Predicting coastal fishing community characteristics in Tanzania using local monitoring data

Abstract

Small-scale marine fisheries in Tanzania provide the main source of subsistence for coastal communities, yet due to poor management, they have been overexploited for decades. These coastal fisheries have historically been described as homogeneous in gear-use and fish community makeup. Yet, regional and local variability in the characteristics of these fishing communities was recently identified with community-based fisheries-dependent data. We proposed a flexible modeling approach that incorporated local monitoring data with spatial data to predict the spatial characteristics of the marine fisheries in Tanzania. The spatial models identified relationships between fishery landings and coral reef, seagrass, and mangrove habitat patch attributes, along with fisher density and a hydrologic index. Furthermore, the predicted spatial characteristics matched previously reported fishery characteristics in both districts. The maps developed by our modeling process provide a means for stakeholders and managers to understand the spatial distribution of their fisheries and in turn, focus on explicitly managing what, how, and where fishers operate. Overall, the flexible modeling approach developed here may act as a first step in incorporating local monitoring data into co-management frameworks, which may promote more sustainable fisheries management strategies in data-poor regions.

Keywords: Co-management; Data-poor; Developing countries; Small-scale fishery (SSF); Spatial model.