Elliott L. Hazen
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Articles (11)
Accurate assessments of human-wildlife risk associated with industrial fishing are critical for the conservation of marine top predators. Automatic Identification System (AIS) data provide a means of mapping fishing and estimating human-wildlife risk; however, risk can be obscured by gaps in the AIS record due to technical issues and intentional disabling. We assessed the extent to which unseen fishing vessel activity due to AIS gaps obscured estimates of overlap between fishing vessel activity and 14 marine predators including sharks, tunas, mammals, seabirds, and critically endangered leatherback turtles. Among vessels equipped with AIS in the northeast Pacific, up to 24% of total predator overlap with fishing vessel activity was unseen, and up to 36% was unseen for some individual species. Waters near 10°N had high unseen overlap with sharks yet low reported shark catch, revealing potential discrepancies in self-reported datasets. Accounting for unseen fishing vessel activity illuminates hidden human-wildlife risk, demonstrating challenges and solutions for transparent and sustainable marine fisheries.
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2024
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2023
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2023
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2022
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2022
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2022
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2022
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2022
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2022
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2022
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2022
Collaborators (12)
Emanuele Di Lorenzo
Professor
Brown University
Rebecca Selden
Assistant Professor
Wellesley College
Nicole Lovenduski
University of Colorado Boulder
Megan Cimino
University of California, Santa Cruz
Alexa Fredston
Assistant Professor
University of California, Santa Cruz
Shirel R. Kahane‐Rapport
-
Jameal F. Samhouri
University of Washington
Jeremy Goldbogen
Associate Professor
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Barbara Muhling
University of California, Santa Cruz
Giulio De Leo
Professor
Stanford University
Max Czapanskiy
Assistant Teaching Professor
University of California, Santa Barbara
Desiree Tommasi
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