Methods for modeling population dynamics

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Modern management and conservation of animal populations requires robust, accurate estimates of population dynamics parameters. The analysis of data from new tagging devices (e.g. photographs from camera traps, light-weight tags for smaller animals, GPS tags, genetic tags) as well as the incorporation of multiple data sources (e.g. capture-recapture, citizen science count data, eDNA) has presented statistical methodology challenges for ecologists and managers alike. The consequence of this knowledge gap is often rudimentary analyses that do not harness all information in the data and may provide misleading results. My research program focusses on developing novel statistical methodology and computational products to answer important scientific questions related to population dynamics for conservation and management. Specific short-term goals are to: 1) develop robust estimates of population size and vital rates using approaches that take advantage of multiple data types; 2) develop new methods to incorporate tag loss in capture-recapture models including complete tag loss; 3) develop methods for extended batch marking experiments to incorporate covariates such as age and size information, and tag loss; and 4) explore the robustness of models for count data replicated through time and/or multiple sites with covariate information for wildlife and epidemiological applications in comparison to capture-recapture estimates including determination of parameter redundancy issues. These objectives will be achieved by developing new methods using state of the art methodology such as hidden Markov models (for batch marking and count data models), latent multinomial models (for modelling complete tag loss), and Bayesian hierarchical models (for integrated population models) while critically assessing these and competing approaches through simulation. Efforts will be made to develop methods to assess goodness-of-fit and explore deviations from model assumptions. These methods will be widely applicable, often through collaborative real-world studies in both ecology (for example salmon on the Taku river, Ancient Murrelets on Limestone Island) and epidemiology (homeless populations on Vancouver Island). My long-term research goal is to make these novel statistical methods available to tackle current applied problems faced by Canadian fisheries scientists, wildlife managers, ecologists, and epidemiologists.