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Roads are a widespread feature of landscapes worldwide, and road trafficsound potentially makes nearby habitat unsuitable for acousticallycommunicating organisms. It is important to understand the influence of roadsat the soundscape level to mitigate negative impacts of road sound onindividual species as well as subsequent effects on the surrounding landscape.We seek to characterize the relationship between anthropogenic and biologicalsounds in western New York and assess the extent to which available trafficdata explains variability in anthropogenic noise. Recordings were obtained inthe spring of 2016 at 18 sites throughout western New York. We used the WelchPower Spectral Density (PSD) at low frequencies (0.5-2 kHz) to representanthropogenic noise and PSD values at higher frequencies (2-11 kHz) torepresent biological sound. Relationships were modeled using a novel two-stagehierarchical Bayesian model utilizing beta regression and basis splines. Modelresults and map predictions illustrate that anthropogenic noise and biologicalsound have an inverse relationship, and anthropogenic noise is greatest inclose proximity to high traffic volume roads. The predictions have largeuncertainty, resulting from the temporal coarseness of public road data used asa proxy for traffic sound. Results suggest that finer temporal resolutiontraffic sound data, such as crowd-sourced time-indexed traffic data fromgeographic positioning systems, might better account for observed temporalchanges in the soundscape. The use of such data, in combination with theproposed modeling framework, could have important implications for thedevelopment of sound management policies.

Characterizing functional relationships between anthropogenic and biological sounds: A western New York state soundscape case study