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.     

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.     

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.     

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.     

基于CMSY和BSM的东海区重要渔业种类资源评估

有限数据方法(data-limited method)可结合少量易获得数据和相关生物学信息对渔业资源状况、生物学参考点以及生物量等进行评估,已经成为全球区域性渔业管理组织和资源评估学者的关注热点。本研究采用基于渔获量的最大可持续渔获量(catch-based maximum sustainable yield,CMSY)和基于贝叶斯状态空间的Schaefer产量模型(Bayesian Schaefer production model,BSM)评估了东海区19个重要经济种类的资源状况,并提出了基于最大可持续渔获量(maximum sustainable yield,MSY)的渔业管理建议。结果显示,19个种类中有1个种类衰竭,3个种类严重衰退,5个种类过度捕捞,5个种类轻度过度捕捞,5个种类健康。种群状态长期评估结果表明,处于生物可持续水平的鱼类种群占比已由1980年的95%下降至2019年的26%。同时对CMSY和BSM方法的结果进行了比较,整合单位捕捞努力量渔获量(catch per unit effort,CPUE)数据的BSM方法导致了置信区间较宽,并调节了生物量轨迹的变化形态...     

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.     

Selectivity metrics for fisheries management and advice

Fisheries management typically aims at controlling exploitation rate (e.g., Fbar) to ensure sustainable levels of stock size in accordance with established reference points (e.g., F_MSY, B_MSY). Population selectivity (“selectivity” hereafter), that is the distribution of fishing mortality over the different demographic components of an exploited fish stock, is also important because it affects both Maximum Sustainable Yield (MSY) and F_MSY, as well as stock resilience to overfishing. The development of an appropriate metric could make selectivity operational as an additional lever for fisheries managers to achieve desirable outcomes. Additionally, such a selectivity metric could inform managers on the uptake by fleets and effects on stocks of various technical measures. Here, we introduce three criteria for selectivity metrics: (a) sensitivity to selectivity changes, (b) robustness to recruitment variability and (c) robustness to changes in Fbar. Subsequently, we test a range of different selectivity metrics against these three criteria to identify the optimal metric. First, we simulate changes in selectivity, recruitment and Fbar on a virtual fish stock to study the metrics under controlled conditions. We then apply two shortlisted selectivity metrics to six European fish stocks with a known history of technical measures to explore the metrics’ response in real‐world situations. This process identified the ratio of F of the first recruited age–class to Fbar (Frec/Fbar) as an informative selectivity metric for fisheries management and advice.     

Using global catch data for inferences on the world’s marine fisheries

Detailed stock assessments, including the estimation of the absolute biomass of the ‘stocks’ exploited by fisheries, are often viewed as the gold standard for indicators of their status. However, such stock assessments are not available for the overwhelming majority of exploited stocks and fisheries globally. This requires the development, testing and dissemination of other, less data‐demanding indicators for use throughout the world, for example, for comparing the status of fisheries between different maritime countries or large marine ecosystems. Stock status plots, initially developed by staff of the United Nations Food and Agriculture Organization to assess global fisheries, are reviewed here, and their most recent incarnation, which accounts for stock rebuilding, is found to provide a robust overview of fisheries and of the major trends besetting them.     

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.     

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.     

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.     

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.     

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.     

Assessing the state of Greek marine fisheries resources

Annual fish landings for the Greek seas were analysed for the period 1982–2007 and classified into exploitation categories based on a catch‐based stock classification method. In 2007, about 65% of the Greek stock were characterised as overfished, 32% as fully exploited and only 3% were characterised as developing; collapsed stocks were not recorded. The cumulative percentage of fully exploited and overfished stocks has been increasing over the past 20 years suggesting overexploitation of resources. The results were contrasted against total landings, the fishing‐in‐balance index (FiB) and fishing effort, and some irregularities on the dataset were explained based on current legislation and management measures. A positive correlation between FiB and total fishing effort confirmed the expansion of the Greek fisheries up to 1994, but contraction thereafter. The results suggest that the apparently stable overall catches and decreasing effort may be deceiving, as they hide an underlying pattern of overexploitation in some of the stocks. It was concluded that the Greek fisheries are no longer sustainable and radical management measures are needed.     

The importance of live‐feed traps – farming marine fish species

This article analyses the challenges of different live‐feed regimes for the rearing of marine finfish larvae and discusses the potential alternative live feeds to avert a future live‐feed trap. Live feeds are indispensable for the successful rearing of larvae of most marine fish species. Brine shrimps (Artemia) and rotifers comprise the live feeds of choice in marine aquaculture today. However, their nutritional composition is deficient in especially essential fatty acids, and enrichment with fish oil is needed. Fish oil is considered a limited resource owing to its origin in fully exploited wild fish stocks. Moreover, fluctuations of the natural population of Artemia will, most likely, influence future availability and prices. This emphasizes the need for optimal exploitation of available live‐feed resources and development of new sustainable alternatives, such as copepods. An array of solutions to these problems are presented to avoid a future live‐feed trap and to reduce dependence on limited resources that influence future production possibilities, species diversification, price volatility and productivity in the aquaculture sector.     

Forecasting fish stock dynamics under climate change: Baltic herring (Clupea harengus) as a case study

Climate change and anthropogenic disturbances may affect marine populations and ecosystems through multiple pathways. In this study we present a framework in which we integrate existing models and knowledge on basic regulatory processes to investigate the potential impact of future scenarios of fisheries exploitation and climate change on the temporal dynamics of the central Baltic herring stock. Alternative scenarios of increasing sea surface temperature and decreasing salinity of the Baltic Sea from a global climate model were combined with two alternative fishing scenarios, and their direct and ecosystem‐mediated effects (i.e., through predation by cod and competition with sprat) on the herring population were evaluated for the period 2010–2050. Gradual increase in temperature has a positive impact on the long‐term productivity of the herring stock, but it has the potential to enhance the recovery of the herring stock only in combination with sustainable fisheries management (i.e., F_msy). Conversely, projections of herring spawning stock biomass (SSB) were generally low under elevated fishing mortality levels (F_high), comparable with those experienced by the stock during the 1990s. Under the combined effects of long‐term warming and high fishing mortality uncertainty in herring SSB projections was higher and increasing for the duration of the forecasts, suggesting a synergistic effect of fishery exploitation and climate forcing on fish populations dynamics. Our study shows that simulations of long‐term fish dynamics can be an informative tool to derive expectations of the potential long‐term impact of alternative future scenarios of exploitation and climate change.     

Size structure,not metabolic scaling rules,determines fisheries reference points

Impact assessments of fishing on a stock require parameterization of vital rates: growth, mortality and recruitment. For ‘data‐poor’ stocks, vital rates may be estimated from empirical size‐based relationships or from life‐history invariants. However, a theoretical framework to synthesize these empirical relations is lacking. Here, we combine life‐history invariants, metabolic scaling and size‐spectrum theory to develop a general size‐ and trait‐based theory for demography and recruitment of exploited fish stocks. Important concepts are physiological or metabolic scaled mortalities and flux of individuals or their biomass to size. The theory is based on classic metabolic relations at the individual level and uses asymptotic size W_∞ as a trait. The theory predicts fundamental similarities and differences between small and large species in vital rates and response to fishing. The central result is that larger species have a higher egg production per recruit than small species. This means that density dependence is stronger for large than for small species and has the consequence that fisheries reference points that incorporate recruitment do not obey metabolic scaling rules. This result implies that even though small species have a higher productivity than large species their resilience towards fishing is lower than expected from metabolic scaling rules. Further, we show that the fishing mortality leading to maximum yield per recruit is an ill‐suited reference point. The theory can be used to generalize the impact of fishing across species and for making demographic and evolutionary impact assessments of fishing, particularly in data‐poor situations.     

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.     

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.     

A simple method for estimating MSY from catch and resilience

The Law of the Sea requires that fish stocks are maintained at levels that can produce the maximum sustainable yield (MSY). However, for most fish stocks, no estimates of MSY are currently available. Here, we present a new method for estimating MSY from catch data, resilience of the respective species, and simple assumptions about relative stock sizes at the first and final year of the catch data time series. We compare our results with 146 MSY estimates derived from full stock assessments and find excellent agreement. We present principles for fisheries management of data‐poor stocks, based only on information about catches and MSY.