Using Automated Cameras to Estimate Wildlife Populations

Abstract

Precise and accurate estimates of demographics such as age structure, productivity, and density are necessary in determining habitat and harvest management strategies for wildlife populations. The importance of incorporating detection rates into these demographic estimates cannot be overstated, as failure to include detection can lead to underestimated parameters. Following some introductory material in chapter one, we describe a modeling exercise to explain heterogeneity in detection for passive-infrared (PIR) triggered cameras in chapter two. This chapter illustrates the necessity of modeling camera detection when using PIR sensors in surveying populations for estimating demographics. We then describe a method for estimating Eastern wild turkey (Meleagris gallopavo sylvesteris) population size and structure in Alabama at a relatively large scale using time lapse cameras in chapter three. Through estimating turkey abundance, we determined and estimated important sources of variation within counts relating to detection, distribution, and density. Prior to implementing this method as a monitoring tool, modeling of hypotheses should be improved for fitting turkey count data. Additional density hypotheses should be modeled to explain extra variation in counts. With the proper survey design and hypotheses, this method should provide unbiased and precise estimates of wild turkey populations. In the final chapter, we provide some comprehensive thoughts on using cameras to survey wildlife populations and on population demographics estimation.