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

Abstract

The complementary nature of diverse knowledge systems is increasingly recognized as essential for addressing climate challenges in fisheries management. However, current theoretical frameworks often oversimplify knowledge production and integration as a linear tool, overlooking its complexity, interpretative nuances, and inherent uncertainties. This study evaluated and integrated scientific data, institutional expert knowledge, and fishermen’s local knowledge to examine the differences and synergies that emerged from employing these diverse knowledge forms to assess social and ecological vulnerability in fisheries under climate change impacts. China is the world’s largest fishing nation, with fisheries increasingly vulnerable to climate change. It also presents a unique context to examine how science and different forms of knowledge inform decision-making, given its distinct governance structure and data environment. Using a case study from China, we conducted desktop research, surveys of experts, and interviews with fishermen to compare assessment outcomes across approaches. Our findings demonstrate that data-driven and knowledge-driven approaches can yield different results in climate vulnerability assessments (CVAs). We identify four key factors that influence these discrepancies, including (1) varying levels of individual familiarity, expertise, and research efforts across species; (2) divergences in the use of assessment indicators and scoring criteria; (3) data and knowledge gaps related to species biological traits and fisheries socioeconomics; and (4) uncertainties stemming from data quality and knowledge confidence. These findings highlight the critical strengths and limitations of different knowledge forms in informing climate vulnerabilities and offer actionable strategies to enhance collaborative efforts and participatory CVAs to build climate-resilient fisheries.