Abstract
1. Markrecapture studies are often used to estimate adult survival probability , which is an important demographic parameter for long-lived species, as it can have a large impact on the population growth rate. We consider the impact of variation in capture probability among individuals (capture heterogeneity) on the estimation of ? from a markrecapture study and thence on estimation of the asymptotic population growth rate .
2. We review the mechanisms by which capture heterogeneity arises, methods of allowing for it in the analysis, and use simulation to assess the power of detecting three types of capture heterogeneity (two-group heterogeneity, trap-response and temporary emigration) using standard mark-recapture lack-of-fit tests.
3. We use simulation to assess the bias that can arise in the estimation of phi from a mark-recapture study when we do not allow for capture heterogeneity. Using a generic population model, we assess the effect this bias has on estimation of lambda.
4. We use our results on the power of the lack-of-fit tests, together with a measure of the size of the bias relative to the standard error of the estimate of phi, to assess which situations might lead to an important level of undetected bias. Our results suggest that undetected bias is not likely to be an issue when there is trap-response, owing to the lack-of-fit tests having sufficient power to detect any trap-response that could lead to non-negligible bias. For two-group heterogeneity, the worst bias generally occurs when the difference between the capture probabilities for the two groups is moderate and both capture probabilities are low. For temporary emigration, the worst bias generally occurs when the rate of emigration and the capture probability are both low.
5. We illustrate the issues for conservation management using data from studies of Hector's dolphin (Cephalorhynchus hectori) in New Zealand and wolves (Canis lupus) in France.
6. Previous studies have suggested that capture heterogeneity will generally lead to a relatively small bias in the estimate of phi. However, given the high sensitivity of the asymptotic population growth rate to adult survival, a small bias in phi might lead to nontrivial bias in the estimate of lambda.