March 5, 2021
Species-habitat-association models: Spatial data, predictive models, and ecological insights
Dr. John Fieberg
Associate Professor, UMN Department of Fisheries, Wildlife and Conservation Biology
Abstract
Solutions to the most pressing problems in fisheries, wildlife, and conservation biology require an in-depth understanding of species-habitat associations. Advances in remote sensing, biologging technologies, and new approaches to data collection (e.g., using camera traps and citizen scientists) have expanded the range of species we can monitor and the types of environmental information we can gather; these advances have also resulted in data sets collected at finer temporal scales and over larger spatial extents. Yet, ecologists are confronted with numerous challenges when analyzing species distribution data (e.g., sampling biases, imperfect detection, autocorrelation, and repeated measures). In this talk, I will review statistical methods commonly used to model species-habitat associations and how they attempt to address several of these important issues. I will also highlight opportunities for further statistical method development.
Biosketch
John Fieberg is an Associate Professor in the Department of Fisheries, Wildlife, and Conservation Biology. He specializes in quantitative ecology, and is interested in helping people make robust statistical inferences when confronted with a variety of messy data situations. He recently co-authored a book, Species-Habitat Associations: Spatial data, predictive models, and ecological insights, that reviews the ecology of species-habitat associations, the mechanistic interpretation of existing empirical models, and their shared statistical foundations that can help us draw scientific insights from field data.