Abstract

Topic: Moose management and monitoring

Evaluating Infrared Cameras as a Tool for Shiras Moose Classification and Population Estimation

Genevieve Elizabeth Fuller¹, Genevieve Fuller², Nick Jaffe³, Brad Banulis², Jonathan Runge⁴, Eric Bergman³

Colorado Parks and Wildlife, 711 Independent Ave., US
Colorado Parks and Wildlife, Grand Junction, Colorado, United States of America
Colorado Parks and Wildlife, Fort Collins, Colorado, United States of America
Colorado Parks and Wildlife, Colorado, United States of America

Abstract
The geographic range of Shiras moose (Alces alces) has expanded along the Rocky Mountains to the south within the lower United States for the last couple of decades through natural migration and trap and transplant operations. How the population has changed over this period is loosely estimated without statistically accurate measures for a lot of moose populations. The extreme variation in vegetative cover, elevation gradients, and habitat use by moose in the Southern Rockies has made population growth difficult to estimate using existing methods. With the advent of newer technological advances in camera technology and unmanned aerial vehicles (UAVs), there may be new methods for effectively monitoring these populations. Through the use of GPS collared moose, we seek to test this new technology to develop better data collection methods for estimating populations and determine calf production on the Grand Mesa in a difficult to survey area of the Colorado Rockies. Moose on the Grand Mesa typically utilize dense mountain shrub habitat with high topographical relief in contrast to the typical riparian willow bottom habitat. With the use of UAVs, we conducted calf-at-heel surveys on collared cow moose in a variety of landscapes to determine the detection rate of calves. Additionally, we are starting to conduct Mark-Resight surveys using drone transects with infrared camera technology to estimate population. This project is in progress and, therefore, has a limited sample size, but preliminary findings suggest that using UAVs to conduct calf-at-heel surveys in challenging environments is more effective than traditional on-the-ground methods.