Behavior population dynamics
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Behavior  Population Dynamics. Behavior Directly Governs Individual Demographic Performance Indirectly Effects Population Dynamics Population Growth Implies Chance of Extinction Here, Take Behavior = Social Organization. Extinction. Population extinction process

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Behavior  Population Dynamics

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Behavior population dynamics

Behavior  Population Dynamics


Directly Governs Individual Demographic Performance

Indirectly Effects Population Dynamics

Population Growth Implies Chance of Extinction

Here, Take Behavior = Social Organization



Population extinction process

Four general causes of extinction

1. Environmental stochasticity

2. Demographic stochasticity

3. Abiotic catastrophes

4. Lack genetic variation



Environmental stochasticity

Random, temporal variation: exogenous factor (s)

Individuals’ experience same birth, death rates Temporal fluctuations, Between-generation scale

Good, Bad Years = Generations: food abundance

Small population & bad year 




Demographic stochasticity

Random variation among individuals,

Within-generation scale

Number offspring, survival

Individuals’ birth and death rates independent,

hence can differ

Important small populations: chance extinction



Demographic stochasticity

Fix time; Extinction Pr

declines with Initial

population ize

Fix Pop size; Extinction Pr

increases with time

MTE = (Extinction Pr)-1



Abiotic (Physical) Catastrophes

Large, sudden density reduction

Environmental, anthropogenic

Climate change

Time scale relative to generation time




Lack variation, population fails to adapt

Rarest, but [again] global climate change

Behavior population dynamics1

Behavior  Population Dynamics

Vucetich et al. 1997. Effects of social structure and prey dynamics on extinction risk in gray wolves. Conservation Biology 11:957.

1. Wolves: social behavior - group, pack

1 litter/year, dominant female

amplify demographic stochasticity

2. Prey availability: fluctuate, source of

environmental stochasticity

Behavior population dynamics2

Behavior  Population Dynamics

Gray wolf (Canis lupus)

Isle Royale, MI; island in Lake Superior

National Park, > 500 mi2

Wolves feed on moose

Abundance of old moose (> 9 yrs) key

Behavior population dynamics3

Behavior  Population Dynamics

Objective: Simulate wolf population dynamics

Predict mean time to extinction (MTE)

1. Age-dependent mortality in wolves

1/3 pups die first year

No wolves older than 11 yrs

2. Random litter size in wolves, Mean = 1

Behavior population dynamics4

Behavior  Population Dynamics

3. Wolf packs:

Some restructuring between years

When prey abundance falls,

smallest pack disperses, mortality cost

Survivors join another pack

Number packs proportional to no. old-moose

Wolf pack count vs moose

Wolf/Pack Count vs Moose

Wolf pack moose dynamics

Wolf, Pack, Moose Dynamics

Behavior population dynamics5

Behavior  Population Dynamics

Mean Time to Extinction, Wolf Population

Weak dependence, initial population size

Standard result not observed

Strong effect, initial number of packs

Simulation results

Simulation results

Behavior population dynamics6

Behavior  Population Dynamics

Reproductive unit is pack

Number packs, not population size critical

extinction process

Social organization, with dominance-based breeding, amplifies effects of

demographic stochasticity on extinction

Behavior population dynamics7

Behavior  Population Dynamics

No. old moose constant = 305

Wolves: MTE = 155 yrs

No. old moose cycles, mean = 305

Wolves: MTE = 105 yrs

Environmental stochasticity

Standard result

Behavior population dynamics8

Behavior  Population Dynamics

Social group size Individual demographic performance

How might group size G influence population dynamics?

Trainor, K.E. & T. Caraco. 2006. Group size, energy budgets and population dynamic complexity. Evolutionary Ecology Research 8:1173-1192.

Behavior population dynamics

Model Assumptions (1)

  • Foragers search in groups, G individuals

  • Rate food-clump discovery

    •  1/(population density)

      Density dependence

    •  G; interference, mutualism

  • Energy consumption random

    • Number clumps, clump size

Behavior population dynamics

Model Assumptions (2)

  • Starvation

    • Consumption  energy requirement

    • Variation between groups

  • Predation while foraging

    • Random independent attacks

    • Increases with consumer density

Behavior population dynamics

Survival & Reproduction

  • Surviving non-breeding season

    • Avert starvation

    • Avoid predation

  • Reproduction: R fixed

    • Survivor + (R-1) offspring

Behavior population dynamics

Return Map (1)

  • nt+1 = F(nt) nt

  • F(nt): Density-dependent reproduction

  • F = R x p(avert starvation |G,n)

    x p(avoid predation |n)

Behavior population dynamics

Stable dynamics: stable node

  • For α > 1, Q = 8, Vc = 1.0; G = 28



Stable dynamics stable node

Stable dynamics: stable node

  • α > 1 (mutualism ?)

    Individual encounters clumps faster as G increases

    Mean energy intake may Increase

    Energy intake variance declines

Behavior population dynamics

Stable Cycle

  • For α = 1.0, Q = 10, Vc = 0.5; G = 32

Stable cycle

Stable Cycle

  • α = 1.0

    Individual encounters clumps independently of G

    Mean energy intake independent of G

    Energy intake variance declines

Behavior population dynamics

Complex dynamics

  • For α = 0.8, Q = 12, Vc = 0.5; G = 20

Complex dynamics

Complex dynamics

  • α < 1 (interference)

  • Individual encounters clumps slower as G increases

    Mean energy intake declines with G

    Chaotic dynamics; often near extinction

Behavior population dynamics9

Behavior  Population Dynamics

Interactions among individual group members

Interference, independence, mutualism

Survival through non-breeding season

Complexity of population dynamics

Likelihood of extinction

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