Welcome to the technical sessions schedule for the 2015 SEAFWA Annual Meeting.
NEW THIS YEAR! The technical schedule is capable of being sorted by date (i.e, Monday, Nov. 2), track (i.e. Wildlife Technical Sessions), or session (i.e. Wildlife Session #1). You can also search for a presentation title (i.e. Changing Landscapes by Coalition), key term (i.e. striped bass), or presenter last name (i.e. Weaver). The sort and search functions can be found on the navigation panel on the right side of this page. If you hover over the "Schedule" button, you’ll also see different schedule view options (i.e. Grid or Simple). Try selecting each of them to see which view you prefer.
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David W. Kramer, Thomas Prebyl* –University of Georgia; James H. Stickles, Florida Fish and Wildlife Conservation Commission; Brian J. Irwin, U.S. Geological Survey, Georgia Cooperative Fish and Wildlife Research, University of Georgia; Nathan P. Nibbelink, Robert J. Warren, Karl V. Miller –University of Georgia
More than 1 million wildlife-vehicle collisions occur annually in the United States. The majority of these accidents involve white-tailed deer (Odocoileus virginianus), and result in >$4.6 billion in damage and >200 human fatalities. Prior research has used collision locations to assess site-specific as well as landscape features that contribute to risk of deer-vehicle collisions. As an alternative approach, we calculated road-crossing locations from data obtained from 25 GPS-instrumented white-tailed deer near Madison, Georgia (n=154,131 hourly locations). We identified crossing locations by creating movement paths between subsequent GPS points and then intersecting the paths with road locations. We were able to calculate the frequency of deer crossings at any point along a roadway. Using AIC model selection, we determined whether 10 local and landscape variables were successful at identifying areas where higher frequencies of deer crossings were likely to occur. Our findings indicate that traffic volume, distance to riparian areas, and the amount of forested area influenced the frequency of road crossings. Roadways that were predominately located in wooded landscapes and 200-300 meters from riparian areas were crossed frequently. Additionally, we found that areas of low traffic volume (i.e., county roads, etc.) had the highest frequencies of deer crossings. Analyses utilizing records of deer-vehicle collision locations cannot separate the relative contribution of deer crossing rates and traffic volume. Increased frequency of road crossings by deer in low-traffic, forested areas may lead to a greater risk of deer-vehicle collision than would be anticipated based upon traffic volume alone.
