Combining participatory and socioeconomic approaches to map fishing effort in small-scale fisheries

• Published in: PloS one Vol. 12; no. 5; p. e0176862
• Main Authors: Thiault, Lauric, Collin, Antoine, Chlous, Frédérique, Gelcich, Stefan, Claudet, Joachim
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.05.2017; Public Library of Science (PLoS)
• Subjects: Acoustics; Biodiversity and Ecology; Bioinformatics; Biology and Life Sciences; Commercial fishing; Computer and Information Sciences; Computer Science; Coral reefs; Decision making; Earth Sciences; Ecology and Environmental Sciences; Ecology, environment; Ecosystems; Electromagnetism; Engineering Sciences; Environment and Society; Environmental aspects; Environmental Engineering; Environmental management; Environmental Sciences; Fisheries; Fisheries management; Fishery management; Fishing; Fishing grounds; Fishing zones; Geography; Global Changes; Humanities and Social Sciences; Image Processing; Life Sciences; Machine Learning; Mapping; Marine resources; Methodology; Modeling and Simulation; Models, Theoretical; Museums; Natural resources; Neural and Evolutionary Computing; Optics; Photonic; Polynesia; Population; Signal and Image processing; Small-scale fisheries; Social aspects; Social Sciences; Socio-economic aspects; Socioeconomic Factors; Spatial data; Statistics; Sustainability; France; Coral reefs; Socio-ecology; Fisheries
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0176862

Mapping the spatial allocation of fishing effort while including key stakeholders in the decision making process is essential for effective fisheries management but is difficult to implement in complex small-scale fisheries that are diffuse, informal and multifaceted. Here we present a standardized but flexible approach that combines participatory mapping approaches (fishers' spatial preference for fishing grounds, or fishing suitability) with socioeconomic approaches (spatial extrapolation of social surrogates, or fishing capacity) to generate a comprehensive map of predicted fishing effort. Using a real world case study, in Moorea, French Polynesia, we showed that high predicted fishing effort is not simply located in front of, or close to, main fishing villages with high dependence on marine resources; it also occurs where resource dependency is moderate and generally in near-shore areas and reef passages. The integrated approach we developed can contribute to addressing the recurrent lack of fishing effort spatial data through key stakeholders' (i.e., resource users) participation. It can be tailored to a wide range of social, ecological and data availability contexts, and should help improve place-based management of natural resources.