Geography Department, University of Victoria, Victoria, British Columbia, Canada.
School of Environmental Studies, University of Victoria, Victoria, British Columbia, Canada.
PLoS One. 2020 May 19;15(5):e0233339. doi: 10.1371/journal.pone.0233339. eCollection 2020.
Spatial conservation prioritization is used worldwide for designing marine protected areas (MPA) that achieve set conservation objectives with minimal impacts to marine users. People involved in small-scale fisheries (SSF) may incur negative and disproportionate impacts from implementing MPAs, yet limited available data often restricts their representation in MPA planning. Using a Philippines case study, we focus here on the systematic design of a MPA network that aims to minimize and distribute costs equitably for SSF whilst achieving representation targets for biodiversity conservation. The objectives of the study are to: (1) document a participatory mapping approach for collecting SSF data for prioritization using the local knowledge of fishers; and (2) examine how the completeness and resolution of SSF data may affect prioritization outputs in terms of biodiversity representation, spatial efficiency, and distribution equity. In the data-poor region, we conducted participatory mapping workshops with fishers in 79 communities to collect data on the spatial distribution patterns of different SSF fisheries and communities, and employed remote sensing techniques to define coastal habitats, which were targeted for inclusion in MPAs. The datasets were integrated within the decision-support tool Marxan with Zones to develop three scenarios. The SSF data incorporated in each scenario varied based on their completeness (considered all fishing methods or only dominant methods) and resolution (fishing methods itemized by community or municipality). All scenarios derived MPA plans that met representation targets with similar area coverage. The outputs, however, varied in terms of distribution equity, measured by the distribution of opportunity costs (loss of fishing grounds) across different fisheries and communities. Scenarios that did not include minority fisheries or variations between communities, led to inequitable costs. These results highlight the need to incorporate detailed data on SSF at appropriate resolutions, and how this can be achieved through participatory approaches.
空间保护优先化被广泛用于设计海洋保护区 (MPA)，以实现既定的保护目标，同时将对海洋使用者的影响降至最低。参与小规模渔业 (SSF) 的人可能会因实施 MPA 而遭受负面和不成比例的影响，但有限的可用数据通常限制了他们在 MPA 规划中的代表性。本文以菲律宾的案例研究为例，重点介绍了一种 MPA 网络的系统设计，旨在最小化和公平分配 SSF 的成本，同时实现生物多样性保护的代表性目标。研究的目的是：(1) 记录一种参与式绘图方法，用于收集 SSF 数据，以便在优先考虑使用渔民的本地知识；(2) 研究 SSF 数据的完整性和分辨率如何影响生物多样性代表性、空间效率和分配公平性等方面的优先排序结果。在数据匮乏的地区，我们与 79 个社区的渔民一起举办了参与式绘图研讨会，收集了不同 SSF 渔业和社区的空间分布模式数据，并利用遥感技术定义了沿海生境，这些生境被指定纳入 MPA。将数据集整合到决策支持工具 Marxan with Zones 中，以制定三种方案。每个方案中纳入的 SSF 数据基于其完整性（考虑所有捕捞方法或仅主要方法）和分辨率（按社区或直辖市细分的捕捞方法）而有所不同。所有方案都制定了满足代表性目标的 MPA 计划，其覆盖面积相似。然而，输出结果在分配公平性方面有所不同，这是通过不同渔业和社区之间的机会成本（捕捞场损失）分布来衡量的。未纳入少数民族渔业或社区之间差异的方案导致成本分配不均。这些结果强调了需要在适当的分辨率下纳入 SSF 的详细数据，以及如何通过参与式方法实现这一目标。
