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Integrating fecal DNA and telemetry to estimate wildlife densities in anthropogenic landscapes

Abstract

Density estimation is central to wildlife management efforts but can be challenging in anthropogenically-dominated landscapes due to small parcel sizes, access restrictions, and limited green space. Reliable density estimates are especially important for managing white-tailed deer ( Odocoileus virginianus ), whose high abundance in urbanized areas increases the need for accurate population assessments to guide management and reduce negative human–wildlife interactions. Herein, we evaluated (a) the use of a plot-based spatial capture-recapture sampling design to estimate deer density in developed landscapes and (b) if integrating telemetry data improved the precision or biological inferences of density estimates. We conducted fecal sampling at 2 study areas reflecting different characteristics of the urbanization gradient in Durham and eastern Orange counties, North Carolina: (1) rural (i.e., forested, large parcels) and (2) suburban (i.e., small parcels, limited continuous access, diversity of landscape features). We collected 223 fecal samples during a 3-week sampling period in July and September 2022, resulting in 157 individual deer detected (112 F:45 M). Rural densities were estimated at 54 deer/km 2 (95% CI = 35–84) and suburban densities at 75 deer/km 2 (95% CI = 48–117). Integrating telemetry data allowed estimation of sex-specific space use and densities, which were not possible from fecal data alone; however, precision of total density estimates was similar across integrated and fecal-only analyses. Overall, our results highlighted key trade-offs inherent to plot-based spatial capture-recapture in suburban landscapes, most notably low recapture rates, accessibility challenges to maintain optimal trap spacing, and the importance of considering auxiliary data streams as part of the study design.

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90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 36.06239165248655° to 36.09994142378521° latitude; -79.04434457969145° to -78.98981712126725° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

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BibTeXRIS

Ashley S. Lynn, Mikiah McGinn, Nathan J. Hostetter, Heather Evans, Christopher E. Moorman, Nils Peterson, John C Kilgo, Elizabeth M. Kierepka. 2026-01-27. Integrating fecal DNA and telemetry to estimate wildlife densities in anthropogenic landscapes. https://doi.org/10.1002/wsb.70022

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