Value of data in stock assessment models with misspecified initial abundance and fishery selectivity

The a4a initiative aims to provide timely and cost effective advice for the circa. 250 fish stocks that,\nthrough the EU Data Collection Framework, will have at least 10 years of data by the year 2020. Current\nprocesses for assessing the state of and managing fish stocks are intensive processes, each stock\nrequiring the attention of one or more stock assessment scientist to produce preliminary catch advice,\nwhich is subsequently reviewed by one or two committees before the final catch advice is published.\nIngrained in the development of these processes has been the development of more and more complex\nstock assessment models which typically require highly skilled personnel to set up and run.

This study aimed to evaluate the stock status of chub mackerel (Scomber japonicus) in the Northwest Pacific Ocean. Chub mackerel is a commercially important fish species in South Korea. The fishing grounds of chub mackerel are in the Northwest Pacific Ocean, off South Korea and the neighboring countries of China and Japan. Previous chub mackerel stock assessments have mostly been based on catch data from a single country. However, in this study we used the total catch data on chub mackerel in the Northwest Pacific Ocean to assess the stock status, owing to their migrations and occurrence in the waters of several different countries. We used a catch and maximum sustainable yield model, which is based on catch and resilience data, using the Monte Carlo method. Moreover, sensitivity analysis was conducted according to the availability of catch data by sea area and country. The results showed that the current level of chub mackerel biomass is lower than the biomass required to achieve a maximum sustainable yield based on median values. Furthermore, analysis of all scenarios showed the same results, while the current biomass showed a decreasing trend. These results indicate that improved cooperative resource management is required to prevent further stock status decline.

Conventional stock assessment models require large amounts of historical catch and effort data, which are often unavailable for small-scale fisheries such as the blue swimming crab ( Portunus pelagicus ) fishery on the east coast of Aceh. The lack of stock assessment models applicable to many fish species with limited data, such as the BSC, has hindered policymakers' ability to monitor fish stock status more effectively. When historical catch data, abundance indices, or age-composition data are unavailable, stock assessment methods can be employed using size and/or life history information. This study aimed to determine the stock status of P. pelagicus using limited data, focusing on the length-based spawning potential ratio. Data were collected periodically at several crab landing sites along the eastern coast of Aceh. Based on the life history parameters analyzed, the crab stock was categorized as overexploited (red flag), with an SPR < 0.2 (20%). In line with this assessment, the crab exploitation ratio ( F / M ) was high at 1.85, with an exploitation rate ( E ) of 0.71, indicating overfishing. Management actions to reduce crab fishing effort are necessary to improve the status of the stock and achieve a healthier stock.

Advice on fishing opportunities is based on stock assessment models. Modern stock assessment frameworks are designed to account for uncertainty in model parameters. However, some parameters are often fixed at specific values and assumed to be known precisely. Paradoxically, these fixed values often relate to parameters we understand the least—such as the natural mortality rate. For example, in the assessment of Norwegian Spring-Spawning Herring, the natural mortality rate is assumed to be exactly 0.9 for age 2 fish and 0.15 for older fish. In this study, we investigate how sensitive the assessment results—and, more specifically, the resulting fishing quotas (total allowable catch, TAC)—are to assumptions regarding natural mortality and maturity-at-age for both Norwegian Spring-Spawning Herring and North-East Arctic Cod. The assessment models for both stocks are formulated within the SAM framework. Furthermore, we explore a simple approach for adjusting harvest control rules that seeks to preserve the TACs when fundamental fixed assumptions are altered. Our intention is that this serves as an exploratory tool to investigate sensitivity to new assumptions, and is not intended to replace a more formal process for defining new biological reference points and harvest control rules. The results indicate that, under the current harvest control rules, the TACs for both herring and cod may be sensitive to assumptions regarding natural mortality rates and maturity-at-age. For herring, sensitivity to natural mortality is significantly greater than is reflected by the estimation uncertainty in model parameters. However, when basic assumptions are changed, it is also natural to consider corresponding adjustments to the harvest control rules. Our proposed simple adjustments to the control rules reduce sensitivity to these assumptions in many cases, though not in all.

How does growth misspecification affect management advice derived from an integrated fisheries stock assessment model?

A previously reported positive influence of a distractor alternative on decision accuracy was driven by an unintended covariation between key variables, beyond which the distractor has a modest negative influence on accuracy, possibly mirroring asymmetric multiattribute context effects.

Cordue, P. L. 2012. Fishing intensity metrics for use in overfishing determination. – ICES Journal of Marine Science, 69: 615–623. The issue of constructing a technically correct fishing intensity metric from the output of a stock assessment model is considered. Four metrics of annual overall “fishing intensity” are defined. The metrics are applicable to age- or length-structured stock assessment models, which may, or may not, include complex spatial and temporal structure in the population and the fisheries. Two of the metrics are termed “direct” as they are calculated from the model output in the given year. Equivalent annual U is a number-based exploitation rate, and equivalent annual F is an average fishing mortality rate. The other two metrics, equilibrium stock depletion (ESD) and spawning potential ratio (SPR), measure fishing intensity in terms of the potential long-term effect on the stock (via 1–ESD and 1–SPR). The use of the metrics for overfishing determination is illustrated with a simple, spatial, two-fishery model. Summary statistics, which are sometimes used as a measure of fishing intensity, such as total catch over a reference biomass, or a number-weighted F are shown to be technically invalid for overfishing determination. The common approach, for virtual population analysis assessments, of using an average F over a specified age range is also discussed.

Punt, A. E., Huang, T., and Maunder, M. N. 2013. Review of integrated size-structured models for stock assessment of hard-to-age crustacean and mollusc species. – ICES Journal of Marine Science, 70:16–33. Crustaceans and molluscs such as crabs, rock lobsters, prawns, abalone, and oysters constitute large and valuable fisheries. However, assessments of these species are hampered because they cannot be production aged, in contrast to many teleosts. The major data sources for these species, in addition to catch and abundance index data, are the size compositions of the catches and of any fishery-independent indices. Assessments of such species have been conducted using age-based methods of stock assessment, as well as surplus production models. However, size-structured methods are now preferred because they can make full use of size-composition data, are able to integrate multiple sources of data, and produce the types of outputs which are needed for management purposes. An advantage of size-based models over age-based models is that all processes can be size-based, and these processes can modify the (unmodelled) size-at-age distribution. We review these methods, highlighting the choices that need to be made when developing integrated size-structured stock assessments, the data sources which are typically available and how they are used for parameter estimation, and contrast a number of such assessments worldwide.

The ICES Benchmark Workshop on Baltic Cod Stocks (WKBALTCOD2) met at ICES Headquarters in Copenhagen, Denmark on 4–8 February 2019, following a data evaluation workshop (Chair Johan Lovgren) and several preparatory web conference meetings. The meeting, cochaired by Meaghan Bryan, USA (External Chair) and Michele Casini, Sweden (ICES Chair), was attended by two invited external experts, Vladlena Gertseva, USA, and Verena Trenkel, France, and 47 participants from 10 countries. Participants represented a diversity of groups including industry, NGOs, managers, and scientists. The objectives of WKBALTCOD2 were to evaluate the appropriateness of the data and the assessment methods to determine stock status for the Western Baltic cod (SD 22-24) and the Eastern Baltic cod (SD 24-32) stocks, evaluate the short-term forecasting methods, re-examine and update the reference points, and update the stock annex as appropriate to these stocks. The workshop started with a group discussion of data issues and decisions that were integral to both assessments. Subsequent, stock-specific discussions were held in smaller subgroups and the main results and conclusions were presented in plenary. Around 15–20 persons, together with at least one external reviewer/co-chair, participated in each of the subgroups. A single modelling approach, the state-space stock assessment model (SAM), was presented for Western Baltic cod. This model has been used previously to determine stock status of Western Baltic cod and the panel agreed that this model should be used for the current assessment. The main issues that emerged and were addressed during the workshop for this stock were stock mixing in SD 24, the inclusion of new recreational data from Sweden and Denmark, the inclusion of a German pound-net survey index of age-0 fish in the assessment model, the extension of the time-series of the assessment back in time, and the update of reference points. Future efforts should be made to update the mixing proportion of Eastern and Western Baltic cod in SD 24 by length and season, and continue improving the stock splitting methods and the geographical coverage of the samples. An analytical quantitative assessment had been lacking since 2014 for the Eastern Baltic cod stock. The key issues addressed during the benchmark included how to best account for changes in productivity (e.g. growth, mortality, maturity) in the assessment model, stock splitting in SD 24, the use of age–length keys in the assessment, and ageing error and bias. Stock assessment models using Stock Synthesis and the stochastic surplus production model (SPiCT) were put forward for the benchmark as two possible model candidates. The panel agreed that the Stock Synthesis model assuming time-varying growth, natural mortality, and maturity to account for changes in productivity was acceptable to provide scientific advice, while the SPiCT model should be maintained as an alternative approach. The accepted model exhibited some residual patterns that were likely due to assuming that ages were precisely known. Stock Synthesis can accommodate an ageing error matrix to account for precision and bias. Ageing error and bias statistics should be developed and thoroughly reviewed for the next benchmark. Additionally, future work should focus on improving the growth estimates, which will allow a more precise separation between growth and natural mortality. The Stock Synthesis model would also benefit from information on sample size associated with length distributions of commercial catches. Estimates of fishing mortality compatible with a precautionary FMSY was not attainable for this stock, therefore probabilistic forecasts with Markov chain Monte Carlo methods were proposed to be used instead.

Integrating the standardization of catch-per-unit-of-effort into stock assessment models: testing a population dynamics model and using multiple data types

Incorporating fecundity into stock assessment models may improve stock assessment and management of Bristol Bay red king crab Paralithodes camtschaticus. To do this, the size—fecundity relationship for the population must be established, including variability due to female reproductive state. In 2012, egg clutches were collected from red king crab in Bristol Bay, AK, and individual fecundity was estimated. Best evidence suggests small females were primiparous (brooding first egg clutch), which provided the opportunity to compare estimated fecundity of primiparous and multiparous (brooding second or subsequent egg clutch) females. In the best-fit model, fecundity increased with female size and below 108.8 mm carapace length (CL) the slope of the size—fecundity relationship decreased by 27%.Multiparous females were 28%–30% more fecund than primiparous females of the same size. If managers incorporate fecundity into stock assessment models, the differences in fecundity between primiparous and multiparous females should be considered, otherwise population fecundity will be overestimated if the size—fecundity relationship of only multiparous females is used in the calculations because of the differences in fecundity between primiparous and multiparous females of the same size.

Evaluation of virgin recruitment profiling as a diagnostic for selectivity curve structure in integrated stock assessment models

Marine recreational fishing (MRF) is a popular outdoor activity that contributes substantially to total harvest in many coastal stocks, yet it is rarely integrated into stock assessments and its impact on target stocks is often unknown. For the red-listed European lobster ( Homarus gammarus ) in Norway , we applied two probabilistic off-site survey methods (diary and recall) to estimate participation, effort, harvest rates and total harvest across regions. The effects of accounting for MRF were then evaluated in a stock assessment model. The recall method achieved higher response rates and resulted in slightly lower harvest estimates than the diary survey. When combined with a mandatory national registration system, these methods enabled cost-efficient and representative estimation of total harvest. Recreational fishers accounted for 71–90% of total lobster removals, confirming their dominant role in the fishery. If recreational harvest was not accounted for, the stock status was overestimated, while current fishing pressure was significantly underestimated. Our findings demonstrate that excluding MRF can mask unsustainable exploitation of an overexploited stock and hinder effective management. We show that combining registration with low-burden methods provides practical and reliable foundation for incorporating MRF into stock assessments, a first step towards achieving sustainable coastal fisheries management. Graphical abstract

Recent advancements in integrated single-species models allow for the inclusion of environmental drivers in stock assessment models, improving stock evaluation and better explaining fish population dynamics. This study applies Stock Synthesis (SS) to assess the European anchovy (Engraulis encrasicolus) stock in the Adriatic Sea, allowing for time-varying growth, recruitment, mortality, and survey catchability. These processes were linked to sea surface temperature (SST), river runoff, chlorophyll-a concentration, and salinity. Model selection, based on AIC and parameter significance, revealed that higher SST is significantly associated with reduced mean length-at-age. Two-variable models further revealed that SST strongly influences growth, while freshwater input modulates mortality at age one and survey catchability. Integrating these environmental factors reduced unexplained recruitment variability and improved model fit to length- and age-composition data, enhancing stock status estimates such as spawning biomass and fishing mortality. Diagnostic evaluations indicate that the integration of environmental covariates, despite inherent challenges associated with data quality, offers valuable insights into the observed declines in anchovy size and recruitment. The findings emphasize the importance of environmental conditions—particularly temperature and freshwater discharge—in driving life-history traits and population dynamics.

Specifying annual catch limits for artisanal fisheries, low economic value stocks, or bycatch species is problematic due to data limitations. Many empirical management procedures (MPs) have been developed that provide catch advice based on achieving a stable catch or a historical target (i.e., instead of maximum sustainable yield). However, a thorough comparison of derived yield streams between empirical MPs and stock assessment models has not been explored. We first evaluate trade-offs in conservation and yield metrics for data-limited approaches through management strategy evaluation (MSE) of seven data-rich reef fish species in the Gulf of Mexico. We then apply data-limited approaches for each species and compare how catch advice differs from current age-based assessment models. MSEs identified empirical MPs (e.g., using relative abundance) as a compromise between data requirements and the ability to consistently achieve management objectives (e.g., prevent overfishing). Catch advice differed greatly among data-limited approaches and current assessments, likely due to data inputs and assumptions. Adaptive MPs become clearly viable options that can achieve management objectives while incorporating auxiliary data beyond catch-only approaches.