Abstract

ABSTRACT


Topic: Moose management and monitoring


Efficacy of an Unoccupied Aerial System (UAS) for Large-Scale Population Monitoring of an Unmarked Ungulate Species

Lily Hall1, Franklin B. Sullivan2, Sophia A. Burke2, Michael W. Palace3, Henry Jones4, Remington J. Moll5

  1. Dep. of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA, 7175 Jola Road, US
  2. Earth System Research Center, University of New Hampshire, 8 College Rd, Durham NH 03824, USA
  3. Earth System Research Center, University of New Hampshire, 8 College Rd, Durham NH 03824, USA and Dep. of Earth Science, University of New Hampshire, 56 College Road, Durham, NH 03824, USA
  4. New Hampshire Fish & Game Department, 629B Main Street, Lancaster, NH 03584, USA
  5. Dep. of Natural Resources and the Environment, University of New Hampshire, 56 College Road, Durham, NH 03824, USA

Abstract
BACKGROUND: Accurate estimates of wildlife densities are important for understanding population dynamics and informing management decisions. Recent technological developments such as improvements of unoccupied aerial systems (UASs) and sensors provide novel pathways to estimate wildlife densities. However, these methods require critical evaluation of efficacy. In this research, we estimated moose (Alces alces) density across northern New Hampshire, USA using longwave infrared imagery via UAS sampling. OBJECTIVES: Our objectives were to 1) quantify sightability using UASs flown over unmarked moose populations, and 2) model spatially explicit moose densities in NH. METHODS: We conducted 137 sampling flights across 9 wildlife management units situated in a broader study area of ~8,000 km2 during January and February 2024. RESULTS: We detected 39 moose via live footage during flights resulting in a naïve estimated density of 1.58 moose/km2 (4.10 moose/mi2) across sampled locations. CONCLUSIONS: This density was much higher than expectations based on an index of density from deer hunter surveys. We will refine this density estimate while accounting for imperfect detection by leveraging special “sightability” maneuver flights conducted during the previous winter. We will also compare densities estimated from UAS deployment to estimates from a concurrently deployed camera trap array. To our knowledge, our study is the first application of a thermal sensor via UAS to estimate density of an unmarked ungulate across a large spatial scale (thousands of square kilometers). Our work suggests that UASs offer a promising, albeit field-intensive, method for estimating density without tagged or GPS-collared individuals. We conclude with future directions for improving UAS survey efficiency and reflect upon lessons learned while deploying this technology.