FIELD COMPARISON OF REMOVAL AND MODIFIED DOUBLE-OBSERVER MODELING FOR ESTIMATING DETECTABILITY AND ABUNDANCE OF BIRDS

Abstract

Abstract For point-count data to reliably index bird abundance or density, estimates must be corrected for variation in detection probabilities across species, observers, and environmental conditions. Removal and double-observer modeling are two recently developed statistical techniques for estimating detection probabilities and bird abundance. We collected point-count data in north-central Indiana and used a Huggins closed-capture model in MARK to directly compare those two methods. We found that when detection probabilities were relatively high for individual observers, the two methods yielded similar estimates of density for nearly all 17 species modeled. However, when true detection probabilities for observers were relatively low, removal estimates of detectability and density were biased high and low, respectively, perhaps because of the effect of low-detection probability on the removal estimator or smaller sample sizes associated with less-skilled observers. In general, we consider removal modeling...