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"STOCK ASSESSMENT"
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Surplus production models: a practical review of recent approaches
Increasing the knowledge of approaches to estimate the status of data-limited stocks is of crucial importance since the vast majority of stocks are data-limited, i.e., there is not enough data to conduct a fully integrated statistical catch-at-age or at-length assessment. Among the different data-limited methods, surplus production models (SPMs) are usually considered the most complete data-limited assessment methods since they are the only method that provides a full stock assessment. Due to high interest in the application of SPMs for assessing data-limited stocks, our contribution focuses on providing a practical review of these models and their corresponding characteristics. Additionally, we review the use of the surplus production concept in the “known biomass production models”, highlighting their potential through examples of relevant applications. After a general introduction to the formulation of SPMs, their framework and features, this review focuses on the SPMs most frequently applied by well-known marine research organisations: ASPIC (a stock-production model incorporating covariates), SPiCT (surplus-production model in continuous time) and JABBA (just another Bayesian biomass assessment). For each model, we provide details of its formulation and main features, in addition to evaluating the quality and characteristics of the available software. Based on this information, our comparative study highlights the advantages and disadvantages of each of the three SPMs. The conclusion provides recommendations for their use in the assessment of data-limited stocks, facilitating a decision about whether SPMs constitute an appropriate tool for guidance on and assessment of specific stocks. Finally, we evaluate which of the SPMs considered in this paper should be applied.
Journal Article
Assessing the exploitation status of Johnius belangerii in Zhanjiang Bay
Fishery stock assessment is the basis of fishery management. This study explored the applicability of the Length-Based Spawning Potential Ratio method (LBSPR) to assess the exploitation status of data-limited fisheries. Using data from bottom trawl surveys in Zhanjiang Bay, the study estimated the relative fishing mortality ( F/M ) of Johnius belangerii stock. The results showed that the average lengths at 50% and 95% selectivity ( L S50 and L S95 ) were 105 mm and 145 mm, respectively, both of which are smaller than the lengths at 50% and 95% sexual maturity length ( L 50 = 125 mm and L 95 = 167 mm) determined via the logistic curve. The estimated spawning potential ratio (SPR) was 0.15 significantly below the reference threshold of 0.2. The study recommended the establishment of a minimum size range (137 to 150 mm) length for harvesting Johnius belangerii to enhance their reproductive potential. It also emphasized the importance of scientific monitoring of fishery resources and the ecological environment in Zhanjiang Bay to ensure sustainable management.
Journal Article
New approaches to old problems: how to introduce ecosystem information into modern fisheries management advice
Ecosystem-based fisheries management (EBFM) aims to go beyond single-species management by incorporating ecosystem considerations to guarantee the sustainable use of marine resources. Although many countries have formally committed to the implementation of EBFM, at a practical level progress has been very slow. At the analytical level, many advances have been made, developing sophisticated ecosystem models and, on the other side, rigorous stock assessment models. Yet it is still unclear how these two parallel approaches can be brought together to provide an efficient EBFM. Here we first present the two groups of models, we then discuss ways to integrate both approaches and their resulting possible implications for fisheries advice towards sustainable management, with a special focus on spatially explicit information.
Journal Article
Assessing abundance of populations with limited data: Lessons learned from data-poor fisheries stock assessment
Estimation of population abundances in the absence of good observational data are notoriously difficult, yet urgently needed for biodiversity conservation and sustainable use of natural resources. In the field of fisheries research, management regulations have long demanded population abundance estimates even if data available are sparse, leading to the development of a range of fish stock assessment methods designed for data-poor populations. Here, we present methods developed within the context of fisheries research that can be applied to conduct population abundance estimations when facing data-limitations. We begin the review from the less data-demanding approaches and continue with more data-intensive ones. We discuss the advantages and caveats of these approaches, the challenges and management implications associated with data-poor stock assessments, and we propose the implementation of the Bayesian hierarchical framework as the most promising avenue for future development and improvement of the current practices.
Journal Article
Transforming Data and Capacity-Limited Stock Assessment: Achieving Risk Equivalence with Hierarchical Assessment Frameworks and Auxiliary Data
Ensuring the sustainability of fisheries worldwide requires that scientific advice remain effective even when data and capacity are limited. To address these challenges, we propose a hierarchical assessment framework (HAF) capable of integrating auxiliary information, such as empirical indicators for fishing pressure, within a Bayesian state-space biomass dynamic modelling framework. The aim is to provide risk-equivalent advice to ensure that management does not penalise data-limited fisheries with undue precaution (and loss of potential yield), nor expose them to a higher risk of overexploitation. To achieve this, we evaluated performance using classification skill metrics, such as true skill, for stock status relative to maximum sustainable yield (MSY)-based reference points. Results demonstrate that incorporating auxiliary data, particularly fishing mortality indices from periods of high exploitation, substantially improves the accuracy of stock status classification. Adoption of hierarchical assessment frameworks will support targeted data collection and evidence-based, adaptive fisheries management.
Journal Article
An Evaluation of the Robustness of Length-Based Stock Assessment Approaches for Sustainable Fisheries Management in Data and Capacity Limited Situations
To ensure sustainability, the Ecosystem Approach to Fisheries (EAF) requires the evaluation of the impacts of fisheries beyond the main targeted species, to include those on bycaught, endangered, threatened and protected populations and keystone species. However, traditional stock assessments require extensive datasets that are often unavailable for data-limited fisheries, particularly in small-scale settings or in the Global South. This study evaluates the robustness of length-based approaches for fish stock assessment by comparing simple indicators and quantitative methods using an age-structured Operating Model. Simulations were conducted for a range of scenarios, for a range of life-history types and recruitment and natural mortality dynamics. Results reveal that while length-based approaches can effectively track trends in fishing mortality, performance varies significantly depending on species-specific life histories and assumptions about key parameters. Simple indicators often matched or outperformed complex methods, particularly when assumptions about equilibrium conditions or natural mortality were violated. The study highlights the limitations of length-based methods for classifying stock status relative to reference points, but demonstrates their utility when used with historical reference periods or as part of empirical harvest control rules. The findings provide practical guidance for applying length-based approaches in data-limited fisheries management, ensuring sustainability in data- and capacity-limited situations.
Journal Article
Reproductive Dynamics and Potential Annual Fecundity of South Pacific Albacore Tuna (Thunnus alalunga)
The reproductive biology of albacore tuna, Thunnus alalunga, in the South Pacific Ocean was investigated with samples collected during broad-scale sampling between 2006 and 2011. Histology was done in a single laboratory according to standard protocols and the data analysed using generalized linear mixed-effects models. The sex ratio of albacore was female biased for fish smaller than approximately 60 cm FL and between 85 and 95 cm, and progressively more male biased above 95 cm FL. Spawning activity was synchronised across the region between 10°S and 25°S during the austral spring and summer where sea surface temperatures were ≥24 °C. The average gonad index varied among regions, with fish in easterly longitudes having heavier gonads for their size than fish in westerly longitudes. Albacore, while capable of spawning daily, on average spawn every 1.3 days during the peak spawning months of October to December. Spawning occurs around midnight and the early hours of the morning. Regional variation in spawning frequency and batch fecundity were not significant. The proportion of active females and the spawning fraction increased with length and age, and mature small and young fish were less active at either end of the spawning season than larger, older fish. Batch fecundity estimates ranged from 0.26 to 2.83 million oocytes with a mean relative batch fecundity of 64.4 oocytes per gram of body weight. Predicted batch fecundity and potential annual fecundity increased with both length and age. This extensive set of reproductive parameter estimates provides many of the first quantitative estimates for this population and will substantially improve the quality of biological inputs to the stock assessment for South Pacific albacore.
Journal Article
Population dynamics and movements of Atlantic tarpon, Megalops atlanticus, in the Parnaíba Delta Protected Area, Brazil: challenges for local fishery management planning
Fishery management in Brazil has many challenges, including the engagement of fishers, building institutional (NGO, university, etc.) relationships to carry out research and provide key data for managers, and strengthening the capacity to articulate effective management strategies (policy institution). Here we report on recent work to address some of these challenges for the Atlantic tarpon (Megalops atlanticus) fishery in the Parnaiba Delta Protected Area. These include meetings to create inter-sector communication, citizen science and ethnobiology to support data collection and biological sampling, satellite tagging to discern tarpon movements, and the first data-limited stock assessment. The research occurred between September 2018 and April 2020 in the Parnaíba Delta and adjacent marine area, specifically in the Canárias Islands (MA), Pedra do Sal (PI), and Bitupitá (CE). Gonadosomatic indices (GSI > 5%) of female tarpon suggested that tarpon migrate to the Parnaíba Delta to spawn in the dry season (July–December). These GSI findings corresponded with the ethnobiology results in which the fishers confirmed more intense fishing effort in the dry periods due in part to the added value of the gonads. Satellite-tagged tarpon remained close to the Buraco and Boca da Barra fishery areas, thus, close to the Parnaíba Delta region. The information collected here will enhance the collaborative formulation of an unprecedented management plan for the tarpon fishery in this region.
Journal Article