Population abundance estimates using predictive models are important for describing habitat use and responses to population‐level impacts, evaluating conservation status of a species, and for establishing monitoring programs. The golden‐cheeked warbler (Setophaga chrysoparia) is a neotropical migratory bird that was listed as federally endangered in 1990 because of threats related to loss and fragmentation of its woodland habitat. Since listing, abundance estimates for the species have mainly relied on localized population studies on public lands and qualitative‐based methods. Our goal was to estimate breeding population size of male warblers using a predictive model based on metrics for patches of woodland habitat throughout the species' breeding range. We first conducted occupancy surveys to determine range‐wide distribution. We then conducted standard point‐count surveys on a subset of the initial sampling locations to estimate density of males. Mean observed patch‐specific density was 0.23 males/ha (95% CI = 0.197–0.252, n = 301). We modeled the relationship between patch‐specific density of males and woodland patch characteristics (size and landscape composition) and predicted patch occupancy. The probability of patch occupancy, derived from a model that used patch size and landscape composition as predictor variables while addressing effects of spatial relatedness, best predicted patch‐specific density. We predicted patch‐specific densities as a function of occupancy probability and estimated abundance of male warblers across 63,616 woodland patches accounting for 1.678 million ha of potential warbler habitat. Using a Monte Carlo simulation, our approach yielded a range‐wide male warbler population estimate of 263,339 (95% CI: 223,927–302,620). Our results provide the first abundance estimate using habitat and count data from a sampling design focused on range‐wide inference. Managers can use the resulting model as a tool to support conservation planning and guide recovery efforts. © 2012 The Wildlife Society.

Conserving habitat is increasingly challenging as human populations grow. Remote-sensing technology has provided a means to delineate species' habitat on large spatial scales. However, by combining habitat delineations with predictions of species' occurrence, habitat models can provide additional utility applications for conservation by allowing us to forecast how changing environmental and landscape conditions affect species' occurrence and distribution. We demonstrate how a spatially explicit habitat occupancy model for the golden-cheeked warbler (Setophaga chrysoparia) can be used as an impact assessment and conservation planning tool. We used predictions of patch-level occupancy rates and created several scenarios that simulated the removal or protection of warbler habitats. Resulting changes to habitat structure and availability were used to assess the resulting impacts of removal or protection on the occurrence probability for remaining habitat patches. By recalculating occupancy based on changes to habitat, our approach provides the ability to assess and compare impacts of location and orientation of development so that the least harmful option relative to predicted occurrence can be chosen. Potential applications of our modeling approach are many because our methods provide a useful tool for identifying potential impacts and assisting with mitigation efforts focused on the conservation and management of a species. ß 2012 The Wildlife Society.

No abstract

No abstract