bio 597 - foraging theory sp06people.cst.cmich.edu/gehri1tm/mammalogy/bio 597 - foraging...

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Foraging Ecology

SOLITARY HUNTERS

Myrmecophagy– anteaters– pangolins– numbat– echidna– aardvark– aardwolf

SOLITARY HUNTERSMyrmecophagy

– Prevalent in tropics, why?

– Narrow niche, so how to avoid competition?

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– Avoid competition?


– banded tamandua– eat ants without sting

(Azteca ants)– ants secrete skin

irritant chemical from abdomen

– Nasutitermes termite soldiers & terpenoidcompounds vs. winged termites

SOLITARY HUNTERSInsectivory

– Bats• 70% eat insects• 3,000 to 7,000 per night per bat• big brown bat maternal colony

of 150 can eat 38,000 cucumber beetles, 1,600 June bugs, 19,000 stinkbugs, 50,000 leafhoppers

• Relation to agricultural pest insects – corn rootworms & cucumber beetles

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SOLITARY HUNTERS

Insectivory– Bats

• frequency modulated

• 5-10 per sec• 10 millisec long• shortened duration

& higher frequency (feeding buzz)

SOLITARY HUNTERSInsectivory

– Shrews

Preuss et al.

Foraging in Shrews

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Foraging in Shrews

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SOLITARY HUNTERS

Planktivory– Mysticete (baleen)

whales

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Gray whale

SOLITARY HUNTERS

Carnivory

SOLITARY HUNTERS

Carnivory: Weasels– Costs of being a weasel

• large SA:Volume ratio• must be active• fur is short, little fat• 2x energy demand• caches of prey• rougher on females?

– size dimorphism

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SOLITARY HUNTERSCarnivory: Weasels

– Costs of being a weasel– Vaudry et al. 1990. Holarctic Ecology 13:265-268.– Captive trials with female & male short-tailed weasels– Females 1/3 the time (searching & handling) for meadow

voles– Females unable to handle short-tailed shrews

King, C.M. 1989. in Carnivore behavior, ecology, and evolution

SOLITARY HUNTERSCarnivory: Weasels

– Inter-specific competition

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Foraging Theory: Predation & Herbivory

1- Many prey items with variable nutritional values

2- Prey items vary in spatial distribution and abundance

3- Variable costs of capturing and processing prey items

4- Forager has limited amounts of time & energy

5- Forager's choices may affect its fitness

Optimality theory

• we expect that natural selection yields efficient, economic animals; maximizing benefits or minimizing costs, thus maximizing net energy/time (e/t)

.....WHY????

Optimality theory

• foraging theory = optimal foraging theory = optimality theory

• includes: – prey selection– optimal diets– marginal value

theorem– central place foraging– optimal group size

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Optimal Foraging Model Components:

1.) Decision assumptions: refers to the type of choice forager makes or that natural selection makes for it

e.g., – pursue or not after

encountering prey item

– stay in habitat patch or move on

“The wolf is kept fed by its feet.”


2.) Currency assumptions: used to evaluate choices

e.g., – # prey items

captured/unit time– relates to profitability

of prey item– often express as net

energy gain/unit time


2.) Currency assumptions: used to evaluate choices

* time minimizers: minimize time needed to gain a fixed amount of energy

* energy maximizers: maximize amount of energy gained in a fixed time period

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3.) Constraint assumptions: factors that limit choices & currencies that might be obtained

e.g., – intrinsic limitations of

the animal (color vision)

– extrinsic limitations due to environment acting on animal

Optimal Foraging Model ComponentsOwen-Smith. 1994. Ecology 75:1050-1062

kudu (Tragelaphus strepsiceros)• Hand-reared, free-ranging• Winter dry season

• expand diet, include evergreen & unpalatable

• increase proportion of palatable tree spp.

• extended feeding

• Targeted energy requirements with least overall cost

• Elastic foraging times & digestive capacity

Optimal Foraging Models

Prey Models• Optimal diet & prey

selection• Predators choose the most

profitable prey item(s)• Gains = nutritional value

of prey item (energy = e)• Costs = handling time, t

(subdue & eat times = h) + search times (s)

• Net gain for given prey item = e/h

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Prey Models• If ignore 1st prey item

with reward e1/h1, then must spend time searching (s) for 2nd prey item with reward e2/h2

• Optimal strategy = pursue 1st prey item if:

e1/h1 > e2 /(s2+h2)


Prey Models• Handling times (h)

relatively short = generalist (wide diet breadth)

• Handling times (h) relatively long = specialist

• Poor habitat (e.g., low prey abundance), then search times (s) long =

• What about high prey abundance?


Prey Models• Other associated factors:

• Prey switching• Search image

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Optimal Foraging ModelsPatch Models

• Marginal value theorem, optimal patch residence times

• Clumped or patchy prey distributions

• How long should a predator stay in 1 patch before moving to another patch?i.e., What is the “marginal

value” of a patch such that it becomes more profitable to move on to another patch?


Patch Models• Maximize e/t• But, also factor in travel

time (T) between patches• So, maximize e/(T+s)• T = long, stay in patch

longer• Low energy patches =

shorter patch residence times






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Optimal Foraging ModelsPatch Models

• Maximize e/t• But, also factor in travel









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Optimal Foraging ModelsCentral-Place Foraging

Models• Extension of M-V

Theorem• Capture prey, then must

bring food load back to a central place, e.g., nest, den, or cache

• Factor in:• Outbound journey• Search time/handling

time• Return journey


Central-Place Foraging Models

• Ability to orient or navigate to find way back to central place

• General Patterns:1) If patch quality constant

– Load size & patch residence time increase with increased distance of patch from central place

65.6523.181.0

55.2431.430.45

52.6320.320.1

Observed Load Size

(mg)

Optimal Load Size(mg)

Travel Time(min)

Foraging Distance

(km)




• General Patterns:2) Increase rate of net

energy delivered to central place by shortening return trip– Cognitive mapping

X

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• General Patterns:2) Increase rate of net

energy delivered to central place by shortening return trip– Cognitive mapping



• General Patterns:3) If predation risk while

foraging– Forage closer to

central place, shorten patch residence times, deliver smaller loads

e.g., gray squirrel• Balance predation

risk with energy gain



• General Patterns:3) If predation risk while

foraging– Forage closer to

central place, shorten patch residence times, deliver smaller loads

e.g., gray squirrel• Balance predation risk

with energy gain• Tendency to carry food

item decreases with distance of food from cover (travel time) and increases with size of item (handling time)

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Linear Programming

• Multivariate approach

• Consider constraints that result in optimal diet

– Time– Nutritional needs– Energy needs

Linear Programming

• Multivariate approach

• Consider constraints that result in optimal diet

– Time– Nutritional needs– Energy needs

Optimal Foraging ModelsOwen-Smith. 1994. Ecology 75:1050-1062

kudu (Tragelaphus strepsiceros)

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Optimal Group Size• Adaptation to

maximize energy intake by reducing search & handling times and/or predation risks


Benefits of Group Living to Prey:

1) Predator has difficulty finding scattered groups or individual lost in group

2) More eyes & ears3) Group intimidation


Benefits of Group Living to Prey:

4) Which individual to chase?

5) Avoid being the victim

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Benefits of Group Living to Predators:

1) Better able to locate food (information exchange)

2) Increased success3) Cooperative strategies4) Catch larger prey (felids

vs. canids)5) Able to compete with

other species




2) Increased success3) Cooperative strategies4) Catch larger prey (felids

vs. canids)5) Able to compete with

other species




2) Increased success• Golden jackals &

Thomson’s gazelle• Spotted hyaenas &

wildebeest calves

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Optimal Foraging ModelsBenefits of Group

Living to Predators:3) Cooperative strategies4) Catch larger prey

(felids vs. canids)5) Able to compete with

other species6) Increased survival

Bekoff and Wells 1980

COOPERATIVE HUNTERS

African Wild Dogs (Lycaon pictus)– pep rallies

COOPERATIVE HUNTERSAfrican Wild Dogs

(Lycaon pictus)– pep rallies– den guards– regurgitation of food– coursing strategy

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COOPERATIVE HUNTERS

C. Orca Whales (Orcinus orca)– pods (matrilines)– females teach young to strand

Optimal Foraging

Ecological Considerations:1) Foraging Strategies –

related to energetic cost of foraging

• Sit-and-Wait (ambush) hunter• Prey densities low or

prey dispersed• Long search times, but

low energy costs• Generally high handling

costs• Occipital crunch or

suffocation hold

SOLITARY HUNTERSCats

– Rush distance is prey-dependent

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Optimal Foraging

Ecological Considerations:

1) Foraging Strategies –related to energetic cost of foraging

• Search-and-Pursuit hunter (& variations)• Prey densities higher

or prey clumped• Less search times, but

huge energy costs• Solitary or group

hunters

FACTORS INFLUENCING FORAGING STRATEGIES

Habitat– Lynx

• sparse cover: stalk• dense cover: ambush


Habitat– Bats

• open areas– low frequency, long distance calls

• around foliage– constant, higher frequencies– sensitive to insect wings

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Habitat– Bats

• gleaners (whispering bats)

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Weasels & Habitat Fragmentation

Gehring and Swihart. 2003. Biological Conservation 109:283-295.

Gehring and Swihart. 2004. Journal of Mammalogy 85:138-145.

ESLIK

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r = 0.95P = 0.0005

r = 0.57P = 0.09

r = -0.66P = 0.10




0.670.6735.5957.500.671.671.532.56Ditch

0.683.00126.18402.470.212.335.1217.66Fencerow

0022.8878.550.321.001.424.33Grass

0031.8291.720.090.911.765.04Field

2.734.1468.33125.370.361.294.085.78Forest

SENumber of

rabbit pellet groupsb

SERelative biomass of small mammalsa

SESpecies richness

a

SERelative abundance of small mammalsa

Habitat

a Fencerow > Field, Grass, Ditchb Fencerow and Forest > Field, Grass, Ditch


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0.6650.2Number of Pellet Groups (RAB)

0.0068.2Prey Biomass (PB)

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Optimal Foraging

Ecological Considerations:

2) Competition –• competitors may

decrease abundance/encounter rates of prey – forcing spp. to expand its diet to lower ranking prey or type of prey patches visited

THE COSTS OF PREDATIONPredator Efficiency: Cats, Dogs

– Wolves: 7%– Wild dogs: 34-85%– Coyotes: 28-51%– Cats: 35%

THE COSTS OF PREDATIONMortality Risks

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Distribution Patterns

Ideal Free Distribution (IFD)

• Assume 2 habitats, 1 rich and 1 poor, relative to resources

• How should competitors distribute themselves?

Distribution PatternsIdeal Free Distribution

(IFD)

Distribution PatternsIdeal Despotic

Distribution (IDD)• Life is never that

simple• Why wouldn’t the IFD

apply in all cases?

bio 597 - foraging theory sp06people.cst.cmich.edu/gehri1tm/mammalogy/bio 597 - foraging...

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