Megan Cimino
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Articles (21)
Year:
2025
Year:
2025
Year:
2025
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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2024
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2024
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2024
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2024
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2024
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2024
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2023
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2023
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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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2021
Year:
2021
Collaborators (13)
Elliott L. Hazen
University of California
Carlos Moffat
Assistant Professor
University of Delaware
Adena Schonfeld
University of California, Santa Cruz
Lesley Thorne
Assistant Professor
Stony Brook University
Scott Shaffer
Professor
San Jose State University
Scott Doney
Joe D. and Helen J. Kington Professor in Environmental Change
University of Virginia
Barbara Muhling
University of California, Santa Cruz
Desiree Tommasi
-
Matthew S. Savoca
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Deborah K. Steinberg
Virginia Institute of Marine Science
Gregory Larsen
Duke University
David W. Johnston
-
Rubao Ji
Woods Hole Oceanographic Institution
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