Download Towards a trait-based quantification of species

Journal of
Plant Ecology
VOLUME 2, NUMBER 2,
PAGES 87–93
Towards a trait-based quantification
of species niche
JUNE 2009
doi: 10.1093/jpe/rtp007
Advanced Access published
on 7 May 2009
available online at
www.jpe.oxfordjournals.org
Cyrille Violle* and Lin Jiang
School of Biology, Georgia Institute of Technology, 310 Ferst Drive, Atlanta, GA 30332, USA
*Correspondence address. Department of Ecology and Evolutionary Biology, University of Arizona, BioSciences
West, Tucson, AZ 85721, USA. Tel: +520-626-3336; Fax: +520-621-9190; E-mail: [email protected]
Abstract
Aims
Although the niche concept is of prime importance in ecology, the
quantification of plant species’ niches remains difficult. Here we propose that plant functional traits, as determinants of species performance, may be useful tools for quantifying species niche
parameters over environmental gradients.
Important findings
Under this framework, the mean trait values of a species determine its
niche position along gradients, and intraspecific trait variability
determines its niche breadth. This trait-based approach can provide
an operational assessment of niche for a potentially large number of
species, making it possible to understand and predict species niche
shifts under environmental changes. We further advocate a promising
method that recently appeared in the literature, which partitions trait
INTRODUCTION
The concept of the ecological niche holds a central role in ecology. It has been widely used to understand species coexistence
within communities, as well as to predict species distributions
along environmental gradients. During the last two decades,
the field of species distribution modelling has expanded to predict species’ range shifts under future global change scenarios
(e.g. Lenoir et al. 2008). Current approaches to modelling species distribution mostly rely on Hutchinson’s (1957) concept of
fundamental and realized niches, i.e. the subset of n-dimensional space of all possible environmental conditions in which
a species can survive without and with species interactions, respectively. Within the general controversy about whether
ecology as a discipline produces general rules and predictions
(Lawton 1999; Simberloff 2004), the debate on the usefulness
of species niche quantification for predicting future species distributions is of significant importance. This is especially the
case for plants, for which fundamental niches are rarely measured (Pulliam 2000). Most projections of species distributions
are indeed based on correlative models (Thuiller et al. 2008)
diversity into among- and within-community components as a way
to quantify the species niche in units of traits instead of environmental parameters. This approach allows the switch of the focus from
ecological niches to trait niches, facilitating the examination of species coexistence along undefined environmental gradients. Altogether, the trait-based approach provides a promising toolkit for
quantifying the species ecological niche and for understanding
the evolution of species niche and traits.
Keywords: functional diversity d plant functional traits
breadth d niche position d trait niche
niche
Received: 12 November 2008 Revised: 24 February 2009 Accepted:
9 April 2009
that used current distribution data to predict future distribution scenarios; the accuracy of such correlative predictions,
however, can be seriously compromised by species interactions (Davis et al. 1998; Jiang and Morin 2004; Suttle et al.
2007). The emergence of a new generation of distribution
models, based on physiological mechanisms linking species
performance and the environment (Morin and Lechowicz
2008), may offer a more accurate framework for predicting
species distributions when taking into account species interactions (Kearney 2006). Such species-based approach is limited
by the large amount of data required for each species, however, and hence can only be applied for a restricted number
of species.
In recognition of the importance of plant functional traits,
McGill et al. (2006) developed a promising trait-based paradigm for community ecology to turn to a more operational,
quantitative and predictive science that can more readily
address issues of species abundances and distributions.The plea
of McGill et al. is based on the trait-based ‘assembly rules’
(Keddy 1992a; Weiher and Keddy 1995), which predict the
selection of species across environmental filters (biotic, abiotic,
Ó The Author 2009. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
All rights reserved. For permissions, please email: [email protected]
d
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dispersion and biogeographical) according to their trait values.
The underlying thesis of the trait-based approach is that traits,
not taxon names, are fundamental units of species sorting
(i.e. selection of species across filters) from a regional pool
of species, and should therefore be a relevant tool to quantify
species’ niches. Here, we argue that this trait-based approach
is particularly useful for determining the species niche, which
can be achieved by tracking plant functional traits related to
individual performance or population abundance. We suggest that the mean and range of trait values exhibited by a species may provide estimates of niche parameters (niche
position and breadth) for a potentially large set of species.
We also suggest that, as a promising method to explain species coexistence when environmental data are not available,
the species niche may be defined in units of the trait, through
partitioning trait diversity into within- and among-community
components.
PLANT FUNCTIONAL TRAITS AS
SURROGATES FOR SPECIES PERFORMANCE
In principle, fundamental and realized species niches can be
quantified by the changes in abundance, or simply occurrence, of a population over environmental gradients. Although niche determination is relatively straightforward
for some organisms, such as microorganisms that can be readily cultured, fundamental niche has almost never been quantified for plants, because of the difficulty to follow the
performance of a species (e.g. population vital rates) over
continuous abiotic gradients under controlled conditions.
In addition, even if population vital rates (e.g. population
growth rate) are the best ‘performance currencies’ (sensu
McGill et al. 2006) to quantify the species niche, they are difficult to measure in plants, especially for a large number of
species. Consequently, plant niches are most often assessed
using habitat models based on existing species presence/absence data across geographical scales (see Thuiller et al. 2008
for a review). Although habitat models describe—by definition—the realized niches of species, these realized niches are
treated as if they were fundamental niches when future species distribution scenarios are projected under environmental
changes. However, species-realized niches can differ substantially from their fundamental niches and the nature and
strength of species interactions can vary in response to
changes in abiotic conditions (e.g. Bertness and Ewanchuck
2002; Jiang and Morin 2004). Hence, studies (Davis et al.
1998; Jiang and Morin 2004; Suttle et al. 2007) have demonstrated that this approach, without considering species interactions, can result in inaccurate predictions on community
responses to climate changes. In this paper, we suggest that,
by using functional traits as surrogates for species performance and by bypassing the complexity of quantifying species interactions in plants, the functional trait-based
approach may be a relevant method to assess the species
niches.
Journal of Plant Ecology
A ‘plant functional trait’ is defined as any morphological,
physiological or phenological feature measured at the individual level that impacts fitness (Violle et al. 2007a). In
plants, fitness is most often assessed by individual performance measured by individual biomass, reproductive output
or survival (Violle et al. 2007a). Empirical approaches to
quantify the relationships between species individual-level
performance and plant functional traits can be statistic
(e.g. Vile et al. 2006) as well as mechanistic (e.g. Kooijman
2000; van der Meer 2006; Wildova et al. 2007). So far, most
trait–performance relationships were established for vegetative biomass (e.g. links between specific leaf area (SLA) and
vegetative biomass: cf Wright and Westoby 2001), whereas
the links between plant traits and survival remain rarely explored because of the difficulty to follow seedling and adult
survival in the field. Even if the connection between population vital rates and plant functional traits is not yet elucidated (but see Poorter et al. 2008 for recent advances in
trees), plant traits can be clearly related to species abundance
(plant cover, population biomass: see e.g. Shipley et al. 2006;
McGill 2006), which is perhaps a more operational population-level performance currency in plants because of the difficulty to track the demography of plants (especially for
herbaceous species).
One advantage of the trait-based approach is that it employs
a non-destructive sampling method, i.e. the whole species (individual or population) biomass does not need to be harvested.
Consequently, functional traits–environment curves can be
used as a surrogate for performance–environment curves to
depict species distribution. For instance, a measure of predawn
leaf water potential (a measure on a leaf at a time when soil
and plant water potentials tend to equilibrate, before the onset
of transpiration) captures the way that plants perceives the soil
water environment (Boyer 1995) and can be used as a surrogate for changes in individual biomass along a soil water availability gradient (e.g. Gebauer et al. 2002; Mitchell et al. 1999;
Violle et al. 2009). Another advantage of using functional
traits instead of performance currencies is that some traits
are relatively ‘easily measurable’ (‘soft’ traits in Weiher et al.
1999), which allows the examination of a large number of species that otherwise would not be possible. This is the power of
the comparative approach in plant functional ecology (i.e.
comparison of trait values between species), which has three
basic tenets: (i) constructing trait matrices through screening
a large number of species; (ii) exploring empirical relationships
among these traits and (iii) determining the relationships
between traits and environments (Keddy 1992b).
FUNCTIONAL RESPONSE TRAITS AS TOOLS
TO QUANTIFY SPECIES NICHE PARAMETERS
‘Functional response traits’ are functional traits that vary in
response to changes in environmental conditions (Lavorel
and Garnier 2002; Suding et al. 2008). A large part of the ‘trait’
literature is related to the identification of functional response
Violle & Jiang
|
Plant traits and species niche
traits to predict the effects of climate change, disturbance and
land use change on vegetation (e.g. Garnier et al. 2007). For
example, age at maturity, seedling relative growth rate,
growth form and shoot height are plant functional response
traits related to fire disturbance (Lavorel and Garnier 2002).
Comparative approaches have established empirical relationships (i) between functional traits and performance currencies
(e.g. Poorter and Bongers 2006; Wright and Westoby 2001;
Wright et al. 2004) and (ii) between functional response traits
and environments (e.g. Ackerly et al. 2002; Garnier et al. 2004;
Wright et al. 2005). Therefore, we advocate here that measuring functional response traits may provide an accurate quantification of species niche parameters. Since the definition of
a niche is based on the identification of the environmental
conditions required by a species to survive, a preliminary necessary step is to identify prioritizing key environmental factors
that significantly influence trait variations (McGill et al. 2006).
This is necessary because the quantification of Hutchinson’s
(1957) n-dimensional environmental space is logistically impossible when n becomes large. Consequently, as for the
species-centred approaches of the niche, the trait-based quantification of niche parameters requires the identification of
a limited number of key environmental gradients. For instance, a combination of temperature and rainfall gradients
accounts for a large part of variability in SLA, an important
plant functional trait, worldwide (Wright et al. 2004).
Applying the trait-based approach to the quantification of
species niche parameters, as promising as it is, still remains
challenging because of the difficulty to select traits specifically
related to biotic versus abiotic filtering processes, i.e. the mechanisms controlling the niche. For instance, there is still is no
agreement on a unique set of functional traits related to competition (Craine 2005; Violle et al. 2009). It could also be
important to disentangle adult vegetative traits (e.g. traits related to photosynthesis activities) and regenerative traits (e.g.
traits related to seed production or seed germinability) when
establishing trait–environment relationships. Indeed one major hypothesis related to both types of traits (Grime 2006),
which remains to be tested, is that (i) they vary independently
across species and (ii) within communities, vegetative traits are
under-dispersed while regenerative traits are over-dispersed,
in relation to community assembly mechanisms.
Comparing mean species traits to detect species
niche position
A trait-based quantification of the species niche needs to establish trait–environment relationships across species. This is
done by amassing numerous data on key traits that exhibit significant shifts across environmental gradients (e.g. Bailey and
Sinnott 1916; Baker 1972; Moles et al. 2007; Wright et al.
2005). Such information will likely increase in the next coming years with the development of worldwide trait databases
combining trait and environmental data (e.g. Garnier et al.
2007; Kleyer et al. 2008). Recently, this trait–environment approach has been improved by the identification of changes in
89
‘community functional parameters’ (sensu Violle et al. 2007a),
i.e. community-level mean traits, along main environmental
gradients. Indeed, traits weighted by the species’ contribution
to the community (e.g. species’ relative abundance at a site)
best reflect the level of physiological adaptation of traits to
the environment (e.g. Garnier et al. 2004; Quétier et al.
2007; Shipley et al. 2006), given that dominants in a given
plant assemblage should have trait values better fitted to environment than minor species (see Cingolani et al. 2007). This
facilitates the identification of key performance-related traits
that were significantly linked to abiotic gradients. For instance,
community mean SLA has been found to be significantly correlated with soil water availability and potential solar insolation (Ackerly et al. 2002). Such changes in community mean
traits over environmental gradients (Fig. 1), when available
(preferentially on separate datasets), provide good assessments
of trait–environment relationships. Given such information,
we can estimate the ‘optimum’ position of a species (Ei) along
an environmental gradient by comparing its mean trait value
(e.g. issued from standardized databases) to the community
mean trait values (Fig. 1a). This provides an estimate of ecological performances (e.g. flooding or frost tolerance) as the
ecologically optimum point for a potentially large set of species. For instance, plant community mean SLA tends to increase with anoxic stress in flood meadows (C. Violle,
unpublished data); therefore analysing mean species SLA in
relation to community means may indicate their flooding tolerance ability. Note that this comparative approach based on
mean trait cannot provide information about niche breadth
(see below; cf Violle et al. 2007a).
Assessing intraspecific trait variability to quantify
species niche breadth
Intraspecific trait variability, which expresses the range of trait
values exhibited by a species grown in different environments,
is frequently neglected in trait-based community ecology,
where a single trait value is often used for each species as provided by existing databases, regardless of geographical localization of the species (but see Garnier et al. 2007 and Kleyer et al.
2008 for recent databases including environmental information). Indeed, a basic assumption of comparative plant ecology
is that the intraspecific trait variability, the magnitude of which
is generally smaller than that of interspecific trait variability,
may be ignored (Keddy 1992b; McGill et al. 2006). Here we
argue that, however, intraspecific trait variability could be
used to assess niche breadth. At a first approximation, intraspecific trait variability can be assessed by the magnitude of trait
variability recorded among existing databases for a given species (Fig. 1b). Alternatively, experiments or observations that
measure the value of a trait along an environmental gradient
could also provide an estimate of intraspecific trait variability.
Even if these methods cannot disentangle genetic versus environmental effects—then cannot assess trait plasticity—they
can provide a rapid, approximate, estimate of niche breadth for
a large set of species by localizing the range of trait values
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Journal of Plant Ecology
(a)
Trait 1
...
Trait k
...
Species 1
...
Species i
Mean
Community mean trait k
...
Ei
Environmental gradient
(b)
Trait 1
...
Trait k
...
Species 1
...
Species i
Min-Max
Community mean trait k
...
Bi
Environmental gradient
Figure 1: trait-based quantification of species niche position and
breadth along an environmental gradient. Community mean traits
(e.g. the average of trait values of all species co-occurring in the community; traits weighted by the species’ relative abundances) reflect the
level of physiological adaptation of traits to the abiotic environment
(see text for further explanation). (a) For a species i and a trait k, comparing its mean trait value (e.g. issued from existing databases) to the
distribution of community mean values provides an estimate of species
niche position (Ei) on the gradient. (b) For a species i and a trait k,
comparing the range of trait values exhibited by species i (e.g. issued
from a combination of existing databases) to the distribution of community mean values provides an estimate of species niche breadth (Bi)
on the gradient under scrutiny.
exhibited by a species on the community mean trait–environment curve (Fig. 1b).
PARTITIONING BETA AND ALPHA
FUNCTIONAL DIVERSITY: TOWARDS A
‘TRAIT NICHE’ DEFINITION
Classical niche approaches require a quantification of the environmental factors that affect species performance. The complexity to assess resource availabilities when they vary over
time (Violle et al. 2007b) and to identify multiple co-limiting
environmental factors (McGill et al. 2006) makes this quantification difficult in many ecosystems. Here we advocate a traitbased method, first proposed by Ackerly and Cornwell (2007),
which does not require information on environmental factors,
to depict the species niches. By replacing environmental gradients with trait gradients and by partitioning within- and
among-communities functional diversity along trait gradients,
this method provides an estimate of niche in units of traits instead of the environment. As detailed below, for a given species, the parameters of its ‘trait niche’ are defined by the
average position of the trait of the species relative to the average position of the mean trait of the communities in which the
species occurs. Hence, the trait niche of a species depends on
the traits of co-occurring species, providing insights for understanding mechanisms shaping species coexistence.
Species diversity patterns depend on the spatial scale under
scrutiny. Therefore, Whittaker (1975) and others proposed
specific terms for defining species diversity in relation to the
scale of applicability. In particular, the alpha diversity refers
to the species richness within local communities/patches,
while the beta diversity refers to the turnover of species between communities. By analogy, Ackerly and Cornwell
(2007) proposed to partition plant trait diversity into withinand among-community components, termed alpha and beta
trait diversity, respectively. This method requires to measure
traits for all species occurring in communities along a gradient
in order to estimate changes in community mean trait (as
a quantification of the gradient) and intraspecific trait variability (as a quantification of species trait shift between communities). The beta trait value is the average (weighted by focal
species abundance) of the mean trait of the communities
where the focal species is present (bi in Fig. 2) and defines
the trait niche position of the species (i.e. the trait value of
its ‘typical habitat’). This information may be further linked
to environmental data, if available, to locate the species over
the environmental gradient (cf Fig. 1a). For instance, applying
this method to woody plant communities of coastal California,
Ackerly and Cornwell (2007) showed that beta trait values for
SLA, leaf size, wood density and maximum height, which all
covaried, reflect species positions across a gradient of soil moisture availability. On the other hand, the alpha trait value (ai in
Fig. 2), which is the difference between the average of trait
values exhibited by the focal species across communities
where it occurs and its beta value, is a measure of how the trait
of the focal species differs, on average, from its co-occurring
species (i.e. niche differentiation). Since alpha values reflect
niche differentiation among coexisting species, they might also
be the base of a measure of trait divergence between species,
providing potential insights into mechanisms of species coexistence. Finally, comparing the range of trait values exhibited
by the focal species against community mean trait provides
a measure of niche breadth (Ri) in units of the trait and a
dimensionless measure (bi) of the sensitivity of intraspecific
variation to changes in community mean trait (Fig. 2).
Violle & Jiang
|
Plant traits and species niche
91
Species trait (tij)
1:1
i
bi
Ri
βi
Community mean trait (pj)
Figure 2: partitioning of species trait values into within- and amongcommunity components (adapted from Ackerly and Cornwell 2007).
The environmental gradient is replaced by a community mean trait
gradient. Plotting species trait values (tij) versus community mean trait
values (pj) for any location j of a gradient allows defining species trait
niche, i.e. the niche of species i in units of the trait considered. The grey
line is the regression line relating species trait values to community
mean trait values for a species i, with slope bi. Species trait values
can be lower or higher than community mean trait values (i.e. regression line located below or above the 1:1 line). For a species i, the grey
point shows the average (weighted by species i abundance) of the
mean (weighted by species relative abundance in the community) trait
of the communities where species i is present (bi, on abscissa) and the
average of trait values exhibited by a species among communities (ti,
on ordinate). Then the beta trait value (bi) defines the trait niche position of the focal species (i.e. the trait value of its typical habitat). The
distance between ti and bi is ai. Therefore, the alpha trait value (ai) is
a measure of how the trait of the focal species differs, on average, from
its co-occurring species. The range of occupied communities by species
i on the x-axis is the species niche breadth (Ri) in units of the trait. See
text for further explanations.
CONNECTING TRAIT-BASED APPROACHES
WITH CONTEMPORARY NICHE CONCEPTS
The Hutchinson’s (1957) concept of the niche focuses on the
response of a species to its abiotic and biotic environment. Leibold (1995) and Chase and Leibold (2003) suggested that this
definition can be expanded to include the effects of a species on
its surrounding environment by distinguishing two components of the niche: (i) a ‘requirement’ niche corresponding
to Hutchinson’s original concept; (ii) an ‘impact’ niche describing effects of species on the environment. Interestingly, this
response/effect niche framework corresponds to the concepts
of functional response/effect traits as defined by Lavorel and
Garnier (2002). Functional response traits are functional traits
that vary in response to changes in environmental conditions,
while ‘functional effects traits’ are functional traits that are related to the effect of a plant on its surrounding environment
(e.g. resource availability, ecosystem functioning). On the one
hand, the requirement niche might be defined by changes in
functional response traits, as described in this paper (e.g.
changes in leaf water potential in response to changes in soil
water availability). On the other hand, the impact niche might
be quantified by changes in functional effect traits. For instance,
plant height can be considered as a functional effect trait that
captures the depletion effects of plants on light and soil water
availabilities in herbaceous systems (Westoby et al. 2002; Violle
et al. 2009), while root biomass may be another functional
effect trait of the depletion effects of plants on soil nitrogen availability (e.g. Wedin and Tilman 1993; Fargione and Tilman
2006). The concordance of the two niche’s components and trait
concepts provides a sound ground for trait-based approaches to
niche quantification. Yet, one remaining limitation is the fact
that response and effect traits may often overlap (Lavorel and
Garnier 2002). For instance, plant height can be considered
as an effect trait (see above) as well as a response trait for a plant
that faces shading (e.g. Vermeulen et al. 2008). Therefore, methods are still required to disentangle ‘response’ and ‘effect’ components of traits in natural communities.
Both species traits and niches are shaped by evolution (Chase
and Leibold 2003). For instance, plants tend to be taller on evolutionary time scales in relation to competition for light (Falster
and Westoby 2003), in an attempt to intercept more light by
overtopping the canopy (plant height considered as a functional
response trait) as well as to reduce the light resource available
for other co-occurring species by shading (plant height considered as a functional effect trait). Hence, both the response and
effect of plants to/on their environment can be involved in trait
evolution, which might be linked to the niche-construction
approach proposed for niche evolution. Indeed, the nicheconstruction concept explores the evolutionary processes that
generate niche selection through an evolutionary feedback between organisms and their environment (see e.g. Odling-Smee
et al. 1996; Kylafis and Loreau 2008), i.e. by considering the evolutionary response of a species to its environment and its evolutionary effect on its environment. While the evolutionary
response of a species to the environment (i.e. the evolution
of requirement niche) can be analysed through the evolution
of functional response traits, the evolutionary effect of plants
on their environment (i.e. the evolution of effect niche), which
has been largely ignored in niche evolution studies, could be
assessed by the evolution of functional effect traits.
ACKNOWLEDGEMENTS
This project was supported by a US National Science Foundation grant
(DEB-0640416) to L.J. and Georgia Tech.
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