Abstract for presentation at Spatial Sciences Institute International Biennial Conference

Adélie penguins have been widely studied as an "indicator" species for the health of the Southern Ocean ecosystem. However, the effects of climatic variability and human activities on Adélie penguin populations are poorly understood. As many of the Adélie penguin colonies used for long-term demographic studies are located near research stations, there is a need to be able to disentangle the effects of human activities and environmental variability on Adélie penguin populations. This study examines whether potential changes in snow cover and/or proximity to human activities best explain the varying population trends of colonies in two breeding localities.
This study uses Geographic Information Systems to generate spatial data of landscape, snow accumulation patterns and proximity to human activity parameters. Snow accumulation patterns are modelled using a complex physically-based GIS model. The parameters are then combined into multivariate statistical models to generate predictions of habitat suitability.
At Whitney Pt, the study site farthest from Casey, modelled snow accumulation parameters explain most of the variation in population trends among colonies (up to 83.7% accuracy, across five classes). At Shirley I, 500 m from Casey, models derived from proximity to human activity parameters correctly predict the trend classes for up to 83.8% of test cells, while models derived from snow accumulation parameters correctly classify up to 57.8% of test cells. This suggests that while snow accumulation patterns are a primary driver of variation in population trends among colonies, the effect of snow accumulation is outweighed by the effects of human activities near Casey.