Density influences accuracy of model‐based estimates for a forest songbird

Golden-cheeked Warblers (Setophaga chrysoparia) are endangered songbirds that breed exclusively in the Ashe juniper (Juniperus ashei) and oak (Quercus spp.) woodlands of central Texas. Despite being the focus of numerous studies, we still know little about the size of the range-wide breeding population and how density varies across the spectrum of juniper co-dominated woodlands. Models that have been tested and shown to be accurate are needed to help develop management and conservation guidelines. We evaluated the accuracy and bias of density estimates from binomial mixture models, the dependent double-observer method, and distance sampling by comparing them to actual densities determined by intensive territory monitoring on plots in the Balcones Canyonlands Preserve, Austin, Texas. We found that the binomial mixture models consistently overestimated density by 1.1-3.2 times (actual density = 0.07-0.46 males/ha), and the other two models overestimated by 1.1-29.8 times at low density and underestimated by 0.5-0.9 times at high density plots (actual density = 0.01-0.46 males/ha). The magnitude of error for all models was greatest at sites with few or no birds (<0.15 males/ha), with model performance improving as actual density increased. These non-linear relationships indicate a lack of sensitivity with respect to true changes in density. Until systematic evaluation demonstrates that models such as those we tested provide accurate and unbiased density estimates for a given species over space and time, we recommend additional field tests to validate model-based estimates. Continued model validation and refinement of point-count methods are needed until accurate estimates are obtained across the density spectrum for Golden-cheeked Warblers and other songbird species.