The Social Graph—Using Bayesian Networks to Identify Spatial Population Structuring Among Caribou in Subarctic Canada
Steven F. Wilson, Ph.D., Standpoint Decision Support, Inc., 302-99 Chapel Street, Nanaimo, BC V9R 5H3, Canada, email@example.com
Recorded at the 5th Annual BayesiaLab Conference in Paris on September 29, 2017.
Understanding the population structure of wide-ranging wildlife species is critical to their conservation. Populations may require different management actions to address natural and anthropogenic stressors; however, population structuring is not always obvious in the absence of geographic barriers. I applied Bayesian unsupervised learning and variable clustering to investigate spatial relationships among caribou in northwestern Canada, based on 1.3 million GPS telemetry locations collected from >1200 animals over the past 25 years. Results suggested that populations in the north are more continuous than previously suspected, but that there is evidence of population fragmentation in the south. Fragmentation could be explained in part by major river corridors and roads, but landscape disturbance and climate change are likely stressing populations and altering animal movements and gene flow.
Steve Wilson has more than 25 years’ experience working at technical and professional levels in strategic and operational planning for public and private-sector clients. He specializes in quantitative approaches to decision support and policy analysis. Steve holds a Ph.D. in wildlife ecology from the University of British Columbia in Vancouver.