Assessing Risk of Noise Pressure on Marine Life Using Bayes Estimator

Abstract

The level of noise in the ocean has been increasing in the last decades, putting at risk a wide variety of marine species that rely on sound for their daily life. An important tool for assessing, and eventually mitigating, the potentially harmful effects of ocean noise on marine species is the so-called risk map. Noise risk maps result from the combination of noise pressure-level distribution and species density in the same time-space framework. A known drawback of the existing risk map methodologies is that they do not allow for direct comparison of the degree of risk between different periods of time, or locations, or between different species. The present study proposes a Bayesian inference-based technique, as an alternative for determining risk maps that return comparable and quantifiable absolute quantities. A simulation of a shallow water seismic survey along the southwest coast of Portugal is used to illustrate the proposed methodology. The test case considered two periods of the year (winter and summer), using as an example the common dolphin (Delphinus delphis) species. The results show that risk maps obtained with the proposed method favorably compare with those obtained with existing methods with, however, the advantage of being based on mean absolute values. These results encourage its use in future studies, targeting different species and/or different areas in order to give some hints for the production of indicators to support ocean protection policies.