A majority of North American breeding habitat for neotropical migrants exists on private lands, requiring monitoring strategies focused on habitat in these private holdings. We outline study designs and protocols using repeated presence–absence surveys across a gradient of patch sizes to develop a range-wide monitoring program for the endangered golden-cheeked warbler (Dendroica chrysoparia) in Texas, USA. We surveyed 200–400 point-count locations across approximately 30 private properties annually from 2005 to 2008. We used data from our surveyed patches (n = 147) and the Ψ (occupancy), p (detection), and γ = 1 − ε parameterization to estimate patch dynamics and associated detection probabilities for golden-cheeked warblers. Patch size had a strong association with patch occupancy, and all patches >160 ha were predicted to be occupied. We found no evidence that large golden-cheeked warbler populations located on public lands in the vicinity of our study area influenced occupancy dynamics. We conducted simulations across a range of detection probabilities to evaluate potential sample sizes for both standard- and removal-based occupancy modeling. Simulations using parameter estimates from our analysis indicated that removal-based sampling is superior to standard sampling. Based on our results, surveying golden-cheeked warbler presence in oak–juniper (Quercus–Juniperus) patches under a removal modeling framework should be considered as one alternative for range-wide monitoring programs because patch-level monitoring would be necessary to estimate proportion of range occupied. Large contiguous patches are rare across the species' range; hence, conservation and management of the mosaic of smaller patches within a landscape context would be required for maintaining species viability. Thus, we recommend the identification of areas where smaller, contiguous patches represent a significant portion of the available habitat within the local landscape and targeting these areas for habitat maintenance and improvement.
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Vol. 74 • No. 1