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

Подождите немного. Документ загружается.

7.4.1 Foraging behavior

There are many questions we might ask about the behavior of a foraging predator.

Where, within the habitat available to it, does it concentrate its foraging? How

long does it tend to remain in one location before moving on to another? And

so on. Ecologists address all such questions from two points of view. The ﬁrst is

from the viewpoint of the consequences of the behavior for the dynamics of

predator and prey populations. We turn to this in Section 7.5.

The second is the viewpoint of ‘behavioral ecology’ or ‘optimal foraging’. The

aim is to seek to understand why particular patterns of foraging behavior have

been favored by natural selection. Most readers will be familiar with the general

approach as applied, for example, to the anatomy of the bird’s wing – we may

seek to understand why a particular surface area, or a particular arrangement

of feathers, has been favored by natural selection for the effectiveness they bring

to the bird’s powers of ﬂight. Of course, this does not imply even a basic under-

standing of aerodynamics theory on the bird’s part – only that those birds with

the most effective wings have been favored in the past by natural selection and

have passed their effectiveness on to their offspring. Likewise, in applying this

approach to foraging behavior, there is no question of suggesting ‘conscious

decision-making’ on the predator’s part.

What, though, is the appropriate measure of ‘effectiveness’ in foraging behavior

– the equivalent of ﬂying ability as a criterion for a successful bird’s wing? Usually,

the net rate of energy intake has been used – that is, the amount of energy obtained

per unit time, after account has been taken of the energy expended by the pre-

dator in carrying out its foraging. For many consumers, however, the efﬁcient

gathering of energy may be less critical than some other dietary constituent (e.g.

nitrogen), or it may be of prime importance for the forager to consume a mixed

and balanced diet. The predictions of optimal foraging theory do not apply to all

the foraging decisions of every predator.

Chapter 7 Predation, grazing and disease

229

(a) (b)

slops

Figure 7.12

The different types of foraging and

transmission. (a) Active predators

seeking (possibly active) prey.

(b) Sit-and-wait predators waiting

for active prey to come to them.

infectious and uninfected hosts

‘bumping into each other’.

(d) Transmission between free-living

stages of a parasite shed by a host

and new, uninfected hosts.

the evolutionary, optimal foraging

approach

9781405156585_4_007.qxd 11/5/07 14:53 Page 229

A range of the aspects of foraging behavior to which the optimal foraging

approach has been applied is illustrated in Figure 7.13. These are elaborated on

brieﬂy here, before the whole approach is demonstrated by examining just one

of them in detail.

Where, within the habitat available to it, does a predator concentrate its

foraging (Figure 7.13a)? Does it concentrate where the long-term

expectation of net energy intake is highest or where the risk of extended

periods of low intake is lowest?

Does the location chosen by a predator reﬂect just the expected energy

intake? Or does there appear to be some balancing of this against the risk

of being preyed upon by its own predators (Figure 7.13b)?

How long does a predator tend to remain in one location – one patch, say,

of a patchy environment – before moving on to another (Figure 7.11c)?

Does it remain for extended periods and hence avoid unproductive trips

from one patch to another? Or does it leave patches early, before the

resources there are depleted?

What are the effects of other, competing predators foraging in the same

habitat (Figure 7.11d)? The expected net energy intake from a location is

Part III Individuals, Populations, Communities and Ecosystems

230

applying the optimal foraging

approach to a range of

foraging behaviors

(a) (b)

(c)

(d)

(e)

Figure 7.13

The types of foraging ‘decisions’

considered by optimal foraging

theory. (a) Choosing between

habitats. (b) The conﬂict between

increasing input and avoiding

predation. (c) Patch stay-time

decisions. (d) The ‘ideal free’

decision – the conﬂict between

patch quality and competitor

density. (e) Optimal diets – to

include or not to include an item

in the diet (when something better

might be ‘round the corner’).

9781405156585_4_007.qxd 11/5/07 14:53 Page 230

now presumably a reﬂection of both its intrinsic productivity and the

number of competing foragers. What is the expected distribution of the

predators as a whole over the various habitat patches?

The remaining ‘question’, in Figure 7.13e, and the one to which we now

turn in Box 7.1 for a fuller illustration of the optimal foraging approach,

is that of diet width. No predator can possibly be capable of consuming

all types of prey. Simple design constraints prevent shrews from eating

owls (even though shrews are carnivores) and prevent humming-birds

from eating seeds. Even within their constraints, however, most animals

consume a narrower range of food types than they are morphologically

capable of consuming.

Chapter 7 Predation, grazing and disease

231

7.1 QUANTITATIVE ASPECTS

7.1 Quantitative aspects

Diet width is the range of food types consumed by

a predator. In order to derive widely applicable pre-

dictions about when diets are likely to be broad or

narrow, we need to strip down the act of foraging to

its bare essentials. So, we can say that to obtain food,

any predator must expend time and energy, ﬁrst

in searching for its prey, and then in handling it (i.e.

pursuing, subduing and consuming it). While search-

ing, a predator is likely to encounter a wide variety

of food items. Diet width, therefore, depends on the

responses of predators once they have encountered

prey. Generalists, those with a broad diet, pursue a

large proportion of the prey they encounter. Specialists,

those with a narrow diet, continue searching except

when they encounter prey of their speciﬁcally preferred

type.

Generalists have the advantage of spending rela-

tively little time searching – most of the items they

ﬁnd they pursue and, if successful, consume. But

they suffer the disadvantage of including relative low-

proﬁtability items in their diet. That is, generalists enjoy

a net intake of energy much of the time – but their

rate of intake is often relatively low. Specialists, on the

other hand, have the advantage of only including

high-proﬁtability items in their diet. But they suffer the

disadvantage of spending a relatively large amount of

their time searching for them. Thus, specialists spend

relatively long periods with a net expenditure of energy

– but when they do take in energy it is at a relatively

high rate. Determining the predicted optimal foraging

strategy for a particular predator amounts to deter-

mining how these pros and cons should be balanced

so as to maximize the overall net rate of energy intake,

while searching for and handling prey (MacArthur &

Pianka, 1966; Charnov, 1976).

We can start by taking it for granted that any pre-

dator will include the single most proﬁtable type of

prey in its diet: that is, the one for which the net rate of

energy intake is highest. But should it include the next

most proﬁtable type of item too? Or, when it comes

across such an item, should it ignore it and carry on

searching for the most proﬁtable type? And if it does

include the second most proﬁtable type, what about

the third, and the fourth? And so on.

Consider ﬁrst this ‘second most proﬁtable food

type’. When will it pay a predator to include an item of

this type in its diet (in energetic terms)? The answer

is when, having found the item, its expected rate of

energy intake over the time spent handling it exceeds

its expected rate of intake if, instead, it continued

to search for, and then handled, an item of the most

proﬁtable type. (The expected times are simply the

average times for items of a particular type.) Express-

ing this in symbols, we call the expected searching

Optimal diet width

9781405156585_4_007.qxd 11/5/07 14:53 Page 231

In summary, Box 7.1 suggests that a predator should continue to add increas-

ingly less proﬁtable items to its diet as long as this increases its overall rate of

energy intake. This will serve to maximize its overall rate of energy intake. This

‘optimal diet model’, then, leads to a number of predictions.

1 Predators with handling times that are typically short compared to their

search times should be generalists (i.e. have broad diets), because in the

short time it takes them to handle a prey item that has already been found,

they can barely begin to search for another prey item. This prediction seems

to be supported by the broad diets of many insectivorous birds feeding in

trees and shrubs. Searching is always moderately time-consuming, but

handling the minute, stationary insects takes negligible time and is almost

always successful. A bird, therefore, has something to gain and virtually

nothing to lose by consuming an item once found, and overall proﬁtability

is maximized by a broad diet.

2 By contrast, predators with handling times that are long relative to their

search times should be specialists: maximizing the rate of energy intake

is achieved by including only the most proﬁtable items in the diet. For

instance, lions live more or less constantly in sight of their prey so that

search time is negligible; handling time, on the other hand, and particularly

pursuit time, can be long (and very energy-consuming). Lions consequently

specialize on those prey that can be pursued most proﬁtably: the immature,

the lame and the old.

3 Other things being equal, a predator should have a broader diet in an

unproductive environment (where prey items are relatively rare and

search times relatively large) than in a productive environment (where

search times are generally smaller). This prediction is supported by a study

of brown and black bears (Ursos arctos and U. americanus) feeding on

salmon in Bristol Bay in Alaska (Figure 7.14). When salmon availability was

high, bears consumed less biomass per captured ﬁsh, targeting energy-rich

ﬁsh (those that had not spawned) or energy-rich body parts (eggs in females,

brain in males). That is, their diet became more specialized when prey

were abundant.

Part III Individuals, Populations, Communities and Ecosystems

232

and handling times for the most proﬁtable type s

and h

, and its energy content E

, and the expected

handling time for the second most proﬁtable type h

and its energy content E

. Then it pays the predator

to increase the width of its diet if E

(i.e. the rate of

intake, energy per unit time, if it handles the second-

best type) is greater than E

/(s

+ h

) (the rate of intake

if instead it searches for the most proﬁtable type).

Suppose now that it did pay the predator to

expand its diet. What about the third most proﬁt-

able type? We argue in the same way as before: it will

pay a predator to include this in its diet if, when it has

found it, its expected rate of intake over the time

spent handling it, h

, exceeds the expected rate if

it searches for and handles either of the two most

proﬁtable types, both already included in its diet.

Thus, if we call s¯, h

, and E

the searching and handling

times and energy content for items already in the

diet, it will pay the predator to expand its diet if

exceeds E

/(s¯ + h

), or, more generally, if E

exceeds E

/(s¯ + h

), where n refers generally to the

‘next’ most proﬁtable prey type (not already in the diet).

The ecological implications of this rule are considered

in the main text.

predictions of the optimal

diet model

9781405156585_4_007.qxd 11/5/07 14:53 Page 232

Overall, then, we can see how an evolutionary, optimal foraging approach can

help us make sense of predators’ foraging behavior – how it makes predictions of

what that behavior might be expected to be, and that these predictions may be

supported by real examples.

7.5 Population dynamics of predation

What roles do predators play in driving the dynamics of their prey, or prey play in

driving the dynamics of their predators? Are there common patterns of dynamics

that emerge? The preceding sections should have made it plain that there are

no simple answers to these questions. It depends on the detail of the behavior

of individual predators and prey, on possible compensatory responses at indi-

vidual and population levels, and so on. Rather than despair at the complexity

of it all, however, we can build an understanding of these dynamics by starting

simply and then adding additional features one by one to construct a more

realistic picture.

7.5.1 Underlying dynamics of predator–prey

interactions: a tendency to cycle

We begin by consciously oversimplifying – ignoring everything but the predator

and the prey, and asking what underlying tendency there might be in the dynamics

of their interaction. It turns out that the underlying tendency is to exhibit coupled

oscillations – cycles – in abundance. With this established, we can turn to the many

other important factors that might modify or override this underlying tendency.

Rather than explore each and every one of them, however, Sections 7.5.4 and 7.5.5

examine just two of the more important ones: crowding and spatial patchiness.

These two factors cannot, of course, tell the whole story; but they illustrate how

the differences in predator–prey dynamics, from example to example, might be

explained by the varying inﬂuences of the different factors with a potential impact

on those dynamics.

Starting simply then, suppose there is a large population of prey. Predators

presented with this population should do well: they should consume many prey

and hence increase in abundance themselves. The large population of prey thus

gives rise to a large population of predators (Figure 7.15). But this increasing

Chapter 7 Predation, grazing and disease

233

Average percent biomass

consumed per fish

Spawner density (salmon m

–2

)

100

32.521.510.50

Figure 7.14

As the spawning density (i.e. the abundance) of salmon increases,

the average percentage of each salmon consumed by bears

decreases: as prey abundance increases, the predators become

more specialized.

AFTER GENDE ET AL., 2001

building a picture from simple

beginnings

9781405156585_4_007.qxd 11/5/07 14:53 Page 233

population of predators increasingly takes its toll of the prey. The large popula-

tion of predators therefore gives rise to a small population of prey. Now the

predators are in trouble: large numbers of them and very little food. Their abund-

ance declines. But this takes the pressure off the prey: the small population of

predators gives rise to a large population of prey – and the populations are back

to where they started. There is, in short, an underlying tendency for predators and

their prey to undergo coupled oscillations in abundance – population cycles

(Figure 7.15) – essentially because of the time delays in the response of predator

abundance to that of the prey, and vice versa. (A ‘time delay’ in response means,

for example, that a high predator abundance reﬂects a high prey abundance in

the past, but it coincides with declining prey abundance, and so on.) A simple

mathematical model – the Lotka–Volterra model – conveying essentially the same

message is described in Box 7.2.

7.5.2 Predator–prey cycles in practice

This underlying tendency for predator–prey interactions to generate coupled

oscillations in abundance could produce an ‘expectation’ of such cycles in real

populations, but there were many aspects of predator and prey ecology that

had to be ignored in order to demonstrate this underlying tendency, and these

can greatly modify expectations. It is no surprise, then, that there are rather

few good examples of clear predator–prey cycles – albeit ones that have received

a great deal of attention from ecologists. Nonetheless, in trying to make sense of

predator–prey population dynamics, cycles – the underlying tendency – are a

good place to start.

Part III Individuals, Populations, Communities and Ecosystems

234

RIP

babies

RIP

babies

Numbers

Prey

Predators

Time

Figure 7.15

The underlying tendency for

predators and prey to display

coupled oscillations in abundance

as a result of the time delays in

their responses to each other’s

abundance.

the ‘expectation’ of cycles is only

rarely fulﬁlled

9781405156585_4_007.qxd 11/5/07 14:53 Page 234

Chapter 7 Predation, grazing and disease

235

(a) (b)

Predator abundance (P)

Prey abundance (N)

7.2 QUANTITATIVE ASPECTS

7.2 Quantitative aspects

Here, as in Boxes 5.4 and 6.1, one of the foundation-

stone mathematical models of ecology is described

and explained. The model is known (like the model of

interspeciﬁc competition in Box 6.1) by the name

of its originators: Lotka and Volterra (Volterra, 1926;

Lotka, 1932). It has two components: P, the numbers

present in a predator (or consumer) population, and

N, the numbers or biomass present in a prey or plant

population.

It is assumed that in the absence of consumers

the prey population increases exponentially (see

Box 5.4):

dN/dt = rN

But now we also need a term signifying that prey

individuals are removed from the population by pre-

dators. They will do this at a rate that depends on

the frequency of predator–prey encounters, which will

increase with increasing numbers of predators (P) and

prey (N). The exact number encountered and con-

sumed, however, will also increase with the searching

and attacking efﬁciency of the predator, denoted by a.

The consumption rate of prey will thus be aPN, and

overall:

dN/dt = rN − aPN (1)

Turning to predator numbers, in the absence

of food these are assumed to decline exponentially

through starvation:

dP/dt =−qP

where q is their mortality rate. But this is counteracted

by predator birth, the rate of which is assumed to

depend on: (i) the rate at which food is consumed,

aPN; and (ii) the predator’s efﬁciency, f, at turning this

food into predator offspring. Overall:

dP/dt = faPN − qP (2)

Equations 1 and 2 constitute the Lotka–Volterra

model.

The properties of this model can be investigated

by ﬁnding zero isoclines (see Box 6.1). There are

separate predator and prey zero isoclines, both of

which are drawn on a graph of prey density (x-axis)

against predator density ( y-axis) (Figure 7.16). The

prey zero isocline joins combinations of predator and

prey densities that lead to an unchanging prey popula-

tion, dN/dt = 0, while the predator zero isocline joins

The Lotka–Volterra predator–prey model

Figure 7.16

See box text for details.

9781405156585_4_007.qxd 11/5/07 14:53 Page 235

They do occur sometimes. It has been possible in several cases, for example,

to generate coupled predator–prey oscillations, several generations in length,

in the laboratory (Figure 7.18a; see also Figure 7.22c). Amongst ﬁeld popula-

tions, there are a number of examples in which regular cycles of prey and

predator abundance can be discerned. Cycles in hare populations, in particular,

have been discussed by ecologists since the 1920s, and were recognized by fur

trappers more than 100 years earlier. Most famous of all is the snowshoe

hare, Lepus americanus, which in the boreal forests of North America follows a

‘10-year cycle’ (although in reality this varies in length between 8 and 11 years;

see Figure 7.18b). The snowshoe hare is the dominant herbivore of the region,

feeding on the terminal twigs of numerous shrubs and small trees. A number of

predators, including the Canada lynx (Lynx canadensis), have associated cycles

Part III Individuals, Populations, Communities and Ecosystems

236

combinations of predator and prey densities that lead

to an unchanging predator population, dP/dt = 0.

In the case of the prey, we ‘solve’ for dN/dt = 0 in

equation 1, giving the equation of the isocline as:

P = r/a

Thus, since r and a are constants, the prey zero

isocline is a line for which P itself is a constant

(Figure 7.16a): prey increase when predator abund-

ance is low (P < r/a) but decrease when it is high

(P > r/a).

Similarly, for the predators, we solve for dP/dt = 0

in equation 2, giving the equation of the isocline as:

N = q/fa

The predator zero isocline is therefore a line along

which N is constant (Figure 7.16b): predators decrease

when prey abundance is low (N < q/fa) but increase

when it is high (N > q/fa).

Putting the two isoclines (and two sets of arrows)

together in Figure 7.17 shows the behavior of joint

populations. The various combinations of increases

and decreases, listed above, mean that the popula-

tions undergo ‘coupled oscillations’ or ‘coupled cycles’

in abundance; ‘coupled’ in the sense that the rises

and falls of the predators and prey are linked, with pre-

dator abundance tracking that of the prey (discussed

biologically in the main text).

It is important to realize, however, that the model

does not ‘predict’ the exact patterns of abundance

that it generates. The world is much more complex

than imagined by the model. But it does capture the

essential tendency for coupled cycles in predator–

prey interactions.

(a)

(b)

Time

Figure 7.17

See box text for details.

plants, hares and lynx in

North America...

9781405156585_4_007.qxd 11/5/07 14:53 Page 236

of similar length. The hare cycles often involve 10–30-fold changes in abund-

ance, and 100-fold changes can occur in some habitats. They are made all the

more spectacular by being virtually synchronous over a vast area from Alaska

to Newfoundland.

But are the hare and lynx participants in a predator–prey cycle? This immedi-

ately seems less likely once one appreciates the number of other species with

which both interact. Their food web (see Section 9.5) is shown in Figure 7.19.

In fact, both experimental studies (Krebs et al., 2001) and statistical analyses

of the population dynamics data (Stenseth et al., 1997) suggest that whereas the

dynamics of the hares are driven by their interactions with both their food

and their predators (especially lynx), the dynamics of the lynx are driven largely

by their interaction with their hare prey, much as the food web might suggest.

Both the hare–plant and the predator–hare interactions have some propensity

Chapter 7 Predation, grazing and disease

237

2.5

5.0

(a)

(b)

302010

Thousands of lynx

Thousands of hares

120

160

1850 1875 1900 1925

Year

Chlorella vulgaris ( )

(106 cells ml

–1

)

Time (days)

Bracionus calyciflorus ( )

(females ml

–1

)

Snowshoe hare

Lynx

Figure 7.18

Coupled oscillations in the

abundance of predators and prey.

(a) Parthenogenetic female rotifers,

Bracionus calyciﬂorus (predators,

maroon circles), and unicellular

green algae, Chlorella vulgaris (prey,

blue circles), in laboratory cultures.

(b) The snowshoe hare (Lepus

americanus) and the Canada lynx

(Lynx canadensis) as determined by

the number of pelts lodged with the

Hudson Bay Company.

(a) AFTER YOSHIDA ET AL., 2003; (b) AFTER MACLULICK, 1937

The Canada lynx and the snowshoe

hare – a predator and prey that may

show coupled oscillations.

. . . but how are the cycles

generated?

9781405156585_4_007.qxd 11/5/07 14:53 Page 237

to cycle on their own – but in practice the cycle seems normally to be generated

by the interaction between the two. This warns us that even when we have a

predator–prey pair both exhibiting cycles, we may still not be observing simple

predator–prey oscillations.

Apparent instances of predator–prey cycles sometimes make the news – see

Box 7.3 for an example.

Part III Individuals, Populations, Communities and Ecosystems

238

Great horned owl

Lynx

Coyote

Red fox

Wolverine

Wolf

Moose

Golden eagleHawk owl

Goshawk

Kestrel

Red-tailed hawk

Northern harrier

Fungi

Forbs Grasses Bog birch Grey willow Soapberry White spruce Balsam poplar Aspen

Red squirrel Ground squirrel Snowshoe hare Willow ptarmigan Passerine birds

Insects

Spruce gooseSmall rodents

(a)

Great horned owl

Moose

Golden eagle

Kestrel

Fungi

Balsam poplar Aspen

Willow ptarmigan Passerine birds

Insects

Spruce gooseSmall rodents

(b)

Snowshoe

hare

Coyote

Red fox

Wolverine

Wolf

Lynx

Red-tailed hawk

Northern harrier

Goshawk

Hawk owl

Forbs Grasses

Red squirrel Ground squirrel

Bog birch Grey willow Soapberry White spruce

Figure 7.19

(a) The main species and groups of species in the boreal forest community of North America, with trophic interactions (who eats who) indicated by

lines joining the species, and those affecting the Canada lynx shown as maroon arrows, pointing toward the consumer. (b) The same community,

but with the interactions of the snowshoe hare shown as arrows.

AFTER STENSETH ET AL., 1997

9781405156585_4_007.qxd 11/5/07 14:53 Page 238