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Abstract
Patterns of precipitation are likely to change significantly in the coming century,
which will have consequences for plant communities. Either experimental or correlative
studies may produce predictions for how communities will respond, but little research has
addressed the degree of concordance between these two approaches. Here, we synthesize
results from four experimental studies of water addition with a correlative analysis of
community changes across a large natural gradient in precipitation. We use plant
functional traits as a basis for comparison among studies and sites, and because they
provide a mechanistic basis for understanding community changes.
Experimental results suggested that communities should shift towards species
with smaller seed sizes and higher leaf N concentrations. In contrast, the natural gradient
analysis showed increasing seed size and decreasing leaf N with higher precipitation. We
suggest that this disagreement is due in part to the limited duration and spatial scale of
experimental manipulations, such that there is little opportunity for significant
community turnover to occur. These results suggest that responses in natural
communities to climate change are likely to be complex, and could involve transient
dynamics that do not reflect the long-term shifts in community composition.
Introduction
There is a growing need to predict how plant communities will respond to
changes in climate (Parmesan and Yohe 2003, Hoegh-Guldberg et al. 2008). Species
within a community may respond idiosyncratically to a particular climate change factor,
but classification of plant strategies may help to organize and understand the responses of
species (Fukami et al. 2005). Thus, there has been considerable interest in understanding
the relationships among plant functional traits (Westoby et al. 2002, Wright et al. 2004)
and between these traits and the environment (Wright et al. 2005, Moles et al. 2006).
Should functional traits prove to be generally predictive of response to a particular
climate change factor, couching climate change predictions in terms of shifts in species
trait composition should be more useful and general than presenting them in speciesspecific terms (Westoby and Wright 2006, McGill et al. 2006).
Patterns of precipitation are likely to shift over the next 100 years, which is
expected to have significant impacts on plant community composition (Weltzin et al.
2003, Meehl et al. 2007). Changes in water availability are likely to have different
impacts on different species, which may be predictable by the leaf, seed and growth
characteristics of those species. For example, plants with more conservative growth and
resource use strategies are expected to perform better in dry conditions (Wright et al.
2004, Angert et al. 2007), while seed size is likely to affect both stress tolerance and the
competitive ability of seedlings (Leishman and Westoby 1994, Pakeman et al. 2008).
Predictions of response to climate change may be derived from either
experimental or observational studies, both of which are amenable to a trait-based
approach (Tautenhahn et al. 2008). While both types of study are common, few authors
have asked whether they produce similar predictions. There are reasons to expect that
they may not. Experimental studies are typically limited in scope, both spatially and
temporally. Thus, there is always cause to question the generality and applicability of
experimental results to large-scale questions. Observational studies can often achieve
scales more appropriate to the question, but suffer from a lack of control over covariates.
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Thus, to minimize the weaknesses of each approach, it has been suggested that more
research should explicitly unite observational and experimental work, perhaps by nesting
experiments at multiple sites within a larger observational study (Hewitt et al. 2007).
In this paper, we take such a nested approach. We synthesize the findings of four
experimental precipitation manipulation studies with an analysis of community changes
along the natural gradient of precipitation across the continental United States. We use a
trait-based approach, summarizing community changes as shifts in mean values of leaf
and seed traits. We present the first synthesis of grassland water manipulation
experiments, and one of the few papers to provide a predictive framework by linking the
change in community composition to change in traits. We ask three questions: 1. Which
traits predict a species’ response to experimental water addition? 2. Do experimental
water manipulations show the same changes in traits that are found along a natural
precipitation gradient? 3. How does the duration of the experimental treatment influence
the perception of trait shifts?
Methods
Experimental data
We compiled data from four experimental studies of water addition. These
studies are a subset of those compiled by Cleland et al. (2008) in a dataset originally
intended to synthesize results on nitrogen fertilization experiments. Four of these
experiments also included a water addition treatment. These experimental sites, and the
years for which plant community composition data were available, are the Shortgrass
Steppe LTER (2000), Jasper Ridge (1999-2003), Konza Prairie LTER (1991-2005) and
Sevilleta LTER (2004-2006). All of these studies were conducted in grassland
communities.
For each year of each study, the data set includes plant community composition
data from replicated control and treatment plots. From these data, we calculated the
relative abundance of all species in each experimental plot. We determined the annual
rainfall at each site in each year of the experiments by using publicly available weather
data from stations close to the experimental sites or from the sites themselves, when
available. We also found or calculated, when necessary, the annual amounts of water
added to each treatment site using experimental design information posted on each LTER
website or described in Cleland et al. (2008).
Natural gradient
We used the VegBank database (www.vegbank.org) to investigate changes in
traits along the natural precipitation gradient in the continental United States. We
downloaded data for all 21566 plots which were available on April 20, 2008. Data for
each plot included the location of the plot and the relative abundance of all plant species
in the plot. We then used PRISM climate data (PRISM group, 2008) to obtain a 30-year
average (1971-2000) precipitation value for each of our VegBank plots.
Traits
For each species in the experimental and natural plots, we searched three datasets
for trait values. We used the USDA Plants database (USDA 2008) to determine growth
form, lifespan and native status. Growth form was separated into three categories: woody
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plant, forb and grass. Lifespan was similarly categorized into perennial, biennial and
annual, using a maximum potential criterion. We obtained seed size data by querying the
Kew Gardens Seed Information Database (http://rbgkew.org.uk/data/sid/) for each
species. For species with more than one record, we took the average of all available
records. Finally, we obtained leaf trait data by searching the Glopnet dataset (Wright et
al. 2004). These traits included carbon assimilation and nitrogen per unit mass and area,
as well as leaf mass per area and leaf longevity. All quantitative trait variables were logtransformed prior to analysis.
For each natural or experimental plot, we then calculated mean trait values for
each continuous trait, by taking the abundance-weighed average of the trait value across
all species in that plot for which data were available. In addition, we calculated the
abundance-weighted standard deviation, maximum and minimum for each trait in each
plot. Categorical traits were summarized at the plot level by simply calculating the
percentage of species for which data was available in each category.
Analysis – Experimental results
For each trait, we performed a two-way, mixed model ANOVA on plot-level trait
values for each trait for the third year of data from the experiments. We treated water
addition as a fixed factor and experimental site as a random factor. We limited our
analysis in this portion of our study to just the third year of each experiment in order to
control for differences in length of study, and to resolve problems with highly unequal
numbers of years used in each study. Three of the sites (Sevilleta, Jasper Ridge and
Konza Prairie) had experiments lasting at least three years. In addition, we performed a
repeated-measures ANOVA across all sites and years, again treating site as a random
factor.
For each analysis of a particular trait’s response to experimental watering, we
used only plots which we had trait data for at least 20% of the species present, weighted
by relative abundance.
To examine whether rates of community turnover differed between water addition
and control plots, we calculated a species-time relationship for each plot from each
experiment. We then tested whether the slope of the STR depended on the experimental
treatment, using an ANOVA with STR slope as the dependent variable, treatment as a
fixed factor, and site as a random factor.
Analysis – Natural gradient
Once we had plot-level trait means for each natural plot, we aggregated plots
together at 1 x 1 degree resolution. For each 1 x 1 degree cell, we calculated a trait
average by taking the average trait value for all plots in that cell, weighted by the
coverage of that trait in each plot. We then calculated an average precipitation for each
cell. Finally, we performed a simple linear regression of cell mean trait values on mean
precipitation.
Results
Our complete species lists included a combined 323 species from the
experimental studies, and 7813 species in the natural vegetation plots. For natural
vegetation plots, trait coverage on a per-species basis varied between 3-5% for leaf traits
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(4.5% for Narea), 27% for seed mass, and 65% for lifespan and growth form. We had
greater per-species trait coverage for the experimental species list, with between 10-12%
(11.5% for Narea) coverage for leaf traits, 45% for seed mass and 95% for lifespan and
growth form.
Trait coverage at the plot level (that is, abundance-weighed coverage) was much
more complete. For natural vegetation plots, our mean growth form and lifespan
coverage was 84%, seed mass coverage was 61% and leaf trait coverage ranged from 1825% (24% for Narea). For experimental sites, growth form and lifespan coverage
averaged 96%, seed mass coverage was 79%, and leaf trait coverage was between 1634% (23% for Narea). This difference between plot- and species-levels indicates a strong
tendency for more abundant species to be better represented in trait databases.
Plots with experimental water addition tended to contain plant assemblages with
smaller mean seed mass, though this was not accompanied by changes in either minimum
or maximum seed size. Again standing in contrast to this experimental result, natural
vegetation plots which naturally receive more precipitation have larger seeded species
(Fig. 2). This increase in seed size with increasing precipitation appears to be driven by
an increase in maximum, but not minimum, seed size.
Mean nitrogen per unit leaf area increased under experimental water addition
(Table 1, Fig. 1). This appears to be driven primarily by an increase in the maximum leaf
nitrogen concentration found in a plot. In contrast, leaf nitrogen per unit area decreased
with increasing precipitation along the natural gradient, which was explained by a
decrease in both minimum and maximum leaf nitrogen concentrations found in a plot.
The relative abundance of grasses, forbs and woody species also varied in both
experimental water manipulation studies and along the natural gradient (Fig. 3). In the
experimental studies, grasses tended toward higher relative abundance with watering,
though there was substantial variation between sites and years. Along the natural
gradient, wetter plots saw higher dominance by woody plants, at the expense of both
forbs and grasses.
These overall trends mask considerable year-to-year and between-site variation in
the magnitude and direction of changes in mean trait values under experimental water
addition (through time figures here, if we use them). Though an ANOVA model which
incorporated all years and sites produced similar results to our year-3 analysis, it also
revealed site by treatment interactions in most cases (Table 2).
Overall, there was low concordance between the effects of naturally and
experimentally increased precipitation on community response, as summarized by shifts
in mean trait values and functional composition.
The slopes of species-time relationships did not differ between watered and
control plots (ANOVA, F = 0.232, p = 0.630).
Discussion
Seed size, leaf nitrogen concentration and growth form showed significant shifts
both along the natural precipitation gradient and within experimental manipulations of
water availability. Thus, in addition to being a useful common measure which allows
synthesis of results from multiple studies, species traits also appear to have predictive
power with respect to changes in precipitation.
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However, there was poor agreement between experimental and observational
results about how traits are expected to shift. Our synthesis of results from four
experimental studies suggests that in conditions of increased precipitation, species with
smaller seeds and higher Narea should be favored. In contrast, the analysis of trait
patterns along the natural precipitation gradient suggests precisely the opposite. Thus, we
conclude that these two approaches do not produce similar predictions.
Why do experimental and observational studies yield different predicted
responses to climate change? One possibility is that one of the results is misleading, due
perhaps to experimental artifacts or covarying factors along the natural gradient. On the
other hand, neither result may be misleading. Changes in experimental treatment plots
are expected to mirror changes along the natural gradient because increasing the
precipitation at a site “imports” the climate of a distant location. So, we might expect the
composition of the community at our site to approach that of the distant location.
However, while an experimental treatment may have imported a feature of the distant
climate, it did not also import the accompanying species pool. Thus, the ability of the
community at our experimental sites to respond to increased precipitation may be
restricted by the absence of species with particular traits in the species pool. The rate at
which new species enter the species pool will therefore be critical in determining the
degree of agreement between experimental and observational studies.
Two lines of evidence suggest that turnover in the species pools at the
experiments was low. First, watered plots did not accumulate more species through time
than did control plots. Were significant turnover occurring in manipulated plots, speciestime curves in these plots should have steeper slopes (Adler and Lauenroth 2003). But,
this was not the case. Second, discrepancies between experimental and observational
results did not disappear as the duration of an experiment increased. Rather, shifts
towards smaller seeds with experimental watering actually became more pronounced
with time, while shifts towards higher Narea showed little trend.
Limited temporal and spatial scales in the experimental studies can both
contribute to low turnover in the species pool. The experimental studies considered here
lasted between one and 15 years. Over such a time scale, changes in community mean
trait values might be due primarily to changes in the relative abundance of species
present, with little influence of a changing regional species pool. However, over perhaps
a century, persistent changes in precipitation might allow the colonization of novel
species and the extinction of some species from the regional pool.
Small spatial scales of the experimental studies may also lead to reduced turnover
in the species pool. In a small experimental plot, colonization of species from outside the
plot is likely to maintain species with disfavored trait combinations at higher than
expected abundances (Pulliam 1988, Dias 1996). This will reduce the rate of species loss
from experimental plots, reducing community turnover rates. On the other hand, water
addition plots might be islands of suitable habitat in a sea of unfavorable habitat for some
species. These species are likely to arrive in the plots at a low rate, again reducing
turnover rates.
Mismatches between species pools and low turnover of species in experimentally
treated plots can explain the fact that trait shifts in experimental plots had less extreme
slopes than shifts along the natural gradient. However, these factors do not easily explain
why shifts in experiments were actually in the opposite direction as those along the
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natural gradient. Theoretical work on population dynamics has shown that a population
perturbed from equilibrium may show complex transient dynamics before arriving at a
new equilibrium. Though a perturbation may increase the equilibrium population of a
species, its initial response to it may be to decline.
This is possible if changing biological interactions cause feedbacks that reverse
the initial changes caused by the experimental treatment. For example, in an
experimental study of water addition, species richness increased initially after water
addition. This increase was due in part to an increase in N fixer diversity, which enriched
the soil and led eventually to dominance by a few annual grass species and an overall
decrease in species richness (Suttle et al. 2007).
In the experiments we examined, communities shifted towards smaller seed size
and higher leaf N concentrations. Both of these shifts are towards species with greater
abilities to take advantage of patches of increased resource availability. Species with
smaller seed mass produce more seeds per photosynthetic area, which confers a higher
colonization probability when a high resource patch occurs. High leaf Narea corresponds
with high specific leaf area, both of which allow fast returns on biomass investments,
which is favorable in high resource patches (Westoby 1998). Thus, the changes we
detected in the experimental plots are consistent with expectations following increased
resource availability.
The pattern along the natural gradient is likely to be due to fundamentally
different mechanisms. As water availability increases over large spatial scales, the
average height of species in the regional species pool should increase. As a result, as
precipitation increases, light will tend to become more limiting than water. Under lowlight conditions, large-seeded species with conservative growth strategies are often
favored (Bazzaz 1979, Pakeman et al. 2008). Thus, mismatch between observational and
experimental work may be due to changes in which resources are most limiting, caused
ultimately by feedbacks due to changes in the traits of the regional species pool. This
view is supported by the fact that taller species did become more abundant in water
addition plots through time, suggesting the beginning of a shift in vegetation type.
Differences in Narea between experimental manipulations and the natural
gradient may reflect differences in the degree of N limitation. Water and nitrogen
availability often covary, and increased precipitation may lead to an initial increase in
nitrogen availability, favoring species with higher Narea in experimental manipulations
(refs). However, across natural gradient sites, it is expected to find a shift to more N
limitation at wetter sites, with a shift in limiting resources. If N is very limited, increased
rainfall could favor species with high leaf area (SLA) and low N content.
Conclusion
The experimental results synthesized here are consistent with existing theory
regarding which plant trait states are likely to be beneficial when resources become more
plentiful. Thus, it seems reasonable to conclude that early changes in communities
following increased precipitation are likely to include increased leaf N concentrations and
decreased seed size.
Our analysis of trait shifts along the natural gradient suggests that long-term
responses might overturn these initial changes. We suggest that, given sufficient time,
shifts in community composition are likely to be dominated by trait-filtered immigration
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into the species pool. This immigration will cause further shifts in community traits,
which may or may not match the changes seen initially (fig. 5). Taken together, these
results highlight the benefits of long-term experimental studies, combining experimental
with observational work, and interpreting results of climate change studies with caution.
References
Adler, P.B. and Lauenroth, W.K. 2003. The power of time: spatiotemporal scaling of
species diversity. Ecology Letters 6: 749-756.
Pulliam, H.R. 1988. Sources, sinks, and population regulation. American Naturalist 132:
652-661
Dias, P.C. 1996. Sources and sinks in population biology. Trends in Ecology and
Evolution 11: 326-330.
Westoby, M. 1998. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant and
Soil 199: 213-227.
Bazzaz, F.A. 1979. The physiological ecology of plant succession. Annual Review of
Ecology and Systematics. 10: 351-371.
Adler, P. B., and W. K. Lauenroth. 2003. The power of time: spatiotemporal scaling of
species diversity. Ecology Letters 6:749-756.
Adler, P. B., and J. M. Levine. 2007. Contrasting relationships between precipitation and
species richness in space and time. Oikos 116:221-232.
Adler, P. B., E. P. White, W. K. Lauenroth, D. M. Kaufman, A. Rassweiler, and J. A.
Rusak. 2005. Evidence for a general species-time-area relationship. Ecology 86:20322039.
Chapin, F. S., E. S. Zavaleta, V. T. Eviner, R. L. Naylor, P. M. Vitousek, H. L. Reynolds,
D. U. Hooper, S. Lavorel, O. E. Sala, S. E. Hobbie, M. C. Mack, and S. Diaz. 2000.
Consequences of changing biodiversity. Nature 405:234-242.
Coomes, D. A., and P. J. Grubb. 2003. Colonization, tolerance, competition and seed-size
variation within functional groups. Trends in Ecology & Evolution 18:283-291.
Davis, M. A., J. P. Grime, and K. Thompson. 2000. Fluctuating resources in plant
communities: a general theory of invasibility. J Ecology 88:528-534.
Fukami, T., T. M. Bezemer, S. R. Mortimer, and W. H. van der Putten. 2005. Species
divergence and trait convergence in experimental plant community assembly. Ecology
Letters 8:1283-1290.
7
Lavorel, S., and E. Garnier. 2002. Predicting changes in community composition and
ecosystem functioning from plant traits: revisiting the Holy Grail. Functional Ecology
16:545-556.
McGill, B. J., B. J. Enquist, E. Weiher, and M. Westoby. 2006. Rebuilding community
ecology from functional traits. Trends in Ecology & Evolution 21:178-185.
Meehl, G. A., T. F. Stocker, W. D. Collins, P. Friedlingstein, A. T. Gaye, J. M. Gregory,
A. Kitoh, R. Knutti, J. M. Murphy, A. Noda, S. C. B. Raper, I. G. Watterson, A. J.
Weaver, and Z.-C. Zhao. 2007. Global Climate Projections.in S. Solomon, D. Qin, M.
Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller, editor. Climate
Change 2007: The Physical Science Basis. Contribution of Working Group I to the
Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
Suding, K. N., S. Lavorel, F. S. Chapin, J. H. C. Cornelissen, S. Diaz, E. Garnier, D.
Goldberg, D. U. Hooper, S. T. Jackson, and M. L. Navas. 2008. Scaling environmental
change through the community-level: a trait-based response-and-effect framework for
plants. Global Change Biology 14:1125-1140.
Thuiller, W., S. Lavorel, M. B. Araujo, M. T. Sykes, and I. C. Prentice. 2005. Climate
change threats to plant diversity in Europe. Proceedings of the National Academy of
Sciences of the United States of America 102:8245-8250.
Weltzin, J. F., M. E. Loik, S. Schwinning, D. G. Williams, P. A. Fay, B. M. Haddad, J.
Harte, T. E. Huxman, A. K. Knapp, G. H. Lin, W. T. Pockman, M. R. Shaw, E. E. Small,
M. D. Smith, S. D. Smith, D. T. Tissue, and J. C. Zak. 2003. Assessing the response of
terrestrial ecosystems to potential changes in precipitation. Bioscience 53:941-952.
Westoby, M. 1998. A leaf-height-seed (LHS) plant ecology strategy scheme. Plant and
Soil 199:213-227.
Westoby, M., and I. J. Wright. 2006. Land-plant ecology on the basis of functional traits.
Trends in Ecology & Evolution 21:261-268.
Wright, I. J., P. B. Reich, J. H. C. Cornelissen, D. S. Falster, P. K. Groom, K. Hikosaka,
W. Lee, C. H. Lusk, U. Niinemets, J. Oleksyn, N. Osada, H. Poorter, D. I. Warton, and
M. Westoby. 2005. Modulation of leaf economic traits and trait relationships by climate.
Global Ecology and Biogeography 14:411-421.
8
Wright, I. J., P. B. Reich, and M. Westoby. 2001. Strategy shifts in leaf physiology,
structure and nutrient content between species of high- and low-rainfall and high- and
low-nutrient habitats. Functional Ecology 15:423-434.
Wright, I. J., P. B. Reich, M. Westoby, D. D. Ackerly, Z. Baruch, F. Bongers, J.
Cavender-Bares, T. Chapin, J. H. C. Cornelissen, M. Diemer, J. Flexas, E. Garnier, P. K.
Groom, J. Gulias, K. Hikosaka, B. B. Lamont, T. Lee, W. Lee, C. Lusk, J. J. Midgley, M.
L. Navas, U. Niinemets, J. Oleksyn, N. Osada, H. Poorter, P. Poot, L. Prior, V. I.
Pyankov, C. Roumet, S. C. Thomas, M. G. Tjoelker, E. J. Veneklaas, and R. Villar. 2004.
The worldwide leaf economics spectrum. Nature 428:821-827.
Tautenhahn, S., H. Heilmeiser, L. Gotzenberger, S. Klotz, C. Wirth and I. Kuhn. 2008.
On the biogeography of seed mass in Germany – distribution patterns and environmental
correlates. Ecography 31: 457-468.
Pakeman, R.J., E. Garnier, S. Lavorel, P. Ansquer, H. Castro, P. Cruz, J. Dolezal, O.
Eriksson, H. Freitas, C. Golodets, J. Kigel, M. Kleyer, J. Leps, T. Meier, M.
Papadimitriou, V. Papanastasis, H. Questad, F. Quetier, G. Rusch, M. Sternberg, J.
Theau, A. Thebault and D. Vile. 2008. Impact of abundance weighting on the response of
seed traits to climate and land use. Journal of Ecology 96: 355-366.
Moles et al. 2006 Global patterns in seed size.
PRISM Group, Oregon State University, http://www.prismclimate.org, created 29 May
2008.
Leishman, M.R., Westoby, M. 1994. The role of seed size in seedling establishment in
dry soil conditions - Experimental evidence from semi-arid species. Journal of Ecology
82: 249-258.
Suttle, K.B., Thomsen, M.A., Power, M.E. 2007. Species interactions reverse grassland
response to changing climate. Science 315: 640-642.
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Figure 1
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Figure 2
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Figure 3
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Figure 4
Figure 5
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Table 1: Comparison of experimental and natural gradient results. (A) Results of mixed
model ANOVA, examining the abundance-weighted mean, abundance-weighted standard
deviation, minimum and maximum of plant traits in the third year of three experimental
water addition studies. Shown are the effects of water addition on the trait in question.
(B) Patterns of traits across a natural precipitation gradient. Linear regression indicated
significant effects on mean Narea, mean seed mass and growth form composition.
Changes in seed mass were controlled by changes in maximum, not minimum seed size
found in a plot.
Figure 1. Summary of the response of mean seed size to experimental and natural
variation in precipitation (A). Along the natural gradient (individual plots: small grey
dots, aggregated at 1x1 degree resolution: black circles), wetter plots have higher mean
seed sizes (black regression line). Each line segment shows the mean seed mass for
control (left end) and water addition (right end) plots for a particular site and year.
Control plots at experimental sites were similar to the natural gradient mean for their
precipitation levels. However, water addition plots showed unusually small seed sizes
relative to the natural gradient plots of similar precipitation. In fact, experimental water
addition tended to decrease seed size (negative slopes of line segments), while it
increased with naturally increasing precipitation. Line segments are coded by
experimental site (Konza LTER = blue diamonds, Jasper Ridge = brown squares,
Sevilleta LTER = purple circles, Shortgrass Steppe LTER = red triangles). Slopes of the
line segments were negative for most sites and years, becoming increasingly negative as
the longest-running experiment progressed (B). Slopes of experimental treatment plots
were always less than that of the natural gradient (heavy dotted line).
Figure 2. Summary of the response of mean leaf N concentration to experimental and
natural variation in precipitation (A). Symbols and colors are as in figure 1. Along the
natural gradient, leaf N concentration decreases with increasing precipitation.
Experimental control plots showed unusually low or high Narea, relative to natural
gradient plots of similar precipitation. Experimental water addition tended to cause an
increase in plot-level Narea, with no indication that manipulated plots were converging
towards the natural gradient slope over time (B).
Figure 3. Summary of changes in relative abundance of grass species (A). Symbols and
colors are as in figure 1. Along the natural gradient, increasing precipitation leads to
decreased cover by grasses. Experimental sites had unusually high cover by grasses, and
showed mixed responses to watering. At Konza, grass cover typically decreased with
watering. Jasper Ridge and the Shortgrass Steppe showed only slight changes in grass
cover, while grass became more abundant with watering at Sevilleta (B).
Figure 4: Changes in the relative abundance of “tall” species in experimental treatments.
Watering increased the abundance of tall species, particularly strongly as experiments
progressed.
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Figure 5: Hypothetical changes in community mean trait values in response to a climate
perturbation. Initially (A), a community shows random fluctuation through time around
some equilibrium trait value. A climate perturbation (B) causes shifts in the community,
which are driven primarily by changes in abundance within the fixed local species pool.
Over time (C), immigration into the species pool overwhelms trait shifts caused by
changes in local abundance, causing initial, transient trait shifts to reverse. Rates of
immigration eventually diminish, and the community settles at a new equilibrium (D).
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