Fisheries groups worldwide are concerned that seismic operations negatively affect catch rates within a given area [2, 7, 8]. Despite the paucity of in situ studies addressing this, several countries have adopted precautionary principles in their seismic survey approvals process based on potential impacts to commercially important species [4, 9, 10]. Australia has not yet done this, although the Commonwealth Fisheries Association nominated seismic surveys to be listed as a ‘key threatening process’ under the EPBC Act 1999 [11].
An increasing number of laboratory experiments are being conducted to investigate the effects of seismic airguns on marine organisms, but many of these incorporate intensities or durations of sound exposures that are unlikely to be encountered in the field, particularly for simulated signals in tanks. These studies may simplify their interpretation to simply show effect or no effect (e.g. [12]), where instead results should be interpreted in the context of realistic exposure scenarios and field conditions. This underscores an urgent need to conduct well-designed observational studies and sound monitoring before, during, and after seismic surveys. With this information in hand, stakeholders can develop, or further refine, precautionary policies according to the best information on species-specific responses to known exposure levels of low-frequency sound [13].
The Gippsland Basin is a hub of marine resource activity, including both fisheries and petroleum industries. Marine seismic surveys have been blamed for recent die-offs of scallops in the area [14], as well as mortality of other benthic invertebrates (Stuart Richey, personal communication). Several studies aimed to address this using catch rates and laboratory experiments, but to date no short-term effects ( 2 months) have been found [2, 5, 8]. In addition, none of these studies incorporated concurrent sound monitoring to quantify acoustic conditions at which negative effects may occur. The current study will build on these past studies to incorporate noise modelling and monitoring and non-invasive methods (i.e., AUV) to enable in situ monitoring at the level of communities and individual organisms.