Identifying spawner biomass per‐recruit reference points from life‐history parameters

Analysis of spawning biomass per‐recruit has been widely adopted in fisheries management. Fishing mortality expressed as spawning potential ratio (SPR) often requires a reference point as an appropriate proxy for the fishing mortality that supports a maximum sustainable yield—F_MSY. To date, a single generic level between F_30% and F_40% is routinely used. Using records from stock assessments in the RAM Legacy Database (RAMLD), we confirm that SPR at MSY (SPR_MSY) is a declining function of stock productivity quantified by F_MSY. We then use general linear models (GLM) and Bayesian errors‐in‐variables models (BEIVM) to show that SPR_MSY can be predicted from life‐history parameters (LHPs, including maximum lifespan, age‐ and length‐at‐maturation, growth parameters, natural mortality, and taxonomic Class) as well as gear selectivity. The calculated SPR_MSY ranges from about 13% to 95% with a mean of 47%. About 64% of the stocks in the RAMLD require SPR_MSY > 40%. Modelling SPR_MSY reveals that LHPs plus Class explain 61% of the deviance in SPR_MSY. Faster‐growing, low‐survival, and short‐lived species generally require a high SPR. With equal LHPs, elasmobranchs require about 20% higher SPR_MSY than teleosts. When F_MSY is estimated from fisheries that harvest older fish, increasing the vulnerable age by one year leads to about an 8% increase in SPR_MSY. The BEIVM yields smaller variance and bias than the GLM. The models developed in this study could be used to predict SPR_MSY reference points for new stocks using the same LHPs for calculating F_x%, but without knowledge of the stock‐recruitment parameters.     

Rebuilding Mediterranean fisheries: a new paradigm for ecological sustainability

In Mediterranean European countries, 85% of the assessed stocks are currently overfished compared to a maximum sustainable yield reference value (MSY) while populations of many commercial species are characterized by truncated size‐ and age‐structures. Rebuilding the size‐ and age‐structure of exploited populations is a management objective that combines single species targets such as MSY with specific goals of the ecosystem approach to fisheries management (EAF), preserving community size‐structure and the ecological role of different species. Here, we show that under the current fishing regime, stock productivity and fleet profitability are generally impaired by a combination of high fishing mortality and inadequate selectivity patterns. For most of the stocks analysed, a simple reduction in the current fishing mortality (F_cur) towards an MSY reference value (F_MSY), without any change in the fishing selectivity, will allow neither stock biomass nor fisheries yield and revenue to be maximized. On the contrary, management targets can be achieved only through a radical change in fisheries selectivity. Shifting the size of first capture towards the size at which fish cohorts achieve their maximum biomass, the so‐called optimal length, would produce on average between two and three times higher economic yields and much higher biomass at sea for the exploited stocks. Moreover, it would contribute to restore marine ecosystem structure and resilience to enhance ecosystem services such as reservoirs of biodiversity and functioning food webs.     

Coping with information gaps in stock productivity for rebuilding and achieving maximum sustainable yield for grouper–snapper fisheries

Maintaining fish stocks at optimal levels is a goal of fisheries management worldwide; yet, this goal remains somewhat elusive, even in countries with well‐established fishery data collection, assessment and management systems. Achieving this goal often requires knowledge of stock productivity, which can be challenging to obtain due to both data limitations and the complexities of marine populations. Thus, scientific information can lag behind fishery policy expectations in this regard. Steepness of the stock–recruitment relationship affects delineation of target biomass level reference points, a problem which is often circumvented by using a proxy fishing mortality rate (F) in place of the rate associated with maximum sustainable yield (F_MSY). Because MSY is achieved in the long term only if an F proxy is happenstance with F_MSY, characterizing productivity information probabilistically can support reference point delineation. For demersal stocks of equatorial and tropical regions, we demonstrate how the use of a prior probability distribution for steepness can help identify suitable F proxies. F proxies that reduce spawning biomass per recruit to a target percentage of the unfished quantity (i.e., SPR) of 40% to 50% SPR had the highest probabilities of achieving long‐term MSY. Rebuilding was addressed through closed‐loop simulation of broken‐stick harvest control rules. Similar biomass recovery times were demonstrated for these rules in comparison with more information‐intensive rebuilding plans. Our approach stresses science‐led advancement of policy through a lens of information limitations, which can make the assumptions behind rebuilding plans more transparent and align management expectations with biological outcomes.     

A tale of two seas: a meta‐analysis of crustacean stocks in the NE Atlantic and the Mediterranean Sea

Meta‐analysis of marine biological resources can elucidate general trends and patterns to inform scientists and improve management. Crustacean stocks are indispensable for European and global fisheries; however, studies of their aggregate development have been rare and confined to smaller spatial and temporal scales compared to fish stocks. Here, we study the aggregate development of 63 NE Atlantic and Mediterranean crustacean stocks of six species (Nephrops norvegicus, Pandalus borealis, Parapenaeus longirostris, Aristeus antennatus, Aristaeomorpha foliacea and Squilla mantis) in 1990–2013 using biomass index data from official stock assessments. We implemented a dynamic factor analysis (DFA) to identify common underlying trends in biomass indices and investigate the correlation with the North Atlantic Oscillation (NAO) index. The analysis revealed increasing and decreasing trends in the northern and southern NE Atlantic, respectively, and stable or slowly increasing trends in the Mediterranean, which were not related to NAO. A separate meta‐analysis of the fishing mortality (F) and biomass (B) of 39 analytically assessed crustacean stocks was also carried out to explore their development relative to MSY. NE Atlantic crustacean stocks have been exploited on average close to F_MSY and remained well above B_MSY in 1995–2013, while Mediterranean stocks have been exploited 2–4 times above F_MSY in 2002–2012. Aggregate trends of European crustacean stocks are somewhat opposite to trends of fish stocks, suggesting possible cascading effects. This study highlights the two‐speed fisheries management performance in the northern and southern European seas, despite most stocks being managed in the context of the European Union's Common Fisheries Policy.     

Quantifying uncertainty in the wild‐caught fisheries goal of the Ocean Health Index

Sustainability indices are proliferating, both to help synthesize scientific understanding and inform policy. However, it remains poorly understood how such indices are affected by underlying assumptions of the data and modelling approaches used to compute indicator values. Here, we focus on one such indicator, the fisheries goal within the Ocean Health Index (OHI), which evaluates the sustainable provision of food from wild fisheries. We quantify uncertainty in the fisheries goal status arising from the (a) approach for estimating missing data (i.e., fish stocks with no status) and (b) reliance on a data‐limited method (catch‐MSY) to estimate stock status (i.e., B/B_MSY). We also compare several other models to estimate B/B_MSY, including an ensemble approach, to determine whether alternative models might reduce uncertainty and bias. We find that the current OHI fisheries goal model results in overly optimistic fisheries goal statuses. Uncertainty and bias can be reduced by (a) using a mean (vs. median) gap‐filling approach to estimate missing stock scores and (b) estimating fisheries status using the central tendency from a simulated distribution of status scores generated by a bootstrap approach that incorporates error in B/B_MSY. This multitiered approach to measure and describe uncertainty improves the transparency and interpretation of the indicator and allows us to better understand uncertainty around our OHI fisheries model and outputs for country‐level interpretation and use.     

Generic harvest control rules for European fisheries

In European fisheries, most stocks are overfished and many are below safe biological limits, resulting in a call from the European Commission for new long‐term fisheries management plans. Here, we propose a set of intuitive harvest control rules that are economically sound, compliant with international fishery agreements, based on relevant international experiences, supportive of ecosystem‐based fisheries management and compatible with the biology of the fish stocks. The rules are based on the concept of maximum sustainable yield (MSY), with a precautionary target biomass that is 30% larger than that which produces MSY and with annual catches of 91%MSY. Allowable catches decline steeply when stocks fall below MSY levels and are set to zero when stocks fall below half of MSY levels. We show that the proposed rules could have prevented the collapse of the North Sea herring in the 1970s and that they can deal with strong cyclic variations in recruitment such as known for blue whiting. Compared to the current system, these rules would lead to higher long‐term catches from larger stocks at lower cost and with less adverse environmental impact.     

Examining common assumptions about recruitment: a meta‐analysis of recruitment dynamics for worldwide marine fisheries

Assumptions about the future productivity of a stock are necessary to calculate sustainable catches in fisheries management. Fisheries scientists often assume the number of young fish entering a population (recruitment) is related to the biomass of spawning adults and that recruitment dynamics do not change over time. Thus, managers often use a target biomass based on spawning biomass as the basis for calculating sustainable catches. However, we show recruitment and spawning biomass are not positively related over the observed range of stock sizes for 61% of 224 stocks in the RAM Legacy Stock Assessment Database. Furthermore, 85% of stocks for which spawning biomass may not drive recruitment dynamics over the observed ranges exhibit shifts in average recruitment, which is often used in proxies for target biomasses. Our results suggest that the environment more strongly influences recruitment than spawning biomass over the observed stock sizes for many stocks. Management often endeavours to maintain stock sizes within the observed ranges, so methods for setting management targets that include changes within an ecosystem may better define the status of some stocks, particularly as climate changes.     

The unfulfilled potential of fisheries selectivity to promote sustainability

The recent reform of the Common Fisheries Policy (CFP) in Europe highlights the need for improvements in both species and size selectivity. Regarding size selectivity, shifting selectivity towards older/larger fish avoids both growth and recruitment overfishing and reduces unwanted catches. However, the benefits to fish stocks and fishery yields from increasing age/size‐at‐selection are still being challenged and the relative importance of selectivity compared to that of exploitation rate remains unclear. Consequently, exploitation rate regulations continue to dominate management. Here, an age‐structured population model parameterized for a wide range of stocks is used to investigate the effects of selectivity on spawning stock biomass (SSB) and yield. The generic effect of selectivity on SSB and yield over a wide range of stocks is compared to the respective relative effects of exploitation rate and several biological parameters. We show that yield is mainly driven by biological parameters, while SSB is mostly affected by the exploitation regime (i.e. exploitation rate and selectivity). Our analysis highlights the importance of selectivity for fisheries sustainability. Catching fish a year or more after they mature combined with an intermediate exploitation rate (F ≈ 0.3) promotes high sustainable yields at low levels of stock depletion. Examination of the empirical exploitation regimes of 31 NE Atlantic stocks illustrates the unfulfilled potential of most stocks for higher sustainable yields due to high juvenile selection, thus underscoring the importance of protecting juveniles. Explicitly incorporating selectivity scenarios in fisheries advice would allow the identification of optimal exploitation regimes and benefit results‐based management.     

Dynamic angling effort influences the value of minimum‐length limits to prevent recruitment overfishing

Recruitment overfishing occurs when stocks are fished to a level where recruitment declines proportionally with adult abundance. Although typically considered a commercial fishery problem, recruitment overfishing can also occur in freshwater recreational fisheries. This study developed an age‐structured model to determine if minimum‐length limits can prevent recruitment overfishing in black crappie, Pomoxis nigromaculatus (LeSueur), and walleye, Sander vitreus (Mitchill) fisheries considering angling effort response to changes in fish abundance. Simulations showed that minimum‐length limits prevented recruitment overfishing of black crappie and walleye, but larger minimum‐length limits were required if angler effort showed only weak responses to changes in fish abundance. Low angler‐effort responsiveness caused fishing mortality rates to remain high when stock abundance declined. By contrast, at high effort responsiveness, anglers left the fishery in response to stock declines and allowed stocks to recover. Angler effort for black crappie and walleye fisheries suggested that angler effort could be highly responsive for some fisheries and relatively stable for others, thereby increasing the risk of recruitment overfishing in real fisheries. Recruitment overfishing should be considered seriously in freshwater recreational fisheries, and more studies are needed to evaluate the responsiveness of angler effort to changes in fish abundance.     

Estimating fisheries reference points from catch and resilience

This study presents a Monte Carlo method (CMSY) for estimating fisheries reference points from catch, resilience and qualitative stock status information on data‐limited stocks. It also presents a Bayesian state‐space implementation of the Schaefer production model (BSM), fitted to catch and biomass or catch‐per‐unit‐of‐effort (CPUE) data. Special emphasis was given to derive informative priors for productivity, unexploited stock size, catchability and biomass from population dynamics theory. Both models gave good predictions of the maximum intrinsic rate of population increase r, unexploited stock size k and maximum sustainable yield MSY when validated against simulated data with known parameter values. CMSY provided, in addition, reasonable predictions of relative biomass and exploitation rate. Both models were evaluated against 128 real stocks, where estimates of biomass were available from full stock assessments. BSM estimates of r, k and MSY were used as benchmarks for the respective CMSY estimates and were not significantly different in 76% of the stocks. A similar test against 28 data‐limited stocks, where CPUE instead of biomass was available, showed that BSM and CMSY estimates of r, k and MSY were not significantly different in 89% of the stocks. Both CMSY and BSM combine the production model with a simple stock–recruitment model, accounting for reduced recruitment at severely depleted stock sizes.     

Revisiting safe biological limits in fisheries

The appropriateness of three official fisheries management reference points used in the north‐east Atlantic was investigated: (i) the smallest stock size that is still within safe biological limits (SSB_pa), (ii) the maximum sustainable rate of exploitation (F_msy) and (iii) the age at first capture. As for (i), in 45% of the examined stocks, the official value for SSB_pa was below the consensus estimates determined from three different methods. With respect to (ii), the official estimates of F_msy exceeded natural mortality M in 76% of the stocks, although M is widely regarded as natural upper limit for F_msy. And regarding (iii), the age at first capture was below the age at maturity in 74% of the stocks. No official estimates of the stock size (SSB_msy) that can produce the maximum sustainable yield (MSY) are available for the north‐east Atlantic. An analysis of stocks from other areas confirmed that twice SSB_pa provides a reasonable preliminary estimate. Comparing stock sizes in 2013 against this proxy showed that 88% were below the level that can produce MSY. Also, 52% of the stocks were outside of safe biological limits, and 12% were severely depleted. Fishing mortality in 2013 exceeded natural mortality in 73% of the stocks, including those that were severely depleted. These results point to the urgent need to re‐assess fisheries reference points in the north‐east Atlantic and to implement the regulations of the new European Common Fisheries Policy regarding sustainable fishing pressure, healthy stock sizes and adult age/size at first capture.     

Examining the knowledge base and status of commercially exploited marine species with the RAM Legacy Stock Assessment Database

Meta‐analyses of stock assessments can provide novel insight into marine population dynamics and the status of fished species, but the world’s main stock assessment database (the Myers Stock‐Recruitment Database) is now outdated. To facilitate new analyses, we developed a new database, the RAM Legacy Stock Assessment Database, for commercially exploited marine fishes and invertebrates. Time series of total biomass, spawner biomass, recruits, fishing mortality and catch/landings form the core of the database. Assessments were assembled from 21 national and international management agencies for a total of 331 stocks (295 fish stocks representing 46 families and 36 invertebrate stocks representing 12 families), including nine of the world’s 10 largest fisheries. Stock assessments were available from 27 large marine ecosystems, the Caspian Sea and four High Seas regions, and include the Atlantic, Pacific, Indian, Arctic and Antarctic Oceans. Most assessments came from the USA, Europe, Canada, New Zealand and Australia. Assessed marine stocks represent a small proportion of harvested fish taxa (16%), and an even smaller proportion of marine fish biodiversity (1%), but provide high‐quality data for intensively studied stocks. The database provides new insight into the status of exploited populations: 58% of stocks with reference points (n = 214) were estimated to be below the biomass resulting in maximum sustainable yield (B_MSY) and 30% had exploitation levels above the exploitation rate resulting in maximum sustainable yield (U_MSY). We anticipate that the database will facilitate new research in population dynamics and fishery management, and we encourage further data contributions from stock assessment scientists.     

Improving estimates of population status and trend with superensemble models

Fishery managers must often reconcile conflicting estimates of population status and trend. Superensemble models, commonly used in climate and weather forecasting, may provide an effective solution. This approach uses predictions from multiple models as covariates in an additional “superensemble” model fitted to known data. We evaluated the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries. We fit four widely applicable data‐limited models that estimate stock biomass relative to equilibrium biomass at maximum sustainable yield (B/B_MSY). We combined these estimates of recent fishery status and trends in B/B_MSY with four ensemble methods: an ensemble average and three superensembles (a linear model, a random forest and a boosted regression tree). We trained our superensembles on 5,760 simulated stocks and tested them with cross‐validation and against a global database of 249 stock assessments. Ensemble methods substantially improved estimates of population status and trend. Random forest and boosted regression trees performed the best at estimating population status: inaccuracy (median absolute proportional error) decreased from 0.42 – 0.56 to 0.32 – 0.33, rank‐order correlation between predicted and true status improved from 0.02 – 0.32 to 0.44 – 0.48 and bias (median proportional error) declined from ?0.22 – 0.31 to ?0.12 – 0.03. We found similar improvements when predicting trend and when applying the simulation‐trained superensembles to catch data for global fish stocks. Superensembles can optimally leverage multiple model predictions; however, they must be tested, formed from a diverse set of accurate models and built on a data set representative of the populations to which they are applied.     

东南太平洋竹?鱼资源评估与捕捞控制规则模拟研究

以东南太平洋智利竹鱼为对象、以资源量动态模型为基础,使用模拟方法构建了"真实"的智利竹鱼种群及其渔业,评估了观测误差和过程误差对智利竹鱼资源评估和管理的影响。模拟的"真实"的智利竹鱼种群及其渔业结果显示,1997—2014年太平洋智利竹鱼资源量总体上呈逐年下降趋势,且远低于B_(MSY)的50%;捕捞死亡系数波动剧烈,仅在2012—2014年低于F_(MSY)且相对稳定。渔业资源评估模拟结果显示,观测误差和过程误差使资源量和B_(MSY)被低估,捕捞死亡系数和F_(MSY)被高估,且随机误差越大,资源量、B_(MSY)被低估,而捕捞死亡系数、F_(MSY)被高估的程度越大。渔业管理模拟的结果表明,捕捞控制规则采用恒定捕捞死亡系数时,未来10年基于50%2014年捕捞死亡系数的管理措施为最佳管理措施。由于捕捞死亡系数被高估,最佳管理措施实施后使得年总可捕捞量高于预期,而年资源量低于预期,资源量增长或恢复的速度变慢,资源可能同时处于过度捕捞状态和正遭受过度捕捞。过度捕捞的风险与随机观测误差和过程误差的大小成正比。     

Guidelines for incorporating fish distribution shifts into a fisheries management context

The impacts of climate change have been demonstrated to influence fisheries resources. One way climate has affected fish stocks is via persistent shifts in spatio‐temporal distribution. Although examples of climate‐forced distribution shifts abound, it is unclear how these shifts are practically accounted for in the management of fish stocks. In particular, how can we take into account shifting stock distribution in the context of stock assessments and their management outputs? Here, we discuss examples of the types of fish stock distribution shifts that can occur. We then propose a decision tree framework of how shifting stock distributions can be addressed. Generally, the approaches for addressing such shifts fall into one of three main alternatives: re‐evaluate stock identification, re‐evaluate a stock unit area, or implement spatially explicit modelling. We conclude by asserting that the approach recommended here is feasible with existing information and as such fisheries managers should be able to begin addressing the role of changes in stock distribution in these fish stocks. The implications of not doing so could be notably undesirable.     

An assessment of vulnerability in Alaska groundfish

Federal fishery management rules in the United States have recently changed, necessitating an examination of which fish stocks require annual catch limits and how appropriate stock complexes are formed. We used an analytical approach termed productivity-susceptibility analysis (PSA) to analyze the vulnerability of federally managed Alaska groundfish stocks to overfishing. The focus of the effort was non-target stocks that have limited data available for determining stock status and vulnerability. The PSA approach was originally created to assess risks to bycatch in Australian trawl fisheries and compares productivity attributes (e.g. life-history traits) to factors that determine a stock's susceptibility to fishing impacts, producing a combined score indicative of a stock's relative vulnerability to overfishing. We used a form of the PSA developed by a working group from the U.S. National Marine Fisheries Service specifically for use in assessing vulnerability in federally managed fisheries. Alaska groundfish displayed a wide range of vulnerability scores, and this result was mainly due to variability in productivity scores. Susceptibility scores varied less than productivity scores and were centered on an intermediate value. The inclusion of target stocks in the PSA was valuable for assessing the relative vulnerability of the non-target stocks. Sensitivity analyses indicated that PSAs respond differently to changes in attribute scores depending on their initial conditions, and managers should be careful in interpreting changes in PSA results when stocks are re-evaluated.     

Proposed harvest control rule for managing the snow crab stock in the southwestern Gulf of St. Lawrence,Canada

We developed limit and target harvest control rules based on an age-, sex- and stage-structured model for managing the southwestern Gulf of St. Lawrence snow crab (Chionoecetes opilio) stock. We determined an F_x% (F resulting in a spawning biomass-per-recruit equivalent to x% of virgin spawning biomass-per-recruit) as a proxy for F_MSY and a minimum spawning stock biomass to open the fishery to incorporate them into the control rules. We evaluated the selected limit and target control rule parameters under stochastic simulations by considering various performance statistics. Because of the complexity in determining an effective female spawning biomass that involves a mating ratio, we choose the total mature male biomass (MMB) regardless of crab size as the spawning index to develop the stock–recruitment relationship for stochastic simulations. The MMB based F_37% appears a reasonable proxy for limit control rule while F_45% appears a reasonable target control rule. The corresponding limit and target harvest rates of legal size crab when the standing stock MMB exceeds the proxy MSY level are approximately 36% and 25%, respectively. The difficulty in establishing an appropriate stock–recruitment relationship for this stock was recognized hence a precautionary F_45% target level was chosen. Scenarios under biomass independent random recruitment were also investigated and performances of F_37% and F_45% control rules under this hypothesis behaved similar to those observed under S–R model based simulations.     

Management strategies for short lived species: The case of Australia's Northern Prawn Fishery: 2. Choosing appropriate management strategies using input controls

A Management Strategy Evaluation framework is used to evaluate management strategies based on input controls for the fishery for two tiger prawn species (Penaeus esculentus and Penaeus semisulcatus) in Australia's Northern Prawn Fishery. Three “assessment procedures” are considered and two forms of decision rule. The performance of the management strategies is evaluated in terms of whether stocks are left at (or above) the spawning stock size at which Maximum Sustainable Yield is achieved (S_MSY), the long-term discounted total catch and the extent of inter-annual variation in catches. The focus of the analysis is on management strategies based on the current method of stock assessment because an alternative method of assessment based on a biomass dynamics model is found to be highly variable. None of the management strategies tested is able to leave the spawning stock size of P. esculentus near S_MSY if the target effort level used in the management strategy is set to E_MSY. Accounting for stock structure through the application of a spatially- (stock-) structured assessment approach fails to resolve this problem. Since the assessment method is generally close to unbiased, the failure to leave the stocks close to S_MSY is because the measure of control is total effort and the two species are found (and caught) together. Reducing the target effort level to below E_MSY increases the final stock size, but the reduced risk comes at a cost of reduced catches. The best management strategy in terms of leaving both species close to S_MSY is found to be one that changes the timing of the fishing season so that effort is shifted from P. esculentus to P. semisulcatus and sets more precautionary effort targets for P. esculentus.     

Biomass management targets and the conservation and economic benefits of marine reserves

The establishment of no‐take marine reserves has been increasingly promoted as a key measure to achieve conservation and sustainability goals in fisheries. Regardless of the wide range of benefits cited, the effectiveness of reserve establishment depends critically on fisheries management outside the reserves. We construct a bioeconomic model of a fishery that allows for the establishment of a no‐take marine reserve and evaluate how the choice of the off‐reserve management target influences the effectiveness of reserve establishment. We evaluate two biomass targets: (i) B_MSY or the biomass that produces the maximum sustainable yield (MSY) and (ii) B_MEY or the biomass that maximizes the net present value of the returns to fishing. The parameterized model shows that, for a wide range of scenarios, the fishery will be better off in terms of both conservation and economic objectives when the no‐take reserve is established in conjunction with the B_MEY target rather than with the B_MSY target. Model results further show that the opportunity cost of securing additional fish biomass, in both deterministic and stochastic environments, is lower when the reserve size is increased under the B_MEY target. This finding is important because marine reserves have been established as a key measure to restore depleted fish stocks, and the results suggest that this objective can be achieved with lower economic costs in a B_MEY managed fishery.     

Verifier of the maximum sustainable yield estimates of the southern Atlantic albacore,Thunnus alalunga,stock

Maximum sustainable yield (MSY) has generally been accepted as one of the target biological reference points. Albacore, Thunnus alalunga Bonnaterre, is a temperate tuna species widely distributed in marine waters. The International Commission for the Conservation of Atlantic Tunas (ICCAT) and the International Seafood Sustainability Foundation (ISSF) had reported the southern Atlantic albacore stock status with different MSY reference points. In addition, the European Commission's Advisory Committee on Fisheries and Aquaculture (ACFA), on 15 September 2006, proposed to amend the Common Fisheries Policy according to the MSY principle, but there is little information on the verifier of the MSY estimates of this albacore stock. This study verifies the MSY estimates of this albacore (T. alalunga) stock to support the management (i.e. setting of MSY) for the southern Atlantic albacore (T. alalunga) stock. The MSY estimates of the albacore stock were evaluated and verified by different models (i.e. Bayesian surplus production model [BSPM], continuous time delay‐difference model [CD‐DM] and Fox surplus production model [SPM]). The MSY estimates from BSPM and CD‐DM were lower than those from conventional estimates; the relative biomass ratio (B₂₀₁₁/B_MSY) and relative fishing mortality ratio (F₂₀₁₁/F_MSY) from BSPM and CD‐DM were higher than those from ICCAT, which showed that measures should be taken for the sustainable utilisation of this fish stock.