Abstract
Several data-poor stock assessment methods have recently been proposed and applied to data-poor fisheries around the world. The Mauritanian pink spiny lobster fishery has a long history of boom and bust dynamics, with large landings, stock collapse, and years-long fishery closures, all happening several times. In this study, we have used catch, fishing efforts, and length-frequency data (LFD) obtained from the fishery in its most recent period of activity, 2015–2019, and historical annual catch records starting in 2006 to fit three data-poor stock assessment methods. These were the length-based Bayesian (LBB) method, which uses LFD exclusively, the Catch-only MSY (CMSY) method, using annual catch data and assumptions about stock resilience, and generalised depletion models in the R package CatDyn combined with Pella-Tomlinson biomass dynamics in a hierarchical inference framework. All three methods presented the stock as overfished. The LBB method produced results that were very pessimistic about stock status but whose reliability was affected by non-constant recruitment. The CMSY method and the hierarchical combination of depletion and Pella-Tomlinson biomass dynamics produced more comparable results, such as similar sustainable harvest rates, but both were affected by large statistical uncertainty. Pella-Tomlinson dynamics in particular demonstrated stock experiencing wide fluctuations in abundance. In spite of uncertain estimates, a clear understanding of the status of the stock as overfished and in need of a biomass rebuilding program emerged as management-useful guidance to steer exploitation of this economically significant resource into sustainability.
Highlights
The resilience of exploited marine species depends largely on their intrinsic capacity to react to increasing fishing pressure
After 20 years of closure, a new active exploitation phase started in 2015 with a fleet that targeted the stock, and yet formal stock assessment has not been implemented to ensure sustainability, leading to high risks of repeating the errors of the past. This is a data-poor fishery and the time series of information available for stock assessment is short, it provides a challenging opportunity to examine the advantages of several stock assessment methods for data-poor fisheries that have been proposed in recent years (Roa-Ureta et al, 2015, 2019; Froese et al, 2017, 2018)
Our results provide useful insights into their applicability in the vast realm of the stock assessment of data-poor and small-scale fisheries
Summary
The resilience of exploited marine species depends largely on their intrinsic capacity to react to increasing fishing pressure. Large slow-growing species with a high age at first maturity are more vulnerable to fishing, exhibiting a larger decrease in abundance for a given fishing pressure (Gislason, 2003; Reynolds et al, 2005; Meissa and Gascuel, 2014) Their exploitation can lead to a sudden collapse of the fishery as it has happened more than once in the pink spiny lobster fishery in Mauritania during its 50 years of exploitation. After 20 years of closure, a new active exploitation phase started in 2015 with a fleet that targeted the stock, and yet formal stock assessment has not been implemented to ensure sustainability, leading to high risks of repeating the errors of the past. Since 1995, the pink spiny lobster has been a by-catch of boats targeting demersal fish and cephalopods in Mauritanian waters (Goñi and Latrouite, 2005)
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