions. Our results suggest that conservatism of plant responses to environmental change, under natural
conditions, is in fact rare. However, these results are limited to
short-term responses to each of the treatments and do not necessarily reflect how species respond to long-term environmental
changes. Although most experiments are of similar length to those
used in this study, plant community responses to long-term manipulations are often different than those witnessed over shorter
intervals (e.g. Silvertown, 1980). Therefore, responses to longterm changes may be conserved, resulting in the loss of some
lineages and the addition of others; however, we are unable to
address this issue with the current data. Plant responses to individual factors can also vary spatially and temporally depending
on soil conditions, neighbour identity, and climate (Bertness and
Callaway, 1994; Knapp et al., 2002; Pennings et al., 2005; Pulliam,
2000; Reader et al., 1994), but they can also be remarkably consistent across sites with highly diverse conditions (Pennings et al.,
2005). Although, site conditions and community properties varied among the years over which the different experiments were
conducted, phylogenetic diversity, with few exceptions, remained
relatively consistent among years and locations. Thus, we see no
reason we should expect a bias in how different lineages would
respond to certain treatments or treatment categories depending
on current conditions. It is possible that under more controlled conditions we would have found greater evidence of conservatism,
but such a requirement would limit its applicability to natural
systems. Additionally, we may have found evidence for phylogenetic conservatism in species’ responses to some treatments
if we were able to include more species (e.g. drought or warming). Each of the tests for phylogenetic signal used are sensitive to
low sample sizes (Münkemüller et al., 2012; Pavoine et al., 2010).
However, in cases where phylogenetic signal is strong (e.g. low
intensity clipping), we detected significant conservatism using the
trait decomposition method. Thus, any evidence for conservatism
in other treatment responses is likely weak if it escaped detection, although we cannot eliminate potential conservatism in the
broader species pool.
Synthesis
Niche conservatism in response to individual treatments
appears to be rare within this grassland community, despite
morphological similarities among related species (Kembel and
Cahill, 2011). Functional convergence and functional trade-offs
likely preclude general conservatism of the ‘response niche’. This
suggests that the ecological relevance of evolutionary history is
limited, at least in a practical sense. Evolutionary relationships
are unlikely to aid in forecasting how species will respond to
global change and other current environmental problems, at least
over terms similar to those used in the study (2–3 years). However, we did find some evidence that responses to grazing and
belowground treatments were conserved among monocots. Conservatism of grazing responses among monocots is consistent with
current understanding (Coughenour, 1985) and conservatism of
responses to belowground treatments is consistent with findings
among agronomic species (Richmond and Sussman, 2003; Sadras
and Milroy, 1996) and with conservatism of traits (e.g. specific
root length) important in multiple belowground functions (e.g.
resource uptake) (Grime and Mackey, 2002; Kembel and Cahill,
2005). However, the lack of conservatism in response to individual factors suggests something about how niches are differentiated
among monocots, in that they appear to specialize in different
335
belowground functions (e.g. nitrogen or water uptake), despite
morphological and foraging similarities.
Acknowledgments
We would like to thank E.W. Bork, S.R. White, E.G. Lamb, B.H.
Shore, M.R. Clark, and M.D. Coupe for supplying the original data,
A.E. Nixon and M.W. Cadotte for their helpful comments, and S.
Pavoine for providing updated versions of the R scripts. We would
also like to thank Jack Welch, Barry Irving and the rest of the staff
at the University of Alberta research ranch at Kinsella, for their
help facilitating a decade of field research. J.F.C. oversaw the development and execution of all original datasets. J.F.C. originated the
broader concept of comparing among all experimental treatments.
J.A.B. developed the concepts of this particular study. J.A.B. conducted all analyses. J.A.B. wrote the paper and J.F.C. edited the
manuscript. J.A.B. was supported by an NSERC PGS-D scholarship.
This work was funded by a NSERC Discovery Grant and Discovery
accelerator award to J.F.C. Funding sources for the original studies
are listed within the associated manuscripts.
Appendix A. Supplementary data
Supplementary material related to this article can be
found, in the online version, at http://dx.doi.org/10.1016/j.ppees.
2013.10.001.
References
Agrawal, A.A., Fishbein, M., 2006. Plant defense syndromes. Ecology 87, S132–S149.
Allison, V.J., Rajaniemi, T.K., Goldberg, D.E., Zak, D.R., 2007. Quantifying direct and
indirect effects of fungicide on an old-field plant community: an experimental
null-community approach. Plant Ecol. 190, 53–69.
Anderson, T.M., Shaw, J., Olff, H., 2011. Ecology’s cruel dilemma, phylogenetic trait
evolution and the assembly of Serengeti plant communities. J. Ecol. 99, 797–806.
Beilstein, M.A., Al-Shehbaz, I.A., Mathews, S., Kellogg, E.A., 2008. Brassicaceae phylogeny inferred from phytochrome A and ndhF sequence data: tribes and
trichomes revisited. Am. J. Bot. 95, 1307–1327.
Bennett, J.A., Lamb, E.G., Hall, J.C., Cardinal-McTeague, W.M., Cahill Jr., J.F., 2013.
Increased competition does not lead to increased phylogenetic overdispersion
in a native grassland. Ecol. Lett. 16, 1168–1176.
Berg, M., Ellers, J., 2010. Trait plasticity in species interactions: a driving force of
community dynamics. Evol. Ecol. 24, 617–629.
Bertness, M.D., Callaway, R., 1994. Positive interactions in communities. Trends Ecol.
Evol. 9, 191–193.
Blomberg, S.P., Garland, T., Ives, A.R., 2003. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57, 717–745.
Bremer, B., Bremer, K., Chase, M., Fay, M., Reveal, J., Soltis, D., Soltis, P., Stevens,
P., 2009. An update of the Angiosperm Phylogeny Group classification for the
orders and families of flowering plants: APG III. Bot. J. Linn. Soc. 161, 105–121.
Brunbjerg, A.K., Borchsenius, F., Eiserhardt, W.L., Ejrnæs, R., Svenning, J.-C., 2012. Disturbance drives phylogenetic community structure in coastal dune vegetation.
J. Veg. Sci. 23, 1082–1094.
Burns, J.H., Strauss, S.Y., 2011. More closely related species are more ecologically
similar in an experimental test. Proc. Natl. Acad. Sci. U. S. A. 108, 5302–5307.
Burns, J.H., Strauss, S.Y., 2012. Effects of competition on phylogenetic signal and
phenotypic plasticity in plant functional traits. Ecology 93, 126–137.
Cahill Jr., J.F., 2003. Neighbourhood-scale diversity, composition and root crowding do not alter competition during drought in a native grassland. Ecol. Lett. 6,
599–603.
Cahill Jr., J.F., Elle, E., Smith, G.R., Shore, B.H., 2008a. Disruption of a belowground
mutualism alters interactions between plants and their floral visitors. Ecology
89, 1791–1801.
Cahill Jr., J.F., Kembel, S.W., Lamb, E.G., Keddy, P.A., 2008b. Does phylogenetic
relatedness influence the strength of competition among vascular plants? Perspect. Plant Ecol. Evol. Syst. 10, 41–50.
Cavender-Bares, J., Keen, A., Miles, B., 2006. Phylogenetic structure of Floridian plant
communities depends on taxonomic and spatial scale. Ecology 87, 109–122.
Cavender-Bares, J., Ackerly, D., Baum, D., Bazzaz, F., 2004. Phylogenetic overdispersion in Floridian oak communities. Am. Nat. 163, 823–843.
Chase, M.W., 2004. Monocot relationships: an overview. Am. J. Bot. 91, 1645–1655.
Chessel, D., Dufour, A., Thioulouse, J., 2004. The ade4 package-I-One-table methods.
R News 4, 5–10.
Clark, M.R., Coupe, M.D., Bork, E.W., Cahill Jr., J.F., 2012. Interactive effects of insects
and ungulates on root growth in a native grassland. Oikos 121, 1585–1592.
336
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
Comas, L.H., Mueller, K.E., Taylor, L.L., Midford, P.E., Callahan, H.S., Beerling, D.J.,
2012. Evolutionary patterns and biogeochemical significance of angiosperm
root traits. Int. J. Plant Sci. 173, 584–595.
Coughenour, M.B., 1985. Graminoid responses to grazing by large herbivores: adaptations, exaptations, and interacting processes. Ann. Missouri Bot. Gard. 72,
852–863.
Coupe, M.D., Stacey, J.N., Cahill Jr., J.F., 2009. Limited effects of above- and belowground insects on community structure and function in a species-rich grassland.
J. Veg. Sci. 20, 121–129.
Craine, J.M., 2009. Resource Strategies of Wild Plants. Princeton University Press,
Princeton, NJ.
Craine, J.M., Froehle, J., Tilman, D.G., Wedin, D.A., Chapin, I.F.S., 2001. The relationships among root and leaf traits of 76 grassland species and relative abundance
along fertility and disturbance gradients. Oikos 93, 274–285.
Craine, J.M., Tilman, D., Wedin, D., Reich, P., Tjoelker, M., Knops, J., 2002. Functional
traits, productivity and effects on nitrogen cycling of 33 grassland species. Funct.
Ecol. 16, 563–574.
Craine, J.M., Wedin, D.A., Chapin, F.S., Reich, P.B., 2003. Relationship between the
structure of root systems and resource use for 11 North American grassland
plants. Plant Ecol. 165, 85–100.
Crawley, M.J., 1989. Insect herbivores and plant population dynamics. Annu. Rev.
Entomol. 34, 531–562.
Darwin, C., 1859. On the Origin of Species by Means of Natural Selection. J. Murray,
London.
Diaz, S., Hodgson, J.G., Thompson, K., Cabido, M., Cornelissen, J.H.C., Jalili, A.,
Montserrat-Marti, G., Grime, J.P., Zarrinkamar, F., Asri, Y., Band, S.R., Basconcelo,
S., Castro-Diez, P., Funes, G., Hamzehee, B., Khoshnevi, M., Perez-Harguindeguy,
N., Perez-Rontome, M.C., Shirvany, F.A., Vendramini, F., Yazdani, S., Abbas-Azimi,
R., Bogaard, A., Boustani, S., Charles, M., Dehghan, M., de Torres-Espuny, L., Falczuk, V., Guerrero-Campo, J., Hynd, A., Jones, G., Kowsary, E., Kazemi-Saeed, F.,
Maestro-Martinez, M., Romo-Diez, A., Shaw, S., Siavash, B., Villar-Salvador, P.,
Zak, M.R., 2004. The plant traits that drive ecosystems: evidence from three
continents. J. Veg. Sci. 15, 295–304.
Dobeš, C., Paule, J., 2010. A comprehensive chloroplast DNA-based phylogeny
of the genus Potentilla (Rosaceae): implications for its geographic origin,
phylogeography and generic circumscription. Mol. Phylogen. Evol. 56, 156–
175.
Döring, E., Schneider, J., Hilu, K.W., Röser, M., 2007. Phylogenetic relationships in
the Aveneae/Poeae complex (Pooideae, Poaceae). Kew Bull., 407–424.
Foster, B.L., Dickson, T.L., Murphy, C.A., Karel, I.S., Smith, V.H., 2004. Propagule
pools mediate community assembly and diversity-ecosystem regulation along
a grassland productivity gradient. J. Ecol. 92, 435–449.
Ganade, G., Brown, V., 1997. Effects of below-ground insects, mycorrhizal fungi and
soil fertility on the establishment of Vicia in grassland communities. Oecologia
109, 374–381.
Gange, A.C., Brown, V.K., Farmer, L.M., 1990. A test of mycorrhizal benefit in an early
successional plant community. New Phytol. 115, 85–91.
Gotelli, N.J., 2000. Null model analysis of species co-occurrence patterns. Ecology
81, 2606–2621.
Grime, J.P., 1977. Evidence for the existence of three primary strategies in plants
and its relevance to ecological and evolutionary theory. Am. Nat. 111, 1169–
1194.
Grime, J.P., 2006. Trait convergence and trait divergence in herbaceous plant communities: mechanisms and consequences. J. Veg. Sci. 17, 255–260.
Grime, J.P., Mackey, J.M.L., 2002. The role of plasticity in resource capture by plants.
Evol. Ecol. 16, 299–307.
Harmon, L.J., Weir, J.T., Brock, C.D., Glor, R.E., Challenger, W., 2008. GEIGER: investigating evolutionary radiations. Bioinformatics 24, 129–131.
Hartnett, D.C., Wilson, G.W.T., 1999. Mycorrhizae influence plant community structure and diversity in tallgrass prairie. Ecology 80, 1187–1195.
Hedges, L.V., Gurevitch, J., Curtis, P.S., 1999. The meta-analysis of response ratios in
experimental ecology. Ecology 80, 1150–1156.
Helmus, M.R., Keller, W., Paterson, M.J., Yan, N.D., Cannon, C.H., Rusak, J.A., 2010.
Communities contain closely related species during ecosystem disturbance.
Ecol. Lett. 13, 162–174.
Howe, G.A., Jander, G., 2008. Plant immunity to insect herbivores. Annu. Rev. Plant
Biol. 59, 41–66.
Kembel, S.W., Cahill Jr., J.F., 2005. Plant phenotypic plasticity belowground: a phylogenetic perspective on root foraging trade-offs. Am. Nat. 166, 216–230.
Kembel, S.W., Cahill Jr., J.F., 2011. Independent evolution of leaf and root traits within
and among temperate grassland plant communities. PLoS ONE 6, e19992.
Kembel, S.W., Cowan, P.D., Helmus, M.R., Cornwell, W.K., Morlon, H., Ackerly, D.D.,
Blomberg, S.P., Webb, C.O., 2010. Picante: R tools for integrating phylogenies
and ecology. Bioinformatics 26, 1463–1464.
Knapp, A.K., Fay, P.A., Blair, J.M., Collins, S.L., Smith, M.D., Carlisle, J.D., Harper, C.W.,
Danner, B.T., Lett, M.S., McCarron, J.K., 2002. Rainfall variability, carbon cycling,
and plant species diversity in a mesic grassland. Science 298, 2202–2205.
Knouft, J.H., Losos, J.B., Glor, R.E., Kolbe, J.J., 2006. Phylogenetic analysis of the evolution of the niche in lizards of the Anolis sagrei group. Ecology 87, 29–38.
Lamb, E.G., 2008. Direct and indirect control of grassland community structure by
litter, resources, and biomass. Ecology 89, 216–225.
Lamb, E.G., Cahill Jr., J.F., 2008. When competition does not matter: grassland diversity and community composition. Am. Nat. 171, 777–787.
Lambers, H., Raven, J.A., Shaver, G.R., Smith, S.E., 2008. Plant nutrient-acquisition
strategies change with soil age. Trends Ecol. Evol. 23, 95–103.
Lavergne, S., Mouquet, N., Thuiller, W., Ronce, O., 2010. Biodiversity and climate
change: integrating evolutionary and ecological responses of species and communities. Annu. Rev. Ecol. Evol. Syst. 41, 321–350.
Lavorel, S., McIntyre, S., Landsberg, J., Forbes, T.D.A., 1997. Plant functional classifications: from general groups to specific groups based on response to disturbance.
Trends Ecol. Evol. 12, 474–478.
Losos, J.B., 2008. Phylogenetic niche conservatism, phylogenetic signal and the relationship between phylogenetic relatedness and ecological similarity among
species. Ecol. Lett. 11, 995–1003.
McGuire, R., Agrawal, A.A., 2005. Trade-offs between the shade-avoidance response
and plant resistance to herbivores? Tests with mutant Cucumis sativus. Funct.
Ecol. 19, 1025–1031.
Mouquet, N., Devictor, V., Meynard, C.N., Munoz, F., Bersier, L.F., Chave, J., Couteron,
P., Dalecky, A., Fontaine, C., Gravel, D., 2012. Ecophylogenetics: advances and
perspectives. Biol. Rev. 87, 769–785.
Münkemüller, T., Lavergne, S., Bzeznik, B., Dray, S., Jombart, T., Schiffers, K., Thuiller,
W., 2012. How to measure and test phylogenetic signal. Meth. Ecol. Evol. 3,
743–756.
Niinemets, U., Valladares, F., 2006. Tolerance to shade, drought, and waterlogging of
temperate Northern Hemisphere trees and shrubs. Ecol. Monogr. 76, 521–547.
Pagel, M., 1999. Inferring the historical patterns of biological evolution. Nature 401,
877–884.
Pavoine, S., Baguette, M., Bonsall, M.B., 2010. Decomposition of trait diversity among
the nodes of a phylogenetic tree. Ecol. Monogr. 80, 485–507.
Pennings, S.C., Clark, C.M., Cleland, E.E., Collins, S.L., Gough, L., Gross, K.L., Milchunas,
D.G., Suding, K.N., 2005. Do individual plant species show predictable responses
to nitrogen addition across multiple experiments? Oikos 110, 547–555.
Prinzing, A., 2001. The niche of higher plants: evidence for phylogenetic conservatism. Proc. R. Soc. B 268, 2383–2389.
Prinzing, A., Reiffers, R., Braakhekke, W.G., Hennekens, S.M., Tackenberg, O., Ozinga,
W.A., Schaminée, J.H.J., Van Groenendael, J.M., 2008. Less lineages–more trait
variation: phylogenetically clustered plant communities are functionally more
diverse. Ecol. Lett. 11, 809–819.
Pulliam, H.R., 2000. On the relationship between niche and distribution. Ecol. Lett.
3, 349–361.
Rao, C.R., 1982. Diversity and dissimilarity coefficients: A unified approach. Theor.
Popul. Biol 21, 24–43.
Reader, R.J., Wilson, S.D., Belcher, J.W., Wisheu, I., Keddy, P.A., Tilman, D., Morris, E.C.,
Grace, J.B., McGraw, J.B., Olff, H., Turkington, R., Klein, E., Leung, Y., Shipley, B.,
Vanhulst, R., Johansson, M.E., Nilsson, C., Gurevitch, J., Grigulis, K., Beisner, B.E.,
1994. Plant competition in relation to neighbor biomass – an intercontinental
study with Poa pratensis. Ecology 75, 1753–1760.
Reich, P.B., Wright, I.J., Cavender-Bares, J., Craine, J.M., Oleksyn, J., Westoby, M., Walters, M.B., 2003. The evolution of plant functional variation: traits, spectra, and
strategies. Int. J. Plant Sci. 164, S143–S164.
Reinhart, K.O., Wilson, G.W.T., Rinella, M.J., 2012. Predicting plant responses to
mycorrhizae: integrating evolutionary history and plant traits. Ecol. Lett. 15,
689–695.
Richmond, K.E., Sussman, M., 2003. Got silicon? The non-essential beneficial plant
nutrient. Curr. Opin. Plant Biol. 6, 268–272.
Sadras, V.O., Milroy, S.P., 1996. Soil-water thresholds for the responses of leaf expansion and gas exchange: a review. Field Crops Res. 47, 253–266.
Sardar, D., Kole, R.K., 2005. Metabolism of chlorpyrifos in relation to its effect on the
availability of some plant nutrients in soil. Chemosphere 61, 1273–1280.
Selliah, S., Brouillet, L., 2008. Molecular phylogeny of the North American eurybioid asters (Asteraceae, Astereae) based on the nuclear ribosomal internal and
external transcribed spacers. Botany 86, 901–915.
Silvertown, J., 1980. The dynamics of a grassland ecosystem: Botanical equilibrium
in the Park Grass Experiment. J. Appl. Ecol. 17, 491–504.
Silvertown, J., Dodd, M., Gowing, D., Lawson, C., McConway, K., 2006a. Phylogeny and the hierarchical organization of plant diversity. Ecology 87, S39–
S49.
Silvertown, J., McConway, K., Gowing, D., Dodd, M., Fay, M.F., Joseph, J.A., Dolphin, K.,
2006b. Absence of phylogenetic signal in the niche structure of meadow plant
communities. Proc. R. Soc. B 273, 39–44.
Silvertown, J., Poulton, P., Johnston, E., Edwards, G., Heard, M., Biss, P.M., 2006c.
The Park Grass Experiment 1856–2006: its contribution to ecology. J. Ecol. 94,
801–814.
Soltis, D.E., Smith, S.A., Cellinese, N., Wurdack, K.J., Tank, D.C., Brockington,
S.F., Refulio-Rodriguez, N.F., Walker, J.B., Moore, M.J., Carlsward, B.S., 2011.
Angiosperm phylogeny: 17 genes, 640 taxa. Am. J. Bot. 98, 704–730.
Swenson, N.G., 2009. Phylogenetic resolution and quantifying the phylogenetic
diversity and dispersion of communities. PLoS ONE 4, e4390.
Thuiller, W., Lavergne, S., Roquet, C., Boulangeat, I., Lafourcade, B., Araujo, M.B.,
2011. Consequences of climate change on the tree of life in Europe. Nature 470,
531–534.
Tilman, D., 1987. Secondary succession and the pattern of plant dominance along
experimental nitrogen gradients. Ecol. Monogr. 57, 190–214.
Tilman, D., 1996. Biodiversity: population versus ecosystem stability. Ecology 77,
350–363.
Turkington, R., John, E., Watson, S., Seccombe-Hett, P., 2002. The effects of fertilization and herbivory on the herbaceous vegetation of the boreal forest in
north-western Canada: a 10-year study. J. Ecol. 90, 325–337.
Valladares, F., Niinemets, Ü., 2008. Shade tolerance, a key plant feature of complex
nature and consequences. Annu. Rev. Ecol. Evol. Syst. 39, 237–257.
J.A. Bennett, J.F. Cahill Jr. / Perspectives in Plant Ecology, Evolution and Systematics 15 (2013) 328–337
vandenBrink, P.J., vanWijngaarden, R.P.A., Lucassen, W.G.H., Brock, T.C.M.,
Leeuwangh, P., 1996. Effects of the insecticide Dursban(R) 4E (active ingredient
chlorpyrifos) in outdoor experimental ditches. 2. Invertebrate community
responses and recovery. Environ. Toxicol. Chem. 15, 1143–1153.
Verdú, M., Pausas, J.G., 2007. Fire drives phylogenetic clustering in Mediterranean
Basin woody plant communities. J. Ecol. 95, 1316–1323.
Wang, P., Stieglitz, T., Zhou, D.W., Cahill Jr., J.F., 2010. Are competitive effect and
response two sides of the same coin, or fundamentally different? Funct. Ecol.
24, 196–207.
Webb, C.O., Ackerly, D.D., McPeek, M.A., Donoghue, M.J., 2002. Phylogenies and
community ecology. Annu. Rev. Ecol. Syst. 33, 475–505.
Westoby, M., 1998. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant
Soil 199, 213–227.
337
White, S., Bork, E., Karst, J., Cahill Jr., J.F., 2012. Similarity between grassland vegetation and seed bank shifts with altered precipitation and clipping, but not
warming. Commun. Ecol. 13, 129–136.
Wiens, J.J., Ackerly, D.D., Allen, A.P., Anacker, B.L., Buckley, L.B., Cornell, H.V.,
Damschen, E.I., Davies, T.J., Grytnes, J.A., Harrison, S.P., Hawkins, B.A., Holt, R.D.,
McCain, C.M., Stephens, P.R., 2010. Niche conservatism as an emerging principle
in ecology and conservation biology. Ecol. Lett. 13, 1310–1324.
Wiens, J.J., Graham, C.H., 2005. Niche conservatism: integrating evolution, ecology,
and conservation biology. Annu. Rev. Ecol. Evol. Syst., 519–539.
Willis, C.G., Ruhfel, B., Primack, R.B., Miller-Rushing, A.J., Davis, C.C., 2008. Phylogenetic patterns of species loss in Thoreau’s woods are driven by climate change.
Proc. Natl. Acad. Sci. U. S. A. 105, 17029–17033.