Stock Assessment Methods Research Articles

Building an ecosystems-type fisheries management approach for the Campeche Bank, subarea in the Gulf of Mexico Large Marine Ecosystem

In this contribution, we discuss the need for an ecosystems-type fisheries management approach, especially when the Campeche Bank subarea of the Gulf of Mexico Large Marine Ecosystem (LME) is strongly influenced by environmental changes. In these circumstances, the carrying capacity and the subarea structure and its organization do not reflect the stability assumed for conventional stock assessment approaches. The subarea re-organizes in response to environmental change, and sustainable fishing and management must be adapted. This necessity is particularly relevant under the effects of climate change since those changes have a defined tendency. We also show evidence of a clear signal of climate change effects on the Campeche Bank subarea of the Gulf of Mexico LME and how changes in fish stocks can be misinterpreted under conventional stock assessment methods. Moreover, evidence is shown regarding how the subarea has evolved during the last six decades, giving a clear example of re-organization. Management schemes are discussed briefly; addressing why they fail and suggesting an approach to identify a limiting subarea reference level termed noxicline, which represents the limit of the loss of biomass of the components of a subarea after which the domain deteriorates. The noxicline also permits identification of the corresponding harvest rate limit at the stock level. As an average the harvest rate to be applied in the Campeche Bank subarea should be no larger than 40%. This approach can be useful under the effects of climate change, since harvest rates reflect the proportion of the stock that is extracted, regardless of its size.

A Bayesian two-stage biomass model for stock assessment of data-limited species: An application to cuttlefish (Sepia officinalis) in the English Channel

Cuttlefish is a key commercial species in the English Channel fishery in terms of landings and value. Age-based assessment methods are limited by time-consuming age determination with statoliths and the lack of stock assessment models tailored to this data-limited species. A two-stage biomass model is developed in the Bayesian state-space modelling framework that allows inferences to be made on the stock biomass at the start, middle and end of each fishing seasons between 1992 and 2014, while accounting for both process and measurement errors and to assimilate various sources of information. A method that uses ancillary length-frequency data is developed to provide an informative prior distribution for the biomass growth rate parameter g (E=0.89) and its annual variability (CV=0.1). The new model is a substantial improvement on the existing stock assessment method used by the International Council for the Exploration of the Seas. Taking into consideration a time-varying g parameter provides a more ecologically meaningful model with regard to the sensitivity of the cuttlefish population dynamics to environmental fluctuations and improves model fit. The model also provides predictions of the unexploited biomass in winter, which is based on survey data, and helps manage the stock in the event of strong depletion.

Estimating stock depletion level from patterns of catch history

AbstractThe degree to which a stock is depleted is one of the most important quantities in fisheries management because it is used to quantify the success of management and to inform management responses. However, stock depletion is extremely difficult to estimate, particularly with limited data. Using the RAM Legacy database, we developed a boosted regression tree (BRT) model to correlate depletion with a range of predictors calculated from catch data, making the model usable for many fisheries worldwide. The most important predictors were found to be catch trends obtained from linear regressions of scaled catch on time, including regression coefficients for the whole catch time series, the subseries before and after the maximum catch, and in recent years. Eight predictors explain about 80% of variation in depletion. There is a correlation of .5 between measured levels of depletion and the predictions of the BRT model. Predictions are less biased when the stock is fished down below half of the carrying capacity. The BRT model outperforms comparable existing catch‐based depletion estimators and could be used to provide priors for depletion for data‐poor stock assessment methods, or used more directly to provide estimates of the probability that depletion is below a given threshold value.

Multi-mesh gillnet selectivity of Oreochromis mossambicus and O. niloticus (Cichlidae) in the fishery of three large perennial reservoirs in Sri Lanka

As in many tropical reservoir fisheries, the major fishing gear in the reservoirs of Sri Lanka is gillnet. Gillnets of a wide range of stretched mesh sizes (6.9 - 11.4 cm) are used in individual boats in Sri Lankan reservoirs targeting mainly two exotic cichlid species, Oreochromis mossambicus and O. niloticus , which dominate the fisheries accounting for over 80% of the landings. Although the filament characteristics and dimensions of gillnets of different mesh sizes are uniform, their mesh composition varies from boat to boat making catch samples in individual boats are under the influence of different selectivity patterns. As such, an approach is presented for constructing the overall selection curves in the sampled boats during different sampling occasions for the two cichlid fish species in the three reservoirs. For this purpose, gillnet selectivity of each mesh size was determined using Baranov-Holt method. Probabilities of capture of mesh-wise gillnet selection curves were then summed up giving weight to the contribution of each mesh size to the total number of net pieces in the sampled boat, to determine the overall gillnet selection from gillnets of all mesh sizes. The importance of the findings of the present study for length-based stock assessment methods and for imposing mesh regulations to the gillnet fisheries in reservoirs of Sri Lanka is discussed.

IMPROVEMENT OF THE EVALUATION METHOD OF RESERVES IN ACCOUNTING

Introduction. The article deals with the main approaches to reserves valuation in accordance with the requirements of national accounting standards. The methods of stock assessment at different stages of their circulation are considered: on stage of admission, on balance sheet date and at the time of disposal. Purpose. The article aims to study the improvement of inventory assessment methodology at different stages of their circulation to ensure the accuracy of accounting information about the cost of stocks. The method (methodology). The study used the methods of theoretical and logical generalization, comparison method, method of analysis and synthesis, method of abstraction and modelling. Results. The article deals with the main approaches to inventory valuation in scientific literature and legal acts. Enterprises can independently choose the most appropriate methods of inventory valuation depending on the established accounting policies. The number of stock valuation methods, on the one hand, provides ample opportunity to reflect the real value of inventories, and on the other hand, it may lead to a reduction in the reliability of accounting data if the inventory method is wrongly chosen. The study found out that most methods of stock assessment are focused on the principle of historical cost and the correct calculation of financial results. It does not always take into account the need to reflect the real (fair) value of inventories, which may lead to a reduction in the reliability of inventory data and indicators of the property status report of the enterprise. Part of stocks has industry-specific features. Thus, agricultural products, unlike other types of inventory, at initial recognition can be assessed at fair value, reduced by expected costs to sell. It is proposed to extend to the assessment of other types of stocks.

Estimate of sustainable yield of blue shark ( Prionace glauca ) in the Indian Ocean using data-poor approach

PDF HTML阅读 XML下载 导出引用 引用提醒 运用数据缺乏方法估算印度洋大青鲨可持续渔获量 DOI: 作者: 作者单位: 1. 上海海洋大学 海洋科学学院, 上海 201306;2. 农业部大洋渔业开发重点实验室, 上海 201306 作者简介: 耿喆(1993-),男,硕士研究生,从事渔业资源评估、渔业生态学研究.E-mail:gengzhe1993@sohu.com 通讯作者: 中图分类号: S931 基金项目: 国家自然科学基金项目（41676120）. Estimate of sustainable yield of blue shark (Prionace glauca) in the Indian Ocean using data-poor approach Author: Affiliation: 1. College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China;2. Key Laboratory of Exploitation of Oceanic Fisheries, Ministry of Agriculture, Shanghai 201306, China Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:运用数据缺乏方法，即基于资源衰减的可持续渔获量估算模型（DCAC），结合Monte Carol模拟，对印度洋大青鲨（增大或最大可持续产量对应的捕捞死亡系数（）增大；若呈减小趋势。资源丰度指数的选择对DCAC结果有较大影响，基于日本延绳钓渔业1998-2014年和2001-2014年两个时间序列的丰度指数得到的结果可靠，且与其他模型估算的MSY值接近。2014年印度洋大青鲨的年渔获量正好处在或略高于最大可持续产量（MSY）水平，但该结果仍具有一定的不确定性。本研究表明运用DCAC方法估算印度洋大青鲨可持续渔获量是可行的，但对其他鲨鱼种类的适用性仍需进一步研究，该结果可为数据缺乏方法在大洋和中国近海渔业中的应用提供参考。 Abstract:Sharks occupy the top trophic level in the marine community and play an important role in maintaining ecosystem stability and diversity. The stock status of shark species is often difficult to assess by formal stock assessment methods due to limited fishery data. Blue shark () is the most widely distributed pelagic shark species in tropical and temperate oceanic waters. This species is often caught as bycatch in oceanic longline fisheries that target billfishes and tunas, and also in the artisanal longline fisheries that operate in coastal areas such as Chile. Because of its slow growth and late maturity, the blue shark is defined as "Near Threatened" globally in the IUCN species list. Determining the stock status of Indian Ocean blue shark using a data-poor approach has been assigned as a high research priority by the Indian Ocean Tuna Commission. In this study, we assessed the Indian Ocean blue shark stock status using the depletion-corrected average catch (DCAC) approach and Monte Carlo simulation. DCAC is a data-poor approach that only needs basic biological information (natural mortality, was estimated by the Hoeing method, resulting in a mean of 0.05. In addition to the annual catch data, the application of DCAC also needs the means and standard errors of the following parameters:depletion of the biomass (. First, we estimated the sustainable yield () of blue shark using abundance indices (standardized catch per unit effort[CPUE] time series) derived from different longline fleets (i.e., Spain, Portugal, Japan, and Taiwan, China). Second, we evaluated the sensitivity of DCAC by considering multiple combinations of different levels of , CPUE indices, and lengths of time series of data. Lastly, we summarized the estimated values and compared our estimates with the results from other assessment approaches for this species. The results showed that when FMSY/M when was close to zero or negative. The results were sensitive to the CPUE index. The estimated was reliable and close to the maximum sustainable yield (estimated from other assessment models) when the Japanese longline CPUE index (1998-2014 or 2001-2014) was used. The current (2014) annual catch of blue shark might be at or just above the estimated maximum sustainable yield, although the estimate is subject to uncertainties. This study suggests that DCAC is suitable for estimating the of Indian Ocean blue shark using catch data and CPUE indices as the main sources. This study also provides guidelines for the application of data-poor approaches in domestic fisheries of China. 参考文献 相似文献 引证文献

Spatial and ontogenetic patterns of Pacific cod (Gadus macrocephalus Tilesius) predation on octopus in the eastern Bering Sea

In 2012, the North Pacific Fishery Management Council adopted a consumption-based stock assessment method to determine catch limits for the non-target, multi-species octopus complex in the Bering Sea-Aleutian Islands (BSAI) fishery management area. The method uses Pacific cod (Gadus macrocephalus) diet data as a basis for estimating octopus complex natural mortality and minimum biomass. To enhance understanding of the predator-prey interaction between Pacific cod and octopus, we examined patterns of octopus consumption by Pacific cod using long-term stomach contents data from the eastern Bering Sea continental shelf, a large, ecologically unique subarea of the BSAI. Generalized additive modeling of octopus presence/absence in Pacific cod diets revealed distinct spatial, ontogenetic and seasonal consumption patterns. Prey octopus frequency of occurrence (FO) generally increased with bottom depth, latitude and Pacific cod fork length, and FO in the southern BSAI was lower during winter and spring than during summer. Prey octopus FO patterns may reflect overall consumption patterns and likely indicate long-term distribution patterns of small-sized (<1 kg) octopus on the EBS shelf, although we could not visually distinguish between octopus species using prey remains. Multi-species beak length-to-body mass regressions developed from three octopus species allowed reasonable estimation of prey octopus mass, and we found Pacific cod fork length was positively correlated with prey octopus mass, suggesting predator-prey interactions are sensitive to predator and prey size composition. Pacific cod consumed octopus with estimated masses ranging from 0.000017 kg to 4.62 kg, while octopus taken during concurrent bottom trawl surveys range from 0.05 kg to greater than 25 kg. Based on our findings, we expect the consumption-based stock assessment underestimates BSAI octopus complex biomass because it cannot account for larger octopus, such as the 10–20 kg Enteroctopus dofleini which dominate incidental take in BSAI Pacific cod pot fishery.

The effects of applying mis-specified age- and size-structured models

Stock assessments estimate biomass and fishing mortality in absolute terms and relative to reference points. Most of the world’s stock assessments are based on age- or size-structured population dynamics models, with few stock assessments directly accounting for both age and size dynamics. However, the life history parameters of fish and invertebrate populations are often functions of both age and size. An operating model that is based on an age- and size-structured population dynamics model is used to evaluate the performance of assessment methods based on age-, size- and age- and size-structured population dynamics models. Variants of the operating model and the assessment methods, which include ‘platoons’ to better represent individual variation in growth, are considered to explore the impact of this source of uncertainty on the performance of stock assessment methods. Simulation experiments based conceptually on the assessment for Pacific cod in the Eastern Bering Sea are used to explore the consequences of applying assessment methods that are mis-specified in terms of the population dynamics model and the way variation in growth is modelled. The age-structured assessment methods perform poorest, most likely because they mis-represent how mortality, due to fishing, is removed from the population in the operating model, but also because of mis-specification of the growth curve. The assessment methods with platoons can outperform those that ignore platoon structure when this is present, but their performance when there are no platoons is such that, overall, simpler assessment methods based on size-structured, or age- and size-structured population dynamics models, appear best. Conducting assessments using multiple model types and selecting the best model based on the lowest AIC was, however, the best approach overall.

Estimating uncertainty of data limited stock assessments

Many methods exist to assess the fishing status of data-limited stocks; however, little is known about the accuracy or the uncertainty of such assessments. Here we evaluate a new size-based data-limited stock assessment method by applying it to well-assessed, data-rich fish stocks treated as data-limited. Particular emphasis is put on providing uncertainty estimates of the data-limited assessment. We assess four cod stocks in the North-East Atlantic and compare our estimates of stock status (F/Fmsy) with the official assessments. The estimated stock status of all four cod stocks followed the established stock assessments remarkably well and the official assessments fell well within the uncertainty bounds. The estimation of spawning stock biomass followed the same trends as the official assessment, but not the same levels. We conclude that the data-limited assessment method can be used for stock assessment and that the uncertainty estimates are reliable. Further work is needed to quantify the spawning biomass of the stock.

Developing risk equivalent data-rich and data-limited harvest strategies

Several fisheries jurisdictions are aiming to achieve risk equivalency (here defined as the probability of a stock being depleted below a limit reference point or not being maintained at a target reference point) irrespective of the stock assessment method used to provide management advice and the amount of data available. Risk equivalency is implicitly required under the USA Magnuson-Stevens Act, while in Australia it is an explicit component of the Australian Commonwealth Government’s Harvest Strategy Policy. Risk equivalency is well understood, but few fisheries have attempted to implement it. The Australian Southern and Eastern Scalefish and Shark Fishery (SESSF) is the only Australian fishery that has explicitly done so, albeit in a semi-arbitrary manner. Assessments and associated harvest strategies are placed into tiers from data-rich to data-limited. There are also meta-rules that control how much catch limits can change from one year to the next, and buffers by tier to achieve risk equivalency. Here, the SESSF tier system was evaluated in an ecosystem context using Management Strategy Evaluation. Two buffer systems were considered, the current SESSF system and a system inferred from how the Acceptable Biological Catches are set for the USA west coast groundfish fishery. Harvest strategies for all tiers were capable of moving productive stocks so their biomasses lay between the limit and target reference points. The USA buffer system was more conservative than the SESSF system, and achieved the fastest recovery for depleted stocks. The latter system led to slightly lower total catches, but was closest to achieving risk equivalency across the tiers. The USA buffer system led to biomass trajectories most similar to those when the system was managed so that biomass moves as rapidly as possible to its target reference point.

Assessing abundance of populations with limited data: Lessons learned from data-poor fisheries stock assessment

Estimation of population abundances in the absence of good observational data are notoriously difficult, yet urgently needed for biodiversity conservation and sustainable use of natural resources. In the field of fisheries research, management regulations have long demanded population abundance estimates even if data available are sparse, leading to the development of a range of fish stock assessment methods designed for data-poor populations. Here, we present methods developed within the context of fisheries research that can be applied to conduct population abundance estimations when facing data-limitations. We begin the review from the less data-demanding approaches and continue with more data-intensive ones. We discuss the advantages and caveats of these approaches, the challenges and management implications associated with data-poor stock assessments, and we propose the implementation of the Bayesian hierarchical framework as the most promising avenue for future development and improvement of the current practices.

An unlikely partnership: fishers’ participation in a small-scale fishery data collection program in the Timor Sea

Traditional fisheries stock assessment methods and fishery independent surveys are costly and time consuming exercises. However fishers trained in data collection and utilising other skills can reduce costs and improve fishery assessments and management. A data collection program was conducted by Australian and Indonesian scientists with small-scale Indonesian sea cucumber fishers to evaluate the approach and then capture its benefits. The data fishers recorded allowed for the first stock assessment of this trans-boundary fishery during its centuries-long existence at Scott Reef in north-western Australia. The program also included interviews with fishers capturing the social, economic, and demographic aspects of the fishery. Economic inputs to fishing were complemented by fishery revenue data voluntarily submitted when fishers returned to port and sold their catch. Catch data recorded by fishers demonstrated much higher abundances than estimates obtained using standard visual transect methods and accurately reflected the true catch composition. However, they also showed extreme rates of exploitation. Interviews revealed social and economic factors that would be important considerations if management interventions were made. The program’s approach and the time scientists spent on the fishers’ vessels were key ingredients to fishers’ participation and the utility of the results. Despite the program’s achievements the information generated has not led to improved management or had any direct benefits for the participants. Sustaining the program in the longer term requires that its value is better captured.

Biodiversity, Carbon Stocks and Community Monitoring in Traditional Agroforestry Practices: Preliminary Results from Two Investigated Villages in Berau, East Kalimantan

Traditional agroforestry practices in Berau, East Kalimantan, are suitable land use types to conserve that potentially support the implementation of REDD+. The objectives of this research are to assess biodiversity and carbon stock in various traditional agroforestry practices, also to determine the accuracy of the ability levels of local community in biodiversity and carbon stock monitoring. This paper presents the implementation plan and preliminary data in Kampung Birang and Kampung Merabu, in Berau district. Professional forester-led methods of biodiversity and carbon stock assessment follow the recommended procedures, while training component are carried out using different method in order to test the accuracy of monitoring level. First round of data collection in both villages identified main fruit trees, locally known as langsat, in Kampung Birang, while different durian were found in Kampung Merabu. Field observation showed that the total time taken for completing the monitoring work has declined in line with the work cycle progress supported by willingness of community to participate in the monitoring program.

Real-time PCR validation of visually identified snapper Chrysophrys auratus (Sparidae) eggs.

In this study, a total of 212 eggs were visually identified as snapper Chrysophrys auratus. Real-time PCR confirmed visual identification in 69% of cases but corroboration varied widely among plankton samples. The use of molecular tools to support visual identification prior to adopting daily egg production stock assessment methods should be considered.

A Mixed-Method Approach for Quantifying Illegal Fishing and Its Impact on an Endangered Fish Species.

Illegal harvest is recognized as a widespread problem in natural resource management. The use of multiple methods for quantifying illegal harvest has been widely recommended yet infrequently applied. We used a mixed-method approach to evaluate the extent, character, and motivations of illegal gillnet fishing in Lake Hovsgol National Park, Mongolia and its impact on the lake’s fish populations, especially that of the endangered endemic Hovsgol grayling (Thymallus nigrescens). Surveys for derelict fishing gear indicate that gillnet fishing is widespread and increasing and that fishers generally use 3–4 cm mesh gillnet. Interviews with resident herders and park rangers suggest that many residents fish for subsistence during the spring grayling spawning migration and that some residents fish commercially year-round. Interviewed herders and rangers generally agree that fish population sizes are decreasing but are divided on the causes and solutions. Biological monitoring indicates that the gillnet mesh sizes used by fishers efficiently target Hovsgol grayling. Of the five species sampled in the monitoring program, only burbot (Lota lota) showed a significant decrease in population abundance from 2009–2013. However, grayling, burbot, and roach (Rutilus rutilus) all showed significant declines in average body size, suggesting a negative fishing impact. Data-poor stock assessment methods suggest that the fishing effort equivalent to each resident family fishing 50-m of gillnet 11–15 nights per year would be sufficient to overexploit the grayling population. Results from the derelict fishing gear survey and interviews suggest that this level of effort is not implausible. Overall, we demonstrate the ability for a mixed-method approach to effectively describe an illegal fishery and suggest that these methods be used to assess illegal fishing and its impacts in other protected areas.

Can a spatially-structured stock assessment address uncertainty due to closed areas? A case study based on pink ling in Australia

Spatial structure in biological characteristics and exploitation rates impact the performance of stock assessment methods used to estimate the status of fish stocks relative to target and limit reference points. Spatially-structured stock assessment methods can reduce the bias and imprecision in the estimates of management-related model outputs. However, their performance has only recently been evaluated formally, in particular when some of the area fished is closed. In order to evaluate the effects of closed areas and spatial variation in growth and exploitation rate when estimating spawning biomass, a spatially-explicit operating model was developed to simulate spatial data, and five configurations of the stock assessment package Stock Synthesis (three of which were spatially structured) were applied. The bias in estimates of spawning stock biomass associated with spatially-aggregated assessment methods increases in the presence of closed areas while these biases can be reduced (or even eliminated) by applying appropriately constructed spatially-structured stock assessments. The performance of spatially-aggregated assessments when estimating spawning stock biomass is found to depend on the interactions among spatial variation in growth, in exploitation rate, and in knowledge of the spatial areas over which growth and exploitation rate are homogeneous.

Biases in biomass estimates: The effect of bin width in size-structured stock assessment methods

Size-structured assessment models require size data to be binned, but it is unclear how a specified bin width can impact the ability of an assessment to estimate quantities important in management. Biases in estimated mature biomass are demonstrated here when increasing the bin width using a simulation framework based on the Pribilof Islands red king crab (PIRKC) assessment. Several potential sources of bias were explored through simulation. The bias was removed by applying an alternative assessment method which used a finer approximation of the integral representing the probability of a crab molting from one size bin. Trade-offs exist at both sides of the bin width spectrum. Precision and model stability may suffer when bin width is too large; slowed parameter estimation and problems fitting multinomial likelihoods to length frequency data may appear when bin widths are too small. Simulation studies (like the one presented here) are useful for identifying optimal bin width for management related tasks.

Which assessment configurations perform best in the face of spatial heterogeneity in fishing mortality, growth and recruitment? A case study based on pink ling in Australia

Most fisheries stock assessment methods are based on the assumption that fish are homogeneously distributed across the area being assessed or that fish movement is such that local fishing pressure does not lead to heterogeneous spatial patterns of abundance. However, this assumption is seldom valid in practice. Seven alternative approaches for conducting assessments when confronted with possible spatial variation in fishing mortality, growth and recruitment are identified. These approaches range from ignoring spatial structure, to conducting a multi-area assessment that accounts for spatial variation in biological and fishery processes. These seven approaches are tested using simulations in which there is a single population with spatial heterogeneity, and the only linkage among areas is larval movement. The simulations are based on fishery and biological characteristics for pink ling, Genypterus blacodes, off southeast Australia. Non-spatial assessment configurations that aggregate spatially-structured data provide more precise, but nevertheless biased estimates of initial and final spawning biomass, as well as biased estimates of the ratio between initial and final spawning biomass. Assessment configurations that allow for spatial structure can provide imprecise and highly biased estimates, although these can be improved by changing the relative weighting applied to different data types. A spatially-structured assessment configuration that correctly matches the structure of the model used to generate the simulated data sets is unbiased but imprecise. When confronted with possible spatial heterogeneity in biological and fishery parameters, we propose conducting sensitivity analyses based on several model configurations to select the appropriate structure for an assessment. The capacity to examine model residuals spatially remains valuable for inferring problems with model specification.

Separating recruitment and mortality time lags for a delay-difference production model

Many fishery production models implicitly incorporate a single time lag for both recruitment and mortality despite the fact that in populations of breeding adults, deaths occur yearly while the entry of new adults comes from juveniles born potentially many years prior to adulthood. Models that do not account for this difference in timing will overestimate abundance for a decreasing stock and underestimate increases during a recovery period. We investigated the effect of incorporating unequal recruitment and mortality time lags into depletion-based stock reduction analysis (DB-SRA), a stock assessment method for data-poor species. Using both simulated data and catch series of Pacific rockfish (Sebastes spp.), we found that for declining stocks with no mortality delay and a recruitment time lag equal to age-at-maturity, estimated overfishing limits were up to 40% lower than those from the model with both time lags equal to age-at-maturity. Deviation between the two models’ predictions increases with age-at-maturity and natural mortality rate, suggesting that time lag separation is most important for long-lived species. We propose a correction factor for net production models that eliminates stock overestimation due to implicitly equal time lags.

Stock assessment methods for sustainable fisheries

Abstract This special volume of the ICES Journal compiles contributions from the World Conference on Stock Assessment Methods for Sustainable Fisheries (July 2013, Boston, USA). The conference was the product of a strategic initiative on stock assessment methods that engaged many national and regional fishery management organizations to assure that scientists can apply the most appropriate methods when developing management advice. An inclusive workshop was designed to evaluate the performance of a variety of model categories by applying multiple models to selected case study data as well as simulated pseudo-data that had realistic measurement error. All model applications had difficulties in recovering the simulated stock and fishing mortality trends, particularly at the end of the assessment time series, when they are most important for informing fishery management. This general result suggests that the next steps in evaluating the performance of stock assessment methods should include stock status relative to sustainable reference points, catch advice, multi-model consideration, and alternative management procedures. Recognition of the limitations of conventional stock assessment methods should promote further development of data-limited approaches, methods with time-varying parameters, or spatial complexity, and a more revolutionary shift towards the application of multispecies and ecosystem models. The contributions in this volume address methodological themes that are expected to improve the scientific basis of fishery management. Furthermore, the limitations of stock assessment methods and associated uncertainty should be more extensively considered in fishery management strategies and tactical decisions. Recommendations developed during the conference called for the establishment of a global initiative to synthesize regional advances, form guidance on best practices, promote strategic investments, and highlight research needs for fish stock assessments.