Five decades of stomach content data allowed insight into the development of consumption, diet composition, and resulting somatic growth of Gadus morhua (Atlantic cod) in the eastern Baltic Sea. We show a recent reversal in feeding level over body length. Present feeding levels of small cod indicate severe growth limitation and increased starvation-related mortality. For young cod, the low growth rate and the high mortality rate are manifested through a reduction in size-at-age. The low feeding levels are likely the result of a decrease in benthic prey abundance due to increased hypoxic areas, while decreasing abundances of pelagic species in the area of cod distribution have prevented a compensatory shift in diet. Our study emphasizes that environmental forcing and the decline in pelagic prey caused changes in consumption and growth rates of small cod. The food reduction is amplified by stunted growth leading to high densities of cod of smaller size competing for the scarce resources. The average growth rate is negative, and only individuals with feeding levels well above average will survive, though growing slowly. These results suggest that the relation between consumption rate, somatic growth and predatorprey population densities is strongly environmentally mediated.

Different ecosystem models often provide contrasting predictions (model uncertainty), which is perceived to be a major challenge impeding their use to support ecosystem-based fisheries management (EBFM). The focus of this manuscript is to examine the extent of model disagreements which could impact management advice for EBFM in the central Baltic Sea. We compare how much three models (EwE, Gadget and a multispecies stock production model) differ in 1) their estimates of fishing mortality rates (Fs) satisfying alternative hypothetical management scenario objectives and 2) the outcomes of those scenarios in terms of performance indicators (spawning stock biomasses, catches, profits). Uncertainty in future environmental conditions affecting fish was taken into account by considering two seal population growth scenarios and two nutrient load scenarios. Differences in the development of the stocks, yields and profits exist among the models but the general patterns are also sufficiently similar to appear promising in the context of strategic fishery advice. Thus, we suggest that disagreements among the ecosystem models will not impede their use for providing strategic advice on how to reach management objectives that go beyond the traditional maximum yield targets and for informing on the potential consequences of pursuing such objectives. This is especially true for scenarios aiming at exploiting forage fish sprat and herring, for which the agreement was the largest among our models. However, the quantitative response to altering fishing pressure differed among models. This was due to the diverse environmental covariates and the different number of trophic relationships and their functional forms considered in the models. This suggests that ecosystem models can be used to provide quantitative advice only after more targeted research is conducted to gain a deeper understanding into the relationship between trophic links and fish population dynamics in the Baltic Sea.

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A B S T R A C TLike other fisheries models, multispecies models are subject to various sources of error. However, with regard to their use for ecosystem-based fisheries management (EBFM) between model errors are likely to be most important. As multispecies models are by definition many-dimensional, comparing them is potentially a complex task. The paper uses a simple approach. This is to calculate the Jacobian matrix of long term steady state catch by species with respect to the fishing mortality relative to status quo levels on all species. This enables the comparison of the relative strength of species interactions among models both within and between regions. This Jacobian matrix approach to comparing multispecies models is applied to available models for the North Sea, the Baltic Sea and from Icelandic waters. Moreover, this information is used to provide the basis for estimating a multidimensional quadratic yield surface for each model in the near field. Used this way it is possible to compare different model estimations of fishing mortality rate changes needed to approach yield-related management goals. The results suggest considerable variation between models in their detailed results but more coherence in suggesting directions for changing fishing mortality rate. Thus the approach is of considerable importance in specifying the confidence with which it is possible to make multispecies predictions for EBFM.

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Predators often predate on a limited size range of prey, which may or may not overlap with size ranges of same prey targeted by fisheries. When they do overlap, the effect of competition over that prey is immediate, as the predator removes prey, which are at the same time suitable for the fishery. However, if the predator consumes the same prey species as the fishery, but targets smaller prey sizes, this predation on smaller sizes may result in a potential loss of future, rather than current, fishing opportunities. Comparative analyses of predator size preference and fisheries selectivity are scarce, despite their relevance in the context of integrated management of fish populations. We evaluated how size-selective cod predation influences the dynamics of sprat and herring in the Baltic Sea, as well as the competition with pelagic fisheries through immediate and delayed effects. We found a large overlap (30–60%) between prey lengths targeted by cod and fisheries, which was largest in the 1970s–1980s,  when cod had higher abundance and was larger in size. Cod generally consumes herring and sprat, which are smaller than those caught by the fisheries, causing both immediate and delayed effects on prey biomass available for the fisheries.

This report summarizes and synthesizes results from the Swedish Agency of Marine and Water Management (SwAM, or HaV) funded project “Förvaltningsmål för nationella arter (Management goals for nationally managed species)”. The objectives of the project have been to promote the development of management goals and associated status assessment methods and indicators, as well as reference points, for some nationally managed fish stocks both in coastal as well as freshwater areas. The report focusses largely on species and stocks that can be defined as data-poor. Such stocks are characterised by marked limitations in data availability and/or resources allocated to detailed analytical stock projections. Data-poor stocks also often lack carefully formulated management goals and associated methods and indicators for assessing stock status. In this report, we provide an overview of potential assessment methods and indicators and try to synthesise how they work and what the strengths and weaknesses are by applying them to selected data poor stocks such as pikeperch, pike, whitefish, and vendace. We also discuss how they relate to different potential management goals and provide recommendations for their application. We grouped the indicators and assessment methods by the three categories that are now used in the yearly status assessment framework provided by SLU Aqua (Resursöversikten/Fiskbarometern) – i) mortality, ii) abundance/biomass and iii) size/age structure. The results are also described for these three main categories of assessment indicators. Included is also a status report from a size- and age-based population dynamics model (Stock Synthesis 3) that is being developed for pikeperch in Lake Hjälmaren. An important experience from the project is that to improve the assessment methods for Swedish national fish stocks, it is important that managers develop both general as well as more detailed quantitative goals for the individual stocks. This should ideally be conducted in various forms of collaboration with the main stakeholders and scientists involved with assessment as participatory processes foster legitimacy. Carefully articulated management goals, which are possible to translate into quantitative targets, will facilitate the development of various approaches and methods to monitor stock statuses. Given the strong and complex interactions of fish and their environments it is also important to consider other pressures than fisheries when developing indicators and assessment methods. Our synthesis highlights a number of areas where the assessment of data-poor stocks can be improved: 1. Apply precautionary principles for data-limited stocks, particularly ones that are known to be vulnerable to exploitation. 2. Tailor approaches to how fisheries are managed in Sweden. Swedish nationally managed fish stocks are not managed by quotas (with one exception, vendace in the Bothnian Bay) and do not aim for maximum sustainable yield. Instead, the coastal and inland fisheries are managed by regulating the effort in the small-scale commercial fisheries (number of fishers/licenses and amount of gear). Regulation of recreational and subsistence fisheries effort, in terms of licenses or number of fishers) is not applied, nor possible since the fisheries is lacking obligatory notification and reporting systems. All national fisheries, however, are regulated by various technical measures (closed areas, size-limits, bag-limits, gear restrictions etc). Thus, goals and assessment methods that result in harvest limits or quota recommendations expressed in e.g. biomass/numbers are difficult to use as basis for management. Instead, there is a need for alternative management goals and associated assessment methods. 3. Use best practice methods and indicators and adapt as scientific knowledge is developed. Data-limited methods are developing rapidly, and new methods/approaches are proposed in the scientific literature every year. It is thus important to be updated on the most recent developments. 4. Clearly describe limitations/assumptions of methods used. It is important to be aware of and critically evaluate the assumptions underlying the analyses, and to carefully communicate uncertainty together with the stock status assessment. 5. Be particularly careful with low sample numbers. Many indicators and methods can be applied also on small sample sizes, however, the accuracy and precision of the estimates risk being low in such cases. 6. Accept that there is no "gold standard" for fisheries assessment. Each case study is unique and needs to be balanced against data availability, local needs and other important factors. This also means that analysts need to be careful when using generic reference levels or “borrowing” data from other stocks. 7. If possible, use several different methods/indicators. Although several indicators aim to measure similar aspects of the stock, small methodological differences can support the overall interpretation of individual indicator values. It is particularly important to incorporate many aspects and indicators (size/age/abundance/mortality) in order to produce a balanced assessment. 8. Develop means of communication. Indicators and goals should be easy to understand. However, interpretation of results from multi-indicator frameworks can be challenging. There is thus a need for finding ways of communication that can convey complicated results in a simple-to-understand manner. 9. For details on additional improvements, we refer the reader to the sub-header “recommendations for the future” found under each chapter. The implementation of Stock Synthesis for pikeperch in Lake Hjälmaren showed that it is possible to develop a more ambitious and detailed stock assessment model for a relatively data-poor stock. The model results partly support earlier interpretations of the development of the stock and the importance of the changes in regulations in 2001 (increased minimum size, increased mesh size and reduced mortality of undersized pikeperch). Before the model can be implemented and used for practical management, a number of actions for improvement are needed, which are highlighted in the relevant chapter. The most important next step is establishing management goals and reference levels for this stock. We recommend that such a dialogue is initiated by managers. The fisheries management goals should consider both biomass, fisheries mortality and size-based targets. To conclude, we stress the importance of improving all ongoing aspects related to the assessments of data-poor Swedish stocks. Strong local stocks and sustainable fisheries are vital for a variety of fisheries-related businesses and practices, particularly in rural areas, providing economical and societal value. Fishes also have important roles in aquatic food-webs and it is important that ecological values are managed wisely in order to reach targets for water quality, ecosystem structure and diversity. Given the strong and complex interactions of fish and their environments it is also important to consider other pressures than fisheries when developing indicators and assessment methods.