4.1 Article

A method to extract fishers' knowledge (FK) to generate evidence for sustainable management of fishing gears

期刊

METHODSX
卷 6, 期 -, 页码 1044-1053

出版社

ELSEVIER
DOI: 10.1016/j.mex.2019.05.008

关键词

Fishers' knowledge; Survey; Fishing gears; Marine pollution; Resource management; Delphi method; Questionnaire

资金

  1. ERDF Interreg VB Northern Periphery and Arctic (NPA) Programme

向作者/读者索取更多资源

The dangerous effects of Abandoned, Lost or Discarded Fishing Gears (ALDFG) is documented in the literature. However, there exists an overall lack of understanding in quantifying the pollution loads of fishing gears (FG) in territorial waters or on the beaches. The lack of data on FG life cycle results in mismanagement of one of the troublesome resources across the globe. In the remote and data-less situations, local stakeholders' knowledge remains the only source of information. Therefore, in this article, we propose: A methodology to extract fishers' knowledge (FK) for generating evidence on FG handling and management practices in Norway. The stepwise approach includes mapping of relevant stakeholders, drafting and finalizing a structured questionnaire using the Delphi method among experts to build the consensus and finally, statistically analyzing the recorded responses from the fishers. The questions are designed to extract both qualitative and quantitative information on purchase, repair, gear loss and disposal rates of commercial FGs. The responses from 114 Norwegian fishers are recorded, analyzed and presented as a part of method validation. The evidence from the survey is then used as an input to coin the regional FG handling and management strategies in Norway. The presented method is proven a robust strategy to retrieve scientific information from the local stakeholders' and can easily be replicated elsewhere to build global evidence around the ALDFG problematic. (C) 2019 The Authors. Published by Elsevier B.V.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.1
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据