Learning from the Past for Future Policy: Approaches to Time-series Catch Data Reconstruction

Abstract

Reliable time-series catch and effort data are fundamental for fisheries assessment and management; however, such data are usually not readily available. The Food and Agricultrual Organization (FAO) compiles statistical reports from its member countries, but their reliability is questionable. Several approaches were explored in this study for the reconstruction of time-series catch data using Red Sea fisheries as case studies, starting from 1950. Historical documents, published and unpublished reports, grey literature, databases, surveys, anecdotal information, interviews, and information on processed seafood products were used as sources. When reliable data were available for a number of years, they were used as anchor points to interpolate for missing data, based on transparent assumptions, which use the basic knowledge of the fisheries. Monte Carlo simulations were used to estimate uncertainty in estimates of the means and 95% confidence intervals. The results revealed that actual catches are up to nine times higher than those reported to the FAO. The resulting catch trends provide interesting historical records and important guidance for the development of future fisheries management policies on resource conservation for the benefit of coastal communities.

Keywords: Catch reconstruction, time-series data, Red Sea, historical records, policy