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Mike Evans

Generally speaking, I am interested in wildlife ecology and human-wildlife dynamics. I am especially interested in understanding the factors governing animals’ resource use and movement behavior and quantitative spatial approaches to describe these processes at multiple scales. My goal is to conduct research answering questions that are directly informative to conservation and management decisions, drawing on multiple disciplines to understand anthropogenic effects on wildlife populations.






















My current dissertation research at UConn concentrates on understanding the effects of human density on black bear population ecology in Connecticut. This work integrates multiple approaches to focus on three complimentary facets of bear ecology – population density, dispersal patterns, and resource selection – in a hierarchical manner to explain emergent patterns in terms of underlying processes. Each component will test hypotheses regarding differences in bear ecology among areas with different levels of human development. First, I am applying spatial mark-recapture methodology using non-invasive genetic data to estimate bear densities along a gradient of human density within the state. This genetic data will be further used to describe differences in the spatial relatedness of individuals along this gradient, to understand how human development may affect bear density through altered dispersal patterns. I will also use stable isotope analysis of bear hairs to estimate anthropogenic composition of bear diets and quantify temporal and spatial differences.


This research is funded primarily with Wildlife Restoration funds from the Connecticut Department of Energy and Environmental Protection (DEEP) Wildlife Division- with whom I am collaborating on this project. We will produce the first robust estimate of the size of Connecticut’s black bear population. Additionally, I am developing methodology based on occupancy modeling using detection data to provide DEEP with easily implemented, non-invasive tools for future bear population monitoring. In quantifying Connecticut’s bear population, my research will offer a mechanistic understanding of bear distribution and density and how these patterns are affected by human populations. This mechanistic perspective can be used to inform proactive bear management, and predict future interaction between bear and human populations.


Other wildlife captured by the trail cameras:





Wildlife and Fisheries Conservation Center
Department of Natural Resources and the Environment
University of Connecticut
1376 Storrs Road, Unit 4087