Factors Affecting Aural Detections of Songbirds

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.

Sources of Measurement Error, Misclassification Error, and Bias in Auditory Avian Point Count Data

“…8). Logistic regression (Alldredge et al 2007b). Note the consistent effect of singing rate on detection probability analyses indicated that species, singing rate, distance, and observer were all significant factors affecting detection probabilities.…”

“…Our approach uses empirical data from field studies of southern Appalachian songbirds (Shriner 2001;Lichstein et al 2002;Brewster 2007) to inform the development of new avian sampling methods Alldredge et al 2007a), and to design field experiments (Simons et al 2007) that assess the factors affecting detection probabilities on auditory counts (Alldredge et al 2007b; Field experiments are conducted using a system for simulating avian census conditions when most birds are identified by sound (Fig. 3).…”

“…Songs were played at low (two songs per count) and high (13-21 songs per count) singing rates (Alldredge et al 2007b). Detection probabilities at 100 m 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 (Fig.…”

“…At least five methods of estimating detection probabilities on avian point counts are currently available (Nichols et al 2008): distance sampling (Buckland et al 2001), multiple-observer methods (Nichols et al 2000;Alldredge et al 2007a), time-of-detection methods Alldredge et al 2007b), double sampling (Bart and Earnst 2002) and repeated count methods (Royle and Nichols 2003;Kery et al 2005). Applications of combined methods are also possible (Kissling and Garton 2006;Alldredge et al 2007a, b).…”

Detecting diversity: emerging methods to estimate species diversity

“…[24]. Surveys are often conducted by different observers, and observer ability, age, and experience affect detectability [25,26]. These factors can also impact whether or not a species is identified correctly, which can result in false positives.…”