Quantitative Stock Assessment Research Articles

Coupling state‐of‐the‐art modelling tools for better informed Red List assessments of marine fishes

Abstract In the face of biodiversity loss worldwide, it is paramount to quantify species' extinction risk to guide conservation efforts. The International Union for the Conservation of Nature (IUCN)'s Red List is considered the global standard for evaluating extinction risks. IUCN criteria also inform national extinction risk assessments. Bayesian models, including the state‐of‐the‐art JARA (‘Just Another Red List Assessment’) tool, deliver probabilistic statements about species falling into extinction risk categories, thereby enabling characterisation and communication of uncertainty in extinction risk assessments. We coupled the state‐of‐the‐art VAST (‘Vector Autoregressive Spatio‐Temporal’) modelling tool and JARA, for better informed Red List assessments of marine fishes. In this framework, VAST is fitted to scientific survey catch rate data to provide indices to JARA whose uncertainty is propagated to JARA outcomes suggesting extinction risk categories (under the population reduction criterion). In addition, VAST delivers a valuable habitat assessment to better understand what may be driving extinction risk in the study region. Here, we demonstrate the coupled VAST‐JARA modelling framework by applying it to five contrasting North Sea species, with or without a quantitative stock assessment and with different conservation statuses according to the latest global Red List assessments. The North Sea application coupled with previous assessments and studies suggest that, among the three elasmobranchs, starry ray is in most need of urgent research (and conservation actions where appropriate), followed by spurdog, while lesser‐spotted dogfish is increasing in biomass. Moreover, both the VAST‐JARA modelling framework and previous research indicate that, while European plaice is not of conservation concern, cod has likely met the IUCN criteria for being listed as Endangered recently. Synthesis and applications. The predictions of the VAST‐JARA modelling framework for North Sea species, including JARA output and VAST habitat assessment, constitute valuable supporting information to make interpretations based on Red List guidelines, which will help decision‐makers in their next North Sea Red List assessment. We foresee applications of the modelling framework to assist Red List assessments of numerous marine fishes worldwide. Our modelling framework has many potential advantageous uses, including informing resource management about climate change impacts on species' extinction risks.

Overexploitation of round sardinella may lead to the collapse of flat sardinella: What lessons can be drawn for shared stocks

This paper describes the fisheries and presents quantitative stock assessments for two stocks of Sardinella in the waters of NW Africa. More robust stock assessments are now possible because of improved sampling in Mauritania and Senegal. Round sardinella (S. aurita), which has a wider distribution than flat sardinella (S. maderensis), is the most important species targeted by the different artisanal and industrial fleets. The industrial fleet is located beyond 13 miles from the coast, taking mainly adults. The average size in the offshore fishery, although it has decreased, remains above 26 cm. The species is also exploited by an artisanal fleet using small purse seiners. Two types of assessment model were applied: a production model and size-based model. The abundance indices were consistent, and showed a continuous decline, increasing in rate in recent years. The Just Another Bayesian Biomass Assessment (JABBA) model (applied for the first time) appeared to be appropriate for the abundance indices (Root Mean Squared Error (RMSE) 18.3–19.2 % for the two models). The results of the two models are consistent in showing increasing fishing mortality and declining biomass for both stocks over the time series. According to the JABBA model, the situation for the round sardinella stock is now critical (biomass at approximately 5 % of unexploited biomass (B0) and 10 % of biomass capable of producing maximum sustainable yields (Bmsy), with fishing mortality 2.5 times above Fmsy), and the flat sardinella is also overfished and suffering massive overfishing (B estimated at 18 %B0 and 25 %Bmsy, with fishing mortality more than 11 times above Fmsy). The results of the Length-based Bayesian Biomass (LBB) model are much more optimistic. It still concludes that both stocks are suffering overfishing (round sardinella F at ∼1.4 times Fmsy proxy, flat sardinella ∼2.2 times Fmsy proxy), but estimates that only the flat sardinella is overfished (B 28%B0 and 80 %Bmsy), while the round sardinella stock is not overfished (B 40 %B0 and 120 %Bmsy). However, these results are not consistent with the abundance index from acoustic surveys (used in the JABBA model) and overall are thought to be less robust. Signs of heavy exploitation have been observed for round sardinella for several years. This situation has been exacerbated since the arrival in late 2016 in the Mauritanian zone of efficient semi-industrial purse seiners targeting small pelagics. The various indirect assessment models used show a difficult stock situation for the round sardinella, on which many fishing communities in the area depend. Abundance indices from acoustic survey confirm the state of overexploitation of this resource. This situation has directed effort towards the flat sardinella, which is characterized by a more coastal distribution and limited migration. This species has been showing signs of overexploitation since 2019. We highlight this result for flat sardinella, which was previously not thought to be overexploited, and propose that managers should also consider how the estimated maximum sustainable catch and fishing mortality can be appropriately distributed between the different fleets in different countries, to ensure that future industry planning in the countries of the region is compatible with the sustainability of these critical stocks. This is a very complex task, as it involves not only discussions between neighboring countries, but also difficult decisions within countries about the economic and socio-economic importance of different fisheries sectors. It is essential that these reflections start immediately.

Risk equivalence in data‐limited and data‐rich fisheries management: An example based on the ICES advice framework

AbstractFisheries management needs to ensure that resources are exploited sustainably, and the risk of depletion is at an acceptable level. However, often uncertainty about resource dynamics exists, and data availability may differ substantially between fish stocks. This situation can be addressed through tiered systems, where tiers represent different data limitations, and tier‐specific stock assessment methods are defined, aiming for risk equivalence across tiers. As case studies, we selected stocks of European plaice, Atlantic cod and Atlantic herring, where advice is provided by the International Council for the Exploration of the Sea (ICES). We conducted a closed‐loop simulation to compare risk equivalence between the data‐rich ICES MSY rule, based on a quantitative stock assessment, and the revised data‐limited empirical management procedures of the ICES advice framework. The simulations indicated that the data‐limited approaches were precautionary and did not lead to a higher risk of depletion than the data‐rich approach. Although the catch based on generic data‐limited approaches was lower, stock‐specific optimisation improved management performance with catch levels comparable with the data‐rich approach. Furthermore, the simulation indicated the ICES MSY rule can fail to meet management objectives due to increased depletion risk when management reference points are set suboptimally. We conclude that the recent revisions of the ICES system explicitly account for risk equivalence for data‐limited fisheries management and are a major step forward. Finally, we advocate further consideration of simple empirical management procedures irrespective of data limitations due to their ability to meet fisheries management objectives with greater simplicity.

Determination of the vulnerability of Korean fish stocks using productivity and susceptibility indices

Stock assessments and management of individual fish species are common tools employed for the continuous use of fish stocks; however, these tools are limited when considering the interactions between species, changes in ecosystem structure, and the influence of fisheries on overall habitats. Moreover, inaccurate stock management measures may severely impact the ecosystems. In South Korea, the marine fishery production has been decreasing since 1986. Moreover, fisheries are complex and diverse within relatively small fishing ground, and available data for ecosystem-based fisheries management (EBFM) are limited. In these situations, risk assessment is possible to identify stock status and propose effective management strategies. Productivity and susceptibility analysis (PSA), a semiquantitative risk assessment analysis, is widely used to evaluate the impact of fisheries on fish stocks. In this study, based on 8 productivity and 5 susceptibility attributes, the vulnerability score of 30 species caught by 35 fisheries were evaluated to identify and prioritize the most vulnerable fish species. Based on the results, the 30 species were classified into low (18 species), medium (10 species), and high (2 species) vulnerability groups. Therefore, management of fish species with high vulnerability should be strengthened using various management measures, including total allowable catch (TAC). In addition, quantitative stock assessment should be promoted for more effective management of these species. Moreover, PSA was found to be a useful tool for identifying and prioritizing the relatively vulnerable fish species with regard to the multispecies and multifisheries relationship in Korea.

Recent trends in abundance and fishing pressure of agency‐assessed small pelagic fish stocks

AbstractSmall pelagic fishes are used for human consumption, fishmeal and fish oil. They constitute 25% of global fish catch and have been of considerable conservation concern because of their intermediate position in aquatic food webs, often being a dominant dietary component of marine predators. This paper provides an overview of trends in abundance and fishing pressure on small pelagic fish stocks from single‐species scientific assessments that constitute 60% of global small pelagic catch. While most individual stocks have exhibited wide variability in abundance (typical of small pelagics compared with other fish taxa), across stocks there has been remarkable stability in average fishing pressure and biomass since 1970. On average, since 1970, the biomass of assessed small pelagic stocks is estimated to have been slightly above the biomass that would produce maximum sustainable yield, but estimation of this quantity for highly fluctuating stocks is quite uncertain. There were significant differences among assessed regions, with the Mediterranean and Black Sea of greatest concern for high and growing fishing pressure. The 40% of global small pelagic fish catch not covered by single‐species quantitative stock assessments since 1970 comes largely from Asia, where catches have continued to increase. At regional levels, the average abundance of assessed small pelagic fish is largely unrelated to average fishing pressure, which we argue results both from the portfolio effect, where numerous stocks fluctuate with little correlation in abundance, and from the short life span of small pelagics coupled with recruitment largely independent of spawning abundance.

Vulnerability of marine resources affected by a small-scale tropical shrimp fishery in Northeast Brazil

Abstract Tropical fisheries tend to be multispecies and require management approaches adapted to high diversity but scarce and poorly informative data. Productivity and Susceptibility Analysis-PSA is particularly useful where catch or biological data are incomplete, aggregated across species or insufficient for quantitative stock assessment. We applied PSA to estimate vulnerability and potential risk to target and non-target species caught by the small-scale shrimp fishery in northeast Brazil, adapting the method to regional conditions and incorporating an assessment of uncertainties caused by its subjective choices. Our findings suggest that non-target species can be more vulnerable than target ones. Bagre marinus, Pseudobatos percellens, Micropogonias furnieri, Hypanus guttatus, Macrodon ancylodon, Polydactylus virginicus, Rhizoprionodon porosus, Cynoscion virescens, Larimus breviceps, and Menticirrhus americanus, were the top 10 species potentially at risk due to their low productivity (long lifespans, low spawning), high capture rates of juveniles and overlap of feeding and breeding grounds with fishing areas. Most species (76%) maintained the same risk category (low, moderate, or high) regardless of the score weighting or productivity and susceptibility attribute boundaries applied. Overall, the target species are not currently the main ones threatened, but bycatch such as elasmobranchs, catfishes and Scianidae should be prioritized for assessment and data collection.

Risk assessment of coastal fisheries in the Azores (north-eastern Atlantic)

The Azores (mid-north Atlantic) has a long history of artisanal multispecific fishery exploiting marine resources around the islands slopes and seamounts. Due to the archipelago´s oceanic character, demersal-deep-sea and pelagic-offshore species are central to local economy. However, a coastal subsistence fishery is also economically and culturally important, as well as understudied, underregulated and, up to the present, lacking independent monitoring. A Productivity and Susceptibility Analysis (PSA) was applied to determine stock vulnerability of 38, criteriously selected, coastal species. The PSA identified 20 stocks of concern (3 of which at major risk), thus considered of (high) priority to benefit from a precautionary management approach, at least until more quantitative stock assessments are developed in the future. All of these species generally share (1) a considerable basic knowledge gap (e.g., demography, trophic links, reproduction, habitat use, fisheries); and (2) the absence of previous formal stock assessments, resulting in unknown current population status. Such gaps become graver considering that most of these coastal resources show patterns consistent with progressive signs of intensive or even overexploitation, due to the intensification of combined pressure from the commercial and recreational coastal fishing dating back as early as the 1980’s. As such, we propose an ecosystem-based framework for the regular monitoring, assessment and guidelines for general management of these data-poor coastal resources and fisheries in the region.

Multiple‐model stock assessment frameworks for precautionary management and conservation on fishery‐targeted coastal dolphin populations off Japan

Abstract Stock assessment approaches are often oversimplified due to lack of biological knowledge and insufficient data. In spite of world‐wide attention, fishery‐targeted coastal dolphin species in Japan have lacked in‐depth quantitative stock assessments because of limited time series of population size and an absence of associated biological information. We consequently developed integrated population models that analysed multiple sources of data simultaneously with published biological information within a Bayesian framework. We estimate population status and trends for three main species targeted by fisheries, bottlenose dolphins Tursiops truncatus, Risso's dolphins Grampus griseu, and short‐finned pilot whales Globicephala macrorhynchus, using single‐species age‐aggregated and age‐structured population dynamics models. Models were fit to absolute abundance estimates from systematic line‐transect surveys, four series of abundance indices calculated from fisher's logbooks, and historical catch records. Published biological information was used to develop prior distributions for the biological parameters. We assessed the possible effects of ecological disturbance and competition using state‐space and multispecies models. The multispecies model was selected by the model selection both for the age‐aggregated and the age‐structured approaches. Single‐species assessments found that population size declined 4.2% (Risso's dolphin) to 8.0% (bottlenose dolphin) for three species since the late 1800s based on median posterior values, while the state‐space and multispecies models found that environmental disturbance and an interaction among species could have reduced population size more substantially. Policy implications. Simple single‐species models are often used to provide conservation and management advice for wild animals but, in this case, results from such models are overly optimistic because they overlook important ecological process. In contrast, current population status could be less favorable if environmental disturbance and interspecific competition actually control population dynamics. Even if that is not the case, considering ecological process in the model will provide more precautionary ways. Our approach of combining multiple modelling frameworks is applicable to many other management systems, and offers increased confidence in estimated status and trends over assessments that consider only a single model.

Determining potential management strategies for the elasmobranchs bycatch of the Mexican shrimp trawl fishery of the Gulf of Mexico through a vulnerability analysis

Shrimp trawl fisheries capture several species of elasmobranchs as bycatch that are commonly unreported, this lack of data makes it difficult to assess their populations using quantitative stock assessment methods. Rapid evaluations like the productivity and susceptibility analysis (PSA), can help to determine species at risk of overexploitation and prioritize research, management and conservation efforts. The relative vulnerability (V) of 16 elasmobranch species associated to the Mexican shrimp trawl fishery in the Gulf of Mexico was determined using a PSA. The information of bycatch elasmobranch was collected by observer’s onboard shrimp fishing vessels in 55 fishing trips during the 2013–2017 period. Two hypothetical scenarios to test potential management strategies were developed to observe changes in V based on the current fishing practices. We determined that most elasmobranch species (n= 14) had low V (<1.8) related to this fishery, mostly as a result of the high productivity (P) of the coastal-demersal species and the low susceptibility (S) of the coastal-semioceanic ones. Only two species had a moderate V, Pseudobatos lentiginosus (1.87) and Squatina dumeril (1.85). The vulnerability of these two species could decrease through ensuring post-capture release practices and the protection of their aggregation, since both actions would lower their S and V. Post-capture release might be the most feasible potential strategy for both species, whereas protection of species aggregations would require further investigation to support its effect in the mitigation of mortality from bycatch.

Linking the performance of a data-limited empirical catch rule to life-history traits

AbstractWorldwide, the majorities of fish stocks are data-limited and lack fully quantitative stock assessments. Within ICES, such data-limited stocks are currently managed by setting total allowable catch without the use of target reference points. To ensure that such advice is precautionary, we used management strategy evaluation to evaluate an empirical rule that bases catch advice on recent catches, information from a biomass survey index, catch length frequencies, and MSY reference point proxies. Twenty-nine fish stocks were simulated covering a wide range of life histories. The performance of the rule varied substantially between stocks, and the risk of breaching limit reference points was inversely correlated to the von Bertalanffy growth parameter k. Stocks with k&amp;gt;0.32 year−1 had a high probability of stock collapse. A time series cluster analysis revealed four types of dynamics, i.e. groups with similar terminal spawning stock biomass (collapsed, BMSY, 2BMSY, 3BMSY). It was shown that a single generic catch rule cannot be applied across all life histories, and management should instead be linked to life-history traits, and in particular, the nature of the time series of stock metrics. The lessons learnt can help future work to shape scientific research into data-limited fisheries management and to ensure that fisheries are MSY compliant and precautionary.

Large-scale fish movement affects metrics of management importance as indicated by quantitative stock assessment

Since achieving population recovery targets, management of the Saginaw Bay stock of walleye in Lake Huron is informed by a statistical-catch-at-age (SCAA) model providing estimates of abundance, spawning stock biomass, mortality rates, and exploitation rates. Movement was examined by an acoustic telemetry study and indicated that 37% of the adult population spends much of spring, summer, and fall in the main basin of Lake Huron and unavailable to the fishery in the bay. The current SCAA model used by managers accounts for this movement by including harvest estimates from main basin fisheries in addition to those within the bay. To quantify the effect of the inclusion of the migration information into the model, we constructed a reduced model version that was limited only to the bay harvest and data sources, and then compared these estimates to the full model estimates. All estimates from the reduced model deviated significantly from the full Lake Huron model’s estimates. Significantly different by year were 61% of population size estimates, 25% of total annual mortality estimates, 18% of recreational exploitation rates, and 52% of spawning stock biomass estimates. Differences between the two models were greatest in years of high walleye abundance (i.e., after recovery) and retrospective analysis indicated that this departure was not an estimation artifact. Generally, the reduced model underestimated predicted abundance. We concluded that incorporation of knowledge of movement of Saginaw Bay walleye from the acoustic telemetry study resulted in better informed stock assessment estimates.

Length-based indicators and reference points for assessing data-poor stocks of diadromous trout Salmo trutta

Many populations of diadromous fish have declined, but data are limited and there are very few quantitative stock assessments. Length-based indicators (LBIs) and reference points (RPs) have been proposed for assessment of data-poor fish stocks. It is likely that RPs will need to be tuned for fish with ‘unusual’ life history traits such as diadromy. Long-term records of the size-distribution of the catch in the rod fishery, and in a fisheries-independent trapping programme are available for sea trout Salmo trutta stocks from the River Dee (Wales, UK). These data were used to estimate a length-based harvest rate (LHR) and a suite of LBIs for the fishery. Appropriate RPs (with uncertainty) were derived for length-based assessment of sea trout. The LBIs and a decision tree suggest that the stock is likely to be sustainably exploited with regard to length-based and a spawner biomass RP. Increasing the overall harvest rate would result in a greater proportion of rare very large sea trout being taken by anglers. Appropriate length-based RPs for sea trout differ to those proposed for marine demersal species. Expected values for the proportion of megaspawners in the catch are very low, which may be explained by fishing gear (hook and line) selection and the cost of multiple spawning migrations in diadromous fish.

Improving stock assessments through data prioritization

The need for “better data” is a common response of stakeholders and managers when confronted with the uncertainty of advice resulting from quantitative stock assessments. Most contemporary stock assessments are based on an integrated analysis of multiple data types, each with their associated cost to collect. Data collection resources are inevitably limited; therefore, it is important to quantify the relative value of increased sampling for alternative data types in terms of improving stock assessments. We approached this universal problem using a simulation study of a hypothetical, amalgam species developed from eight separate stock assessments conducted for species found in southeastern US Atlantic waters. We simulated a population and a stock assessment from the amalgam species and then individually improved alternative data types (indices, age compositions, landings, and discards) by increasing either precision or sample size. We also simulated the effects of increased sampling for alternative groupings of data that might be collected in concert (e.g., commercial, recreational, or survey). Our results show that for the snapper–grouper complex we modeled, age composition data have the largest effect on the accuracy of assessments, with commercial age compositions being the most influential. This is due in part to the relative paucity of age composition data for many southeast US marine stocks, so that modest increases in collection efforts have relatively high benefits for age-based assessment models currently in use for the region. Though this study used data from a particular region of the US, our investigative framework is broadly applicable for quantitatively evaluating the benefits of improved data collection in terms of the precision of stock assessments in any region.

Management strategy evaluation of a multi-indicator adaptive framework for data-limited fisheries management

In data-limited fisheries, making informed management decisions based on scientific advice is challenging. Here, we evaluate a multi-indicator adaptive management framework (AMF) that allows dynamic responses to changing environmental, socioeconomic, and fishing conditions. Using stakeholder-defined goals as a foundation for specifying performance metrics, we employ management strategy evaluation (MSE) to explore the performance of the AMF relative to prescriptive alternatives that are sometimes used in data-limited situations. We conduct simulations involving the two most economically-important fisheries in Belize, spiny lobster, Panulirus argus (Latreille, 1804), and queen conch, Strombus gigas (Linnaeus, 1758). Spiny lobster fishery simulations demonstrate that when relatively stable catches have historically persisted, an AMF can help to ensure that stable catches continue to persist into the foreseeable future when faced with factors such as increased entry to the fishery or environmentally-induced recruitment fluctuations. The queen conch fishery simulations demonstrate that optimizing economic performance is complicated without stock status indicators and depends greatly upon the current, yet typically unknown, state of the resource. Since our indicator-based approach could not provide direct information about resource status in relation to management reference points such as maximum sustainable yield, economic objectives could not be achieved. Nevertheless, implementing the AMF served as a beneficial control against stock collapse and could function well as an interim fishery policy during which sufficient fishery data could be collected to inform population modeling and quantitative stock assessment.

Ecological risk assessments for the effects of fishing: A comparison and validation of PSA and SAFE

Two tools to assess impacts of fisheries on fish species have been developed for use as part of the Ecological Risk Assessment for the Effects of Fishing (ERAEF) toolbox, namely, the Productivity and Susceptibility Analysis (PSA) and the Sustainability Assessment for Fishing Effect (SAFE). Both have been applied to major Australian Commonwealth fisheries and, with various modifications, adopted internationally. However, there has been no formal comparison between the two approaches and no validation against other data-rich assessment methods. Here, we conduct three comparisons: between PSA and SAFE, between PSA, SAFE and Fishery Status Reports (FSR), and between PSA, SAFE and data-rich quantitative stock assessments. PSA and SAFE use similar data. However, PSA typically downgrades quantitative information into an ordinal scale between 1 and 3, whereas SAFE uses the quantitative information as continuous numerical variables in equations at each assessment step. As intended in its original design, PSA is more precautionary toward protecting species, classifying many more species at medium or high risk than SAFE. A comparison with FSR for overfishing classification shows an overall misclassification rate of 27% (26 stocks) by PSA (overestimating risk in all these cases) and 8% (59 stocks) by SAFE (overestimating risk in 3% and underestimating risk in 5% of cases). A comparison with Tier 1 stock assessments (18 stocks) shows an overall misclassification rate of 50% by PSA and 11% by SAFE (all overestimating risk). These comparisons show that the performance of these two ERA tools may deliver the expected benefits in terms of prioritizing high risk species, but, in the case of PSA, the screening may be too precautionary. Validation with more quantitative methods is an important step to guide the further improvement of these important tools.

Risk assessment of cartilaginous fish populations

Abstract We review three broad categories of risk assessment methodology used for cartilaginous fish: productivity-susceptibility analysis (PSA), demographic methods, and quantitative stock assessments. PSA is generally a semi-quantitative approach useful as an exploratory or triage tool that can be used to prioritize research, group species with similar vulnerability or risk, and provide qualitative management advice. Demographic methods are typically used in the conservation arena and provide quantitative population metrics that are used to quantify extinction risk and identify vulnerable life stages. Stock assessments provide quantitative estimates of population status and the associated risk of exceeding biological reference points, such as maximum sustainable yield. We then describe six types of uncertainty (process, observation, model, estimation, implementation, and institutional) that affect the risk assessment process, identify which of the three risk assessment methods can accommodate each type of uncertainty, and provide examples mostly for sharks drawn from our experience in the United States. We also review the spectrum of stock assessment methods used mainly for sharks in the United States, and present a case study where multiple methods were applied to the same species (dusky shark, Carcharinus obscurus) to illustrate differing degrees of model complexity and type of uncertainty considered. Finally, we address the common and problematic case of data-poor bycatch species. Our main recommendation for future work is to use Management Strategy Evaluation or similar simulation approaches to explore the effect of different sources of uncertainty, identify the most critical data to satisfy predetermined management objectives, and develop harvest control rules for cartilaginous fish. We also propose to assess the performance of data-poor and -rich methods through stepwise model construction.

Selecting relative abundance proxies for BMSY and BMEY

AbstractThe objectives for many commercial fisheries include maximizing either yield or profit. Clearly specified management targets are a key element of effective fisheries management. Biomass targets are often specified for major commercial fisheries that are managed using quantitative stock assessments where biomass is calculated and tracked over time. BMSY, the biomass corresponding to Maximum Sustainable Yield, is often used as a target when maximizing yield is important, while BMEY is the biomass target to maximize profit. There are difficulties in estimating both quantities accurately, and this paper explores default proxies for each target biomass, expressed as biomass levels relative to carrying capacity, which are more easily estimated. Integration across a range of uncertainties about stock dynamics and the costs of fishing suggests that a proxy for BMSY in the range of 35–40% of carrying capacity minimizes the potential loss in yield compared with that which would arise if BMSY was known exactly, while a proxy for BMEY of 50–60% of carrying capacity minimizes the corresponding potential loss in profit. These estimates can be refined given stock-specific information regarding productivity (particularly the parameter which defines the resilience of recruitment to changes in spawning stock size) and costs and prices. It is more difficult to find a biomass level that achieves a high expected profit than a biomass level that achieves a high expected catch, because the former is sensitive to uncertainties related to costs and prices, as well as parameters which determine productivity.

Reconciling Approaches to the Assessment and Management of Data‐Poor Species and Fisheries with Australia's Harvest Strategy Policy

AbstractThere is an increasing expectation for decision makers to use robust scientific advice on the status of exploited fish stocks. For example, Australia has recently implemented a harvest strategy policy for federally managed fisheries based on limit and target biomass reference points. In common with most fisheries jurisdictions, however, Australia has many data‐poor species and fisheries for which biomass estimates are unavailable. Consequently, the challenge for those tasked with providing management advice for Australian fisheries has been reconciling the need to achieve specific risk‐related sustainability objectives with the reality of the available data and assessments for data‐poor species and fisheries. Some general recommendations regarding how to achieve this balance are drawn using case studies from two multispecies trawl fisheries. The lack of data on which to base quantitative stock assessments using population dynamics models does not preclude the development of objective harvest control rules. Evaluation of harvest control rules using technical procedures (e.g., the management strategy evaluation approach) is ideal, but implementation before rigorous testing is sometimes a necessary reality. Information from data‐rich species and fisheries can be used to inform “assessments” for data‐poor species and thereby develop appropriate control rules. This can be done through formal methods, such as the “Robin Hood” approach (in which assessments from data‐rich species are used to inform assessments of data‐poor species), or less formally by grouping species into “baskets” and basing management decisions on one appropriate member of the group. Stakeholder knowledge and buy‐in to the process of developing appropriate harvest strategies are essential when species or fisheries are data poor. Use of this information, however, needs to be constrained by policy decisions, such as prespecified performance standards. There will always be a trade‐off between the cost of data collection and the value of a fishery; in this article, we highlight that this trade‐off does not have to be a major impediment to the development of realistic and sufficiently precautionary control rules for the management of data‐poor species and fisheries.

The novel use of harvest policies and rapid visual assessment to manage spatially complex abalone resources (Genus Haliotis)

To date, the development of fisheries harvest policies has typically focused on the use of indices estimated from quantitative stock assessment models. Where does this leave the small-scale and spatially complex resources for which costs and logistics prevent adequate data collection for the construction of quantitative assessment models at scales appropriate for the component populations being fished? This paper presents a novel harvest policy framework developed in Australia by the Victorian Western Zone Abalone Diver’s Association (WADA) to assess and manage their resource at the scale of component abalone reefs (100s–1000s m). This novel harvest policy framework uses a rapid visual evaluation of population fecundity based on shell shape and appearance. Codified and applied using a decision tree, it is being used in Australia by an increasing number of zonal abalone industry associations. Abalone populations on reef complexes are being assessed and managed with voluntary catch caps and voluntary minimum lengths larger than legal minimum lengths. It will probably be decades before a satisfactory quantitative analysis on the efficacy of the approach will be possible, but positive anecdotal accounts and the relatively rapid spread of the approach suggest industry members believe they are seeing benefits.

Global estimates of shark catches using trade records from commercial markets

Despite growing concerns about overexploitation of sharks, lack of accurate, species-specific harvest data often hampers quantitative stock assessment. In such cases, trade studies can provide insights into exploitation unavailable from traditional monitoring. We applied Bayesian statistical methods to trade data in combination with genetic identification to estimate by species, the annual number of globally traded shark fins, the most commercially valuable product from a group of species often unrecorded in harvest statistics. Our results provide the first fishery-independent estimate of the scale of shark catches worldwide and indicate that shark biomass in the fin trade is three to four times higher than shark catch figures reported in the only global data base. Comparison of our estimates to approximated stock assessment reference points for one of the most commonly traded species, blue shark, suggests that current trade volumes in numbers of sharks are close to or possibly exceeding the maximum sustainable yield levels.