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Author ORCID Identifier

https://orcid.org/0009-0005-5958-5802

Date Available

7-2-2026

Year of Publication

2026

Document Type

Master's Thesis

Degree Name

Master of Science in Forest and Natural Resource Sciences (MSFNRS)

College

Agriculture, Food and Environment

Department/School/Program

Forestry and Natural Resources

Faculty

John J. Cox

Faculty

Matthew T. Springer

Abstract

Estimation of population parameters is important for wildlife management decisions. Elk reintroduced to southeastern Kentucky experienced early irruptive population growth and are currently monitored using a statewide harvest-based statistical population reconstruction model (SPR) across the Kentucky Elk Restoration Zone (KERZ). Because the SPR model is spatially coarse and difficult to scale to the smaller management units comprising the KERZ, we conducted a spatially explicit capture-recapture study using a clustered camera-trapping array deployed for 10 weeks from June–August 2024 to estimate elk population parameters within Management Unit 4. Due to a lack of resights of GPS-marked elk, population parameters were estimated via unmarked spatial capture-recapture (SCR) models incorporating camera-trap locations, detection counts, and movement information from GPS-collared elk. We modeled environmental variables previously found to be relevant to elk distribution. Abundance (N) was estimated at 37.6 elk (95% HDI: 15.5–77.9) averaged across univariate models, and average density (D) at 0.01 (95% HDI: 0.004–0.021) elk/km2 across models. Proximity to reintroduction sites had the strongest influence on density. Elk harvest following our survey (n = 39) indicated either that almost all elk were harvested from the unit or, more likely, that our findings were underestimated due to a sparse detection history compounded by the inherent challenges of unmarked SCR and the nature of elk sociality. We discuss an alternative interpretation of N for aggregating species based upon average group size, which resulted in an adjusted range of N for our top 3 most explanatory models of 68.2–91.4 elk.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2026.335

Archival?

Archival

Funding Information

This study was supported by the Kentucky Department of Fish and Wildlife Resources in 2024 and the McIntire-Stennis Capacity Grant Program (KY009040) in 2024.

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