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Qualitative correlation of marine mammals with physical and biological parameters in the Ligurian Sea
Authors:D'Amico  A Bergamasco  A Zanasca  P Carniel  S Nacini  E Portunato  N Teloni  V Mori  C Barbanti  R
Institution:SACLANT Undersea Res. Centre, La Spezia, Italy;
Abstract:In support of its acoustic risk mitigation policy, NATO SACLANT Undersea Research Centre (SACLANTCEN) is sponsoring a series of sea trials, entitled "Sirena" to collect a multiyear integrated oceanographic, biological, and hydrographic data set, the goal being to explain, based on these parameters, the distribution of marine mammals found in specific locations. By understanding how ocean dynamics affects the distribution and behavior of whales and the organisms forming the food web upon which the whales feed, it may be possible to conduct acoustic exercises in areas of low cetacean density. The first two Sirena multidisciplinary cruises were conducted in the Ligurian Sea in late summer time frame during 1999 and 2000. The focus of this analysis is to determine whether remotely sensed satellite data can indicate nutrient-rich regions in areas where the oceanography is known and to determine if these regions of higher productivity, coupled with knowledge of cetacean presence from all available sources, could be used as an indicator of marine mammal presence for acoustic risk mitigation purposes. For the two years of data examined, cooler sea-surface temperature data correlated with high levels of chlorophyll production as seen by remotely sensed images. This remotely sensed data correlated well with measured subsurface values of the same parameters. Coincident sightings of three species of marine mammals indicated that fin and sperm whales generally preferred the deep, nutrient-rich portion of the basin while Cuvier's beaked whales preferred a submarine canyon where there is a frontal influence, as indicated from satellite data and historical oceanography. This paper is intended as a contribution to the longer term objective of developing the means to accurately predict cetacean presence from physical oceanographic characteristics.
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