Predicting patch occupancy in fragmented landscapes at the rangewide scale for an endangered species: an example of an American warbler

Abstract

Aim Our objective was to identify the distribution of the endangered golden-cheeked warbler (Setophaga chrysoparia) in fragmented oak–juniper woodlands by applying a geoadditive semiparametric occupancy model to better assist decision-makers in identifying suitable habitat across the species breeding range on which conservation or mitigation activities can be focused and thus prioritize management and conservation planning. Location Texas, USA. Methods We used repeated double-observer detection/non-detection surveys of randomly selected (n = 287) patches of potential habitat to evaluate warbler patch-scale presence across the species breeding range. We used a geoadditive semiparametric occupancy model with remotely sensed habitat metrics (patch size and landscape composition) to predict patch-scale occupancy of golden-cheeked warblers in the fragmented oak–juniper woodlands of central Texas, USA. Results Our spatially explicit model indicated that golden-cheeked warbler patch occupancy declined from south to north within the breeding range concomitant with reductions in the availability of large habitat patches. We found that 59% of woodland patches, primarily in the northern and central portions of the warbler’s range, were predicted to have occupancy probabilities ≤0.10 with only 3% of patches predicted to have occupancy probabilities >0.90. Our model exhibited high prediction accuracy (area under curve = 0.91) when validated using independently collected warbler occurrence data. Main conclusions We have identified a distinct spatial occurrence gradient for golden-cheeked warblers as well as a relationship between two measurable landscape characteristics. Because habitat-occupancy relationships were key drivers of our model, our results can be used to identify potential areas where conservation actions supporting habitat mitigation can occur and identify areas where conservation of future potential habitat is possible. Additionally, our results can be used to focus resources on maintenance and creation of patches that are more likely to harbour viable local warbler populations.

Using LiDAR‐derived vegetation metrics for high‐resolution, species distribution models for conservation planning

“…Two independent observers conducted surveys at the same time and location (MacKenzie 2006, Laake et al 2011, Collier et al 2012. For each survey occasion, detection/non-detection histories for each sampling location were 10, 11, 01, or 00 (detected by first observer only, by both observers, by second observer only, or not detected, respectively; MacKenzie and Royle 2005).…”

“…We conducted all analyses using the RMark v. 2.1.1 (Laake and Rexstad 2012) interface to MARK (White and Burnham 1999) and developed all map predictions in R 2.15.0 (R Development Core Team 2012). Candidate models included survey day and survey time as covariates for detection as both have been shown to influence warbler and vireo detection rates in Texas (Noa et al 2007, Collier et al 2010, Collier et al 2012. We used an information theoretic approach to model selection and assessed model strength based on Akaike's Information Criterion adjusted for small sample size (AIC c ) and Akaike weights (w i ; Burnham and Anderson 2002).…”

“…Vireos, on the other hand, are thought to prefer mid-successional, mixed-species shrub land, with vegetation '0.5-3 m in height, moderate percent woody cover with substantial breaks or openings in the woody cover, and vireo habitat is often qualitatively described as being structurally heterogeneous (Grzybowski 1995, Campbell 1996. Across the landscape, warbler and vireo habitat can often be found nearby or directly adjacent to one another within a region (Collier et al 2012, McFarland et al 2012a. In some cases, habitat that is thought to be suitable for vireos, if left undisturbed, may succeed into the mature woodland used by warblers; conversely, habitat that is actively managed for vireos may prevent succession into potential warbler habitat.…”

“…Thus, management for these two species can sometimes be viewed as competing, and clearly requires strategic planning if both species are to be effectively managed. Most research on distributions for both species has focused on coarse landscape metrics, such as patch size, patch configuration, and woody cover in the landscape scale (De Boer and Diamond 2006, Magness et al 2006, Collier et al 2012) providing a foundation for predicting patterns of warbler distribution at coarse resolutions over broad spatial extents. Efforts have been less successful at prediction of vireo distributions using coarse landscape metrics (McFarland et al 2012a, Wilsey et al 2012.…”

“…Many SDMs provide general predictions of distribution based on coarse-grain metrics often over broad spatial extents (e.g., patch size) that can reflect coarse patterns of habitat use and provide predictions for broad spatial extents for a variety of conservation and management goals (Betts et al 2007, Collier et al 2012. However, habitat use and resulting distributions can be driven by habitat characteristics assessed by organisms at multiple spatial extents and grains, including fine-grained conditions across relatively small spatial extents (Orians and Wittenberger 1991, Meyer and Thuiller 2006, Chalfoun and Martin 2007.…”