Fishing pressure and lifespan affect the estimation of growth parameters using ELEFAN

Abstract

Length-based methods of stock assessment to support scientific fisheries management are desirable in data-limited fisheries where formal stock assessments are commonly constrained. Based on length-frequency (LFQ) data, Electronic length frequency analysis (ELEFAN) is widely used to fit growth curves, but the performance of this method is sensitive to various factors especially the quality of data. Fishing pressure is one of the main drivers that modify the length composition of fish stocks, but the consequent effects on ELEFAN are not well understood. This study aims to clarify the role of fishing pressure on the performance of ELEFAN given fish species with different life history traits. We designed a simulation-estimation framework to simulate the population dynamics of short-, medium-, and long-lived fish species, and to evaluate the performance of ELEFAN under varying fishing scenarios. The simulation results demonstrate that ELEFAN is robust to changes in size-structure due to fishing, while its accuracy and precision of outputs depends on the intensity of fishing pressure and the life-history characteristics. The estimates of the parameters of the von-Bertalanffy growth function (VBGF) are reliable in short- and medium-lived species, while for long-lived species, fishing may substantially bias the estimates depending on the intensity of fishing pressure. ELEFAN may yield >70% bias in the estimates of K along with large confidence intervals for long-lived species subject to heavy fishing intensity. ELEFAN will perform such better with prior knowledge about quantities such as lifespan. This study may contribute to the understanding of the reliability of ELEFAN for exploited fisheries and to increasing confidence for adopting ELEFAN in data-limited fisheries.