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31 May 2019 A Spatially and Temporally Concurrent Comparison of Popular Abundance Estimators for White-tailed Deer
Jacob M. Haus, T. Brian Eyler, Jacob L. Bowman
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The enumeration of Odocoileus virginianus (White-tailed Deer, hereafter, Deer) populations is an important objective for many managers, but no consensus regarding the most appropriate scientific methodology exists. Extensive research has been conducted involving comparisons of multiple methods to evaluate the effectiveness of estimating demographics of free-ranging populations; however, most fail to account for spatial or temporal differences in their comparisons. We estimated the density of an open population of Deer on a strict concurrent spatial and temporal scale during 3 separate 14-day periods (August 2012, February 2013, August 2013) using 4 methods: road-based distance sampling using spotlight surveys, FLIR surveys, and camera surveys using both the Jacobson analysis method or an N-mixture model abundance analysis. Spotlight surveys were affordable but required substantial effort to achieve the precision necessary for management decisions. FLIR surveys had greater detection probabilities relative to spotlight surveys and required less effort to achieve sufficient precision. Jacobson camera surveys appeared to overestimate Deer density and provided no measures of precision. The N-mixture model camera surveys provided sufficient precision and generated point estimate and detection probabilities similar to FLIR surveys. Camera surveys were costlier and more labor intensive relative to road-based surveys. We recommend road-based distance sampling using FLIR technology to estimate Deer density, but managers should understand the limitations and biases associated with any density estimate before incorporating the results into a management program.

Jacob M. Haus, T. Brian Eyler, and Jacob L. Bowman "A Spatially and Temporally Concurrent Comparison of Popular Abundance Estimators for White-tailed Deer," Northeastern Naturalist 26(2), 305-324, (31 May 2019).
Published: 31 May 2019
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