Stochasticity

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Stochasticity

• Environmental and Demographic

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Types of Stochasticity

• Environmental Stochasticity
• Environment varies over time
• Results in variation in birth and death rates
• Results in variation in growth rates (r, ?)
• Can result in lower population growth compared to
  fixed or average r
• Can result in population extinction even if r is
  positive

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Environmental Stochasticity

• No difference in average population size from
  non-variable but actual population trajectory
  could be quite different
• Variance increases as time progresses, increasing
  uncertainty in projection
• Variance sensitive to mean and variance in r
• Fast growing populations more sensitive than slow
  growing, high variance more sensitive than low
  variance populations
• Extinction possible if variance gt 2 times mean r

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Ramas Ecolab Stochasticity

• Ramas Ecolab can model both types of
  stochasticity
• Environmental stochasticity is modeled by
  specifying the standard deviation of R there is
  in the Population window
• You must have more than
• 1 replicate to do this in the
• general information window.

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Environmental Stochasticity
R1.02 St. dev of R0.02 N(0)10
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R1.02 St. dev of R0.5 N(0)10
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R1.2 ST. Dev 0.2 N(0)10
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R1.3 ST. Dev 0.7 N(0)10
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Demographic Stochasticity

• Individuals either die or live, give birth or do
  not. Death and birth are discrete, but birth and
  death rates are per capita.
• One cannot die 50 nor give birth to 2.1 kids.
• Analagous to genetic drift, chance can lead to
  certain outcomes
• Demographic stochasticity is particularly
  important in small populations
• Also sensitive to relative sizes of b and d

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Ecolab and Demographic Stochasticity

• Demographic stochasticity is modeled by checking
  the Use Demographic Stochasticity Box in the
  General Information Window