Abstract

Many factors affect the number of birds detected on point count surveys of breeding songbirds. The magnitude and importance of these factors are not well understood. We used a bird song simulation system to quantify the effects of detection distance, singing rate, species differences, and observer differences on detection probabilities of birds detected by ear. We simulated 40 point counts consisting of 10 birds per count for five primary species (Black-and-white Warbler Mniotilta varia, Black-throated Blue Warbler Dendroica caerulescens, Black-throated Green Warbler Dendroica virens, Hooded Warbler Wilsonia citrina, and Ovenbird Seiurus aurocapillus) over a range of 15 distances (34-143 m). Songs were played at low (two songs per count) and high (13-21 songs per count) singing rates. Detection probabilities averaged across observers ranged from 0.60 (Black-and-white Warbler) to 0.83 (Hooded Warbler) at the high singing rate and 0.41 (Black-and-white Warbler) to 0.67 (Hooded Warbler) at the low singing rate. Logistic regression analyses indicated that species, singing rate, distance, and observer were all significant factors affecting detection probabilities. Singing rate x species and singing rate X distance interactions were also significant. Simulations of expected counts, based on the best logistic model, indicated that observers detected between 19% (for the worst observer, lowest singing rate, and least detectable species) and 65% (for the best observer, highest singing rate, and most detectable species) of the true population. Detection probabilities on actual point count surveys are likely to vary even more because many sources of variability were controlled in our experiments. These findings strongly support the importance of adjusting measures of avian diversity or abundance from auditory point counts with direct estimates of detection probability.

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