A dynamic approach to estimate the probability of exposure of marine predators to oil exploration seismic surveys over continental shelf waters

Autor: Hückstädt, LA, Schwarz, LK, Friedlaender, AS, Mate, BR, Zerbini, AN, Kennedy, A, Robbins, J, Gales, NJ, Costa, DP
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Endangered Species Research, Vol 42, Pp 185-199 (2020)
Druh dokumentu: article
ISSN: 1863-5407
1613-4796
DOI: 10.3354/esr01048
Popis: The ever-increasing human demand for fossil fuels has resulted in the expansion of oil exploration efforts to waters over the continental shelf. These waters are largely utilized by a complex biological community. Large baleen whales, in particular, utilize continental shelf waters as breeding and calving grounds, foraging grounds, and also as migration corridors. We developed a dynamic approach to estimate the likelihood that individuals from different populations of blue whales Balaenoptera musculus and humpback whales Megaptera novaeangliae could be exposed to idealized, simulated seismic surveys as they move over the continental shelf. Animal tracking data for the different populations were filtered, and behaviors (transit and foraging) were inferred from the tracks using hidden Markov models. We simulated a range of conditions of exposure by having the source of noise affecting a circular area of different radii (5, 25, 50 and 100 km), moving along a gridded transect of 270 and 2500 km2 at a constant speed of 9 km h-1, and starting the simulated surveys every week of the year. Our approach allowed us to identify the temporal variability in the susceptibility of the different populations under study, as we ran the simulations for an entire year, allowing us to identify periods when the surveys would have an intensified effect on whales. Our results highlight the importance of understanding the behavior and ecology of individuals in a site-specific context when considering the likelihood of exposure to anthropogenic disturbances, as the habitat utilization patterns of each population are highly variable.
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