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结合参与式和社会经济方法绘制小规模渔业的捕捞努力量图。

Combining participatory and socioeconomic approaches to map fishing effort in small-scale fisheries.

作者信息

Thiault Lauric, Collin Antoine, Chlous Frédérique, Gelcich Stefan, Claudet Joachim

机构信息

National Center for Scientific Research, PSL Research University, CRIOBE, USR 3278 CNRS-EPHE-UPVD, PSL Research University, Perpignan, France.

Laboratoire d'Excellence CORAIL, France.

出版信息

PLoS One. 2017 May 9;12(5):e0176862. doi: 10.1371/journal.pone.0176862. eCollection 2017.

Abstract

Mapping the spatial allocation of fishing effort while including key stakeholders in the decision making process is essential for effective fisheries management but is difficult to implement in complex small-scale fisheries that are diffuse, informal and multifaceted. Here we present a standardized but flexible approach that combines participatory mapping approaches (fishers' spatial preference for fishing grounds, or fishing suitability) with socioeconomic approaches (spatial extrapolation of social surrogates, or fishing capacity) to generate a comprehensive map of predicted fishing effort. Using a real world case study, in Moorea, French Polynesia, we showed that high predicted fishing effort is not simply located in front of, or close to, main fishing villages with high dependence on marine resources; it also occurs where resource dependency is moderate and generally in near-shore areas and reef passages. The integrated approach we developed can contribute to addressing the recurrent lack of fishing effort spatial data through key stakeholders' (i.e., resource users) participation. It can be tailored to a wide range of social, ecological and data availability contexts, and should help improve place-based management of natural resources.

摘要

在决策过程中纳入关键利益相关者的同时,绘制捕捞努力的空间分布对于有效的渔业管理至关重要,但在分散、非正式且多方面的复杂小规模渔业中却难以实施。在此,我们提出一种标准化但灵活的方法,该方法将参与式绘图方法(渔民对渔场的空间偏好,即捕捞适宜性)与社会经济方法(社会替代指标的空间外推,即捕捞能力)相结合,以生成预测捕捞努力的综合地图。通过法属波利尼西亚莫雷阿岛的一个实际案例研究,我们表明,预测捕捞努力高的区域并不只是位于高度依赖海洋资源的主要渔村前方或附近;在资源依赖性中等的地方以及通常在近岸区域和珊瑚礁通道也会出现。我们开发的综合方法有助于通过关键利益相关者(即资源使用者)的参与来解决捕捞努力空间数据经常缺乏的问题。它可以根据广泛的社会、生态和数据可用性背景进行调整,并且应该有助于改善基于地点的自然资源管理。

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