Reporting the accuracy of small-scale fishing data by simply applying Benford’s law

Abstract

Small-scale fisheries (SSFs) play essential economic, social, and cultural roles for many fleets in the Atlantic region. The basis of fisheries assessment and management is the landings reported by observers or fishers. Even though the information from the landings is essential, it can be subject to a fisher’s bias, such as the tendency to inflate catches and the refusal to fill the logs. The feasibility for managers using field surveys to validate these datasets is held up by the high costs, shortage in monitoring, and the lack of prior information. Alternatively, Benford analysis overcomes those limitations since it can be applied directly on the logbook data. This method is growing in popularity, underlining its suitability to many economic and biological fields. Hence, in this study, we inspected small-scale fisheries data by the Benford’s distribution, aiming to validate fish landing data from 27 points in Brazil’s northeastern region over 3 years. Our results suggest that 20% of landings data are considered highly imprecise (misinformation), especially from non-motorized canoes. Also, harbors in remote locations provide poorer quality data, specifically monthly catch values reported by several boats. The way we mine our data affects the sensitivity of the analysis, with monthly data being less prone to be accessed by this method than daily information. As the results match our prior knowledge on the location, we endorse the suitability of the method and reliability for assessing accuracy in fishing data. Hence, we recommend that it ought to be used as an audit tool for SSF landing data aiming to enlighten data reliance and support managers for planning management actions.