1. Many animal species are detected primarily by sound. Although songs, calls and other
sounds are often used for population assessment, as in bird point counts and hydrophone surveys of cetaceans, there are few rigorous methods for estimating population density from acoustic
2. The problem has several parts – distinguishing individuals, adjusting for
individuals that are missed, and adjusting for the area sampled. Spatially explicit capture–recapture (SECR) is a statistical methodology that addresses jointly the second and third parts of
the problem. We have extended SECR to use uncalibrated information from acoustic signals on the distance to each source.
3. We applied this extension of SECR to data from an acoustic survey of ovenbird
Seiurus aurocapilla density in an eastern US deciduous forest with multiple four-microphone arrays. We modelled average power from spectrograms of ovenbird songs
measured within a window of 0·7 s duration and frequencies between 4200 and 5200 Hz.
4. The resulting estimates of the density of singing males
(0·19 ha−1 SE 0·03 ha−1) were consistent with estimates
of the adult male population density from mist-netting (0·36 ha−1 SE 0·12 ha−1). The fitted model predicts sound attenuation of 0·11 dB m−1 (SE
0·01 dB m−1) in excess of losses from spherical spreading.
5. Synthesis and applications. Our method for estimating animal
population density from acoustic signals fills a gap in the census methods available for visually cryptic but vocal taxa, including many species of bird and cetacean. The necessary equipment
is simple and readily available; as few as two microphones may provide adequate estimates, given spatial replication. The method requires that individuals detected at the same place are
acoustically distinguishable and all individuals vocalize during the recording interval, or that the per capita rate of vocalization is known. We believe these
requirements can be met, with suitable field methods, for a significant number of songbird species.