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Global hotspots of shark interactions with industrial longline fisheries
被引:6
作者:
Burns, Echelle S.
[1
,2
,3
]
Bradley, Darcy
[1
,2
,3
]
Thomas, Lennon R.
[1
,2
,3
]
机构:
[1] Univ Calif Santa Barbara, Marine Sci Inst, Santa Barbara, CA 93106 USA
[2] Univ Calif Santa Barbara, Bren Sch Environm Sci & Management, Santa Barbara, CA 93117 USA
[3] Univ Calif Santa Barbara, Environm Markets Lab, Santa Barbara, CA 93106 USA
关键词:
shark catch hotspot;
industrial longline fishing;
machine learning;
random forest;
tRFMO;
MORTALITY CANNOT;
BYCATCH;
PATTERNS;
CONSERVATION;
D O I:
10.3389/fmars.2022.1062447
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Sharks are susceptible to industrial longline fishing due to their slow life histories and association with targeted tuna stocks. Identifying fished areas with high shark interaction risk is vital to protect threatened species. We harmonize shark catch records from global tuna Regional Fisheries Management Organizations (tRFMOs) from 2012-2020 and use machine learning to identify where sharks are most threatened by longline fishing. We find shark catch risk hotspots in all ocean basins, with notable high-risk areas off Southwest Africa and in the Eastern Tropical Pacific. These patterns are mostly driven by more common species such as blue sharks, though risk areas for less common, Endangered and Critically Endangered species are also identified. Clear spatial patterns of shark fishing risk identified here can be leveraged to develop spatial management strategies for threatened populations. Our results also highlight the need for coordination in data collection and dissemination by tRFMOs for effective shark management.
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页数:16
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