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17 November 2017 Predicting Anuran Abundance Using an Automated Acoustics Approach
Paul Crump, Keith Berven, Tess E. Youker-Smith, David Skelly, Scott Thomas, Jeff Houlahan
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Abstract

Estimating abundance is critical in many areas of ecology and conservation biology. Despite this, methodological limitations prevent population monitoring at large spatial scales. Automated acoustic methods, such as recording devices and sound recognition models, can determine occupancy and phenology but have not been utilized to estimate abundance in amphibians. Here we evaluate a method to estimate the number of breeding female Wood Frogs (Lithobates sylvaticus) on the basis of the relationship between egg mass abundance and the acoustic activity of males, using an automated recognizer to count and quantify their vocalizations. We collected egg mass abundance data and recorded acoustic activity at sites in New Brunswick, Canada and the northern United States in 2015 and 2016. Egg mass abundance at a site was best predicted by the maximum daily number of calls on the basis of a model selection approach and the predictive ability of models (root mean square error ± 16–19 egg masses or 59–70%). The number of males in the pond was best explained by mean calls per recording in 2016 but in 2015 no acoustic metric explained male abundance well. Although this method shows promise, variation in 1) the quality of the recordings, 2) the timing of vocalization activity, and 3) the sex ratios among sites and years combine to increase the error in abundance estimates. With additional research, this method could be useful for monitoring at large spatial scales and we encourage additional trials of acoustic estimates of abundance, especially where estimates of abundance already exist using other methods.

Copyright 2017 Society for the Study of Amphibians and Reptiles
Paul Crump, Keith Berven, Tess E. Youker-Smith, David Skelly, Scott Thomas, and Jeff Houlahan "Predicting Anuran Abundance Using an Automated Acoustics Approach," Journal of Herpetology 51(4), 582-589, (17 November 2017). https://doi.org/10.1670/16-174
Accepted: 14 August 2017; Published: 17 November 2017
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