Implementation of Bayesian Inference Technique to Address Data Limited Problems in Acology: A Case study with Peary Caribou in Canadian Arctic Archipelago

In the present era, rates of decline in species’ abundance provide some of the most compelling evidence of biodiversity loss rates globally. To address the problem of biodiversity loss, a critical piece of knowledge is the understanding of species interactions with their environment, because environmental variables are generally better predictors of population integrity than intrinsic biological traits. Peary caribou (Rangifer tarandus pearyi), the smallest of all caribou subspecies, are endemic to the Canadian Arctic Archipelago (CAA) and a characteristic example of species at risk. Climate change can affect their habitat availability, as well as the makeup of the entire Arctic ecosystem. Logistical and financial constraints in the CAA often compromise the frequency and the spatial extent of Peary caribou surveys, and therefore inconsistent sampling, errors in measurements, or faults in data acquisition encumber the robust assessment of their population status. To remedy such data gaps in surveys and, improve the robustness of any modelling exercise, I first developed a regression-based imputation framework to reconstruct the Peary caribou time series. The model was able to capture more than 65% of the variability in the dataset. To date, little work has been done to evaluate the net impact of changes from the climate on Peary caribou population dynamics, as it has been argued that the net balance of limited forage accessibility due to severe weather conditions relative to that of increased forage biomass due to prolonged growing season will depend on local climate, floral abundance and composition, and landscape characteristics. Using a two-pronged modelling approach, I characterized the year-to-year variability of the habitat conditions across the CAA, using meteorological variables, landscape features, and resource competition. My dissertation also introduced a spatially explicit modelling framework to examine the strength and nature of the relationships of snow density and vegetation with Peary caribou populations. My dissertation concludes by identifying critical augmentations of the available scientific knowledge that necessitate to design the optimal management actions of Peary caribou populations across the Canadian Arctic Archipelago.Ph.D