Download Resource quantity, not resource heterogeneity, maintains plant

Ecology Letters, (2002) 5: 420–426
REPORT
Resource quantity, not resource heterogeneity,
maintains plant diversity
M. Henry H. Stevens* and Walter
P. Carson
Program in Ecology and
Evolution, Department of
Biological Sciences, University
of Pittsburgh, Pittsburgh, PA
15260, U.S.A.
*Correspondence and present
address: Department of Botany,
316 Pearson Hall, Miami
University, Oxford, OH 45056
USA. E-mail:
[email protected]
Abstract
Resource heterogeneity has often been proposed to explain the maintenance of plant
species diversity and patterns of species diversity along productivity gradients. Resource
heterogeneity should maintain biodiversity by preventing competitive exclusion because
different species are superior competitors in different parts of a heterogeneous
environment. In natural systems, however, resource heterogeneity covaries with average
resource supply rate, making the effect of heterogeneity difficult to isolate. Using a novel
experimental approach, we tested the independent effects of resource heterogeneity and
average supply rate on plant species diversity. We show that the average supply rate of
the most limiting resource controlled species diversity, whereas heterogeneity of this
resource had virtually no effect. These findings also suggest that biodiversity declines
with increasing productivity because at high enough levels of productivity one resource
may always be driven to sufficiently short supply to exclude many species.
Keywords
Assemblage level thinning, enemy free space, heterogeneity, productivity gradient,
resource ratio, species diversity, species richness.
Ecology Letters (2002) 5: 420–426
INTRODUCTION
Spatial heterogeneity of one or more limiting resources
should prevent competitive exclusion and maintain high
species richness (Hardin 1960; MacArthur 1970; Grubb
1977; Ricklefs 1977; Tilman 1982; Palmer 1994; Crawley
1997; Nicotra et al. 1999; Kassen et al. 2000). Several general
theoretical models of local species interactions (MacArthur
1970; Levin 1976; Tilman 1982; Abrams 1988; Pacala
& Tilman 1994) make at least two robust predictions:
(1) spatial heterogeneity of limiting resources governs the
number of co-occurring species (i.e. species richness), and
(2) species habitat requirements and the relative abundance
of different microhabitat types determine species relative
abundances. In contrast, a wide variety of other hypotheses
suggest that species richness is determined by the average
supply rates of the most limiting resources (Preston 1962;
MacArthur & Wilson 1963; Wright 1983; Rosenzweig &
Abramsky 1993; Abrams 1995; Hurtt & Pacala 1995;
Srivastava & Lawton 1998; Grace 1999; Stevens & Carson
1999b; Morin 2000; Hubbell 2001). Although critical
differences exist within this group of hypotheses, each
predicts that: (1) species richness will increase with
increasing resource and energy availability, and (2) the most
!2002 Blackwell Science Ltd/CNRS
abundant species in the species pool may dominate any
particular site by chance alone. For the remainder of this
paper, we will refer to these two sets of predictions as the
heterogeneity hypothesis and the energy hypothesis.
Here we test the heterogeneity hypothesis and the energy
hypothesis by measuring the relative importance of spatial
heterogeneity and the average supply rate of light in
governing a widespread but paradoxical pattern: plant
species richness falls as soil resource availability and
productivity rise (Grime 1973; Tilman 1982; Rosenzweig
& Abramsky 1993; Tilman & Pacala 1993; Waide et al. 1999;
Gough et al. 2000; Gross et al. 2000; Mittelbach et al. 2001).
The resolution to this paradox appears to lie with how light
availability covaries with productivity (Tilman & Pacala
1993; Huston & DeAngelis 1994). As soil resources rise, and
plant communities become more productive, light availability in the understorey declines. Understorey light availability
probably governs species richness because all individuals of
both canopy species and understorey specialists must
survive and grow in the understorey at some point in their
ontogenies (Grubb 1977; Harper 1977). Heterogeneityrelated hypotheses assume that species specialize in different
light levels (e.g. Ricklefs 1977; Pacala et al. 1996; Kobe 1999)
or different ratios of light and soil resources (Tilman 1982;
Resource quantity and plant diversity 421
Tilman & Pacala 1993) and each predicts that light
heterogeneity should govern species richness. Energyrelated hypotheses (Preston 1962; MacArthur & Wilson
1963; Wright 1983; Rosenzweig & Abramsky 1993; Hurtt &
Pacala 1995; Oksanen 1996; Grace 1999; Stevens & Carson
1999b; Hubbell 2001) do not necessarily rely on assumptions about species specializations and predict that the
average supply rate of light should govern species richness.
We used a novel experimental approach to test the
independent contribution of light heterogeneity to plant
species richness (Stevens 1999). After establishing an
experimental productivity gradient in an herbaceous plant
community, we used shade frames to manipulate independently understorey light heterogeneity, and the average supply
rate of understorey light. This allowed us, for the first time,
to test whether light heterogeneity governs species richness
along productivity gradients. This also allowed us to test the
key underlying assumption of whether species specialize in
low-light environments.
METHODS
In 1995, we sprayed with herbicide and ploughed an
abandoned agricultural field in north-western Pennsylvania,
USA. We fertilized 192 plots (4 · 4 m, each separated by
1 m) at four different rates for 3 years (1996–8) (OsmocoteTM slow release fertilizer, 18–6–12 NPK, at rates of 0, 8, 16
and 32 g N m)2 year)1). By 1997, the field was dominated
by several Solidago spp., Agropyron repens and Milium effusum
(Stevens 1999). In free-standing vegetation without shade
frames, our soil resource gradient created patterns widely
observed in other studies of herbaceous plant productivity
gradients: as soil resources rise, above-ground biomass
increases, and species richness, average understorey light
supply rate, and understorey light spatial heterogeneity fall
(e.g. Grime 1973; Al-Mufti et al. 1977; Tilman 1987; Stevens &
Carson 1999b; Stevens 1999).
Six designs of shade frames (Fig. 1) (1 m W · 0.75 m
H · 3 m L) provided three levels of spatial heterogeneity at
each of two average supply rates when placed over growing
vegetation (‘‘heterogeneity’’ and ‘‘average supply rate’’ are
the standard deviation and mean of a spatial array of point
light measurements) (Table 1). We selected the levels of
supply rate and heterogeneity to represent the range of each
observed in free-standing vegetation at the above levels of
fertilizer (Table 1). Over a two-year period (1997, 1998), the
shade frames took the place of the canopies formed by the
tallest plants (e.g. Euthemia graminifolia, Solidago altissima). As
plants grew taller throughout the growing season, they were
guided around the opaque outside walls of the shade frames,
so that tall plants did not cast shade in the 30 · 150 cm
sample plots (Fig. 1) and confound the shade treatments. At
the beginning of the 1997 growing season, one shade frame
was placed in each of the 192 plots fertilized with one of
four levels of soil fertilizer (above) resulting in 24 unique
treatment combinations (n ¼ 8). The shade frames did not
Schematic 2-D overviews
Sample plot
(gray)
of shade frame types
30 cm
Low-Light (2%)
Uniform Continuum Gap
Moderate-Light (30%)
3-D frame in
surrounding
vegetation
3m
3m
ated three levels of light heterogeneity at
each of two levels of average light supply
rate (see Table 1). In this schematic, the
degree of shading indicates shade cloth
opacity (density) with black areas transmitting < 1% of ambient light and white
(no shade cloth) transmitting 100%
ambient light. Shade frames were orientated north–south and placed over
growing vegetation. Ramets over 50 cm
tall were guided around the outside,
plastic-sheet walls of the frames. Plants
were sampled in three contiguous
30 · 50 cm subplots, and light was
sampled at 150 1.0 cm intervals along the
dashed transect.
50 cm
Figure 1 The six shade frame types cre-
1m
!2002 Blackwell Science Ltd/CNRS
422 M.H.H. Stevens and W.P. Carson
Table 1 Average supply rate and heterogeneity of light in shade frames (n ¼ 32/type) and in free-standing vegetation (n ¼ 12/level) along
the experimental productivity gradient (mean[standard error]). Light under shade frames was independent of fertilizer level
Frame type
Av. Supply rate (mean)
Heterogeneity (SD)
High – Gap
High – Cont.
High – Unif.
Low – Gap
Low – Cont.
Low – Unif.
0.34 (0.013)
0.36 (0.015)
0.38 (0.011)
0.021 (0.00062)
0.025 (0.0014)
0.018 (0.0023)
0.306
0.151
0.060
0.072
0.059
0.005
(0.021)
(0.012)
(0.0072)
(0.0095)
(0.0054)
(0.00058)
Free-standing vegetation ( g N m)2 year)1)
0
8
16
32
0.23 (0.022)
0.092 (0.019)
0.031 (0.011)
0.010 (0.0030)
0.130
0.056
0.029
0.006
(0.014)
(0.014)
(0.012)
(0.0012)
substantially affect other environmental variables, and they
controlled light heterogeneity independently of average
supply rate of light and soil resources (Stevens 1999). The
size of the sample plots and the scale of the spatial
heterogeneity was proportional to the size of individuals
(Fig. 1), so that many small individuals or a fraction of the
largest clonal individuals could occupy a patch of a given
light availability. Thus, the spatial scale of the heterogeneity
was proportionally similar to most canopy gaps found in
forest and old-fields (Goldberg & Gross 1988; Canham et al.
1990; Kelly & Canham 1992). The spatial patterns of the
spectrum neutral shade cloth (PAK Unlimited, Inc.,
Cornelia, Georgia, USA) mimicked levels of light heterogeneity observed in free-standing vegetation at the same
levels of fertilizer addition (Stevens 1999). Even though the
vast majority of these species spread clonally, we removed
the shade frames at the end of the 1997 growing season to
allow natural colonization by seed. Frames were replaced at
the beginning of the following growing season.
We measured percentage PAR (photosynthetically active
radiation, lmol photons m)2 s)1) at 150 points spread out
at 1 cm intervals along the length of a 30 · 150 cm sample
plot centred under each frame (Fig. 1). We used two
Quantum point sensors (LiCorr, Inc., Lincoln, NE), one
15 cm above the soil surface, the other above the
vegetation, and converted PAR readings to percentage
transmittance by the canopy (percentage PAR transmitted).
We used the mean and standard deviation (Tilman 1982;
p. 103) to quantify average supply rate and heterogeneity of
light in each sample plot. We derived species richness and
relative abundance from estimates of percentage cover of
each species in each sample plot. We recorded all light and
cover data so that, within each 30 · 150 cm sample plot,
three contiguous 30 · 50 cm subplots could be analysed
separately, resulting in 576 subplots used for analyses where
specifically indicated below.
!2002 Blackwell Science Ltd/CNRS
To test the direct effects of light heterogeneity, average
light supply rate, and average supply rate of soil resources,
we regressed ln(species richness) on the ln(SD[percentage PAR]), ln(mean[percentage PAR], and ln(g N m)2 + 2),
each measured directly for each 30 · 150 cm sample plot.
To test whether species were common in low-light plots
because they were regionally common, or because they
preferred low-light conditions, we regressed species’ frequencies of occurrence in low-light plots on (1) species’
frequencies of occurrence in moderate-light plots and
(2) their observed resource ratios in the moderate-light
plots (all variables log transformed). Unlike other measures
of abundance (e.g. density, biomass), each species’ frequency
of occurrence (i.e. the number of plots in which a species is
present/total number of plots) is precisely the contribution
of each species to overall mean species richness, and the
sum of all species frequencies equals mean species richness
(Palmer & van der Maarel 1995; Stevens & Carson 1999a).
We calculated each species’ resource ratio as the mean of
(subplot percentage PAR)/(g N applied m)2 + 2), using
only data from the moderate-light shade frames. Thus, the
resource ratio used for each species in this study should be
considered a ‘‘realized resource ratio’’.
To test the assumption that species had different
resource requirements, we used ECOSIM software (Gotelli
& Entsminger 2001) to test whether mean electivity
overlap was smaller than expected by chance, using the 15
species that occurred in at least 50 of the 576 30 · 50 cm
subplots. Electivity overlap takes resource abundance into
account, and is preferred to niche overlap (cf. Silvertown
et al. 1999) when resources vary in abundance (Lawlor
1980; Gotelli & Graves 1996). This analysis retained each
species’ niche breadth and reshuffled zero abundance
values (randomization algorithm 3, Gotelli & Graves
1996). We calculated the mean percentage PAR transmitted
in each subplot, and pooled each of these means into one
Resource quantity and plant diversity 423
RESULTS AND DISCUSSION
Average supply rate of light, and not light heterogeneity,
governed species richness. The decline in average supply
rate of light caused a substantial decline in plant species
richness that was independent of the effects of soil resource
availability and light heterogeneity (Fig. 2a; partial
R2 ¼ 0.402***). In contrast, the increase in soil resources
(partial R2 ¼ 0.056*) and the decline in light heterogeneity
(partial R2 ¼ 0.004 NS) caused much smaller declines in
richness (Figs 2b.c). The results agree with results obtained
in previous years (Stevens 1999), and they provide no
support for a role of light heterogeneity in influencing
species richness.
Species composition in the species-poor, low-light plots
was best predicted by species’ relative abundances in the
moderate-light plots and not by species’ habitat preferences.
Specifically, species’ frequencies of occurrence in moderatelight plots explained 37% of the variability in species’
frequencies in low-light plots (Fig. 3a), whereas species’
light : nitrogen ratios explained only 6% of the variability
(Fig. 3b). These results favour the energy hypothesis, where
random assembly from the species pool generates local
neighbourhoods, and total density in each local community
determines local species richness (Hurtt & Pacala 1995;
Stevens & Carson 1999a; Hubbell 2001). In addition, most
species occurred most often in similar light : nitrogen
conditions, and this also is consistent with the energy
hypothesis. Specifically, mean pairwise electivity overlap
(similar to niche overlap, Lawlor 1980; Gotelli & Graves
1996) was substantially greater than expected by chance
(observed mean electivity overlap ¼ 0.516, bootstrapped
mean ¼ 0.441, P < 0.001), and this broad overlap was
consistent among several levels of habitat resolution (see
Methods). These findings provide no support for the
assumptions that underlie the heterogeneity hypothesis.
The above support for the energy hypothesis is consistent
with a variety of possible mechanisms. First and foremost,
decreasing understorey light availability generally causes a
large decrease in stem density (Stevens & Carson 1999b),
and consequently richness should decrease by chance alone
(‘‘More Individuals’’ hypothesis, Preston 1962; Rosenzweig
& Abramsky 1993; Srivastava & Lawton 1998). Assuming
that not all species exist in every plot, different species will
disappear from different plots, and many species will ‘‘win
by default’’ because the best low-light specialists are not
present everywhere (Hurtt & Pacala 1995). The effect of
increasing productivity is to exacerbate this ‘‘winning by
default’’, and is not related directly to specialization in any
particular light level. Further, any strict interspecific hierarchy can be weakened by positive indirect effects (Miller
1994), by large within-population variability in resource
requirements (Clements 1929; Linhart & Grant 1996), or by
equally strong intraspecific effects (Brokaw & Busing 2000;
Hubbell 2001).
Our conclusions may apply to other light-limited plant
communities because the plant community used in
this experiment shares many characteristics with other
2
a
2
Partial R = 0.402***
1
0
-4
-3
-2
-1
-1
0
1
2
3
1
2
3
1
2
3
-2
Light
Average
LightQuantity
Supply Rate
Species richness
of seven categories of light levels (0–5%, 5–15%, 15–25%,
25–35%, 35–45%, 45–55%, and > 55%; higher light levels
were exceedingly rare). The seven light categories and
four soil fertility categories resulted in 28 different
resource combinations. Other combinations, including
fewer resource combinations (moderate vs. low light) and
more combinations (10 light levels · 4 soil fertilizer levels)
achieved the same qualitative result.
2
b
1
0
-4
-3
-2
-1
-1
0
Partial R 2 = 0.056***
-2
Fertilizer
c
2
2
Partial R = 0.004*
1
0
-4
-3
-2
-1
-1
0
-2
Light Heterogeneity
Figure 2 Effects of (a) average light supply rate (units ¼ log[mean
PAR]), (b) fertilizer (units ¼ log[g N m)2 + 1]) and (c) light heterogeneity (units ¼ log[SD PAR]) on species richness (log[no. of
spp. 0.45 m)2 + 1]) (multiple R2 ¼ 0.824***; Type III sums of
squares on all factors, *P < 0.05, ***P < 0.001). The above partial
regression plots plotted all variables as residuals of the labelled
variable, given the two factors not shown in the plot (Neter et al.
1996). As a result, these partial regression plots obscure the clustering of light supply rate treatments (low, high) and heterogeneity
treatments (uniform, continuum, gap) that would be apparent in a
simple scatter plot.
!2002 Blackwell Science Ltd/CNRS
Low-Light Frequency of Species i
424 M.H.H. Stevens and W.P. Carson
1.0
a
Partial R 2 = 0.34
Partial R 2 = 0.06
b
0.5
0.0
-0.5
-1.0
-1.0
-0.5
0.0
0.5
1.0
Moderate-Light Freq. of Species i
-1.0
-0.5
0.0
light-limited plant communities. As in virtually all other
communities, the community used here had already
undergone a sorting process, where some potential
community members (e.g. annuals) had been largely
excluded. As in other plant communities (e.g. Bazzaz
1996; Pacala et al. 1996), this community exhibited no
stable equilibrium prior to experimental treatments. As
with species in other communities, the herbaceous species
in this community undoubtedly differed significantly in
many ways (Grime et al. 1988) including physiological
responses to variation in light levels (Latham 1992; Kobe
et al. 1995; Larcher 1995; Kobe 1999). Herbaceous
perennials also commonly exhibit a large degree of
genetic variation within populations (Thomas & Bazzaz
1993; Geber & Dawson 1997) and local adaptation
(Linhart & Grant 1996). Thus it is not clear that the
community used in this experiment differs from other
communities in ways that would prevent generalization
to other communities where light is limiting (Bazzaz
1996).
Lastly, our results and those of other studies along
productivity gradients (Leibold 1996; Bohannan & Lenski
2000) suggest that the average abundance of a single
resource that limits most species in a community also
controls species richness. Favoured explanations for why
species diversity declines with increasing productivity
appear to depend on the system where the pattern occurs
(Waide et al. 1999; Mittelbach et al. 2001). In terrestrial
plant assemblages, increasing soil resource supply rates
increase above-ground biomass, which causes declines in
another key resource, light. In our study, it was the decline
in average light supply rate that drove down species
richness along our soil fertility gradient. In aquatic systems,
increasing the inorganic nutrients increases predation rates,
and this increase in predation can drive down prey species
richness (Leibold 1996; Bohannan & Lenski 2000). If we
envision a set of conditions that reduces the effects of
predation, this set of conditions could constitute a resource
that we call predator-free space (Holt 1977; Jeffries &
!2002 Blackwell Science Ltd/CNRS
0.5
1.0
Resource Ratio of Species i
Figure 3 (a, b)Partial regression plots of
species’ frequencies (log[freq. of sp. i ])
and resource ratios (log[light/g N]) in
(a) moderate-light shade frames as
predictors of species’ frequencies in lowlight shade frames (multiple R2 ¼
0.438***; Type III sums of squares on
both factors, *P < 0.05, ***P < 0.001).
Lawton 1984; Holt & Lawton 1994). One species may be a
superior competitor for predator-free space when it
‘‘consumes’’ this resource by supporting higher predator
abundances than other species, and reduces remaining
predator-free space to such an extent that other species fail
to persist (Holt & Lawton 1994). The decline in species
richness observed along productivity gradients in both
terrestrial and aquatic systems thus results from a decline
in the average supply rate of the most limiting resource,
whether that resource is light or predator-free space. The
symmetry of the effect of predators and competitors on a
population is an old idea (MacArthur 1970), and it now
promises to unify explanations for the loss of diversity
along productivity gradients in different ecological systems.
We suggest that reducing the resource that limits most
species, not the resource most limiting to total ecosystem
productivity, will cause species richness to decrease as well.
We propose that such a relatively simple idea, analogous to
Liebig’s law of the minimum, has been overlooked in
previous explanations for the complexity of ecological
systems.
ACKNOWLEDGEMENTS
We thank A. E. K. Long and other research interns for
technical assistance, and J. Fox, M. Leibold, Z. Long,
T. E. Miller, P. J. Morin, and O. Petchey for comments.
Supported by NSF grant DEB 9903912 to W. P. Carson,
NSF grant DEB 9806427 to P. J. Morin and T. M.
Casey, the New Jersey Agricultural Experiment Station,
University of Pittsburgh, and Pymatuning Laboratory of
Ecology (Pymatuning Laboratory publication number
110).
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Editor, A. Troumbis
Manuscript received 11 December 2001
First decision made 11 January 2002
Manuscript accepted 19 February 2002