Modeling Spatially Explicit Densities of Endangered Avian Species in a Heterogeneous Landscape

Relating population density to spatially explicit habitat characteristics can inform management by directing efforts to areas with lower densities or focusing conservation and land protection on high-density areas. We conducted point-transect surveys for the endangered Golden-cheeked Warbler (Setophaga chrysoparia) and Black-capped Vireo (Vireo atricapilla) in the live-fire region of Fort Hood, Texas. We used mark—recapture distance sampling and combined a Horvitz-Thompson estimator with a habitat-based, resourceselection gradient to estimate spatially explicit density for both species. We detected Golden-cheeked Warblers at 120 locations (202, 197, and 89 detected by primary, secondary, and both observers, respectively) and Black-capped Vireos at 173 locations (241, 255, and 107 detected by primary, secondary, and both observers, respectively). For Golden-cheeked Warblers, the average (± SE) composite detection probability estimate within a 100-m point-sample radius was 0.57 ± 0.14, and for vireos it was 0.24 ± 0.02. Estimated mean density (singing males ha⁻¹) was 0.14 ± 0.03 (95% confidence interval [CI]: 0.08–0.23) and 0.47 ± 0.05 (95% CI: 0.38–0.60) for Golden-cheeked Warblers and Black-capped Vireos, respectively. Our analysis suggested evidence of heterogeneity in the detection process for both species, as well as imperfect detection at distance g(0), both of which would bias estimated densities if ignored. Additionally, both species exhibited spatial variability in estimated densities, with those areas that had higher occurrence probabilities typically having higher estimated density. In the absence of spatially explicit density prediction, managers must treat all losses of potential habitat for endangered species uniformly, despite likely differences in conservation value. Our approach could be used to ascertain areas of changing density in relation to changing habitat conditions over time and space.