Download Species evenness and productivity in experimental plant communities

OIKOS 107: 50 /63, 2004
Species evenness and productivity in experimental plant communities
C. P. H. Mulder, E. Bazeley-White, P. G. Dimitrakopoulos, A. Hector, M. Scherer-Lorenzen and B. Schmid
Mulder, C. P. H., Bazeley-White, E., Dimitrakopoulos, P. G., Hector, A., SchererLorenzen, M. and Schmid, B. 2004. Species evenness and productivity in experimental
plant communities. / Oikos 107: 50 /63.
In nature, plant biomass is not evenly distributed across species, and naturally
uncommon species may differ from common species in the probability of loss from the
community. Understanding relationships between evenness and productivity is
therefore critical to understanding changes in ecosystem functioning as species are
lost from communities. We examined data from a large multi-site grassland experiment
(BIODEPTH) for relationships between evenness of species composition (proportional
abundance of biomass) and total biomass of communities. For plots which started with
the same and even species composition, but which diverged in evenness over time, those
with lower evenness had a significantly greater biomass. The relationship between
evenness and biomass across all plots was also negative. However, for communities
where the most common species represented one of the three largest species in
monoculture at that site (inclusion of a large dominant species), the relationship was
neutral. Path analyses indicated that three paths contributed to this negative
relationship. First, higher species richness decreased evenness, but increased biomass
(primarily through an increase in maximum plant size). Contrary to predictions,
maximum plant size had either no effect on evenness, or a positive effect (in year 3 plots
with a large dominant species), thereby reducing this relationship. In year 2, large
variation among species in plant size (as measured in monoculture) both decreased
evenness and increased biomass, thus increasing the strength of the negative
relationship between evenness and biomass. However, the former effect was only
found in plots with a large dominant species, the latter only in plots without a large
dominant species. When species richness, maximum plant size, and variation in size
were accounted for, in year 2 evenness positively affected biomass in plots that included
a large dominant species. Our results are consistent with the view that naturally
uncommon species may be unaffected by (or even benefit from) the presence of a large
naturally common species, and that uncommon plants may have little ability to increase
productivity in the absence of such a species. We conclude that the observed negative
relationship between evenness and biomass resulted from multiple direct and indirect
effects, the relative strength of which depended in part on the presence of large
dominant species.
C. P. H. Mulder, Dept. of Forest Ecology, Swedish Univ. of Agricultural Sciences, SE90183 Umeå, Sweden. Present address: Inst. of Arctic Biology and Dept of Biology and
Wildlife, Univ. of Alaska Fairbanks, Fairbanks, AK 99775, USA ([email protected]).
/ E. Bazeley-White and A. Hector, NERC Center for Population Biology, Imperial
College London at Silwood Park Campus, Ascot, Berkshire, UK, SL5 7PY. / P. G.
Dimitrakopoulos, Dept of Environmental Studies, Univ. of the Aegean, University Hill,
Mytilene, Lesbos, GR-811 00, Greece. / B. Schmid and AH (present address), Inst. of
Environmental Sciences, Univ. of Zürich, Winterthurerstr. 190, CH-8057 Zürich,
Switzerland. / M. Scherer-Lorenzen, Max-Planck-Institute for Biogeochemistry, P.O.
Box 10 01 64, d-07701 Jena, Germany. Present address: Inst. for Grassland Science,
Swiss Federal Institute of Technology (ETH), Universitätstrasse 2, CH-8, Zürich,
Switzerland.
Accepted 27 February 2004
Copyright # OIKOS 2004
ISSN 0030-1299
50
OIKOS 107:1 (2004)
Over the past decade a large and rapidly growing
number of experimental studies (primarily using plants)
have addressed how species richness affects ecosystem
functioning (recently reviewed by Loreau et al. 2002,
Kinzig et al. 2002). Results of experiments evaluating the
effects of plant species richness on productivity (Naeem
et al. 1996, Tilman et al. 1996, Hector et al. 1999,
Mulder et al. 2001), decomposition (Andrén et al. 1995,
Wardle et al. 1997, Hector et al. 2000), nutrient cycling
(Hooper and Vitousek 1998, Mulder et al. 2002, SchererLorenzen et al. 2003), and stability (Tilman 1996,
Pfisterer and Schmid 2002) have led to a vigorous and
ongoing debate over the relative importance of species
richness, functional groups, individual species effects,
and the mechanisms by which these variables can affect
ecosystem functioning. To date, few studies have investigated the effects on ecosystem functioning of the
second component of diversity: evenness, the relative
contribution of each species to the total biomass or
number of individuals (Wilsey and Potvin 2000, Wilsey
and Polley 2002, Polley et al. 2003). Experiments using
plants usually attempt to create communities in which
number of species differ but for which proportional
abundances of all component species are similar (Tilman
1996, Hooper and Vitousek 1998, Hector et al. 1999,
Mulder et al. 2001). Yet in nature biomass and number
of individuals are almost never evenly distributed
between species (Ugland and Gray 1982, Wilson et al.
1996, Weiher and Keddy 1999). Many different mathematical descriptions have been devised to depict the
relative abundances of coexisting species (MacArthur
1960, Whittaker 1965, Pielou 1975, Gray 1987), but they
all agree in one respect: most communities have a few
very common species and many uncommon and rare
species.
The relationship between evenness and productivity in
natural communities is of interest for both theoretical
and practical reasons. First, one goal of the recent work
on diversity and productivity (or other aspects of
ecosystem functioning) is to be able to predict what
will happen as species disappear from the community.
Yet, a species on the way to extirpation is likely to go
through a low-abundance stage before vanishing altogether, and many changes in natural communities
following disturbance are alterations of relative distribution, not local extirpation (Chapin et al. 2000, Wilsey
and Potvin 2000). Thus, evenness may decline long
before species richness does. Second, the species that
are lost from real communities are not a random sub-set
of all species. The few studies available suggest that they
tend to be species of low relative abundance, both
because such species appear to be inherently vulnerable
(Fischer and Stöcklin 1997, Rooney and Dress 1997,
Duncan and Young 2000, Gonzalez and Chaneton 2002)
and because chance events are likely to have a larger
impact on small populations (MacArthur and Wilson
OIKOS 107:1 (2004)
1967, Pimm et al. 1988, 1995, Hubbell 2001). Understanding the extent to which evenness impacts productivity directly and indirectly will improve our ability to
predict changes in productivity of natural systems
following species loss.
Terminology
Throughout this paper we will refer to a species that has
a large biomass per unit area in monoculture as ‘‘large’’
(regardless of the size of individuals), and one that
contributes a large proportion of the biomass in a
polyculture as ‘‘dominant’’. Conversely, species with
low biomass per unit area in monoculture are ‘‘small’’
while ones with a small proportion of the biomass in
monoculture are ‘‘sub-dominant’’. Species that contribute a large proportion of the biomass in natural
communities will be referred to as ‘‘common’’, and those
that are not common in natural communities (either
because of low frequency or because they represent a
small but persistent component of the vegetation) will be
referred to as ‘‘uncommon’’.
Potential mechanisms affecting relationships
between evenness and biomass
The presence of more species may increase functional
diversity of the community, allowing a more complete
exploitation of available niche space, and thus increasing
resource use and biomass production (niche complementarity; reviewed by Kinzig et al. 2002, Loreau et al.
2002). A greater evenness may be biologically equivalent
to having more species, since a species that is present in
small numbers or has small individuals is unlikely to
contribute much to biomass either directly or through
species interactions (‘‘mass ratio hypothesis’’; Grime
1998). This hypothesis was supported by an experimental study: when communities with the same three species
were compared, those with a greater (experimentally
controlled) evenness were more productive (Wilsey and
Potvin 2000). The authors attributed their results to
greater opportunities for complementary resource use.
However, this study used three species, all of which were
common in nature, and the results may differ for
communities with a greater range of species.
Several mechanisms could result in indirect rather
than direct causal relationships between evenness and
biomass. A negative relationship between evenness and
biomass may result because large species both reduce
evenness and increase productivity (Cotgreave and
Harvey 1994, Drobner et al. 1998, Nijs and Roy 2000).
This may occur even in the absence of biological
interactions, but the effect will be exacerbated if species
that are large in monoculture are also dominant in
polyculture (‘‘sampling mechanism’’ of Aarssen 1997,
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Huston 1997, ‘‘positive selection’’ in Loreau 2000),
thereby reducing evenness even more than expected
based on size in monoculture. Variation in morphology
between species may also affect both productivity and
evenness, but the direction may depend on whether
plants differ primarily in size (e.g. plant height, total leaf
area) or in shape (e.g. height to width ratio of leaves,
taproots vs fibrous roots). Variation in size is likely
correlated with biomass, and should decrease evenness.
If species that differ more in shape also differ more in
their use of resources (greater niche differentiation;
Trenbath 1974, Harper 1977, Ewel 1986), then greater
variation in shape may result in greater evenness (less
asymmetrical interspecific competition) and productivity
(Hooper and Vitousek 1998, Farley and Fitter 1999).
These proposed mechanisms are not mutually exclusive; several may be operating at once, and thus their
relative importance may determine the overall relationship between evenness and biomass. Furthermore, community composition in terms of naturally common
versus uncommon species may affect both evenness
and the extent to which these mechanisms operate,
because common and uncommon species may differ in
their interspecific interactions. Competitive ability includes both the ability of an individual to reduce
resources for others (competitive effect), and the ability
to tolerate a reduction in resources (competitive response; Aarssen 1983, Goldberg and Werner 1983).
Common species are likely to excel at reducing resources,
while uncommon species (sub-dominants) may be better
at tolerating sub-optimal conditions. For example, in an
old-field plant community, the most common species
had the strongest per-gram competitive effect, but there
was no relationship between natural abundance and
survival of neither seedlings nor adults (Howard 2001,
Howard and Goldberg 2001). Furthermore, since an
uncommon species will be involved primarily in interspecific encounters (while common species will compete
primarily with conspecifics), selection for niche differentiation may operate more on rare or inferior competitors than on common superior competitors, thereby
increasing their competitive response (Aarssen 1983).
Thus, two of the factors likely to reduce evenness (the
inclusion of a large species and large variation in plant
size between component species) may have a greater
impact in communities where a large number or proportion of species are naturally common than on those
where most or all species are naturally uncommon.
Testing for effects of evenness in experimental
communities
Observational studies have found negative relationships
between evenness and biomass for a wide range of
vegetation types (Drobner et al. 1998, Weiher and Keddy
52
1999, Laird et al. 2003). Since in observational studies
both evenness and biomass may be affected by other
variables (such as resource availability and species
richness), and cause and effect are difficult to determine,
experimental studies which control for such factors are
called for. However, experimentally evaluating the role of
evenness is more difficult than evaluating effects of
species richness because any experimental manipulation
of evenness is likely to be short-lived, and there is no one
way to alter evenness since multiple combinations of
different relative abundances can give rise to the same
evenness index. In this paper we examine data from a
multi-site, multi-year European experiment (BIODEPTH). The original goal of this project was to test
for relationships between species richness and ecosystem
functioning at eight grassland sites across Europe.
Species were initially planted at similar densities, and
the only variables manipulated were species richness and
number of functional groups (grasses, legumes, nonleguminous forbs). Thus, although we did not experimentally manipulate evenness, environmental variables
such as resource availability were held constant, and
species richness was controlled. Other results from this
data-set have been presented elsewhere; here we examine
relationships between evenness and productivity, and
evaluate the potential for different mechanisms to
explaining the observed relationships.
Methods
Experimental design
The BIODEPTH study consisted of a basic design
repeated across eight sites in Europe (Table 1): one site
each in Sweden, Germany, Switzerland, Ireland, Greece
and Portugal, and two in the UK (Silwood and Sheffield). At each site, experimental communities were sown
with five levels of species richness (Table 1) at a fixed
total seeding rate of 2000 viable seeds m 2. Details for
individual sites can be found in Hector et al. 2000
(Silwood, UK), Scherer-Lorenzen et al. 2003 (Germany),
Troumbis et al. 2000 (Greece), Caldeira et al. 2001
(Portugal), Mulder et al. 2002 (Sweden), and Pfisterer et
al. 2004 (Switzerland). Plot size was 2 /2 m, except in
Sweden (2/5 m) and Switzerland (2 /8 m). Species
composition was maintained through weeding of species
not sown in the plots. All sites were sown in spring 1996
except for Portugal (fall 1996) and Switzerland (spring
1995). Because of the different start dates we will refer to
the year of the local experiment (e.g. ‘‘year 2’’) rather
than the calendar year. Since in the first year most
species were still small and had had little time to interact,
only data from years 2 and 3 were used in these analyses.
Several variables measured at all sites were used.
Biomass calculations were based on live aboveground
biomass from samples that were harvested from a
OIKOS 107:1 (2004)
Table 1. Site characteristics. Values are mean9/SEM for all plots (including monocultures). ‘‘Biomass’’ refers to aboveground
biomass only. N is the total number of plots (monocultures and polycultures). Differences between years: * (P B/0.05), ** (P B/0.01),
***(PB/0.001).
Site, country
N Latitude,
longitude
Species
richness
Shoot biomass
year 2,3 (g m 2)
Total biomass
years 2,3 (g m 2)
% cover
years 2,3
Bayreuth, Germany
Riverstick, Ireland
Silwood, U.K.
Sheffield, U.K.
Lupsingen, Switzerland
Lezirias, Portugal
Umeå, Sweden
Mytilini, Greece
60
70
66
54
64
56
58
52
1,2,4,8,16
1,2,3,4,8
1,2,4,8,11
1,2,4,8,12
1,2,4,8,32
1,2,4,8,14
1,2,4,8,12
1,2,4,8,18
7109/55,
3869/21,
5549/32,
5289/32,
4849/38,
1899/25,
2039/28,
2289/14,
11299/63, 10249/60
NA, 15539/45
18409/96, 19929/115
11749/55, 17459/65***
7519/50, 7879/45
3289/47, 899/14***
4679/46, 5199/53
8139/74, 8629/83
879/1.1, 789/1.7***
94.29/1.3, 98.69/0.6*
94.79/1.6, 92.59/1.9
94.29/1.3, 96.79/0.8*
76.49/2.4, 64.19/2.9***
38.89/4.0, 14.89/2.0***
80.99/2.9, 64.59/4.1***
80.29/2.4, 84.59/2.6
508N,
528N,
518N,
538N,
478N,
398N,
648N,
398N,
128E
088W
018W
018W
088E
098W
208E
278E
0.5 /0.2 m area (0.5 /0.5 m in Ireland) in the center of
each plot. Plants were cut at 5 cm height (in Sweden, an
additional smaller sub-plot was cut to ground level), and
sorted by species. For sites where two harvests per
summer were performed (Germany, Ireland, Switzerland) we used the sum of the two harvests. All plots were
mowed to 5 cm height after each harvest. Cover for the
whole plots was visually estimated. Three additional
plant measurements were obtained at most sites. Canopy
height in each plot was estimated by taking multiple
measurements of the height of the tallest leaf lamina at
random points. Root biomass was obtained by collecting
cores (20 cm deep) at the end of the summer and
washing, drying, and weighing the roots. Fine roots
( B/1 mm) were separated from coarse roots ( /1 mm),
but for the analysis only fine roots were considered.
Light reduction by the canopy was measured by obtaining multiple measurements of photosynthetically active
radiation (PAR) above and below the canopy in each
plot using a ceptometer (Delta-T Sunscan system, DeltaT devices, Cambridge, UK or LI-COR Line Quantum
Sensor, Lincoln, Nebraska, USA), and was expressed as
% PAR below the canopy.
Calculation of normalized biomass and evenness
variables
Evenness calculations were based on aboveground
biomass only, because roots could not be sorted to
species. The root biomass data has some additional
limitations: the 20 cm depth to which root biomass was
estimated is likely to represent a different proportion of
5409/40***
6679/28***
4869/30***
2469/33***
3949/30***
339/5***
1979/27
3949/31
total biomass for different plots and sites, weeds could
not be removed, and root biomass was not available
from all sites in both years. Therefore, all analyses were
performed for both aboveground (shoot) biomass and
for total biomass (roots plus shoots).
Data were combined from all sites to increase the level
of replication. However, there were large differences in
the means and ranges for individual sites, particularly for
biomass (Table 2). To prevent confounding effects of site,
we used the standard normal deviate of all variables
included in the analysis. Thus, normalized biomass
(hereafter ‘‘biomass’’) described the biomass of a plot
relative to that of other plots at the same site and in the
same year:
Normalized biomassplot (xplot xsite )
STDsite
Evenness was not manipulated experimentally. Monocultures were excluded from evenness analyses (since
their evenness is undefined), resulting in a total sample
size of 308 polycultures. We calculated an evenness index
(E) based on Simpson’s dominance index (Simpson
1949), for biomass in years 2 and 3:
X
S
ED=S 1=
P2i =S
i1
where Pi is the proportion of biomass in species i, and S
is the number of species sown in the plot. This index
ranges from 0 (all biomass in one species) to 1 (/1
species present in equal abundance), with lower values
indicating larger differences in abundance between
species. This evenness index was selected because we
Table 2. Characteristics of plots in different groups. N is the number of plots in each group (except for total biomass in year 2, where
N for DOM/ /78, for DOM / /147). Values (mean9/SEM) presented here are raw data; analyses used data normalized for each
site and year. Differences between large- and small-dominant groups within a year: PB/0.05 (*), P B/0.01 (**) or P B/0.001 (***).
Year
Group
N
Shoot biomass
Total biomass
E
MAXPLANT
VSIZE
2
DOM/
DOM /
DOM/
DOM /
111
163
147
140
5269/35***
4309/22
5169/24*
4899/30
10209/66***
9569/55
12779/64
9959/57
0.459/0.02
0.499/0.02
0.459/0.02**
0.549/0.03
655.89/31.2***
491.79/20.4
509.49/24.5**
390.99/26.8
3.279/0.27***
1.569/0.15
2.699/0.21***
1.389/0.15
3
OIKOS 107:1 (2004)
53
were interested in separating direct effects of evenness on
biomass from indirect effects mediated by species richness, and E is mathematically independent of species
richness (Smith and Wilson 1996). An evenness index
normally describes the relative distribution of those
species present, while absent species (including ones
that were recently lost) do not contribute. However, to
calculate E we used the number of species sown as the
denominator, rather than the number of species found in
the sub-sample from which biomass was derived, because it produced a better estimate of evenness at the
whole-plot level. Searches of the whole plot revealed the
continued presence of almost all species (mean % of
sown species persisting /97% in both years) but
biomass sub-samples often lacked species present in
low abundance (% of sown species included in subsamples: 91.2% in year 2, 90.3% in year 3). Thus,
although our values are underestimates of true evenness
for the sub-plot sampled, they more accurately reflect
evenness at the plot level and allow us to compare
evenness values between years.
Analyses
Whole data-set
All analyses were performed using SAS (v. 8; SAS
Institute, Cary, NC, USA). Changes in biomass, evenness, and percent cover between years were tested by
ANOVA (plots blocked by species mixture at each site).
Overall relationships between evenness and biomass
were tested using regression. Since species richness was
manipulated in these experiments, and it may affect both
evenness and biomass, the relationship between evenness
and biomass may be in part the result of the effects of
species richness on both. To test for effects of evenness
given a particular species richness, we also report results
after including species richness in the models. To
examine plots with identical species composition but
which diverged in evenness over time (n/2 for each
mixture), we performed a paired t-test comparing plots
with above-average evenness to those with below-average
evenness. In this test the effect of evenness is not
confounded with differences in species composition.
Comparing dominance groups
To test the effect of the presence of a large dominant
species we split the data-set into two groups. The ‘‘largedominant’’ (DOM/) group consisted of plots for which
the species with the greatest biomass in the plot was also
one of the largest three species in monoculture (at that
site and in that year). The ‘‘small-dominant’’ (DOM /)
group comprised plots for which the dominant species
was not one of the three largest species in monoculture;
this included those with species that were large in
monoculture but not dominant in mixture. We used the
54
top three most common species because most sites had
2 /3 plant species that were clearly dominant (based on
abundance on a linear scale), and because this split
resulted in two groups of similar size and thus similar
power to detect significant relationships in each group.
We predicted that the large-dominant group would have
a greater mean biomass and a lower mean evenness (due
to greater differences in size between species) than the
small-dominant group. Furthermore, we expected a
stronger negative relationship between evenness and
biomass within the DOM/ group than within the
DOM / group, since the presence of a large competitive
species should increase total biomass and negatively
impact the growth of other species through asymmetric
competition, thereby reducing evenness even further.
Again, both results with and without species richness in
the model are reported.
Path analyses
Since all three mechanisms may be operating simultaneously, and many of the variables of interest are
correlated, we examined the direct and indirect effects
of species richness (log2-transformed), evenness (E),
morphological variability (VSIZE, below) and biomass in
monoculture of the largest plant species (MAXPLANT) on
biomass using a path analysis (Wright 1934). Path
analysis allows one to test models of causal relationships
among several independent and dependent variables
from the correlations which exist between variables
(Schemske and Horvitz 1988). Causality is assumed
rather than demonstrated, since additional unmeasured
variables may be the true cause of correlations. The
magnitude of the path coefficient (standardized regression coefficient) indicates the strength of the direct effect
of an independent variable on a dependent variable.
Only plots for which all species were sown in monoculture at the same site were used in path analyses
(n /259). MAXPLANT was defined as the standardized
(for each site) biomass of the largest species in monoculture. If sampling effects and positive selection play a
large role in determining biomass, then MAXPLANT
should have a strong positive effect on biomass. Morphological variability between species was calculated
using monoculture data of aboveground biomass, canopy height, shoot to root biomass ratio, and % light
absorbed by the canopy. We used principal components
analyses (PCA; PROC PRINCOMP) to reduce the
variation in these four variables. Since variables were
measured on different scales and timing of data collection and measurement techniques differed between sites,
variables were standardized to a range between 0 and 1
and a separate PCA was run for each year and each site.
For sites where a variable was missing (root biomass in
year 2 in Ireland, canopy height in Germany) PCA was
run on the remaining variables.
OIKOS 107:1 (2004)
The first axis (PC1) explained between half and twothirds of the variation between species in the component
variables for all sites (year 2 range/46 /69%; year 3
range /42 /73%). PC1 scores reflected overall aboveground size: aboveground biomass, canopy height, shoot
to root ratio, and % light absorbed by the canopy loaded
positively on the first axis (except for canopy cover in
Greece). From this score we generated VSIZE, defined as
variance in PC1 scores among all species in the plot
(‘‘variance in size’’).
The path diagram used is shown in Fig. 1. A positive
direct relationship between evenness (E) and biomass
would lend support to the hypothesis that greater
evenness is equivalent to having a greater number of
species present (Fig. 1 pathway A). Two potential
indirect pathways resulting in a negative relationship
between evenness and biomass are also pictured: greater
maximum plant size (MAXPLANT) resulting in both lower
evenness and greater biomass (pathway B), and greater
variation in plant size (VSIZE) resulting in lower evenness
and greater biomass (pathway C). Path analyses were
run for the entire data-set, and then separately for the
DOM/ and DOM / plots.
Results
Differences between years
Shoot biomass declined significantly between years in
five sites (Germany, Portugal, Switzerland, and both
U.K. sites), was unchanged in two (Greece and Sweden)
and increased significantly in one (Ireland); the pattern
was the same for percent cover (Table 2). Total biomass
declined significantly in Portugal and Sheffield. Mean
evenness (E) scores were 0.4839/0.012 in year 2 and
Fig. 1. The path diagram and associated empirical variables.
Heavy lines indicate causal relationships expected under the
proposed mechanisms presented in the text; solid lines indicate
positive coefficients while dotted lines indicate negative coefficients. Double-headed arrows indicate correlations. Path A
indicates a direct positive relationship, suggesting that greater
evenness (E) is equivalent to a greater number of species present.
Path B indicates that maximum plant size (as measured in
monoculture) results in both increased biomass and decreased
evenness. Path C indicates that increased variance in plant size
(as measured in monoculture) both increases biomass and
decreases evenness. Additional unknown sources of variation
are not shown.
OIKOS 107:1 (2004)
0.4939/0.013 in year 3. For all sites combined this was
not a significant change (F(1,301) /1.55, P /0.21),
although three sites showed a significant mean increase
(Germany: F(1,39) /11.40, P/0.002; Ireland: F(1,48) /
5.33, P /0.025; Sheffield, UK: F(1,29) /14.32,
PB/0.001) and one site showed a significant decrease
between years (Greece: F(1,37) /5.26, P/0.028).
Relationships between evenness and biomass for the
whole data-set
When we compared plots with the same species mixture
within a site (n /2 for each mixture), plots with an
above-average evenness (for that mixture) had a lower
shoot biomass than those with a below-average evenness
(year 2: F(1,298) /9.74, P/0.002; year 3: F(1,301) /3.30,
P/0.070). However, differences in both biomass and
evenness were fairly small (year 2: a 40.7 g m 2 /8.7%
difference in aboveground biomass, and E/0.449/0.02
vs 0.599/0.02; year 3: a 22.13 g m 2 /4.5% difference,
E/0.449/0.02 vs 0.659/0.02). In contrast, total biomass
was significantly higher in the higher-evenness plots
in year 2 (F(1,250) /161.46, PB/0.001; a difference of
297 g m 2 /25.9%) and marginally higher in year 3
(F(1,301) /3.78, P /0.053, a difference of 64 g m 2 /
5.7%).
In both years, there was a negative linear relationship
between evenness and normalized shoot biomass
(F(1,305) /29.35, P B/0.001 in year 2, F(1,301) /35.13,
PB/0.001 for year 3; Fig. 2A, B). Relationships between
total biomass and evenness were also negative (year 2:
F(1,255) /19.69, PB/0.001; year 3: F(1,301) /31.30,
PB/0.001). Plots with a higher species richness (the
variable manipulated in these experiments) had a lower
mean evenness in both years (Fig. 2C, D); when using log
(base 2) of species richness this relationship was very
strong (year 2: R2 /0.51, F(1,305) /327.85, PB/0.001;
year 3: R2 /0.52, F(1,301) /331.12, PB/0.001). Since
plots with higher species richness also had a greater
biomass (year 2: t(304) /4.27, P B/0.001; year 3: t(300) /
5.15, PB/0.001), the negative relationship between evenness and biomass may be caused by the effect of species
richness on both biomass (positive) and evenness
(negative). To examine how evenness affected biomass
for a given number of species, species richness was
included in the model as a categorical variable. For
both years the negative relationship between evenness
and biomass was retained (year 2: F(1,296) /10.79, P/
0.001; year 3: F(1,292) /9.20, P /0.003). When we
included species richness in the analyses using total
biomass, for year 3 the negative relationship was
retained (F(1,292) /7.44, P /0.007) but for year 2 it
was no longer significant (F(1,247) /2.05 P /0.15).
We examined individual sites to ensure there was not
one site driving these negative relationships. When
species richness was not included the direction of the
55
Fig. 2. Relationship between normalized biomass and evenness (E) for all plots with more than one species sown. A value of zero
indicates that only one species remained in the plot. (A) Evenness calculated from biomass proportions in year 2. (B) Evenness
calculated from biomass proportions in year 3.
relationship between evenness and shoot biomass was
negative for all sites but one site (Sweden) in year 2 (and
significantly so for Germany, Portugal, Greece and
Sheffield, UK) and for all sites in year 3 (but significantly so only for Germany and Switzerland). When
species richness was included in the model, the relationship remained significant and negative for Germany and
Greece in year 2, and for Germany and Switzerland in
year 3. For total biomass, all sites but Sheffield showed a
negative relationship in year 2 (significant for Germany,
Portugal, and Silwood, UK) and all sites in year 3
(significant for Germany, Switzerland and Sheffield).
When species richness was included, only Germany in
year 2 and Germany and Sheffield in year 3 still retained
a negative relationship. These data support an overall
negative relationship between evenness and biomass that
is consistent across almost all sites in the study.
Large-dominant vs small-dominant plots
Plots that had one of the three largest species at the site
as the dominant (DOM/ plots) had a significantly higher
mean shoot biomass, maximum biomass and (for year 2)
56
total biomass than those that did not contain one of
these species (DOM / plots, Table 2). However, mean
evenness was lower in DOM/ plots only in year 3, and
the difference was small (approx. 20%; Table 2). Variation in size was greater in the DOM/ plots in both years.
The correlation between dominance groups for the two
years was significant (P /0.005) but low (r /0.17).
Regressing normalized shoot biomass against evenness
produced a marginally significant difference in slope
between the two groups in year 2 (interaction between
dominance type and evenness: F(1,270) /2.78, P/0.09)
and a highly significant difference in year 3 (F(1,282) /
34.33, PB/0.001). When species richness was included in
the model the interaction was significant (P B/0.05) for
both years. For DOM/ plots there was no relationship
between E and biomass (P /0.1 in both years, with and
without species richness in the model; Fig. 3A, B). In
contrast, DOM- plots exhibited a negative linear relationship between E and shoot biomass (P B/0.01 for both
years, both with and without species richness in the
model; Fig. 3C, D). When analyses were repeated using
normalized total biomass, there was no interaction
between evenness and dominance group in year 2
OIKOS 107:1 (2004)
Fig. 3. Relationships between normalized biomass and evenness (E) by dominance group. Dotted lines indicate one standard
deviation above and below the mean for each site. (A) Results for high-dominance plots (those for which the species with the highest
biomass was one of the three largest species in monoculture) in year 2. (B) Results for low-dominance plots (those for which the
species with the highest biomass was not one of the three largest species in monoculture) in year 3. (C) Results for high-dominance
plots in year 3. (D). Results for low-dominance plots in year 3.
(P/0.1 with and without species richness) but a highly
significant interaction in year 3 (P B/0.001 both with and
without species richness). As for shoot biomass, the
relationship between total biomass and evenness was
negative for DOM / plots while there was no effect for
DOM/ plots.
Path analyses
Results of the path analyses for the whole data-set using
shoot biomass are shown in Fig. 4. There was no
evidence for a direct positive effect of evenness on
biomass in either year: the trend is negative in both
years (significant in year 3). Maximum plant size had a
positive effect on biomass in both years, but no effect on
evenness. In year 2 variation in size had a positive effect
on biomass and a negative effect on evenness. Species
richness had a very strong significant direct effect on
evenness, but not on biomass. Results using total
OIKOS 107:1 (2004)
biomass instead of shoot biomass (for standardized
biomass and MAXPLANT) gave almost identical results.
Separate path diagrams (using shoot biomass) constructed for the large-dominant and small-dominant
groups revealed some differences in relationships for
the two groups (Fig. 5). In DOM/ plots, direct effects of
evenness on biomass tended to be positive (significantly
so in year 2), while in DOM / plots they were negative.
Variation in size tended to have a negative effect on
evenness in DOM/ plots, (significantly so in year 2), but
no effect on DOM / plots. Again, using total biomass
instead of shoot biomass revealed no new relationships.
Discussion
Changes over time
Conditions for growth were less favourable overall in
year 3 than in year 2: at most sites biomass and percent
57
Fig. 4. Results of the path analysis for years 2 (A) and 3 (B): all plots. Solid lines indicate positive relationships, dashed lines
indicate negative relationships. Black lines are significant relationships at P B/0.05 (*), P B/0.01 (**) or P B/0.001 (***). Grey lines
indicate non-significant relationships (P/0.05). Values are path coefficients; lines with a path coefficient B/0.1 are not shown.
Model R2 values are indicated for E (evenness) and biomass. Additional unknown sources of variation are not shown.
cover were significantly lower. Plots had been fertilized
in years prior to the start of the experiment but not
during the experiment at some sites, and at all sites most
aboveground biomass was removed by mowing at least
once a year. Thus, nutrient availability is likely to have
declined over time (as it did in Sweden; Mulder et al.
2001, and Germany; Scherer-Lorenzen 1999). Unfavourable weather may also have played a part in Portugal
(cold winter, M. Caldeira, pers. comm.), Sweden (heavy
frost damage, C. Mulder pers. obs.) and Germany (low
precipitation after first cutting, Scherer-Lorenzen 1999).
There was no evidence for a consistent decline in
evenness over time in our plots; at most sites there was
no significant difference between years. This is contrary
to predictions from theory (Nijs and Roy 2000) but
consistent with observations by Wilson et al. (1996) for a
grassland community undergoing succession. However,
it is difficult to compare our results to theory without
knowing to what extent the effects of a decline in
growing conditions may have countered any effects of
successional time.
Relationships between evenness and species richness
Plots with many species had a lower evenness (as
measured by E) than plots with few species. The range
for E was large up to 12 species, but above 12 species
evenness was consistently low ( B/0.4; Fig. 2A). This
pattern is generally similar to that found by Weiher and
Keddy (1999) for herbaceous wetland communities,
where high-species richness plots were limited to very
low evenness values.
58
Evaluation of support for the hypotheses
When we consider the whole data-set, there is little
support for the concept that greater evenness is equivalent to having more species. For plots that were sown
with an identical and even species composition, those
with above-average evenness values had lower biomass
than those with below-average evenness, but the opposite
was true when root biomass was included. Although this
is our best test of the effects of evenness per se (since
results are not confounded by differences in species
richness or other aspects of species composition), the
small range in evenness for plots with the same species
limits its applicability to other situations. Furthermore,
since variation in evenness in these comparisons was the
result of chance events and not experimental manipulation, we cannot be certain that a third factor did not
affect both evenness and biomass. However, the relationship between evenness and shoot biomass or total
biomass across all plots was also negative, whether
examined across or within species richness levels.
We had predicted a stronger negative relationship
between evenness and biomass for DOM/ plots than for
DOM /; instead, plots with large dominant species
showed no overall relationship between evenness and
biomass, while those without large dominant species
showed a negative relationship in both years. This was
not the result of selecting only plots with high biomass
and low evenness (thereby reducing variation in both to
the point where no relationship was evident) since the
variance for the two variables was similar in the two
groups. In the path analysis, plots with at least one
dominant species had a neutral or positive effect of
OIKOS 107:1 (2004)
Fig. 5. Results of the path analysis by dominance group. Solid lines indicate positive relationships, dashed lines indicate negative
relationships. Black lines are significant relationships at P B/0.05 (*), P B/0.01 (**) or P B/0.001 (***). Grey lines indicate nonsignificant relationships (P /0.05). Values are path coefficients. Model R2 values are indicated for E (evenness) and biomass.
Additional unknown sources of variation are not shown.
evenness on biomass, while plots without a dominant
plant species had a negative relationship. Thus, the only
support for the concept that higher evenness directly
increases biomass came from the DOM/ plots in year 2.
We hypothesized that the negative relationships between evenness and biomass found for the whole data-set
could be the result of a large species (particularly if also
dominant) both increasing biomass and reducing evenness (pathway B in the path diagram). Our results
showed that the inclusion of a dominant plant that is
large in monoculture does increase biomass (as indicated
by the higher biomass of the DOM/ plots than the
DOM / plots, and the positive effect of maximum plant
size on biomass in the path analyses). However, there
was little evidence that such large dominant species
reduce evenness: mean evenness for large-dominant plots
was lower only in year 3, and path analyses showed no
significant effect of MAXPLANT on evenness for the
whole data-set, and even a significant positive effect
for large-dominant plots in year 3. The second hypothOIKOS 107:1 (2004)
esis, that high variation in plant size both reduced
evenness and increased biomass, was also not well
supported. Although both effects were found for year 2
overall, the former effect was restricted to the DOM/
group while the latter was found only in the year 2
DOM / group.
In all plots the overall negative correlation between
evenness and biomass was driven at least in part by the
negative effect of species richness on evenness, coupled
with the positive effect of species richness on maximum
plant size, which in turn increases biomass. However, this
does not completely explain the results for any of the
dominance group/ year combinations. In both years 2
and year 3 the overall relationship for DOM/ groups was
neutral, but in year 2 this was due to a positive direct
effect of evenness on biomass (thereby countering the
indirect negative effects), while in year 3 there was a
direct positive effect of maximum plant size on evenness.
In contrast, in the DOM / groups the indirect negative
effects were exacerbated by direct negative effects in both
59
years. These results raise two questions: 1) why are direct
effects of evenness on biomass positive or neutral for
plots for which the dominant species is large, and
negative for plots for which it is not? And 2) why might
maximum plant size increase evenness under some
conditions for plots with a large dominant species?
Aarssen et al. (2003) predicted that species complementarity should result in a neutral or positive relationship
of productivity to evenness. Could there be more species
complementarity in DOM/ plots than in DOM / plots?
By definition, all of the dominant plant species in the
DOM/ plots are large. We had expected a strong
negative relationship between evenness and biomass for
this group: if the large dominant plant was particularly
successful, it should grow fast and suppress all other
species (leading to high biomass and low evenness); if it
was not as successful, evenness should be higher but
biomass lower. Indeed, there are very few plots with a
very high evenness value ( E/0.8), and this accounts for
the slightly lower mean evenness in DOM/ plots
compared to DOM / plots. However, over the rest of
the evenness range (0.1 /0.8) both high- and lowbiomass plots can be found. High biomass can be
achieved in two ways: through dominance by a single
large species (high biomass / low evenness), or through
co-dominance of several large or medium-sized species
that show some niche complementarity or ‘‘ecological
combining ability’’ (Aarssen 1983; high biomass / high
evenness). As illustrated by the examples in Fig. 6 (A,B),
both combinations exist in this group. This makes more
sense if one assumes that the large dominant plants
represent species that are common in nature. Uncommon species may not be negatively affected by the
presence of common species due to little niche overlap
(Aarssen 1983, Smith and Knapp 2003). Furthermore,
large common species may actually provide some
benefits to naturally uncommon species. For example,
smaller plants may suffer increased herbivory when
Fig. 6. Examples of plots illustrating common biomass distribution patterns for high-dominance (DOM/) and low-dominance
(DOM /)groups. Values for biomass are raw values, but determination of ‘‘high’’ or ‘‘low’’ biomass was based on normalized values.
Examples illustrate (A) DOM/ plot with low evenness and high biomass from Sweden (species: Phleum pratense, Trifolium pratense,
Rumex acetosa and Ranunculus acris ); (B) DOM/ plot with high evenness and high biomass from Switzerland (Trifolium repens,
Arrehnatherum elatius, Festuca rubra , Trisetum flavescens ); (C) DOM / plots with low evenness and high biomass from Ireland
(Plantago lanceolata , Trifolium pratense, Lotus pedunculatus, Ranunculus repens ; and (D) a DOM / plot with high evenness and low
biomass from Greece (Phalaris coerulescens, Securigera parviflora , Hirschfeldia incana , Hordeum geniculatum ; authority for all: L.).
60
OIKOS 107:1 (2004)
associative refuges provided by larger plants are removed
(Hay 1986, Mulder and Ruess 1998). Data from
individual BIODEPTH sites also suggested that high
aboveground biomass may facilitate growth of some
species through a variety of mechanisms. Legumes,
which were dominant plants at a number of the sites,
had a positive effect on productivity of other species by
increasing nitrogen availability (Spehn et al. 2000, 2002,
Mulder et al. 2002). Based on d13C values, plants in
mixtures at the Portuguese site suffered less water stress
than those in monocultures, suggesting a positive feedback loop between increased plant growth and increased
water availability (Caldeira et al. 2001). In Sweden the
presence of greater aboveground dead biomass in winter
may have reduced the impact of damaging freeze /thaw
cycles in spring (C. Mulder, pers. obs.). If common
species have positive effects on some uncommon species
(or under some conditions), this should increase both
evenness and biomass. The positive effect of maximum
plant size on evenness in year 3 may represent the result
of beneficial effects of large dominant plants on
uncommon plants under stressful conditions.
The converse may also be true: species that are
naturally uncommon may not show increased growth
in the absence of a common species (MacGillivray et al.
1995, Hooper and Vitousek 1998, Symstad et al. 1998,
Smith and Knapp 2003). This could explain the results
for the DOM / group, where plots with high biomass
( /1 standard deviation above the mean) were clustered
around E/0.2 and E/0.5, while the biomass of high-E
plots was consistently low (particularly in year 3). In
other words, although both high biomass/low evenness
and low biomass/high evenness combinations exist
(Fig. 6C, D), the combination of high biomass and
high evenness is lacking. Uncommon species might be
unable to respond to release from competition by
common plants as the result of physical factors (e.g.
photoinhibition or drought stress; Knapp and Seastadt
1986, Mulder et al. 2001, Caldeira et al. 2001) or
physiological limitations (e.g. low light saturation levels
or low maximum growth rates; Turner and Knapp 1996,
Pavlov et al. 1998, Smith and Knapp 2003). High
evenness, then, is represented by multiple small and
uncommon species.
Comparison with theoretical and previous
experimental results
Do our results differ from those of Wilsey and Potvin
(2000) and Polley et al. (2003), who found, respectively, a
linear positive effect and no effect of evenness on
biomass in their three-species communities? The species
used in their studies were all large common species, so
the best comparison may be with the high-dominance
plots for which we did find a positive effect in year 2, and
OIKOS 107:1 (2004)
no effect in year 3. Furthermore, when root biomass was
included the negative relationships were much less
pronounced (and for plots with the same species
composition plots with higher evenness actually had
higher biomass), consistent with Wilsey and Potvin’s
finding that the positive effect was due to root productivity. Drobner et al. (1998) showed a negative relationship between evenness and photosynthetic biomass
because plots with a high range of biomass values also
had, by definition, low evenness, which is consistent with
our findings that inclusion of a large species increased
biomass while large variation in sizes of species reduced
evenness. Our data did not support the model of Nijs
and Roy (2000), which suggested that the relationship
between evenness and biomass should depend on
whether the dominant species were those with average
productivity (in which case a positive relationship was
expected) or with high productivity (in which case it
should be negative). Our results showed the opposite:
plots with large dominants (DOM/) had a more positive
relationship than those in which average or belowaverage sized plants were dominant (DOM /). However,
their model is a pure competition model: they assumed
that resource acquisition rates and growth rates in
mixtures were a function only of species-specific traits,
while we know from both our results and from previous
studies that large species were not consistently dominant
(Hector et al. 2002) and that interactions between species
play a significant role in affecting biomass (Caldeira et
al. 2001, Hector et al. 2002, Mulder et al. 2002).
Our results are consistent with those of Smith and
Knapp (2003), who removed dominant and sub-ordinate
species from grassland communities. They found that
dominant species could compensate completely (in terms
of biomass) for the removal of sub-ordinate species.
Although they did not calculate evenness values, this
presumably led to a neutral relationship between biomass and evenness. However, the removal of common
species, even up to 50%, did not increase production of
the sub-ordinate species, thereby resulting in a negative
relationship between biomass (highest when there were
lots of dominant individuals) and evenness (highest
when dominants were reduced). Finally, Smith and
Knapp found evidence for complementary interactions
between sub-ordinate species (but not dominant species),
consistent with our finding that for year 2 species in the
DOM / group variation in size had a positive effect on
biomass.
Conclusions
Our data suggest that the relationship between evenness
and biomass is the result of multiple direct and indirect
effects. Although the overall negative relationship was
primarily the result of species richness affecting both
61
evenness (negatively) and biomass (positively), the presence and strength of several other pathways depended
at least in part on the presence of large dominant species.
Experiments in which both evenness and the presence of
large dominant species are manipulated simultaneously
are needed to better understand how these two variables
interact in affecting productivity. Furthermore, greater
consideration of the ecological roles of naturally dominant and sub-dominant species is likely to improve our
understanding of biodiversity /ecosystem functioning
relationships.
Acknowledgements / We would like to thank all BIODEPTH
participants for producing the data-set and allowing us to use it
for this analysis. K. Huss-Danell and L. Aarssen provided
helpful comments on the manuscript. The BIODEPTH project
was supported by the European Commission (ENV-CT95-0008)
and by the Swiss Federal office for Education and Science
(Project EU-1311 to B.S.).
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