Stochastic surplus production and length-based assessment models to compare Maximum Sustainable Yield advice for the Moroccan Atlantic chub mackerel

Abstract

Fisheries management needs to ensure that resources are exploited sustainably and the risk of depletion is at an acceptable level. In developing countries, multi-gear, multispecies fisheries often lack data, making conventional stock assessment approaches unsuitable. Data-limited methods have been developed to compare quantitative measures of fishery and stock status with management and biological reference points. In Morocco, despite its large productive ecosystems, most of the fishing stocks remain unassessed. We selected a stock of chub mackerel, considering the availability of survey data, and the fact that it occupies an important place in small pelagic resources. Although this is an important stock, there is a lack of new information on migration and possible exchange between the two stocks of chub mackerel (central and southern). This study presents the first attempt at a combined assessment to provide Maximum Sustainable Yield (MSY) estimates and related indicators of the Moroccan chub mackerel (center and south) by using two of the most used data-limited approaches, the Stochastic Surplus Production model in Continuous Time (SPiCT) and the Length Based Spawning Potential Ratio estimation (LBSPR). These two approaches were applied to analyze the chub mackerel stock state and estimate how far away it was from the estimated harvest relative to MSY using all available time series data. The findings provide valuable information on MSY advice for this stock while remarking the advantages and limitations of two data-limited approaches for the assessment of chub mackerel. The SPiCT results show that the current harvest level closely aligns with the estimated MSY, and that the estimated biomass (B) is below BMSY, and the estimated fishing mortality (F) exceeds FMSY. For LBSPR, most SPR values are lower than the reference point of 40%, which serves as a proxy for BMSY, indicating also a biomass below BMSY. Both models suggest full to overexploited stock status mainly for the period (2016-2020), and this is a different perception to the one provided only by analyzing survey indices fluctuations that indicate critical status over a longer period. Then, this exercise is also pointing out the importance of having different data sources for a better stock status estimation.