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.
翻译:公路是全世界地貌中一个广泛特征,公路交通状况良好,有可能使附近的生境不适合进行声学交流生物。重要的是要了解公路在声景层的影响,以减轻公路声声对个别物种的不利影响以及随后对周围地貌的影响。我们试图对纽约西部的人为声音和生物声音之间的关系进行定性,并评估现有交通数据解释人为噪音变化的程度。2016年春,在纽约西部18个地点获得记录。我们使用Welch Power Spectural Dentsity(PSD)低频率(0.5-2 kHz)代表高频率(2-11 kHz)的人为噪音和私营部门值,以代表生物声音。我们试图用新型的两阶段级巴伊西亚型模型来描述纽约西部的人为声音和生物声音之间的关系,并评估现有交通量高的混合模型。我们使用低频率(0.2-2 kHz)的Welch Pow Power Sepectral Density(PSD)来代表高频率(2-11 kHz)来代表人为噪音和私营部门的价值。我们用高频(2-11 kHz)来代表生物声音。我们使用这种声音。我们用的人为交通状况时势数据进行定位分析的结果表明,根据精确数据定位的精确数据定位系统进行精确数据定位系统,结果,因此,模型进行精确数据定位数据定位系统可能更好进行精确的定位,因为精确的定位,因此,因此,在重要的地理数据系统进行精确的定位系统进行精确度数据系统在重要交通状况下进行精确定位,因此,因此进行精确定位系统进行精确测量测量测量学学学学学学学学学学学学学学学学。结果。结果。在重要。结果显示:精确测量学学学学学学学学学学学学学学学学学学学学学学学学学学学的精确。结果。