A Socio-Ecological Model Approach to Data Deficiency in Fishery Management: Case Study of Amami-Oshima, Japan

Abstract

Numerous models and tools have been developed in response to the growing recognition of the importance of incorporating fisherpersons’ behavior and knowledge into fisheries management. This study focused on the Scyllarides squammosus fishery in Amami-Oshima, which is currently experiencing a decline with limited available quantitative catch data. To address this data limitation, a fuzzy cognitive map （FCM） model was used to integrate qualitative knowledge from various stakeholders with existing quantitative data. The objectives were to identify the drivers of the fishery and examine management scenarios. The findings revealed that sea surface temperature and COVID-19 were the primary drivers influencing the fishery. Additionally, a scenario analysis demonstrated that increased management measures may initially boost catches but ultimately lead to the collapse of an already struggling fishery. This study highlighted the utility of the FCM for incorporating qualitative and quantitative information, providing insights into the dynamics and potential management strategies of the S. squammosus fishery in Amami-Oshima.