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Nathan Snow
Michigan State University
nsnow@msu.edu


I grew up in rural southwest Michigan, near Kalamazoo. I earned my bachelor's degree in biology with natural resources emphasis at Central Michigan University (B.S., 2004), with a minor in business administration. I moved to Colorado to work as a field technician for Colorado State University and eventually converted to a graduate student.

I earned my master's degree from Colorado State University (M.S., 2009) studying the effects of roads on the San Clemente Island fox off the coast of southern California. In 2009, I was hired as a Biological Research Technician at the National Wildlife Research Center, Wildlife Services, US Department of Agriculture to conduct research for developing management strategies for invasive vertebrate species. I was accepted to Michigan State University as a Boone and Crockett Fellow in the Department of Fisheries and Wildlife and began my Ph.D. research in August 2010.

After completion of my Ph.D. degree, my goal is to establish a career in applied wildlife research at a university or governmental agency, where I can inform wildlife management and policy decisions.


Nathan Snow

Analytical techniques for evaluating and mitigating wildlife-vehicle collisions

Roads are a widespread and increasing feature on most landscapes throughout the world, and their presence can have substantial negative consequences for many species of wildlife. Wildlife-vehicle collisions (WVCs) result in millions of mortalities of wildlife annually, and cause property damage, injury, and occasionally death for humans. Unless we find effective ways to reduce WVCs, this human-wildlife conflict will continue to threaten public support for conservation of wildlife more than any other. Recent studies suggest that landscape-scale factors may be important determinants of where WVCs occur, although these findings are often equivocal because of inconsistent data collection, small study areas, or subjective modeling procedures.

My objective is to improve predictive modeling procedures for identifying influences of WVCs. Specifically, I will: 1) use the landscape to delineate where hotspots of WVCs occur; 2) develop a large-scale predictive model for WVCs of white-tailed deer (Odocoileus virginianus) to inform broad scale management actions in the Midwestern US, and 3) develop spatio-temporal predictive models for locations of moose (Alces alces) WVCs throughout Maine to account for changes in landscapes through time. Results from this research are intended to provide resource managers with better information to reduce pervasive WVC problems throughout the Unites States. Ultimately, this will help support the future of wildlife conservation.


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