March 7, 2018 | 3:30 p.m. | Trainer Natural Resources Bldg. Room 170
Why might we choose ice cream on a hot and sunny day but not
a cold wet day or when the line at the parlor is long? Because context matters.
Emerging methods provide new opportunities to evaluate the context of
ecological relationships that we have learned about in theory but have limited
opportunities to assess empirically. For example, many ecological processes are
presumed to be density dependent (e.g., population growth, disease
transmission, and habitat suitability, but the difficulty of estimating the
density of wild animals, particularly beyond values at spatially-imposed scales
(i.e., study area), often prohibits our capacity for inference. Likewise, the
surrounding landscape should impact whether, when and how animals select for or
avoid resources, but we seldom consider context. I’ll use black bears as a case
study to share how we are quantifying spatially explicit densities in the Lower
Peninsula of Michigan, what factors influence those densities, and how
selection of resources changes in different density and landscape contexts.
David Williams, Ph.D., is an Assistant Professor, Department of Fisheries and Wildlife, at Michigan State University and Associate Director at Boone and Crockett Quantitative Wildlife Center. He received his B.S. degree from Eastern Nazarene College, Quincy, Mass., his M.S. degree from the University of Rhode Island, Kingston, R.I. and his Ph.D. from the State University of New York College of Environmental Science and Forestry, Syracuse, N.Y.
Williams' research interests are broad but focus on understanding how landscape heterogeneity influences populations, animal movements, and habitat use and applying that knowledge in the context of larger ecological processes and management decisions. His teaching has included courses on the analysis and management of wildlife populations, wildlife ecology, and applications of geographic information systems to the management of natural resources. His dissertation evaluated the role of white-tailed deer movement behavior in regard to the potential risk of disease spread through a population in New York State. As part of that work, he used a large number of GPS collared individuals to quantify the temporal and spatial structure of direct and indirect contacts between individuals and applied that information to models evaluating the risk of spread of chronic wasting disease.