Biosciences Seminar Series - Spring 2019
16 May 2019 - 1pm - Zoology Museum
Methods for modeling among-animal variability in habitat selection studies
Dr John Fieberg
Our Biosciences Seminar Series continues for the spring term with a talk by Dr John Fieberg from our College of Food, Agricultural and Natural Resource Sciences - CFANS at the University of Minnesota. John is an Associate Professor of Quantitative Ecology and McKnight Presidential Fellow. He is a Biostatistician and Biomathematician, broadly interested in the application of statistical and mathematical models to problems in ecology and natural resource management. A special focus concerns the analysis of wildlife telemetry data, with application to survival, home range, and habitat selection modelling.
Abstract
Understanding the causes and consequences of among-animal variation in habitat selection is key to addressing many fundamental questions in ecology and evolution. Popular conceptual frameworks used to study habitat selection include resource selection functions (RSFs) and step-selection functions (SSFs) estimated using logistic and conditional logistic regression, respectively. Both frameworks compare environmental covariates associated with locations that animals visit with environmental covariates at a set of locations assumed available to the animal. Conceptually, hierarchical models with animal-specific coefficients could be used to accommodate inter-individual heterogeneity when fitting RSFs or SSFs. A review of the literature suggests, however, that RSFs rarely include animal-specific selection coefficients. Further, straightforward and efficient one-step procedures for fitting SSFs with animal-specific coefficients have until now been lacking.
We demonstrate simple methods for exploring among-animal variability in habitat selection parameters using models fit to individual animals. We also describe recent research showing how generalized linear mixed effects models, available in most statistical software packages, can be modified to fit hierarchical RSFs and SSFs in a single step. Together, these examples highlight the benefits of having multiple tools in the toolbox, including simple methods for exploratory data analysis and more sophisticated and comprehensive methods for modeling individual and population-level habitat-selection patterns.
We demonstrate simple methods for exploring among-animal variability in habitat selection parameters using models fit to individual animals. We also describe recent research showing how generalized linear mixed effects models, available in most statistical software packages, can be modified to fit hierarchical RSFs and SSFs in a single step. Together, these examples highlight the benefits of having multiple tools in the toolbox, including simple methods for exploratory data analysis and more sophisticated and comprehensive methods for modeling individual and population-level habitat-selection patterns.
Hope to see many of you - everyone most welcome to attend!
For the list of forthcoming seminars see here
For the list of forthcoming seminars see here
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