Population dynamics of exploited species in a stochastic environment

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The long-term goals of my research are to improve our understanding of the population dynamics of wildlife species, and to develop new tools to model the effect of human exploitation and natural perturbations on the dynamics of populations based on marked animals. I will focus on multistate capture-mark-recapture (CMR) models with unobservable states, a powerful class of models recently developed. A state can be the condition of an individual at recapture (e.g. breeder/non-breeder) and an unobservable state is when non-breeders are absent from the breeding site, and thus cannot be captured. We address these questions with a unique dataset from an on-going marking program of Greater Snow Geese in the Arctic (since 1989, we banded 60,000 birds). Given our increasing level of understanding of the species, this population is an excellent model system to test general questions in ecological theory and wildlife management. Geese breed in the Arctic, a highly stochastic environment impacted by climate change, and this population is currently subject to a spring hunt, a unique conservation measure in North America because they are considered overabundant. My objectives are to 1- apply multistate models with mixture of information (live encounters and dead recoveries) to test the effects of spring hunt on recruitment rate, age at first breeding, and survival in snow geese; 2- determine if mixture of information allows less restrictive assumptions in multistate models and can be used to examine the relationship between survival and hunting mortality on a seasonal basis; 3- determine to what extent long-lasting aggregations in flocking birds violate the assumption of independence of fate in CMR analyses; 4- continue to develop the Kalman Filter modelling approach, a novel mathematical approach in ecology designed to reduce uncertainties in population model predictions; 5- examine how variability in climatic factors in the Arctic affects vital rates of snow geese and model these effects on population dynamics. The models developed in this project will be applicable to a wide range of animal species exploited by humans. I will train several highly qualified people (PhD, MSc and post-doctorate) in the area of management of arctic wildlife population.