Department of Physics, University of Bath, Bath BA2 7AY, UK.
Mar Pollut Bull. 2012 Jul;64(7):1320-9. doi: 10.1016/j.marpolbul.2012.05.004. Epub 2012 Jun 2.
Underwater noise from shipping is a growing presence throughout the world's oceans, and may be subjecting marine fauna to chronic noise exposure with potentially severe long-term consequences. The coincidence of dense shipping activity and sensitive marine ecosystems in coastal environments is of particular concern, and noise assessment methodologies which describe the high temporal variability of sound exposure in these areas are needed. We present a method of characterising sound exposure from shipping using continuous passive acoustic monitoring combined with Automatic Identification System (AIS) shipping data. The method is applied to data recorded in Falmouth Bay, UK. Absolute and relative levels of intermittent ship noise contributions to the 24-h sound exposure level are determined using an adaptive threshold, and the spatial distribution of potential ship sources is then analysed using AIS data. This technique can be used to prioritize shipping noise mitigation strategies in coastal marine environments.
航运产生的水下噪声在全球海洋中越来越普遍,可能使海洋动物长期暴露在慢性噪声中,从而产生潜在的严重后果。在沿海环境中,密集的航运活动与敏感的海洋生态系统同时存在,这尤其令人担忧,因此需要描述这些区域声音暴露的高时间变异性的噪声评估方法。我们提出了一种使用连续被动声学监测和自动识别系统(AIS)船舶数据来描述船舶噪声暴露的方法。该方法应用于在英国法尔茅斯湾记录的数据。使用自适应阈值确定间歇性船舶噪声对 24 小时声暴露水平的绝对和相对水平,然后使用 AIS 数据分析潜在船舶源的空间分布。该技术可用于优先考虑沿海海洋环境中的航运噪声缓解策略。