A Mitigation Hierarchy Approach for Managing Sea Turtle Captures in Small-Scale Fisheries

A Mitigation Hierarchy Approach for Managing Sea Turtle Captures in Small-Scale Fisheries
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DOI:
10.3389/fmars.2020.00049
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发表时间:
2020-02-14
影响因子:
3.7
通讯作者:
Milner-Gulland, E. J.
Milner-Gulland, E. J.
中科院分区:
生物学2区
文献类型:
--
作者:
Arlidge, William N. S.;Squires, Dale;Milner-Gulland, E. J.

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The mitigation hierarchy has been proposed as an overarching framework for managing fisheries and reducing marine megafauna bycatch, but requires empirical application to show its practical utility. Focusing on a small-scale fishing community in Peru as a case study system, we test how the mitigation hierarchy can support efforts to reduce captures of sea turtles in gillnets and link these actions to broader goals for biodiversity. We evaluate three management scenarios by drawing on ecological risk assessment (ERA) and qualitative management strategy evaluation to assess trade-offs between biological, economic, and social considerations. The turtle species of management focus include leatherback turtle Dermochelys coriacea, green turtle Chelonia mydas, and olive ridley turtle Lepidochelys olivacea. Adopting a mixed-methods iterative approach to data collection, we undertook a literature review to collate secondary data on the fishery and the species of turtles captured. We then collected primary data to fill the knowledge gaps identified, including establishing the spatial extent of the fishery and calculating turtle capture rates for the fishery. We identified and evaluated the potential risk that the fishery poses to each turtle species within Pacific East regional management units using a qualitative ERA. Finally, we evaluated potential management strategies to reduce turtle captures, incorporating stakeholder preference from questionnaire-based surveys and considering preliminary estimates of trends across a range of performance indicators. We illustrate how the proposed framework can integrate existing knowledge on an issue of marine megafauna captures, and incorporate established decision-making processes to help identify data gaps. This supports a holistic assessment of management strategies toward biodiversity goals standardized across fisheries and scales.