Title:  Use of Passive Camera Grids to Monitor Activity Patterns of White-tailed Deer
Author(s): Michael T. Biggerstaff, Richard B. Chandler, James T. Johnson, Karl V. Miller, University of Georgia; Michael J. Cherry, Virginia Polytechnic Institute and State University; L. Mike Conner, Joseph W. Jones Ecological Research Center; Charlie H. Killmaster, Georgia Department of Natural Resources
Year: 2018
Abstract: White-tailed deer (Odocoileus virginianus) activity rates are typically calculated using GPS collars on a sample of individuals that may not be representative of the population, but trail cameras allow managers to non-invasively monitor population-level activity patterns. We deployed cameras (one camera/50 acres) on four 2,500-acre grids in Southwestern Georgia with different herd characteristics and management regimes. Between September 2014 and February 2017, we collected 174,048 observations of deer while simultaneously collecting weather data. We used linear mixed effects models to assess the effects of seasonal and environmental factors on activity rates. Diel period was the best predictor of doe behavior across all seasons, with crepuscular activity rates being greater than day or night. The best predictor of adult buck activity in most grids was biological season, with the greatest activity occurring during the rut. However, in the lowest density grid diel period was a better predictor of activity than biological season, with greatest activity occurring during night. During most biological seasons, temperature was the best predictor of doe activity with a negative relationship. Activity of all demographic groups increased during the 2016 drought, while the influence of other individual weather factors differed among biological seasons. Our results support previous research regarding seasonal and diel activity, and provide new insight into influences of weather patterns on deer activity.

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