Abstracts

Presented by Susan Witherly - Email: s_witherly@ducks.ca

The boreal forest of northern Alberta supports a large portion of North Americas breeding duck population and is an area of importance to the petroleum industry. Breeding duck surveys in the Boreal Plains ecozone show several ground nesting species are in decline while cavity and overwater nesters are showing both positive and negative population trends since the 1970s. Industry has been hypothesized as a limiting factor that may influence duck populations and species composition in the region, but there has been limited empirical research to test this assertion. Likewise, climate is an important influence on waterfowl population trends and is often used as a covariate when examining other hypotheses. However, while climate data has been aggregated in many ways, the impact of aggregation method on outcomes of hypotheses testing has not been assessed. To evaluate effects of seasonal classification and relationships between ducks and industry, we used mixed effects logistic regression models with a combination of climate, environmental, landscape, and industry variables. Monthly climate data aggregated into annual (one), two, four, and five seasonal classifications were used to generate predictions of duck densities across a gradient of industry measures. Industry variables retained in models varied by seasonal classification, although we observed similar direction and magnitude of trends for specific industrial variables where retained. Cavity and overwater nesting guilds were best modelled with a four-season aggregation, and the ground nesting guild was best modelled with the five-season aggregation. Based on these best aggregation models, results were consistent across nesting guilds, with a small, negative relationship between breeding pairs and cumulative areas of petroleum infrastructure, and a positive relationship between both cumulative infrastructure edge and industrial activity with breeding pairs. We recommend analyses of waterfowl population data include an assessment of the best aggregation of climate data by nesting guild.