Characterizing functional relationships between biophony and technophony

Abstract

We present a modeling framework to characterize the functional relationship between anthropogenic (technophony) and biological (biophony) sounds in western New York. The proposed framework also facilitates statistical attribution of sound sources to observed technophony and/or biophony, a capability we use to assess technophony variance explained by a road sound variable. Roads are a widespread feature of most landscapes worldwide, and the sound from road traffic potentially makes nearby habitat unsuitable for acoustically communicating organisms. Thus, it is important to understand the influence of roads at the soundscape level to mitigate negative impacts of road sound on individual species as well as subsequent effects on the surrounding landscape. Recordings were obtained in the spring of 2016 at 18 different sites throughout western New York. Model parameter estimates and resulting map predictions illustrate the intuitive result that technophony and biophony have an inverse relationship, and technophony is greatest in close proximity to high traffic volume roads. The predictions have large uncertainty, resulting from the temporal coarseness of public road data used as a proxy for traffic sound. Results suggest that finer temporal resolution traffic sound data, such as crowd-sourced time-indexed traffic data from geographic positioning systems, might better account for observed temporal changes in the soundscape.

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Providence, Rhode Island
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Jeff Doser
PhD Student