9th International Deer Biology Congress

AUTHORS: Sonja A. Christensen, David Williams, and William Porter –Department of Fisheries and Wildlife, Michigan State University

ABSTRACT: Aerial surveys are a practical method for estimating wildlife population densities. However, methods to account for imperfect detection using aerial surveys are limited and not always practical for wildlife managers. Distance sampling is a well-established method for obtaining abundance and density estimates, while accounting for imperfect detection, and has been applied to aerial surveys. N-mixture models are a new analytic tool that have recently been applied to wildlife population estimation. N-mixture models explicitly estimate detection probability and abundance yet have not been applied to aerial surveys of terrestrial free-ranging wildlife. While these methods are fundamentally analogous, there are important conceptual and statistical differences. Application of both methods to real data for simultaneous comparison have been rare and there are no direct comparisons of the relative efficacy of each with real data. Our objectives were to: 1) compare detection and abundance parameters estimated from N-mixture models and distance sampling methods and 2) to test the sensitivity of the spatial unit size inherent in the study design to the N-mixture approach. We evaluated the N-mixture model and distance sampling analytical approaches with data collected from surveys for white-tailed deer (Odocoileus virginianus) conducted during the winter via fixed-wing aircraft. Estimates from both modeling approaches were similar, but N-mixture models provided abundance estimates with greater precision. We found that aerial surveys using N-mixture binomial models are a practical tool for estimating abundance of a free-ranging wildlife population. Further, we found the selected spatial unit size in the N-mixture model had a significant effect on abundance and detection probability estimates, and their associated variance. These results suggest that managers and researchers evaluate the spatial unit used for these models prior to survey implementation. N-mixture models may provide an improved approach to estimate populations from aerial surveys in the future.