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The complexities of ecosystem-based management require stepwise approaches, ideally involving stakeholders, to scope key processes, pressures, and impact in relation to sustainability and management objectives. Use of qualitative methods like Fuzzy Cognitive Mapping (FCM) with a lower skill and data threshold than traditional quantitative models afford opportunity for even untrained stakeholders to evaluate the present and future status of the marine ecosystems under varying impacts. Here, we present the results applying FCM models for subregions of the North Sea. Models for the southern North Sea, Skagerrak, Kattegat, and the Norwegian Trench were developed with varying level of stakeholder involvement. Future scenarios of increased and decreased fishing, and increased seal biomass in the Kattegat, were compared with similar scenarios run on two quantitative ecosystem model. Correspondence in response by the models to the same scenarios was lowest in the southern North Sea, which had the simplest FCM model, and highest in Norwegian Trench. The results show the potential of combining FCM and quantitative modelling approaches in integrated ecosystem assessments (IEAs) and in future ecosystem-based management advice, but to facilitate such comparisons and allow them to complement and enhance our IEAs, it is important that their components are aligned and comparable. [ABSTRACT FROM AUTHOR]

Ecosystem-based management requires understanding of food webs. Consequently, assessment of food web status is mandatory according to the European Union's Marine Strategy Framework Directive (MSFD) for EU Member States. However, how to best monitor and assess food webs in practise has proven a challenging question. Here, we review and assess the current status of food web indicators and food web models, and discuss whether the models can help addressing current shortcomings of indicator-based food web assessments, using the Baltic Sea as an example region. We show that although the MSFD food web assessment was designed to use food web indicators alone, they are currently poorly fit for the purpose, because they lack interconnectivity of trophic guilds. We then argue that the multiple food web models published for this region have a high potential to provide additional coherence to the definition of good environmental status, the evaluation of uncertainties, and estimates for unsampled indicator values, but we also identify current limitations that stand in the way of more formal implementation of this approach. We close with a discussion of which current models have the best capacity for this purpose in the Baltic Sea, and of the way forward towards the combination of measurable indicators and modelling approaches in food web assessments. [ABSTRACT FROM AUTHOR]

The occurrence of regime shifts in marine ecosystems has important implications for environmental legislation that requires setting reference levels and targets of quantitative restoration outcomes. The Baltic Sea ecosystem has undergone large changes in the 20th century related to anthropogenic pressures and climate variability, which have caused ecosystem reorganization. Here, we compiled historical information and identified relationships in our dataset using multivariate statistics and modeling across 31 biotic and abiotic variables from 1925 to 2005 in the Central Baltic Sea. We identified a series of ecosystem regime shifts in the 1930s, 1970s, and at the end of the 1980s/beginning of the 1990s. In the long term, the Central Baltic Sea showed a regime shift from a benthic to pelagic‐dominated state. Historically, benthic components played a significant role in trophic transfer, while in the more recent productive system pelagic–benthic coupling was weak and pelagic components dominated. Our analysis shows that for the entire time period, productivity, climate, and hydrography mainly affected the functioning of the food web, whereas fishing became important more recently. Eutrophication had far‐reaching direct and indirect impacts from a long‐term perspective and changed not only the trophic state of the system but also affected higher trophic levels. Our study also suggests a switch in regulatory drivers from salinity to oxygen. The "reference ecosystem" identified in our analysis may guide the establishment of an ecosystem state baseline and threshold values for ecosystem state indicators of the Central Baltic Sea. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Biomass reconstructions to pre-assessment periods for commercially important and exploitable fish species are important tools for understanding long-term processes and fluctuation on stock and ecosystem level. For some stocks only fisheries statistics and fishery dependent data are available, for periods before surveys were conducted. The methods for the backward extension of the analytical assessment of biomass for years for which only total catch volumes are available were developed and tested in this paper. Two of the approaches developed apply the concept of the surplus production rate (SPR), which is shown to be stock density dependent if stock dynamics is governed by classical stock-production models. The other approach used a modified form of the Schaefer production model that allows for backward biomass estimation. The performance of the methods was tested on the Arctic cod and North Sea herring stocks, for which analytical biomass estimates extend back to the late 1940s. Next, the methods were applied to extend biomass estimates of the North-east Atlantic mackerel from the 1970s (analytical biomass estimates available) to the 1950s, for which only total catch volumes were available. For comparison with other methods which employs a constant SPR estimated as an average of the observed values, was also applied. The analyses showed that the performance of the methods is stock and data specific; the methods that work well for one stock may fail for the others. The constant SPR method is not recommended in those cases when the SPR is relatively high and the catch volumes in the reconstructed period are low. [ABSTRACT FROM AUTHOR]

Highlights: [•] It is difficult to predict food-web consequences resulting from arrival of a new non-native species. [•] We explore implications using a novel suite of complimentary ecosystem modelling tools. [•] Fistularia commersonii is reported as the fastest spreading lessepsian fish migrant ever recorded. [•] We used the Rank Proportion Algorithm (RPA) to predict the diet composition of this species. [•] An Ecopath with Ecosim (EwE) model was used to simulate consequences for commercial fisheries. [Copyright &y& Elsevier]