  Roads are a widespread feature of landscapes worldwide, and road traffic
sound potentially makes nearby habitat unsuitable for acoustically
communicating organisms. 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.
We seek to characterize the relationship between anthropogenic and biological
sounds in western New York and assess the extent to which available traffic
data explains variability in anthropogenic noise. Recordings were obtained in
the spring of 2016 at 18 sites throughout western New York. We used the Welch
Power Spectral Density (PSD) at low frequencies (0.5-2 kHz) to represent
anthropogenic noise and PSD values at higher frequencies (2-11 kHz) to
represent biological sound. Relationships were modeled using a novel two-stage
hierarchical Bayesian model utilizing beta regression and basis splines. Model
results and map predictions illustrate that anthropogenic noise and biological
sound have an inverse relationship, and anthropogenic noise 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. The use of such data, in combination with the
proposed modeling framework, could have important implications for the
development of sound management policies.
