Incorporating sampling error in count-based PVA

# Incorporating sampling error in count-based PVA - that...

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Incorporating sampling error  in count-based PVA ESM 211 6 Nov. 2006

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From uncertainty in N to uncertainty in  λ Let be the square of the standard error of Then the squared SE of is: var( ) t N t N 2 2 1 1 1 2 2 1 log log var(log ) var( ) var( ) var( ) var( ) t t t t t t t t t t t N N N N N N N N λ λ λ + + + + ° ° + ° = + log t λ
A simple correction to account for  sampling error Calculate the “average” uncertainty in the growth rate: Subtract this from the raw estimate of environmental stochasticity: 1 2 2 1 1 var( ) var( ) 1 var(log ) q t t t t t N N q N N λ + = + = + ° 2 2 ˆ var(log ) corr σ σ λ = -

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A better correction (White’s method) Set up the equation: where Use solver to find the value of
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Unformatted text preview: that solves the equation ( 29 2 2 1 1 1 1 var( ) q t t t r r q r σ =-=-+ & log and var( ) var(log ) t t t t r r λ = = 2 Sampling error and density dependence Sampling error in N t (independent variable) creates bias in parameter estimates Will tend to underestimate strength of density dependence Estimate of K will be unbiased if mean population size is near K If mean pop size is below K , we will overestimate K , and vice versa Estimate of r will be too small...
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