Hierarchical Modelling of Complex Ecological Data

点击翻译按钮获取中文摘要

Ecological systems are complicated by the interplay of processes at distinct levels. Biological and environmental phenomena may affect entire communities, populations within a community, or individuals within a population, and these effects may also vary over time. Moreover, the difficulties in tracking individuals in the wild means that data from these systems are often collected by repeatedly observing marked individuals. In traditional mark-recapture experiments, animals individuals from the population are physically captured and marked with, for example, bands on a birds legs or tags in a fishes fin. More recently, scientists are relying on natural methods to identify individuals with pigmentation patterns that can be identified from photographs or genotype information available from DNA samples in skin, hair, or scat. I develop statistical methods for analysing ecological data that help ecologists and wildlife managers to study the effects of human impacts and other factors in the environment at the individual, population, and community levels. I am particularly interested in creating hierarchical models that capture the multi-level nature of ecological data and on implementing the complex computer algorithms that are necessary, and I will work on three themes within this area in the next five years. First, I will extend available models to account for possible errors when individuals are identified through computerized matching of photographs and develop new computing methods to fit these models to large data sets. Second, I will develop new models to study social behaviour within a population using data from marked individuals and to identify the impacts this behaviour might have on individual movements and the transmission of disease. Finally, I will work on new methods that can be applied generally to analyse very large mark-recapture data sets. The tools I develop will directly impact the work of researchers and wildlife managers studying populations of wild animals. They will allow these researchers to answer new questions about these populations dynamics and the factors that affect ecological systems at different levels. In turn, this will help to manage populations threatened by the effects of climate change, habitat loss, and other human impacts.