A Classical Study of Catch-Effort Models for Hector's Dolphins

Plumage polymorphism and fitness in Swainson's hawks

We examine the maintenance of a plumage polymorphism, variation in plumages among the same age and sex class within a population, in a population of Swainson's Hawks. We take advantage of 32 years of data to examine two prevalent hypotheses used to explain the persistence of morphs: apostatic selection and heterozygous advantage. We investigate differences in fitness among three morph classes of a melanistic trait in Swainson's Hawks: light (7% of the local breeding population), intermediate (57%) and dark (36%). Specifically, we examined morph differences in adult apparent survival, breeding success, annual number of fledglings produced, probability of offspring recruitment into the breeding population and lifetime reproductive success (LRS). If apostatic selection were a factor in maintaining morphs, we would expect that individuals with the least frequent morph would perform best in one or more of these fitness categories. Alternatively, if heterozygous advantage played a role in the maintenance of this polymorphism, we would expect heterozygotes (i.e. intermediate morphs) to have one or more increased rates in these categories. We found no difference in adult apparent survival between morph classes. Similarly, there were no differences in breeding success, nest productivity, LRS or probability of recruitment of offspring between parental morph. We conclude that neither apostatic selection nor heterozygous advantage appear to play a role in maintaining morphs in this population.

Analyzing complex capture-recapture data in the presence of individual and temporal covariates and model uncertainty

SUMMARY

We consider the issue of analyzing complex ecological data in the presence of covariate information and model uncertainty. Several issues can arise when analyzing such data, not least the need to take into account where there are missing covariate values. This is most acutely observed in the presence of time-varying covariates. We consider mark-recapture-recovery data, where the corresponding recapture probabilities are less than unity, so that individuals are not always observed at each capture event. This often leads to a large amount of missing time-varying individual covariate information, because the covariate cannot usually be recorded if an individual is not observed. In addition, we address the problem of model selection over these covariates with missing data. We consider a Bayesian approach, where we are able to deal with large amounts of missing data, by essentially treating the missing values as auxiliary variables. This approach also allows a quantitative comparison of different models via posterior model probabilities, obtained via the reversible jump Markov chain Monte Carlo algorithm. To demonstrate this approach we analyze data relating to Soay sheep, which pose several statistical challenges in fully describing the intricacies of the system.

On the Bayesian estimation of a closed population size in the presence of heterogeneity and model uncertainty

We consider the estimation of the size of a closed population, often of interest for wild animal populations, using a capture-recapture study. The estimate of the total population size can be very sensitive to the choice of model used to fit to the data. We consider a Bayesian approach, in which we consider all eight plausible models initially described by Otis et al. (1978, Wildlife Monographs 62, 1-135) within a single framework, including models containing an individual heterogeneity component. We show how we are able to obtain a model-averaged estimate of the total population, incorporating both parameter and model uncertainty. To illustrate the methodology we initially perform a simulation study and analyze two datasets where the population size is known, before considering a real example relating to a population of dolphins off northeast Scotland.