Chap.10 Foraging

鄭先祐 (Ayo) 教授國立台南大學 環境與生態學院

生態科學與技術學系 環境生態研究所 + 生態旅遊研究所

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Foraging

Finding food and the search imageOptimal foraging theory

What to eat Where to eat Specific nutrient constraints Risk-sensitive foraging

Foraging and group lifeNatural selection, phylogeny, and

seed cachingLearning and foraging

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Foraging

Searching for and consuming food, foraging, is a critical part of every animal’s existence.

Many animals spend a good deal of their waking hours foraging (Fig, 10.1) (A) a black bear (B) a Richardson’s ground squirrel

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Ant-fungus relationship

About 50 million years ago, ants began cultivating their own food by entering into a mutually beneficial relationship with certain species of fungi. The ants promote the growth of the fungi, while

also feasting on the vegetative shoots produced by their fungal partners.

Aside from humans, ants are one of the few groups on the planet that grow their own food.

Fig. 10.2, A worker of the leaf-cutter ant tending a fungus garden. The thick whitish-gray coating of the worker is the mutualistic bacterium that produces the antibiotics that suppress the growth of parasite in the fungus garden.

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Ant-fungus relationship

1. All twenty species of the fungus-growing ants examined had Streptomyces bacteria associated with them

2. Ants actually transmit the bacteria across generation, with parents passing the bacteria on to offspring.

3. Only females posses the bacteria.4. The bacteria found on fungus-growing

ants produce antibiotics that wipe out only certain parasitic diseases.

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Finding food and the search image

When animals encounter a prey type more and more, they form some sort of representation of that target- the prey- and that this representation or image becomes more and more detailed with experience, which in turn translate into the forager becoming more successful at finding that type of prey (Tinbergen, 1960)

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Optimal foraging theory (OFT)

What to eat? Where to eat?

How long should a forager stay in a certain food patch?

Specific nutrient constraints Risk-sensitive foraging

How does variance in food supply affect a forager’s decision about what food types to eat?

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What to eat?

Cheetah (the forager)Fig. 10.3 foraging decision.

Here a female cheetah has killed a hare (the prey)

In making the decision whether to take hares rather than some other prey, the animal will compare the energy value, encounter rate, and handling time for each putative prey.

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Optimal prey choice model

The model assumes:1. Energy intake from prey can be

measured in some standard currency

2. Foragers can’t simultaneously handle one prey item and search for another

3. Prey are recognized instantly and accurately

4. Prey are encountered sequentially

5. Natural selection favors foragers that maximize their rate of energy intake.

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Great tit foraging

One classic early experiment using optimal foraging theory had mealworms of different sizes presented on a conveyor belt to great tits. (Fig. 10.4)

Fig. 10.5 optimal choice of diet (A) great tits (B) bluegill sunfish

• The fit between expected and observed foraging is quite good, although the fish tended to oversample medium and small Dophnia in the high density treatment.

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Great tits

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Bluegill sunfish

•The fit between expected and observed foraging is quite good, although the fish tended to oversample medium and small Dophnia in the high density treatment.

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Patch choice

For a bee, different flowers in a field of flowering plants might represent different patches

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Where to eat

Marginal value theorem( 邊際價值定律 ) (Charnov, 1976)1. A forager should stay in a patch until the

marginal rate of food intake– that is, the rate of food intake associated with the next prey item in its patch– is equal to that of the average rate of food intake across all patches available.

2. The greater the time between patches, the longer a forager should stay in a patch.

3. For patches that are already of generally poor equality when the forage enters the patch, individuals should stay longer in such patches than if they were foraging in an environment full of more profitable patches. Fig. 10.7 graphical solution to marginal value problem

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Great tits: optimal time in patch and travel time (Fig. 10.8)

(A) an artificial tree that allowed him to control both patch quality and travel time.

(B) the solid line is the predicted optimal time in a patch plotted against the travel time, which was calculated based on the marginal value theorem, while the data points are the observed times the birds stayed in the patch plotted as a function of travel time between patches. The results clearly demonstrate that the amount of

time birds spent in a patch matched the optimal time predicted by the marginal value theorem.

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Specific nutrient constraints

Fig. 10.9 Moose foraging on a salt budget. Sodium is a particularly good candidate for a

nutrient constraint study because vertebrates require large amounts of sodium, sodium is scarce, and besides water, sodium is the only nutrient for which a “specific hunger” has been documented in animals.

Moose need salt, and they acquire it from energy-poor plants. This takes time away from foraging on energy-rich terrestrial plants. (Fig. 10.10)

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Risk-sensitive foraging

Risk, the term was first used in economics, where more variance implied a greater chance of loss (or gain). Increased variance in prey availability increases.

Rick-sensitive optimal foraging models (Fig. 10.11) 2 patches, patch 1 that always yields eight

pellets once the cover is removed Patch 2 in which half the time there are no

pellets and half the time there are sixteen pellets.

Both patches have the same mean (eight), but the variance is greater in patch 2.

If forager takes variance into account, it is foraging in a rick-sensitive manner.

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Forager, 3 different hunger states

Forager 1 has a hunger stat, in which it values every new food item equality. Risk insensitive (Fig. 10.12 (A))

Forager 2 is fairly satiated ( 相當飽足 ), and although every additional item it takes in has some value, each additional item is worth less and less. Risk adverse (Fig. 10.13 (B))

Forager 3 is starving, and every additional item it eats is worth more and more (to a limit). Risk prone (Fig. 10.13 (C) )

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Fig. 10.12 (A) hunger ： Risk insensitiveFig. 10.13 (B) fairly satiated ( 相當飽足 ) ： Risk adverse Fig. 10.13 (C) starving ： Risk prone

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Rule of thumb

As with all the mathematical models we analyze, we are not suggesting that animals make the mental calculations that we just went through, but rather that natural selection favors any “rule-of-thumb behavior.

The favored rule-of-thumb might be “when starving, use patches of food that have high variances.”

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Junco foraging behavior has been used to test numerous optimal foraging models.

Fig. 10.14. utility functions and risk sensitivity

(A) risk-prone juncos. The utility function for this junco indicates that each additional item the bird eats is worth more and more.

(B) Risk adverse juncos. Each additional item a junco receives is worth less and less.

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Risk adverseRisk prone

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Foraging and Group Life

Foraging in a group Increasing the foraging group size

increases the amount of food each forager receives.

Foraging in bluegills (Fig. 10.15, 16, 17)Disentangling( 解開 ) the effect of group

size and cooperation on foraging success. Wild dogs Chimp (Tai chimp vs. Gombe chimp)

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Foraging in bluegills

Fig. 10.16 group size and foraging success. In bluegill sunfish, the mean rate of prey captured increases with group size until group size reaches about four individuals.

Flushing effect, when bluegills forage in groups, they flush out more prey and attract other fish to the foraging site. (Fig. 10.17)

Meta-analysis on foraging success and group size in seven different species that hunt in groups. Overall, a strong positive relationship between foraging success and group size.

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Bluegill sunfish forage for small aquatic insects in dense vegetation.

The bluegills’ foraging patterns approximate those predicted by theory.

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Disentangling the effect of group size and cooperation on foraging success Individuals may cooperate with one another

when hunting in groups. For example, wild dogs

Cooperative hunting in chimp populations, Tai chimps and Gombe chimps. Tai chimps, cooperation hunting Gombe chimps, no correlation between group size

and hunting success. The success rate for Gombe solo hunters was

quite high compared with the individual success rate for Tai chimps.

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Groups and public information

in public information models, individuals simply use the actions of others as a means of assessing the condition of the environment, and as such, public information allows group members to reduce environmental uncertainty.

Solitary foragers vs. foragers in a group. Starlings were tested using an array of

food placed into cups. (Fig. 10.19)

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Public information in starlings

A given bird (B1) fed from such a feeder either alone or paired with a second bird (B2) .

Prior to being paired with B1 partners, B2 birds had either been given the chance to sample a few cups in this feeder, or to sample all such cups.

Two results support the predictions of public information models. When tested on completely empty feeding

patches, B1 birds left such patches earlier when paired with any B2 bird than when foraging alone.

B1 birds left patches earliest of all when paired with B2 birds that had complete information about the patches.

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Natural selection, phylogeny and seed caching

Hippocampal ( 海馬體的 ) size and caching ability To be associated with food

retrieval. (food storage) Fig. 10.20 Foraging and brain

size. The volume of the hippocampal region relative to body mass was positively correlated with the extent of food storing in six species of birds,

Phylogeny and caching ability

A. Alpine cough

B. Jackdaw

C. Rook and crow combined

D. Red-billed blue magpie

E. Magpie

F. European jay

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A. Alpine cough

B. Jackdaw

C. Rook and crow combined

D. Red-billed blue magpie

E. Magpie

F. European jay

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Chickadees ( 山雀 ) from Colorado or Alaska

Bring them back to laboratory at the University of California at Davis.

The results: The birds from Alaska (food-scarce

population) cached a greater percentage of seeds than the birds from Colorado (food-rich population).

The Alaska birds found more of their cached seeds than did the Colorado birds, and their searches were more efficient in that they made fewer errors (Fig. 10.21)

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Phylogeny and caching ability

Evolutionary history of caching behavior in the corvid family ( 鴨科 ).

Phylogeny of 46 species Non-cachers Moderate cachers Specialized cachers

Result: The ancestral state of

caching in corvids is “moderate caching”.

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Learning and foraging

Foraging, learning, and brain size in birds Hypothesized a neurobiological link between

forebrain size and learning abilities in animals. Table 10.1 examples of foraging innovations in

birds. Data on 322 foraging innovations, including those in this list.

Relative forebrain size correlated with foraging innovation. Larger forebrains were more likely to have high incidences of foraging innovation (Fig. 10.22)

Learning and planning for the future Social learning and foraging

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Planning for the future

If animals could plan for the future based on prior experience, as we humans clearly do, there would be huge fitness benefits associated with such an ability.

Two requirements The behavior must be novel, so that we can be

certain that we are not seeding the manifestation of some innate action

The behavior in question must not be tied to the current motivational state of the animal, but rather to the anticipated motivational state at some point in the future.

案例： Western scrub jays modify their foraging behavior in an attempt to plan for the future (Fig. 10.24)

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Western scrub jays and planning for the future

On alternate morning over the course of six days, birds were exposed to one of two compartments- one compartment contained food in the form of ground-up pine nuts, and the other compartment contained no food. On the evening before each test, the birds were not fed

any food, and they were therefore hungry during their exposure to test compartments.

After the six days of exposure to the two compartments, the birds were denied access to any food for two hours before dark, and then they were unexpectedly provided with a bowl of whole pine nuts – that is, food that could be cached. Jays cached more nuts in the compartment in which

they had consistently received no food in the past.

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Social learning and foraging in pigeons

Fig. 10.25 urban foragers. Pigeons are scavengers, coming across novel food items all the time. Such a species is ideal for study foraging and cultural transmission.

Fig. 10.26 Pigeons in this experiment need to learn to pierce the red half of paper covering a box of seed. The graph shows average latency to eating for four groups: NM (no model) group, Bl (blind imitation) group, LE (local enhancement) group, and OL (observational learning) group. Pigeons in NM and Bl treatments never learned

to feed in the experimental apparatus. The quickest learning occurred in the OL treatment.

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Producers and scroungers

Producers find and procure foodScroungers make their living

parasitizing the food that producers have uncovered.

Fig. 10.27 producers and scroungers when a group member finally opens a

tube with food in it, the food spills on the floor and is accessible to all. Out of sixteen pigeons, only two learned to open tubes, while fourteen acted as scroungers.

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Scrounging prevents social learning

Fig. 10.28 Scrounging prevents social learning (A) one group of birds saw a model bird

peck at a stick in a rubber stopper at the end of the tube. This provided food to the model. These birds learned to peck,

(B) scroungers fared much worse than non-scroungers when faced with the task of pecking at the stick.

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Ayo NUTN website:http://myweb.nutn.edu.tw/~hycheng/

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