Class
Article
College
S.J. & Jessie E. Quinney College of Natural Resources
Department
Wildland Resources Department
Faculty Mentor
Erica Stuber
Presentation Type
Oral Presentation
Abstract
With current mule deer (Odocoileus hemionus) populations in decline, wildlife managers have increased their efforts on improving factors that limit population growth. In Utah, these efforts have included habitat restoration which is expected to improve conditions for deer. Although previous work has demonstrated that restoration can improve deer populations, it is unknown at what spatial scales restoration efforts have the greatest effect, or what landscape composition of restoration efforts are optimal. Our objectives are to (1) Identify the scale-specific environmental drivers that influence deer use of restored habitat, and (2) Determine the ideal landscape matrix composition that maximizes deer on habitat treatments. To accomplish these objectives, we first performed autocorrelated kernel density home range analysis on GPS location data seasonally and annually from over 3,000 deer during 2014-2021 across Utah. Next, we overlaid estimated home ranges with habitat restoration treatment areas implemented through the Utah Watershed Restoration Initiative to extract an index of relative deer abundance on treatment sites. To identify relevant spatial scales of environmental drivers of relative use-intensity, and ideal landscape composition, we use Bayesian latent indicator scale selection analysis to relate deer use of treatment sites to amounts and diversity of landcover within multiple increasing extents surrounding treatment sites. Our results provide decision support for determining the optimal locations for future restoration treatments to strategically design subsequent landscape-scale management plans for deer.
Location
Logan, UT
Start Date
4-11-2023 10:30 AM
End Date
4-11-2023 11:30 AM
Included in
Identifying “Good Neighborhoods” for Watershed Restoration Initiative Treatments for Mule Deer
Logan, UT
With current mule deer (Odocoileus hemionus) populations in decline, wildlife managers have increased their efforts on improving factors that limit population growth. In Utah, these efforts have included habitat restoration which is expected to improve conditions for deer. Although previous work has demonstrated that restoration can improve deer populations, it is unknown at what spatial scales restoration efforts have the greatest effect, or what landscape composition of restoration efforts are optimal. Our objectives are to (1) Identify the scale-specific environmental drivers that influence deer use of restored habitat, and (2) Determine the ideal landscape matrix composition that maximizes deer on habitat treatments. To accomplish these objectives, we first performed autocorrelated kernel density home range analysis on GPS location data seasonally and annually from over 3,000 deer during 2014-2021 across Utah. Next, we overlaid estimated home ranges with habitat restoration treatment areas implemented through the Utah Watershed Restoration Initiative to extract an index of relative deer abundance on treatment sites. To identify relevant spatial scales of environmental drivers of relative use-intensity, and ideal landscape composition, we use Bayesian latent indicator scale selection analysis to relate deer use of treatment sites to amounts and diversity of landcover within multiple increasing extents surrounding treatment sites. Our results provide decision support for determining the optimal locations for future restoration treatments to strategically design subsequent landscape-scale management plans for deer.