4.7 Review

Multiple values and knowledge integration in indigenous coastal and marine social-ecological systems research: A systematic review

期刊

ECOSYSTEM SERVICES
卷 37, 期 -, 页码 -

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecoser.2019.100910

关键词

Indigenous and local knowledge (ILK); Indigenous people; Ecosystem services; DPSIR; Knowledge integrations

资金

  1. Graduate Program in Sustainability Science - Global Leadership Initiative (GPSS-GLI), at the University of Tokyo

向作者/读者索取更多资源

This systematic review explores patterns in the peer-reviewed literature related to the integration of multiple values in coastal/marine SES in indigenous settings. We extract metadata from 109 papers across five domains: 1) general study characteristics, 2) transdisciplinarity, 3) methodology, 4) SES elements (and their relationships), and 5) values. We use latent class analysis, descriptive statistics, and different visualization tools to elicit, synthesise and highlight the identified research patterns. Our results suggest that the peer-reviewed literature can be categorised across two main research approaches, contextual research and causal research. The former mainly uses qualitative techniques to study the drivers and pressures in such coastal/marine SES, providing a rather comprehensive understanding of these issues. The latter tends to engage better relevant stakeholders as a means of explaining relationships/impacts within such SES. Furthermore, causal research studies employ a more robust methodological portfolio. We argue that cross-fertilization between these distinct research approaches can contribute towards a more effective integration of different knowledge systems and values in indigenous coastal/marine contexts. In particular, contextual research can point where we need to go, while causal research can employ novel tools to assess in depth the multiple values related to the ecosystem services provided by indigenous coastal/marine SES.

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

4.7
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