Thermal Drones for White-tailed Deer: Precision and accuracy, seasonal limitations, best practices, and spatial applications

Abstract

Unmanned aerial vehicles, or drones, have emerged as an increasingly utilized tool within wildlife population research and management with the potential to collect previously infeasible data. However, the precision and accuracy of population estimates gathered using thermal drones remain unknown. White-tailed deer are an excellent candidate species for evaluating the performance of thermal drones due to their ubiquity, size, and substantial stakeholder interest. Our research evaluated the precision and accuracy of thermal drone surveys of white-tailed deer for use in density estimation in both leaf-on and leaf-off conditions. We also determined best practices in terms of flight transect spacing, season, and minimum sample size. Building on these findings, we then applied thermal drones to gather fine-scale spatial data on white-tailed deer. There is a notable lack of information on the mathematical distribution and space use of wildlife including white-tailed deer. By mathematically describing the distribution of white-tailed deer on the landscape, we can create and test more realistic models as well as account for sightability errors in sampling and disease transmission in management. As such, we have evaluated a novel method of acquiring previously infeasible data and applied it to describe the previously unknown spatial dynamics and relative distribution of white-tailed deer with applications in management, model-building, and study design across a variety of environments.