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We now realize that the world’s flora and
fauna are disappearing at rates greater
than the mass extinction events whose
collapses punctuate the fossil record1–3. It
is also true that species invasions have
been elevated to unprecedented rates accompanying the
increased globalization of our world4,5. These high rates of
extinction and invasion put ecosystems under enormous
stress, making it critical that we understand how the loss,
or addition, of a species influences the stability and
function of the ecosystems we rely on. We are, in a very
real sense, deconstructing the Earth under the implicit
assumption that ecosystems have evolved the ability to
withstand such assault without collapse.
Several advances in the diversity–stability debate form a
conceptual thread that suggests that diversity can be expect-
ed, on average, to give rise to ecosystem stability. This does
not infer that diversity is the driver of this relationship.
Instead, diversity can be regarded as the passive recipient of
important ecological mechanisms that are inherent in
ecosystems. One promising mechanism that has been pro-
posed recently is that weakly interacting species stabilize
community dynamics by dampening strong, potentially
destabilizing consumer–resource interactions6. Empirical
descriptions of the distribution of interaction strengths
in real communities are consistent with this theory. If this
is true then, all else being equal, decreasing biodiversity will
be accompanied by increases in average interaction
strengths within ecosystems, and a concomitant decrease in
ecosystem stability.
Historical perspectives of the diversity–stability debate
The relationship between diversity and stability has fasci-
nated ecologists. Before the 1970s, ecologists believed that
more diverse communities enhanced ecosystem stability7–9.
A strong proponent of this view was Charles Elton8, who
argued that “simple communities were more easily upset
than that of richer ones; that is, more subject to destructive
oscillations in populations, and more vulnerable to
invasions”. In fact, both Odum7and Elton8arrived at similar
conclusions based on the repeated observation that greatly
simplified terrestrial communities are characterized by
more violent fluctuations in population density than
diverse terrestrial communities. For example, invasions
most frequently occur on cultivated land where human
influence had produced greatly simplified ecological
communities, and outbreaks of phytophagous insects occur
readily in boreal forests but are unheard of in diverse
tropical forests. These observations led Elton8to believe that
complex communities, constructed from many predators
and parasites, prevented populations from undergoing
explosive growth. His ideas were closely akin to MacArthur9,
who reasoned that multiplicity in the number of prey and
predator species associated with a population freed that
population from dramatic changes in abundance when one
of the prey or predator species declined in density.
These early intuitive ideas were challenged by the work of
Robert May10 in 1973. May turned to mathematics to rigor-
ously explore the diversity–stability relationship. By using
linear stability analysis on models constructed from a statis-
tical universe (that is, randomly constructed communities
with randomly assigned interaction strengths), May found
that diversity tends to destabilize community dynamics.
Other ecologists, using similar approaches, found results
that were consistent with this hypothesis11,12. The results
were puzzling, as real ecosystems were undoubtedly
complex and diverse. The results also seemed to counter the
ideas of Elton7, Odum8and MacArthur9. Yodzis13 height-
ened this paradox by showing that models structured from
compiled food-web relationships, with plausible interac-
tion strengths, were generally more stable than randomly
constructed food webs. Although the early food-web data
that Yodzis structured his models around were incomplete,
these data reflected real feeding relationships. Yodzis’ result
indicated that interaction strength was probably crucial to
stability; but the exact reason for this remained elusive. If
diversity and stability were positively correlated, as early
empirical evidence had indicated, then more had to be
happening than simply increasing the number of species
and the number of pathways. Something fundamental was
missing from the early arguments.
In the remainder of this paper I review recent investiga-
tions of the diversity–stability debate. I first discuss a change
in perspective that is beginning to allow us to unravel this
long-standing problem and then review two different lines
of investigation. One approach has searched for a general
diversity–stability relationship, and a second, more mecha-
nistic approach has sought a relationship between food-web
structure and stability.
Changing perspectives
Much of ecological theory is based on the underlying assump-
tion of equilibrium population dynamics. Although this
assumption is aesthetically pleasing, in that it suggests the
balance of nature is infinitely precise, an alternative and viable
ecological perspective exists. As real populations are variable,
it is possible that the persistence of complex communities
depends to some degree on population fluxes (that is, the
The diversity–stability debate
Kevin Shear McCann
1205 Docteur Penfield Avenue, Department of Biology, McGill University, Montreal, Quebec, Canada H3A 1B1
There exists little doubt that the Earth’s biodiversity is declining. The Nature Conservancy, for example, has
documented that one-third of the plant and animal species in the United States are now at risk of extinction.
The problem is a monumental one, and forces us to consider in depth how we expect ecosystems, which
ultimately are our life-support systems, to respond to reductions in diversity. This issue — commonly
referred to as the diversity–stability debate — is the subject of this review, which synthesizes historical
ideas with recent advances. Both theory and empirical evidence agree that we should expect declines in
diversity to accelerate the simplification of ecological communities.
© 2000 Macmillan Magazines Ltd
fairly regular waxing and waning of a population’s density). Such back-
ground population variability, whether driven by biotic or abiotic
processes, can provide species with the opportunity to respond differ-
entially to their environment. In turn, these differential species
responses weaken the destructive potential of competitive exclusion.
Because such variability can significantly change our understand-
ing of ecological interactions6,14–19, ecologists have begun to relax
equilibrium-based measures of stability. A recent theoretical
analysis17 has shown that population fluctuations, driven by compe-
tition, can actually promote the persistence of large numbers of
competing phytoplankton communities on a minimal number of
limiting resources (but greater than two resources). Coexistence was
found to rely on the fluctuation in population densities, while
community-level densities (the summation of the competing plank-
ton densities) varied little. We will see that a similar relationship
appears in diversity–stability experiments. Here, too, the evidence
points to variable population densities that sum to produce a
relatively constant biomass at the community level.
Definitions of stability
Definitions of stability in ecology can be classified generally into two
categories (Table 1) — stability definitions that are based on a sys-
tem’s dynamic stability, and stability definitions that are based on a
system’s ability to defy change (resilience and resistance in Table 1).
Despite the breadth of definitions, ecological theory has tended
traditionally to rely on the assumption that a system is stable if, and
only if, it is governed by stable equilibrium dynamics (that is, equilib-
rium stability and equilibrium resilience). As discussed in the
previous section, these are strong assumptions with no a priori
justification. In fact, the variable nature of population dynamics
found both in field and in laboratory experiments has led experimen-
talists to use measures of variability as indices of a system’s stability.
This discontinuity between stability experiments and equilibrium-
based theory has made it difficult to unite theory and experiment in
the diversity–stability debate.
More general definitions of stability exist. In Table 1, general
stability is defined such that stability increases as population
densities move further away from extremely low or high densities.
This is a broad definition, including equilibrium and non-
equilibrium dynamics as well as subsuming the definition of
permanence18 (a population is considered permanent if the lower
limit to its density is greater than zero). Because the definition of gen-
eral stability implies decreased variability (owing to greater limits on
density), it is closely related to field measurements of stability, which
tend to rely on variability in population or community densities as a
measure of stability. One can also extend equilibrium resilience to a
less biologically restrictive form by defining resilience as the return
time after a perturbation to an equilibrium or a non-equilibrium
attractor (Table 1). In a nonlinear system there is no reason to believe
that an equilibrium that attracts weakly in a local setting (near the
equilibrium) also attracts weakly far away from the equilibrium,
where the issue of a species’ permanence is resolved18. For the remain-
der of the paper, unless stated otherwise, the definitions of general
stability and variability will be used to consider empirical and
theoretical results on the relationship between diversity and stability
under a common framework.
The search for a general diversity–stability relationship
In 1982, David Tilman began a long-term study to delineate experi-
mentally the relationship between diversity and stability in plant
communities. The undertaking involved four grassland fields at
Cedar Creek Natural History Area, Minnesota, divided into over 200
experimental plots, and gathered information on species richness,
community biomass and population biomass through time. The
results of this and other extensive studies converge on the finding that
diversity within an ecosystem tends to be correlated positively with
plant community stability (that is, decreased coefficient of variability
in community biomass)20–23. At the same time, diversity seems to
show little influence on population variability22. The basic arguments
for a positive relationship between diversity and stability for primary
producers at the community level have been classified into two, not
mutually exclusive, hypotheses called the averaging effect24 and the
negative covariance effect25 (see Table 2 for the underlying logic
behind these ideas). In essence, these hypotheses argue that diversity
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Figure 1 The Ecotron experiment creates model multitrophic community assemblages
containing plants, herbivores, parasitoids and decomposers in 16 different chambers.
The Ecotron is an ambitious attempt to bridge the scale between field communities and
laboratory experiments. (Photographs show the inside of an Ecotron chamber and a technical
service corridor between two banks of chambers; courtesy of the Centre for Population
Biology, Imperial College at Silwood Park.)
© 2000 Macmillan Magazines Ltd
(species richness) increases stability at the community level because
diverse plant communities respond differentially to variable back-
ground processes. The differential responses of populations sum,
through time, to give stable community dynamics.
If diversity and stability are positively correlated, then both the aver-
aging and negative covariance effect predict that population variance
has to scale as a function of mean population densities in a precise way
(see Table 2). Tilman20 has used these predictions to show that his field
experiments are consistent with the interpretation that increasing
diversity increases community stability. Although this is a clever
combination of theory and experiment, it cannot be used to infer that
diversity is responsible directly for stability26,27. As a counter example,
no correlation was found between diversity and stability at the cross-
ecosystem scale26. Other experiments have found that the positive
diversity–stability correlation is not a pure species effect (that is, a
diversity effect), and have indicated that ecosystem function and stabil-
ity are more directly related to functional diversity (for example,
graminoids or grasses, nitrogen-fixing legumes and other herbs)27–30.
In a similar manner, plant community stability and productivity
in European grasslands were shown to be tightly coupled to the
functional diversity of mutualistic arbuscular mycorrhizal fungi
(AMF)31. In this system, large fluctuations in plant biomass were
associated with low diversities of AMF, whereas more constant
biomass and greater productivity accompanied high AMF
diversities. This study highlights that higher-level interactions,
which are inherent in food webs (for example, microbial interac-
tions, herbivory and predation), are of great importance in
understanding the relationship between the diversity and stability of
whole ecological communities. The complexity of whole ecological
communities — the basis from which Odum, Elton and MacArthur
formed their diversity–stability hypotheses — cannot manifest itself
in experiments that focus on single trophic levels.
Field tests at the scale of the food web are few in number. But one
thorough examination32 tested seven different stability–diversity
criteria in the grazing ecosystem of the Serengeti under naturally
variable conditions (that is, strong seasonal changes). Of these seven
stability measures, five were positively related to diversity whereas
two were unrelated to diversity. The study found that greater diversity
reduced the relative magnitudes of fluctuations in productivity
induced by seasonal change. Although a relationship between
stability and diversity exists within the Serengeti, the evidence again
points to the importance of functional species in understanding this
relationship. For example, the grazing-tolerant plant species have a
disproportionately large role in the Serengeti community dynamics
by preventing herbivores from dramatically reducing plant biomass.
The paucity of field tests at the scale of the food web reflects the
fact that such experiments require an enormous undertaking. As an
alternative, ecologists have approached this problem by investigating
how diversity influences stability and function within a multitrophic
setting in controlled microcosm experiments (often referred to as
bottle experiments as they are attempts to create realistic ecological
communities within a controlled setting). The main advantage of
microcosms is that the experiments can easily be manipulated and
replicated33. Nonetheless, the issue of how scale influences outcome
looms over microcosm experiments — can we extrapolate results to
the whole ecosystem? Ambitious experimental set ups such as that
currently underway in the Ecotron (Fig. 1) are attempting to bridge
the gap between the complexity of real field communities and the
simplicity of laboratory or greenhouse experiments.
The evidence that has emerged from microcosm experiments,
regardless of scale and system type (that is, terrestrial or aquatic), has
tended to agree that diversity is positively related to ecosystem stabili-
ty34–39. In addition, and consistent with field experiments on plant
communities, experiments using aquatic microcosms have shown
that population-level variation is relatively uninfluenced by diversity,
whereas community-level variance tends to decrease with increased
diversity35. Two ideas have been advanced in explanation of these
findings. One explanation is that increasing diversity increases the
odds that at least some species will respond differentially to variable
conditions and perturbations37–39. The second is that greater diversity
increases the odds that an ecosystem has functional redundancy by
containing species that are capable of functionally replacing impor-
tant species37–39. Taken together, these two notions have been called
the insurance hypothesis (Table 2). This idea has been extended to
suggest that the greater the variance in species’ responses contained
in a community then the lower the species richness required to insure
the ecosystem40. As with the averaging and negative covariance effect,
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Table 1 Definitions of stability
Term Definition
Definitions of dynamic stability
Equilibrium stability A discrete measure that considers a system stable if it returns to
its equilibrium after a small perturbation away from the
equilibrium. A stable system, therefore, has no variability in the
absence of perturbations.
General stability A measure which assumes that stability increases as the lower
limit of population density moves further away from zero. Under
non-equilibrium dynamics, such limits to population dynamics
generally imply a decrease in population variance (see variability
definition below).
Variability The variance in population densities over time, usually measured
as the coefficient in variation. Common in experimental tests of
stability.
Definitions of resilience and resistance stability
Equilibrium resilience A measure of stability that assumes system stability increases as
time required to return to equilibrium decreases after a
perturbation. A rapid response means that a system recoils
rapidly back to its equilibrium state.
General resilience A measure of stability that assumes system stability increases as
return time to the equilibrium/non-equilibrium solution decreases
after a perturbation. A rapid response means that a system
recoils rapidly back to its equilibrium/non-equilibrium state.
Resistance A measure of the degree to which a variable changes after a
perturbation. Frequently used as a discrete measure that
assesses a community’s ability to resist invasion (that is, if an
invader fails, the community resists invasion).
Table 2 General diversity–stability theory
Theory Underlying logic
Averaging effect24,25 Assume covariances between species are zero and variance (si
2) in abundance of individual species iin a plant community is equal to cmi
z,where cand
zare constants and miis the mean density of species i. Given that all kspecies of a community are equal in abundance and sum to m (that is, mi= m/k),
then the coefficient of variation (CV) of community abundance can be determined as:
CV = 100s/m= 100(c/k)1/z
For the case z> 1, increasing k(species number) decreases the variation in biomass for the plant community.
Negative-covariance effect25 If covariances between species (say, species a and b) are negative (that is, cov(a,b) < 0), then the variance in the abundance of two species
s2
(a+b) = sa
2+ sb
2+ 2cov(a,b)
will be less then the sum of the individual variances (that is, sa
2+ sb
2), and so will decrease overall biomass variance in the plant community.
Insurance effect37–40 An ecosystem’s ability to buffer perturbations, loss in species and species invasions is dependent on the redundancy of the species having important
stabilizing roles, as well as on the ability of the species in the community to respond differentially to perturbations. Increasing diversity increases the
odds that such species exist in an ecosystem. This idea has been extended40 to suggest that the greater the variance of species’ responses in a
community then the lower the species richness required to buffer an ecosystem.
© 2000 Macmillan Magazines Ltd
which are intimately related, the insurance hypothesis does not infer
that diversity actively promotes stability.
In summary, the results indicate that within an ecosystem, diver-
sity tends to be correlated positively with ecosystem stability. This
correlation does not necessarily extend to population-level stability.
Much work is still required to determine the driver of the positive
diversity–stability relationship; however, it seems that community-
level stability is dependent on the differential response of species or
functional groups to variable conditions, as well as the functional
redundancy of species that have important stabilizing roles. I now
turn to a separate approach that has not focused on diversity, but has
concentrated instead on understanding the implications of common
food-web structures on stability.
Food-web structure and stability
In an important theoretical contribution, Chesson and Huntley41
showed that diversity cannot be maintained by variation alone. Rather,
maintenance of diversity requires the two following components: the
existence of flux or variability in ecosystems; and populations capable of
differentially exploiting this flux or variability. Regardless of the source
of the variability (for example, whether spatially or temporally generat-
ed), their results indicate that coexistence requires that populations
must be released, either directly or indirectly, from the limiting
influences of species interactions such as predation and competition.
Species interactions, therefore, must be important in maintaining and
promoting persistence in diverse communities in spite of, and perhaps
because of, the variability that underlies ecosystems. Several more
specific models can be included under this general framework, and all
reveal that flux interacting with specific biotic, nonlinear responses can
promote persistence6,14,17. We now turn to a set of food-web models that
have shown how persistent, complex ecosystems can be an outcome of
this combination of flux and density-dependent food-web interactions
(that is, competitive and predatory influences that vary with density).
The weak-interaction effect
Over the past decade, ecologists have begun to replace the conceptu-
alization of the ecosystem as a linear food chain with the view that
food webs are highly interconnected assemblages42–45 characterized
by recurrent food-web structures (for example, omnivory and
apparent competition). Because combinations of competition and
predation can represent these common food-web structures, the use
of simple food-web modules has been advocated46 to explore the
repercussions of these ubiquitous species interactions.
Several model investigations have grown out of this approach
to show that natural food-web structures can, indeed, enhance
ecosystem stability6,47–49. These food-web models are extensions of a
bioenergetic consumer–resource model50that constrains parameters
to empirically determined relationships of body size. The approach is
akin to the dynamic modelling of a population’s energy budgets
through time, and has the important consequence of placing
food-web models within a biological universe with reasonable con-
straints operating on energy flow between any consumer–resource
interaction — a feature that is considerably different from a statistical
universe. The result is that increasing diversity can increase food-web
stability under one condition: the distribution of
consumer–resource interaction strengths must be skewed towards
weak interaction strengths. I will refer to this as the weak-interaction
effect (Table 3), and to connect this to general diversity–stability
theory I briefly discuss the stabilizing mechanisms behind this effect.
Two general stabilizing mechanisms underlie the weak-interac-
tion effect. First, the weak-interaction effect generates negative
covariances and promotes community-level stability. Second, these
negative covariances ensure that the weak interactors dampen the
destabilizing potential of strong consumer–resource interactions.
These mechanisms can be best understood with a simple example.
Figure 2a depicts a simple food-web interaction in which a strong
consumer–resource interaction (C–R1) is coupled to a weak
consumer–resource interaction (C–R2). Being a weakly interacting
species, R2is an inferior competitor whose ability to persist is mediat-
ed by the top predator. This food-web relationship ensures that the
resources negatively covary. For example, R2is released from compet-
itive limitation to flourish whenever R1is suppressed by high
densities of consumer C. This occurs because R2is weakly coupled to
C and so is not strongly influenced by high densities of C. In this man-
ner, the weak interaction drives the differential responses of species.
We can use the knowledge of this negative covariance to deter-
mine qualitatively the consumption rate of C on its preferred
resource, R1. Figure 2b depicts C’s consumption rate on R1under two
different densities of R2, assuming an optimally foraging, type II
multispecies functional response (for full details, see refs 49, 51).
High densities of R2reduce the overall consumption rates on R1.
Because the resources negatively covary, then for low densities of R1
we expect C’s consumption rates to fall on the R2-high curve in Fig. 2
(the lower dashed circle). Similarly, for high densities of R1we expect
consumption rates to be on the R2-low curve in Fig. 2 (the upper
dashed circle). Piecing these functions together we see that the asyn-
chrony in resource densities drives a sigmoid-shaped response that is
qualitatively similar to what ecologists refer to as a type III functional
response. This has the non-equilibrium effect of releasing the prey
(R1) from strong consumptive pressures when it is at low densities,
and thereby the weak interaction dampens the oscillatory potential
of the strong C–R1interaction. Consistent with the above discussion
is the fact that investigators have found that donor control (in which a
consumer responds numerically to a resource but has no influence on
resource dynamics) also promotes community stability45,48. Donor
control can generate differential responses of species by allowing
species using these resources to disconnect themselves from fluxes
that are inherent to the community.
I have discussed the weak-interaction effect within the context of
relatively simple food-web modules. Does the effect operate for real,
complex communities with enormous numbers of direct and
indirect interactions? It is still too early to tell, but Kokkoris et al.52
followed the distribution of interaction strengths as competitive
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a
b
C
R1
R1
R2
Consumption
rate of C
R2-low
R2-high
Figure 2 Consumer–resource interactions. a, A simple food-web diagram depicting a
strong consumer–resource interaction (C–R1) coupled to a weak consumer–resource
interaction (C–R2). b, Consumption rates by consumer C of R1for two different densities
of R2. Because the resources negatively covary, the actual consumption response is
qualitatively similar to a combination of these two curves (dashed circles and line). In
the presence of R2, resource R1is less influenced by consumption when at low
densities.
© 2000 Macmillan Magazines Ltd
model communities were assembled. They found that as the
assembly process progressed, larger permanent communities (that
is, with a lower limit above zero) attained lower mean interaction
strengths. They also found that communities with lower mean inter-
action strength were more resistant to invasion. These results are
encouraging and indicate that the weak-interaction effect might
scale to the whole ecosystem. If the weak-interaction mechanism is
operating in real communities then the distributions of interaction
strengths will be skewed towards weak interactions in order that a few
potentially excitable consumer–resource interactions are muted. I
now turn to empirical investigations of food-web structure and
stability, first reviewing experiments concerned with the distribution
of interaction strengths in natural communities before examining
experiments that have investigated directly the influence of food-web
structure on stability.
Interaction strength and species invasions
Although quantitative field estimates of interaction strength are still
in the process of development, work by a few ecologists has enabled a
preliminary glimpse into the nature of the distributions of interac-
tion strength within real food webs53–57. The early data indicate
unequivocally that distributions of interaction strength are strongly
skewed towards weak interactions53–57. Nonetheless, these experi-
ments also highlight that the removal or addition of a single key
species can have pronounced impacts on the dynamics and
persistence of the species in the enclosure or exclosure. For example,
experimental removal of the predatory starfish, Pisaster ochraceus,
resulted in greatly simplified lower-intertidal communities because
the mussel, Mytilus californianus, competitively dominates all other
sessile benthic organisms when freed from predation58.
A recent experiment59 has confirmed the abundance of weak inter-
actions in ecosystems, but showed that weak average interaction
strength in a rocky intertidal community tends to be correlated with
high variability in interaction strength. In this study, variation in the
magnitude of the weak interactions seemed to excite spatial variation
in community structure. The variation in interaction strength may be
important in generating landscape-scale variation that promotes the
maintenance of diversity, an area that demands further investigation.
It is important to know if these phenomena can be extended
beyond the scale of the enclosure/exclosure experiment. Species
invasions may be seen as the uncontrolled version of species addition
experiments. Similar to the experiments described above, the current
evidence indicates that, although most species invasions have a weak
impact on ecosystems60, the occasional invasive species alters an
ecosystem profoundly61–63. For example, a recent study61 used stable
isotopes to document energy flow through food webs. Lakes that
were uninvaded by bass were compared with lakes that had just been
invaded, and the recently invaded lakes showed marked differences in
energy flow patterns (implying a severely altered food-web structure)
as well as rapid declines in forage fish diversity61. These results
indicate that the addition of a single species can precipitate a form of
ecosystem collapse that sends a wave of extinction through the
ecosystem. Another noteworthy case concerns the introduction of
the large predatory fish, the Nile perch (Lates niloticus), in Lake
Victoria in the 1950s. The addition of the Nile perch was followed by a
sequence of amazing ecological and genetic changes that culminated
in a cascade of cichlid extinctions63. Overall, however, the invasion
literature is harmonious with enclosure/exclosure experiments60 —
most invasions have a weak impact with infrequent occurrences of an
invasive species capable of precipitating monumental changes to an
ecosystem.
Food-web structure and stability experiments
Some direct experimental tests of stability and food-web structure
exist. In a clever experimental manipulation, Fagan64 tested commu-
nity response to a perturbation (aphicide application) as a function
of the degree of omnivory. Fagan accomplished this by controlling
the relative proportion of nonomnivorous damselbugs versus
omnivorous wolf spiders in arthropod assemblages of the Mount
Saint Helen ‘blowdown zone’. The results showed that increasing the
degree of community omnivory (that is, increasing the proportion of
wolf spiders) decreased variation in the population responses after an
aphicide application.
In an earlier investigation, de Ruiter et al.65 investigated model
communities constructed from empirical estimates based on some
well-studied food webs from native and agricultural soils. Their
results are consistent with the experiments on interaction strength
and the weak-interaction effect discussed above, as most interactions
had only a negligible impact on community dynamics. Although
their results indicate that energetics are important in constraining
interaction strength, they found no positive correlation between
feeding rates and community impact. This, too, is consistent with the
weak-interaction effect. Similarly, experiments on both terrestrial
and aquatic microcosms have tended to find that increasing the num-
ber of prey items enhances stability66–68, although one microcosm
experiment69 found that the addition of an alternate prey destabilized
community dynamics. This last case can be reconciled with other
experiments as the alternate prey introduced was efficient fare for the
predator. In essence, the alternative prey energetically fuelled the
predator, and so the experiment may be viewed as evidence that a
strong consumer–resource interaction is potentially destabilizing.
Conclusion
Taken together, recent advances indicate that diversity can be expected,
on average, to give rise to ecosystem stability. The evidence also
indicates that diversity is not the driver of this relationship; rather,
ecosystem stability depends on the ability for communities to contain
species, or functional groups, that are capable of differential response .
All of these views are consistent with the ideas put forth by the influen-
tial figures of Odum7, Elton8, MacArthur9and May10. May’s result
reflects the fact that random distributions (that is, a null universe where
dynamics are influenced by diversity alone), on average, do not create
the necessary tension between community members that forces differ-
ential response and community stability. In a randomly constructed
community, for example, strong interactions are not necessarily
coupled to weak interactions that mute their destabilizing potential. In
fact, one can expect that random communities will generally not create
such couplings, and so tend to produce diverse communities with
complex, wildly oscillatory dynamics. Furthermore, Odum, Elton and
MacArthur recognized that real food webs contain a complex array of
energetic pathways that can act as buffers against dramatic population
explosions. Specifically, MacArthur’s hypothesis — that greater
connectance drives community and ecosystem stability — seems a
strong possibility provided most pathways are constructed from weak
interactions that mute the potentially destabilizing roles of a few strong
consumer–resource interactions.
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Table 3 Food-web structure and stability theory
Theory Underlying logic
Weak-interaction effect6,46–48 Weak interactions serve to limit energy flow in a
potentially strong consumer–resource interaction and,
therefore, to inhibit runaway consumption that
destabilizes the dynamics of food webs. In addition, the
weak interactions serve to generate negative covariances
between resources that enable a stabilizing effect at
the population and community level. The negative
covariances ensure that consumers have weak
consumptive influences on a resource when the
resource is at low densities. See text and Fig. 2 for
further clarification.
Berlow57 suggested an additional influence of weak
interactions. Weak interactions in intertidal communities
seem to be extremely variable in strength, and as a
result may drive spatial variability in community
structure. This community variability in space can
provide a canvas for species to respond differentially,
and so may further promote the maintenance of
diversity.
© 2000 Macmillan Magazines Ltd
The current empirical evidence indicates that communities may
be dominated by such weak trophic interactions. If this is true, then it
is also true that the removal, or addition, of any species (weak or
strong) can lead to pronounced changes in community composition
and structure. It follows that decreasing biodiversity will tend to
increase the overall mean interaction strength, on average, and thus
increase the probability that ecosystems undergo destabilizing
dynamics and collapses. Just how much ecosystem deterioration is
sufficient to precipitate a collapse is difficult to assess, but current
experiments and theory agree that drastic community changes can
accompany the removal or addition of even a single species. Further-
more, if Elton’s observation is correct — that simplified communities
are more vulnerable to invasion — than we should also expect an
increase in frequency of successful invaders as well as an increase in
their impact as our ecosystems become simplified. The lessons for
conservation are obvious: (1) if we wish to preserve an ecosystem and
its component species then we are best to proceed as if each species is
sacred; and (2) species removals (that is, extinction) or species
additions (that is, invasions) can, and eventually will, invoke major
shifts in community structure and dynamics.
It is important to point out that the mechanistic ideas outlined
here omit higher-scale ecosystem influences that are likely to be
linked intricately to ecosystem stability and function70–73. Some
promising work is now beginning to show us how we can link models
of nutrient and energy flow70–72 as well as uncover the potential
influence of diversity and stability on large-scale biogeochemical
processes73. Investigations of this sort will be necessary to bridge
important stabilizing processes that act across ecological scales. ■■
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Acknowledgements
This paper benefited from comments by D. Raffaelli. I also thank J. Rasmussen and P.
Yodzis for conversations on this issue, and D. Kramer for providing a single comment that
led me to a different viewpoint.
insight review articles
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