Integrating scientific data, local knowledge, and expert knowledge to assess climate vulnerability in fisheries

Abstract

Paper summary generated by OpenAI: This study explores the integration of scientific data, local knowledge, and expert insights to assess climate vulnerability in fisheries, particularly within the context of China, the world’s largest fishing nation. By employing a combination of desktop research, expert surveys, and interviews with fishermen, the research reveals significant differences in climate vulnerability assessments derived from data-driven versus knowledge-driven approaches. Key factors influencing these discrepancies include variations in expertise, assessment indicators, data gaps, and uncertainties related to data quality. The findings underscore the importance of recognizing the strengths and limitations of diverse knowledge systems and propose strategies for enhancing collaborative efforts in participatory climate vulnerability assessments to foster climate-resilient fisheries.