Experimental Analysis of the Auditory Detection Process on Avian Point Counts

Detecting diversity: emerging methods to estimate species diversity

“…As more components of the observation process are considered, variation in the probability of detection increases. [24]. Surveys are often conducted by different observers, and observer ability, age, and experience affect detectability [25,26].…”

“…Surveys that rely on visual and aural cues are particularly susceptible to misclassification [24,26] and small errors in classification can lead to large biases in occupancy [78,79]. Distance from observer, observer error, and simultaneous vocalizations of multiple species are the leading causes of misclassification.…”

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

“…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).…”

“…Measurement error factors relate to observer skill in identifying and localizing individual birds , and hearing ability Dejong 1981, 1992;Sauer et al 1994;Kendall et al 1996;Downes 2004). Signal to noise ratio factors include the spectral qualities of songs (Schieck 1997), song volume, singing rate (Best 1981;Ralph 1981;Skirvin 1981), time of day (Sheilds 1977;Robbins 1981a;Skirvin 1981), the orientation of singing birds (toward or away from observers), (Alldredge et al 2007c) presence of an observer (McShea and Rappole 1997), the number of species and number of individuals singing during a count (Simons et al 2007), pairing status (Krebs et al 1980;Johnson 1983;Cuthill and Hindmarsh 1985;Gibbs and Wenny 1993), stage of nesting cycle (Wilson and Bart 1985), vegetation structure (Diehl 1981;McShea and Rappole 1997;Simons et al 2006;Pacifici et al in press), topography, weather (Mayfield 1981;Robbins 1981b), temperature, humidity, and ambient noise (Simons et al 2007). Systematic variation in any of these factors will impart a systematic bias in count data.…”

“…Although common survey methods are largely unvalidated, most practitioners assume that current methods for estimating detection probability are accurate, and that observer training obviates the need to account for measurement and misclassification errors in point count data. Given the substantial time, effort, and money expended conducting avian point counts to address ecological research and monitoring objectives (Bart 2005;Simons et al 2007), validating current avian sampling methods has enormous practical importance. In this paper we first review factors that influence detection probabilities on auditory counts, and we then summarize key findings of recent field experiments aimed at understanding the factors affecting detection probabilities, and the sources and magnitude of measurement and misclassification errors inherent in several common sampling methods.…”