Townsend C.R., Begon M., Harper J.L. Essentials of Ecology

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We now take this approach a stage further to focus on systems with at least

three trophic levels (plant–herbivore–predator), and consider not only direct but

also indirect effects that a species may have on others on the same or other trophic

levels. The effects of a predator on individuals or even populations of its herbivorous

prey, for example, are direct and relatively straightforward. But these effects may

also be felt by any plant population on which the herbivore feeds, or by other

predators of the herbivore, or other consumers of the plant, or competitors of the

herbivore, or by the myriad species linked even more remotely in the food web.

9.5.1 Indirect and direct effects

The deliberate removal of a species from a community can be a powerful tool in

unraveling the workings of a food web. We might expect such removal to lead to

an increase in the abundance of a competitor, or, if the species removed is a

predator, to an increase in the abundance of its prey. Sometimes, however, when

a species is removed, a competitor may actually decrease in abundance, and the

removal of a predator can lead to a decrease in a prey population. Such unexpected

effects arise when direct effects are less important than effects that occur through

indirect pathways. For example, removal of a species might increase the density

of one competitor, which in turn causes another competitor to decline.

These indirect effects are brought especially into focus when the initial removal

is carried out for some managerial reason, since the deliberate aim is to solve a

problem, not create further, unexpected problems. For example, there are many

islands on which feral cats have been allowed to escape domestication and now

threaten native prey, especially birds, with extinction. The ‘obvious’ response is

to eliminate the cats (and conserve their island prey), but as a simple model shows

(Figure 9.17), the programs may not have the desired effect, especially where,

as is often the case, rats have also been allowed to colonize the island. The rats

typically both compete with and prey upon the birds. The cats normally prey upon

the rats as well as the birds. Hence, removal of the cats will relieve the pressure

on the rats and is thus likely to increase not decrease the threat to the birds.

For example, introduced cats on Stewart Island, New Zealand preyed upon an

endangered ﬂightless parrot, the kakapo, Strigops habroptilus (Karl & Best, 1982).

But controlling cats alone would have been risky, since their preferred prey are

three species of introduced rats, which, unchecked, could pose far more of a

threat to the kakapo. In fact, Stewart Island’s kakapo population was translocated

to smaller offshore islands where exotic predators (like rats) were absent.

The indirect effect within a food web that has probably received most attention

is the so-called trophic cascade. It occurs when a predator reduces the abundance

of its prey, and this cascades down to the trophic level below, such that the prey’s

own resources (typically plants) increase in abundance. Of course, it need not stop

there. In a food chain with four links, a top predator may reduce the abundance

of an intermediate predator, which may allow the abundance of a herbivore to

increase, leading to a decrease in plant abundance.

One example of a trophic cascade, but also of the complexity of indirect

effects, is provided by a 2-year experiment in which predation by birds was experi-

mentally manipulated in an intertidal community on the northwest coast of

the United States to determine the consequences for three limpet species and

their algal food. Glaucous-winged gulls (Larus glaucescens) and oystercatchers

Chapter 9 From populations to communities

309

food webs – shifting the focus to

systems with at least three

trophic levels

cats, rats and birds

trophic cascades – effects of

shorebirds on limpet populations

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(Haematopus bachmani) were excluded by means of wire cages from large areas

(each 10 m

) in which limpets were common. It became evident that excluding

the birds increased the overall abundance of one of the limpet species, Lottia

digitalis, as might have been expected, but a second limpet species (L. strigatella)

became rarer, and the third, L. pelta, which was the one most frequently con-

sumed by the birds, did not vary in abundance. The reasons are complex and go

well beyond the direct effects of birds eating limpets (Figure 9.18).

L. digitalis, a light-colored limpet, tends to occur on light-colored goose

barnacles (Pollicipes polymerus) where it is camouﬂaged, whereas the dark L. pelta

occurs primarily on dark Californian mussels (Mytilus californianus). Predation

by birds normally reduces the area covered by goose barnacles, and so excluding

the birds increased goose barnacle abundance and also increased the abundance

of L. digitalis (Figure 9.18). Increasing barnacle abundance also led to a decrease

in the area covered by mussels, because they were now subject to more intense

competition from the barnacles. This, one imagines, might have led to a decrease

in the abundance of L. pelta, living predominantly on those mussels. However,

the third limpet species, L. strigatella, is competitively inferior to the others,

and the increase in abundance of L. digitalis therefore led to a decrease in the

abundance of L. strigatella, which in turn released pressure on L. pelta such that

overall its abundance remained effectively unchanged.

But the effects of bird predation also cascade down to the plant trophic level,

because by consuming limpets, the birds normally reduce the grazing pressure

of the limpets on ﬂeshy algae, and by consuming goose barnacles, the birds

Part III Individuals, Populations, Communities and Ecosystems

310

(a)

Prey

MesopredatorSuperpredator

(b)

Reproduction

Predation

Time Time

Population size

Figure 9.17

(a) Schematic representation of a model of an interaction in which

a superpredator (such as a cat) preys both on mesopredators

(such as rats, for which it shows a preference) and on prey

(such as birds), while the mesopredator also attacks the prey.

Each species also recruits to its own population, ‘reproduction’.

(b) The output of the model with realistic values for rates of

predation and reproduction: with all three species present, the

superpredator keeps the mesopredator in check and all three

species coexist (left); but in the absence of the superpredator,

the mesopredator drives the prey to extinction (right).

AFTER COURCHAMP ET AL., 1999

9781405156585_4_009.qxd 11/5/07 14:56 Page 310

normally free up space for algal colonization. Hence, when the birds were

excluded, algal cover decreased (Figure 9.18).

In a four-trophic-level system, if it is subject to trophic cascade, we might

expect that as the abundance of a top carnivore increases, the abundances of

primary carnivores in the trophic level below decrease, those of the herbivores

therefore increase, and plant abundance decreases. This is what was found in a

study, in the tropical lowland forests of Costa Rica, of Tarsobaenus beetles preying

on Pheidole ants that prey on a variety of herbivores that attack ant-plants, Piper

cenocladum (Figure 9.19a). These showed precisely the alternation of abundances

expected in a four-trophic-level cascade: relatively high abundances of plants and

ants associated with low levels of herbivory and beetle abundance at three sites,

but low abundances of plants and ants associated with high levels of herbivory and

beetle abundance at a fourth (Figure 9.19b). Moreover, when beetle abundance

was manipulated experimentally at one of the sites, ant and plant abundance were

signiﬁcantly higher, and levels of herbivory lower, in the absence of beetles than

in their presence (Figure 9.19c).

However, in another four-trophic-level community, in the Bahamas, consist-

ing of sea grape shrubs, which were fed upon by herbivorous arthropods, and

then web spiders (primary carnivores) and lizards (top carnivores), the results of

Chapter 9 From populations to communities

311

AFTER WOOTTON, 1992

200

400

L. digitalis

Birds present Birds excluded

L. pelta L. strigatella L. digitalis L. pelta L. strigatella

Number of limpets (m

–2

)

Barnacles Mussels Barnacles Mussels

Percentage cover

Fleshy al

al species

Percentage cover

Figure 9.18

When birds are excluded from the intertidal community, barnacles

increase in abundance at the expense of mussels, and three limpet

species show marked changes in density, reﬂecting changes in

the availability of cryptic habitat and competitive interactions

as well as the easing of direct predation. Algal cover is much

reduced in the absence of effects of birds on intertidal animals

(means and standard errors are shown).

four trophic levels...

. . . that can act like three

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Part III Individuals, Populations, Communities and Ecosystems

312

(a)

Herbivores

Ants/herbivory (%)

(c)

Abundance/herbivory

1000

Site

(b)

Leaf areaHerbivoryAnts4321

100

Tarsobaenus

beetles

Pheidole ants

Piper cenocladum

trees

Leaf area (cm

per 10 leaves)

experimental manipulations indicated a strong direct effect of the lizards on the

herbivores but a weaker effect of the lizards on the spiders. Consequently, the net

effect of top predators on plants was positive and there was less leaf damage in

the presence of lizards. In essence, this four-trophic-level community functions as

if it has only three levels.

We have seen that trophic cascades are normally viewed ‘from the top’, starting

at the highest trophic level. So, in a three-trophic-level community, we think of

the predators controlling the abundance of the herbivores and exerting top-down

control. Reciprocally, the predators are subject to bottom-up control: abundance

determined by their resources. The plants are also subject to bottom-up control,

having been released from top-down control by the effects of the predators on

the herbivores. Thus, in a trophic cascade, top-down and bottom-up controls

alternate as we move from one trophic level to the next.

But suppose instead that we start at the other end of the food chain, and assume

that the plants are controlled bottom-up by competition for their resources. It is still

possible for the herbivores to be limited by competition for plants – their resources

– and for the predators to be limited by competition for herbivores. In this scenario,

all trophic levels are subject to bottom-up control, because the resource controls

the abundance of the consumer but the consumer does not control the abundance

of the resource. The question therefore arises: ‘Are food webs – or are particular

types of food web – dominated by either top-down or bottom-up control?’

The widespread importance of top-down control, foreshadowing the idea

of the trophic cascade, was ﬁrst advocated in a famous paper by Hairston et al.

(1960), which asked ‘Why is the world green?’ They answered, in effect, that the

world is green because top-down control predominates: green plant biomass

accumulates because predators keep herbivores in check.

Murdoch (1966), in particular, challenged these ideas. His view, described by

Pimm (1991) as ‘the world is prickly and tastes bad’, emphasized that even if the

world is green (assuming it is), it does not necessarily follow that the herbivores

are failing to capitalize on this because they are limited, top down, by their predators.

Figure 9.19

(a) Schematic representation of a four-level food chain in Costa Rica. Green arrows denote mortality and maroon arrows a contribution to the

consumer’s biomass; arrow breadth denotes their relative importance. Both (b) and (c) show evidence of a trophic cascade ﬂowing down from the

beetles: positive correlations between beetles and herbivores and between ants and trees. (b) At four sites, the relative abundance of ant-plants

(blue bars), the abundance of beetles (maroon bars) and of ants (green bars) and the strength of herbivory (yellow bars) are shown. Means and

standard errors are shown; the units of measurement are various and are given in the original references. (c) The results of an experiment at site 4

when replicate enclosures were established without beetles (maroon bars) and with beetles (green bars).

AFTER LETOURNEAU & DYER, 1998A, 1998B; PACE ET AL., 1999

top-down or bottom-up control

of food webs?

why is the world green?...

. . . or is it prickly and bad

tasting?

9781405156585_4_009.qxd 11/5/07 14:56 Page 312

Many plants have evolved physical and chemical defenses that make life difﬁcult

for herbivores. The herbivores may therefore be competing ﬁercely for a limited

amount of palatable and unprotected plant material; and their predators may, in

turn, compete for scarce herbivores. A world controlled from the bottom up may

still be green.

That very little is required to switch control from one type to the other is

emphasized by a study that examined the effect of nutrient concentrations on

a freshwater web comprising an insect predator (Physella gyrina) feeding on two

species of herbivorous snails feeding on water plants and algae (Figure 9.20).

At the lowest nutrient concentrations, the snails were dominated by the smaller

P. gyrina (they were vulnerable to predation), and the predator gave rise to a trophic

cascade extending to the plants and algae. But at the highest nutrient concentrations,

the snails were dominated by the larger Helisoma trivolvis (they were relatively

invulnerable to predation), and no trophic cascade was apparent. This study,

therefore, also lends support to Murdoch’s proposition that ‘the world tastes bad’,

in that invulnerable herbivores gave rise to a web with a relative dominance of

bottom-up control. Overall, though, the elucidation of clear patterns in the pre-

dominance of top-down or bottom-up control remains a challenge for the future.

9.5.2 Population and community stability and

food web structure

Of all the imaginable food webs in nature, are there particular types that we tend

to observe repeatedly? Are some food web structures more stable than others?

(We discuss what stable means in Box 9.5.) Do we observe particular types of

Chapter 9 From populations to communities

313

(a) Low nutrients

High nutrients

Low

High

(b) Low nutrients

High nutrients

Initial snail density and predator treatments

Snail biomass (g tank

–1

)Snail biomass (g tank

–1

)

Plant biomass (g tank

–1

)Plant biomass (g tank

–1

)

Low +

pred

High +

pred

Low High

Low +

pred

High +

pred

Helisoma

Physella

Macrophytes

Algae

Figure 9.20

Top-down control, but only with low

productivity. (a) Snail biomass and

(b) plant biomass in experimental

ponds with low or high nutrient

treatments (vertical bars are standard

errors). With low nutrients, the snails

were dominated by the insect

predator Physella (vulnerable to

predation) and the addition of

predators led to a signiﬁcant decline

(indicated by *) in snail biomass

and a consequent increase in plant

biomass (dominated by algae).

But with high nutrients, Helisoma

snails (less vulnerable to predation)

increased their relative abundance,

and the addition of predators led

neither to a decline in snail biomass

nor an increase in plant biomass

(often dominated by macrophytes).

AFTER CHASE, 2003

9781405156585_4_009.qxd 11/5/07 14:56 Page 313

food web because they are stable (and hence persist)? Are populations themselves

more stable when embedded in some types of food web than in others? These are

important practical questions. We require answers if we are to determine whether

some communities are more fragile (and more in need of conservation) than

others; or whether there are certain ‘natural’ structures that we should aim for

when we construct communities ourselves; or whether communities that have

been restored are likely to stay ‘restored’.

‘Stability’, of course, means stability in the face of a disturbance or perturbation,

and most disturbances are, in practice, the loss of one or more populations from

a community. What are the knock-on effects of such a loss? How profound are the

consequences of the loss of that population for the rest of the community? Some

species are more intimately and tightly woven into the fabric of a food web than

others. A species whose removal would produce a signiﬁcant effect (extinction

or a large change in density) in at least one other species may be thought of as a

strong interactor. The removal of some strong interactors leads to signiﬁcant

changes spreading throughout the food web – we refer to these as keystone species.

Part III Individuals, Populations, Communities and Ecosystems

314

9.5 QUANTITATIVE ASPECTS

9.5 Quantitative aspects

Among several, there are two important qualiﬁcations

that can be made when we come to decide what we

mean by stability. The ﬁrst is the distinction between

the resilience of a community and its resistance.

A resilient community is one that returns rapidly to

something like its former structure after that struc-

ture has been altered. A resistant community is one

that undergoes relatively little change in its structure

in the face of a disturbance.

The second distinction is between fragile and

robust stability. A community has only fragile stability

if it remains essentially unchanged in the face of a

small disturbance but alters utterly when subjected

to a larger disturbance, whereas one that stays

roughly the same in the face of much larger disturb-

ances is said to have stability that is dynamically

robust.

To illustrate these distinctions by analogy, consider

the following:

a pool or billiard ball balanced carefully on the

end of a cue

the same ball resting on the table

the ball sitting snugly in its pocket

The ball on the cue is stable in the narrow sense that

it will stay there forever as long as it is not disturbed

– but its stability is fragile, and both its resistance

and its resilience are low: the slightest touch will send

the ball to the ground, far from its former state (low

resistance), and it has not the slightest tendency to

return to its former position (low resilience).

The same ball resting on the table has a similar

resilience: it has no tendency to return to exactly its

former state (assuming the table is level), but its

resistance is far higher: pushing or hitting it moves it

relatively little. And its stability is also relatively robust:

it remains ‘a ball on the table’ in the face of all sorts

and all strengths of assault with the cue.

The ball in the pocket, ﬁnally, is not only resistant

but resilient too – it moves little and then returns – and

its stability is highly robust: it will remain where it is in

the face of almost everything other than a hand that

carefully plucks it away.

What do we mean by ‘stability’?

keystones in food web

architecture

9781405156585_4_009.qxd 11/5/07 14:56 Page 314

In building construction, a keystone is the wedge-shaped block at the highest point

of an arch that locks the other pieces together. The removal of the keystone species,

just like removal of the keystone in an arch, leads to collapse of the structure: it

leads to extinction or large changes in abundance of several species, producing a

community with a very different species composition. A more precise deﬁnition of

a keystone species is one whose impact is ‘disproportionately large relative to its

abundance’ (Power et al., 1996). This has the advantage of excluding from keystone

status what would otherwise be rather trivial examples, especially species at lower

trophic levels that may provide the resource on which a whole myriad of other

species depend – for example, a coral, or the oak trees in an oak woodland.

Although the term was originally applied only to predators, it is now widely

accepted that keystone species can occur at any trophic level. For example, lesser

snow geese (Chen caerulescens caerulescens) are herbivores that breed in large

colonies in coastal marshes along the west coast of Hudson Bay in Canada. At their

nesting sites in spring, before growth of above-ground foliage begins, adult geese

grub for the roots and rhizomes of plants in dry areas and eat the swollen bases

of shoots of sedges in wet areas. Their activity creates bare areas (1–5 m

) of peat

and sediment. Few pioneer plant species are able to recolonize these patches, and

recovery is very slow. Furthermore, in areas of intense summer grazing, ‘lawns’

of Carex and Puccinellia spp. have become established. Here, therefore, high

densities of grazing geese are essential to maintain the species composition of

the vegetation and its above-ground production (Kerbes et al., 1990). The lesser

snow goose is a keystone species – the whole structure and composition of these

communities are drastically altered by its presence.

For a long time, the conventional wisdom, arrived at largely through ‘logical’

argument, was that increased complexity within a community leads to increased

stability (MacArthur, 1955; Elton, 1958); that is, more complex communities are

more stable in the face of a disturbance such as the loss of one or more species. For

example, it was argued that in more complex communities, with more species and

more interactions, there were more possible pathways by which energy passed

through the community. Hence, if there was a perturbation to the community (a

change in the density of one of the species), this would affect only a small proportion

of the energy pathways and would have relatively little effect on the densities of

other species: the complex community would be resistant to change (Box 9.5).

However, as analyses of mathematical models of food webs have become more

sophisticated, the conventional wisdom has by no means always received support

(May, 1981; Tilman, 1999), and conclusions differ depending on whether we focus

on individual populations within a community or on aggregate properties of the

community such as their biomass or productivity. Brieﬂy, the model food webs have

been characterized by one or more of the following: (i) the number of species they

contain; (ii) the connectance of the web (the fraction of all possible pairs of species

that interact directly with one another); and (iii) the average interaction strength

between pairs of species. At the level of the individual population, models have not

always come to the same conclusion, but overall they suggest that increases in the

number of species, increases in connectance and increases in average interaction

strength – each representing an increase in complexity – all tend to decrease the

tendency of individual populations within the community to return to their former

state following a disturbance (their resilience, e.g. Figure 9.21). Thus these models

suggest, if anything, that community complexity leads to population instability.

Chapter 9 From populations to communities

315

a long-standing belief that

complexity leads to stability...

. . . that is not supported by

mathematical models for

individual populations

9781405156585_4_009.qxd 11/5/07 14:56 Page 315

Part III Individuals, Populations, Communities and Ecosystems

316

155

2.0

1.5

1.0

0.5

Species richness

Population

Community

Coefficient of variation

Figure 9.21

The effect of species richness (number of

species) on the temporal variability (coefﬁcient

of variation, CV) of population size and

aggregate community abundance in model

communities in which all species are equally

abundant and have the same CV. Thus, high

values for CV equate to low levels of stability.

AFTER COTTINGHAM ET AL., 2001

0.8

0.4

0.8

25050

25 400 80 12030

200406080

(a) (b)

0.2

0.6

0.4

0.2

0.6

0.4

0.2

0.3

0.2

0.1

Species richness (S)

Connectance (C)

Figure 9.22

The relationships between

connectance and species richness.

(a) A compilation from the literature

of 40 food webs from terrestrial,

freshwater and marine environments.

(b) A compilation of 95 insect-

dominated webs from various

habitats. (c) Seasonal versions of a

food web for a large pond in northern

England, varying in species richness

from 12 to 32. (d) Food webs from

swamps and streams in Costa Rica

and Venezuela.

(a) AFTER BRIAND, 1983; (b) FROM SCHOENLY ET AL.,

1991; (c) FROM WARREN, 1989; (d) FROM WINEMILLER,

1990; AFTER HALL & RAFFAELLI, 1993

However, the effects of complexity, especially species richness, on the stability

of aggregate properties of model communities have been more consistent. Broadly,

in richer communities, the dynamics of these aggregate properties are more stable

(Figure 9.22). In large part, this is because, as long as the ﬂuctuations in different

populations are not perfectly correlated, there is an inevitable ‘statistical averaging’

effect when populations are added together – when one goes up, another is going

down – and this tends to increase in effectiveness as richness (the number of

populations) increases. Certainly, models indicate that there is no necessary,

unavoidable connection linking stability to complexity.

What is the evidence from real communities? Various studies have sought to

build on the mathematical models by examining the relationships among number of

species, connectance and interaction strength. The argument runs as follows. The

only communities we can observe are those that are stable enough to exist. Hence,

those with more species can only be sufﬁciently stable if there are compensatory

decreases in connectance and/or interaction strength. But data on interaction

strengths for whole communities are unavailable, so we assume, for simplicity, that

average interaction strength is constant. Thus, communities with more species will

only retain stability if there is an associated reduction in average connectance.

but aggregate properties are

more stable in richer model

communities

complexity and stability in

practice: populations

9781405156585_4_009.qxd 11/5/07 14:56 Page 316

Early analyses of published food web data found, as predicted, that con-

nectance decreased with species number (Figure 9.22a). These data, however,

were not collected for the purpose of quantitative study of food web properties.

In particular, the accuracy of identiﬁcation varied substantially from web to web,

and even in the same web components were sometimes grouped at the level of

kingdom (e.g. ‘plants’), sometimes as a family (e.g. Diptera) and sometimes as a

species (polar bear) (see review by Hall & Raffaelli, 1993). More recent studies,

in which food webs were more rigorously documented, indicate that connectance

may decrease with species number (as predicted) (Figure 9.22b), or may be inde-

pendent of species number (Figure 9.22c), or may even increase with species

number (Figure 9.22d). Thus, the stability argument does not receive consistent

support from food web analyses either.

The prediction that populations in richer communities are less stable when

disturbed was also investigated by Tilman (1996), who pooled data for 39

common plant species from 207 grassland plots in Cedar Creek Natural History

Area, Minnesota, collected over an 11-year period. He found that variation in

the biomass of individual species increased signiﬁcantly, but only very weakly,

with the richness of the plots (Figure 9.23a). Thus, like the theoretical studies,

empirical studies hint at decreased population stability (increased variability) in

more complex communities, but the effect seems to be weak and inconsistent.

Chapter 9 From populations to communities

317

(b)

024681012 024681012

2 4 6 8 10 12 14 16 40 8 12 16 20

Species richness

(a)

0 5 10 15 20

100

150

200

250

CV for species biomass

r = 0.15**

Avera

e species richness

Field A

r = –0.39**

Field B

r = –0.32*

Field C

r = –0.09(NS)

Field D

r = –0.53***

Figure 9.23

(a) The coefﬁcient of variation (CV) of population biomass for 39

plant species from plots in four ﬁelds in Minnesota over 11 years

(1984–1994) plotted against species richness in the plots.

Variation increased with richness but the slope was very shallow.

(b) The CV for community biomass in each plot plotted against

species richness for each of the four ﬁelds (A–D). Variation

consistently decreased with richness. In both cases, regression

lines and correlation coefﬁcients are shown (*, P < 0.05; **,

P < 0.01; ***, P < 0.001).

AFTER TILMAN, 1996

9781405156585_4_009.qxd 11/5/07 14:56 Page 317

Turning to the aggregate, whole-community level, evidence is largely consist-

ent in supporting the prediction that increased richness in a community increases

stability (decreases variability). For example, in Tilman’s (1996) Minnesota grass-

lands study, in contrast to the weak negative effect found at the population level,

there was a strong positive effect of richness on the stability of community bio-

mass (Figure 9.23b). Also, McGrady-Steed et al. (1997) manipulated richness in

aquatic microbial communities (producers, herbivores, bacterivores, predators)

and found that variation in another community measure, carbon dioxide ﬂux (a

measure of community respiration), also declined with richness (Figure 9.24).

On the other hand, in an experimental study of small grassland communities

perturbed by an induced drought, Wardle et al. (2000) found detailed community

composition to be a far better predictor of stability than overall richness. Indeed,

it is clear that the whole concept of a keystone species (see above) is itself a

recognition of the fact that the effects of a disturbance on structure or function

are likely to depend very much on the precise nature of the disturbance – that is,

on which species are lost. Reinforcement of this idea is provided by a simulation

study carried out by Dunne et al. (2002), in which they took 16 published food

webs and subjected them to the sequential removal of species. Secondary extinc-

tions followed most rapidly when the most connected species were removed, and

least rapidly when the least connected were removed, with random removals

lying between the two (Figure 9.25). This reminds us that the idiosyncrasies of

individual webs are likely always to undermine the generality of any ‘rules’ even

if such rules can be agreed on.

In fact, even if complexity and instability are connected in models, this does not

necessarily mean that we should expect to see an association between complexity

and instability in real communities. Unstable communities will fail to persist when

they experience environmental conditions that reveal their instability. But the range

and predictability of environmental conditions will vary from place to place. In a

stable and predictable environment, a community that is dynamically fragile may

nevertheless persist. But in a variable and unpredictable environment, only a com-

munity that is dynamically robust will be able to persist. Hence, we might expect

to see: (i) complex and fragile communities in stable and predictable environments,

with simple and robust communities in variable and unpredictable environments; but

(ii) approximately the same observed stability (in terms of population ﬂuctuations,

Part III Individuals, Populations, Communities and Ecosystems

318

1200

Species richness

1000

800

600

400

200

0 1510 20

Standard deviation of CO

flux (µl 18 h

–1

)

= 0.74

Figure 9.24

Variation (i.e. ‘instability’) in

productivity (standard deviation of

carbon dioxide ﬂux) declined with

species richness in microbial

communities observed over a

6-week period.

AFTER MCGRADY-STEED ET AL., 1997

complexity and stability in

practice: whole communities

importance of the nature of the

community: keystones again

environmental predictability

linked to community fragility?

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