Managing fisheries and ecosystems: current good practices and the EcoScope project experience

Abstract

Ecosystem Based Management (EBM) is a comprehensive way of managing fisheries and marine resources. As such, it needs a large and complex suite of concepts and tools to address a variety of problems ranging from climate change, through various forms of water pollution, to trophic interactions and social-economic sustainability. Industry, scientists, managers, and policy makers involved in the fisheries sector are the main actors in EBM. EBM objectives based on policy needs, legal requirements, and ecosystem considerations may target specific fish stocks, or encompass several ecosystem components aiming for balanced fisheries, but they need to address the trade-offs between maximizing economic gains versus sustainable fisheries and healthy ecosystems. Fishing at Maximum Sustainable Yield (MSY), setting ecosystem reference points, discards ban, avoiding bycatch of protected species, habitat protection, accounting for the effects of climate change, achieving good environmental status, setting effective marine protected areas, and considering ecosystem effects from marine spatial planning, are all examples of EBM objectives. The EcoScope project aimed to address ecosystem degradation, anthropogenic impacts, and unsustainable fisheries by developing an efficient, holistic, ecosystem-based approach to sustainable fisheries management that can easily be used by policy makers and advisory bodies. The EcoScope consortium reflects an interdisciplinary advisory team of biologists, modelers, economists, and social scientists. It performed comprehensive reviews of data, data gaps, and various tools (models, indicators, management evaluation procedures). An online platform, toolbox, academy, and a mobile application are end products delivered and maintained by EcoScope to facilitate knowledge sharing, communication, and education. The EcoScope project has built modules ready to be used in the implementation of EBM, but a more direct approach by the responsible organizations, such as ICES, FAO, GFCM and the EC, is needed to set explicit and formal research and managerial frameworks for implementing and coordinating the EBM activities.

1 Introduction

The ecosystem approach to fisheries (EAF) was introduced in 2001 with the Reykjavik Declaration on Responsible Fisheries in the Marine Ecosystem (Garcia et al., 2003). While the term was not used in the Reykjavik Declaration, organizations such as the International Council for Exploration of the Sea (ICES) and the Food and Agriculture Organization (FAO) of the United Nations adopted EAF for incorporating ecosystem considerations into fishery management. In 2002, the World Summit on Sustainable Development determined that the EAF should be implemented by 2010 (FAO, 2003, 2008, 2009). The term ecosystem-based management (EBM) was defined in the Ecosystem Principles Advisory Panel Report to the US Congress in 1998 (US EPAP, 1998). Steps toward actual implementation of the ecosystem approach followed much later (e.g. Fulton et al., 2019; Townsend et al., 2019; Bastardie et al., 2021; Ramírez-Monsalve et al., 2021; EU, 2022a). Over the years, the management of ecosystems and fisheries has been included in the context of slightly different formulations of Ecosystem Approach to Fisheries (EAF, Garcia et al., 2003), Ecosystem Approach to Fisheries Management (EAFM, EU, 2022a), Ecosystem Based Fisheries Management (EBFM, Craig and Link, 2023), Ecosystem Based Management (EBM, Link and Browman, 2014; Craig and Link, 2023). These formulations have some pronounced differences (Garcia et al., 2003), or describe different application levels of ecosystem management (Patrick and Link, 2015; Dolan et al., 2016); however, the multitude of similar terms creates linguistic uncertainty (Dolan et al., 2016) that might lead to confusion among stakeholders and the general public. The different types of fisheries management approaches (including Single Species fisheries management, SSFM) were addressed in EcoScope (Table 1). As EBM encompasses all other levels, further in this paper we refer to it.

Mapping of the legal base and the main policy players was one of the first tasks in EcoScope (Rodriguez-Perez et al., 2023). Several international acts are relevant to managing fisheries and ecosystems (Table 2). The identification of the EBM starts with the definition of relevant policy problems to be solved (FAO, 2003; Townsend et al., 2019, Table 3). A thorough knowledge of the existing legal and policy basis is a necessary prerequisite in this process (Tables 2, 3).

In the EU, the Common Fisheries Policy (CFP; EU, 1970) reformed in 2013 (CFP; EU, 2013; Tables 2, 3) provides directions that are relevant for the implementation of the ecosystem approach, in particular: the Technical Measures Regulation (EU, 2019a), the Data Collection Framework Regulation, (DCF; EU, 2017a), the Deep Sea Stocks in the North-east Atlantic Regulation (EU, 2016), and the European Maritime and Fisheries Fund Regulation (EMFF; EU, 2014a; Rodriguez-Perez et al., 2023). Unlike the CFP which aims to regulate the fisheries, the Marine Strategy Framework Directive (MSFD; EU, 2008; Table 2) aims to achieve Good Environmental Status (GES) through an ecosystem approach to the management of human activities, and therefore accentuates on keeping safe and healthy ecosystems and their services. Other EU regulations such as the Habitats Directive (HD, EU, 1992), the Water Framework Directive (WFD, EU, 2000), the Birds Directive (BD, EU, 2010), and the Maritime Spatial Planning Directive (MSPD, EU, 2014b), also emphasize nature protection and ecosystem management (Tables 2, 3). The EU Biodiversity Strategy 2030 (EU BS 2030; EU, 2020) is a core part of the European Green Deal (EU, 2019b; Table 3). A core commitment under the BS is the expansion of protected areas to cover 30% of the sea. For fisheries, it sets the targets to maintain or reduce fishing mortality to or under Maximum Sustainable Yield (MSY) levels; to eliminate or reduce bycatch, particularly for sea mammals, turtles, and birds; and to tackle practices that damage the seabed. The Nature Restoration Regulation (NRR, coming into force in mid-2026; EU, 2024), as a key element of the BS, aims to restore ecosystems, habitats, and species, to enable the long-term sustained recovery of biodiverse and resilient nature, and to achieve the EU’s climate mitigation and adaptation objectives. The General Fisheries Commission for the Mediterranean (GFCM) 2030 strategy (FAO, 2021) is binding for the Mediterranean and Black Sea member countries of the GFCM, and includes targets on achieving sustainable fisheries and aquaculture and constraining by-catch of Protected, Endangered, and Threatened Species (PETS).

In this paper, we aim to review the main issues with the state-of-the-art implementation of the EBM, and to share the EcoScope project experience on that matter. The main objective of EcoScope is to pilot the EBM implementation in European seas: the Baltic Sea, the North Sea, the Bay of Biscay, the Balearic Sea, the Adriatic Sea, the Black Sea, the Aegean Sea, and the Levantine Sea. In doing so, EcoScope provides building blocks to be used in assembling the necessary science, managerial, communication, and educational frameworks in Europe.

2 EBM data

EBM needs copious data, and the issue of its scarcity has been raised on a number of occasions (Murawski, 2007; Patrick and Link, 2015; Heymans et al., 2020; Rodriguez-Perez et al., 2023). Data gaps were also found to be a significant barrier reducing the statistical and explanatory power, as well as the predictive ability of models needed in EBM (Heymans et al., 2020). Given the call for more and better data, EcoScope aimed to identify and fill gaps in biological, fisheries, ecological, and socio-economic knowledge across marine ecosystem components and models (Supplementary Material (SM), Abucay et al., 2023; Kesner-Reyes et al., 2025). A short description of the fisheries, ecological, and socio-economic data required for EBM and their deficiencies are presented in the SM.

3 EBM tools

3.1 Fisheries models and indicators

Single stock assessment models (SSMs) are in use with EBM, together with single stock management practices of MSY and total allowable catch (TAC), as well as management strategy evaluations (MSEs) based on operational SSMs. In addition, SSMs are used to produce input data for multi-species and marine ecosystem models (MEMs), bio-economic models, and ecosystem MSE. EcoScope applied tools suitable for assessing data poor stocks such as most of the stocks in the Mediterranean and Black Sea. Commercial and non-commercial fish and invertebrate stocks were assessed in the context of MSY based on a series of new tools: catch maximum sustainable yields (CMSY++; Froese et al., 2023) for commercial species with catch and survey data, and Abundance Maximum Sustainable Yields (AMSY; Froese et al., 2020) for non-commercial stocks for which catch data are lacking but time-series of survey data are available. In data rich situations, when size and/or age structure of catches and abundance surveys are available, statistical catch-at-age models are commonly used, such as stock synthesis (SS3; Methot and Wetzel, 2013), assessment for all (a4a; Jardim et al., 2015), and yield-per-recruit analyses (e.g. STECF, 2023).

A series of community indicators were examined to assess ecosystem health and anthropogenic effects (climate and fisheries) on marine communities to complement the analysis of species distributions. These indicators include recently developed metrics such as the N90 diversity indicator, which is sensitive to both fishing and environmental impacts on diversity (Farriols et al., 2015), the BEnthos Sensitivity Index to Trawling Operations (BESITO; González-Irusta et al., 2018), and widely used indicators such as the mean weighted trophic level of the catch (mTLc), the Fishing-in-Balance index (FiB), and the Fishing Sustainability Index (FSI), which have been used to assess the effect of fisheries on marine ecosystems (Cury et al., 2005). The mean temperature of the catch has been used to evaluate the effect of climate change and variability in marine communities. The populations of sharks and rays were assessed using JARA (Just Another Red-List Assessment), which is a Bayesian state-space model that allows both process error and uncertainty to be incorporated into International Union for Conservation of Nature (IUCN) Red List assessments (Sherley et al., 2020). Finally, three ecosystem indicators and the accompanying thresholds were used to detect and delineate ecosystem fisheries exploitation or ecosystem overfishing: the Ryther index, the Fogarty ratio index, and the Friedland ratio index (Link and Watson, 2019). These indices rely on catch and satellite data, linking fisheries catch/landings to primary production through established constraints of trophic transfer efficiency. They have been previously applied on a global (Link and Watson, 2019) and regional scale (Link et al., 2020; Link, 2021) to determine the degree to which ecosystem overfishing may be occurring, if at all.

Implementing EBM is complex due to the many aspects that have to be considered, such as multi-species interactions, environmental/climate forcing, habitat status, human activities, and stakeholder acceptance. Marine ecosystem models (MEMs) are capable of predicting the effects of management decisions on some of these interrelated variables and can therefore make an important contribution to an effective EBM implementation. The term MEM refers to temporally and/or spatially dynamic models that simulate the marine food-web or the entire ecosystem by incorporating physical, chemical, and biological (i.e. food web) processes under the influence of natural and anthropogenic stressors (Steenbeek et al., 2021). Because models can differ in their structures and functioning, not all ecosystem models can address all EBM policy needs equally. For example, not all MEMs can address spatial issues such as MPAs, and species interactions in the models can be based on functional groups, trophic levels, or size classes, making MSY hard to address. Comprehensive overviews of how MEMs can be used to help EBM are presented by Townsend et al. (2019); Chust et al. (2022), and Craig and Link (2023).

In EcoScope, the common ecosystem modeling platform Ecopath with Ecosim (EwE; Christensen et al., 2024; De Mutsert et al., 2024) was used to create MEMs in different European Sea basins. EwE models use information on fish biomass dynamics, as well as information on other non-fish trophic groups and fisheries, to build mass balanced models (Ecopath), which are then validated as time dynamic models (Ecosim) using time series data (Christensen et al., 2024). These can be further expanded spatially with 3-dimensional spatial-temporal dynamic models (Ecospace, Steenbeek et al., 2013). EwE models can be coupled with low trophic level (LTL) models (Libralato and Solidoro, 2009; Akoglu et al., 2015) to ensure the bottom-up processes are well represented and feed into the higher trophic level interactions represented by EwE. EwE models were compiled and applied to all EcoScope case studies. Environmental and management scenarios were developed and tested in accordance with policy needs (e.g. CFP, MSFD, national policies), and to explore climate change impacts. Policy scenarios under deep uncertainty were tested in relation to future climate conditions and the impact of fisheries and non-indigenous species (NIS). The input and output data for all these models and indicators are freely available online within the EcoScope platform (https://data.ecoscopium.eu).

EcoScope also created Ecological Niche Models (ENM), which predict the actual or potential distribution of a species across a geographic area and time based on environmental and geophysical data (Coro et al., 2016). EcoScope used multiple Artificial Intelligence (AI)-based ENMs to determine the native areas of 1,508 rare and commercial fish and invertebrate species, marine mammals, and reptiles that were indexed by AquaMaps (www.aquamaps.org) as residing in the European Seas based on empirical observations (Coro et al., 2024). The ENMs included Maximum Entropy, AquaMaps, Artificial Neural Networks, and Support Vector Machines. These models were combined into species-specific ensemble models to make the best use of their complementary features and to increase ecological niche prediction accuracy. Distribution maps were produced according to IPCC Representative Concentration Pathways (RCPs) 4.5 and 8.5, representing future environmental projections under medium- and high-greenhouse gas emission scenarios, respectively. The resulting species distribution maps are available through the EcoScope Platform (https://data.ecoscopium.eu), and are used in assessing ecosystem models and simulations. Additionally, a biodiversity-richness map was produced from the ensemble models and published on the platform.

3.2 Fisheries socio-economic modeling

Modeling tools used for EBM (from SSMs to complex end-to-end modeling approaches) can be strengthened by: 1) re-expressing their outputs in socio-economic terms, and 2) by constraining relationships among model components using socio-economic factors (Thébaud et al., 2023). However, the use of food web models to assess the socio-economic consequences of change, albeit driven by the environment or management actions, on the fisheries systems has been very limited (Chakravorty et al., 2024). Food web models were found to be effective at characterizing the socio-economic importance of fisheries systems, and at simulating the socio-economic consequences of environmental or policy driven changes in the system. We developed an approach for assessing the socio-economic consequences in fisheries systems built upon existing capabilities of EwE: the value chain plugin (Christensen et al., 2011) and the policy search routine (Christensen and Walters, 2004). The framework aims to produce socio-economic indicators to explicitly address trade-offs among economic, social, and ecological objectives. Within EcoScope, the framework is being used to: (a) assess the consequences of alternative fishing effort restrictions on fleet profitability, fishers’ salaries, and employment contributions of Greek fleets operating in the Aegean Sea; (b) characterize the consequences of species invasions on the Israeli EEZ seafood value chain; (c) identify the consequences of fishing effort reductions across the Balearic Islands seafood value chain over time; and (d) highlight the trade-offs between existing management arrangements and fisheries policies that are optimized to maximize fisheries revenue, employment, biodiversity, or ecosystem maturity in the Aegean Sea, Balearic Islands, Baltic Sea, Israeli EEZ, and North Sea.

4 EBM implementation

4.1 Policy goals, actors and communication with stakeholders

The correct, clear, and transparent formulation of policy questions for EBM is important to kick off the implementation process (Townsend et al., 2019). Understanding policy and regulatory framework issues were mentioned as a problem in the stakeholder survey (Rodriguez-Perez et al., 2023), including weak policy frameworks for EBM, insufficient inclusion of ecosystem aspects by decision makers in requests to scientists, poor enforcement of regulations, and the complexity of different regulatory mechanisms in different countries. Identifying the policy question is often difficult and needs to be an interactive process within the existing management framework. It should be supported by the existing legislation relative to EBM (Tables 2, 3). Link et al. (2019) pointed out the different strengths of EBM-related regulations, differentiating between rather strict mandates of some protective or forbidding rules (e.g. protecting PETS), and more “relaxed” instructions (soft law, such as international law or conventions). Many EBM-related regulations seem to be holistic, and require several further steps for formulating operational measures regulating the fisheries and protecting/restoring ecosystems.

Fisheries industry, scientists, managers, and policy makers are the main actors involved in the EBM implementation (Figure 1). Their involvement is ensured through their participation in organizations (usually international and cooperative) providing advice to the EU on EBM (Figure 1; Ramírez-Monsalve et al., 2021; Rodriguez-Perez et al., 2023). Collaboration and communication between various actors are essential because they clarify objectives, promote information exchange, and facilitate the identification of trade-offs (Townsend et al., 2019). The roles and functions of the various actors are detailed in the SM. It is important to have regular open communication between various stakeholders to build trust and provide transparency of the process. This also helps the review process and mitigates the risk of model and advice rejection (Townsend et al., 2019). In the EU, the advisory councils (ACs) are a focal point of stakeholder communication because they provide experience-based information and a platform to discuss social, economic, and ecological outcomes (EU, 2017b; Ramírez-Monsalve et al., 2021).

Figure 1

The EcoScope consortium involving biologists, modelers, economists, and social scientists reflects the interdisciplinary science team needed to advise the implementation of EBM. To provide successful EBM advice, the team of scientists should include researchers, arbiters, advisers, and participatory experts (facilitators, mediators; Linke et al., 2023). However, as a team of interdisciplinary scholars, the EcoScope consortium lacks the means of collaboration with the main actors necessary for implementing project results into practice as well as directly communicate needs and tools. As it was carried out, the communication with stakeholders in EcoScope relied mostly on surveys (including workshops) rather than direct interaction. In order to provide efficient advice, the research team should participate in the decision process, ensuring that the tools produced, are tailored to purpose and contribute to EBM-related decision making. This can be achieved by associating future projects with dedicated EBM activities carried out by the ICES, GFCM, and ACs. Future projects could formally seek support for involvement in dedicated EBM efforts by the EC, ICES or other relevant organizations.

4.2 Objectives, trade-off between fisheries profits, ecosystem consideration, and societal needs

EBM objectives need to be formulated based on actual policy requirements, legal requirements, and ecosystem considerations. In some cases, they touch only on specific components of the ecosystem (e.g. the recovery of certain stocks), while in others they may encompass several components, aiming for balanced fisheries within the ecosystem, or addressing the trade-offs between sustainable fisheries and healthy ecosystems (Tables 3, 4; Rice and Duplisea, 2014). Setting double (e.g. optimize fishing, protect ecosystems) or multiple objectives (e.g. when recovering PETS, mitigating climate change, and enhancing human wellbeing are added to the first two, Table 4) unsurprisingly creates trade-offs, which need to be dealt with (Table 4).

A typical trade-off discussed for a long time for multispecies fisheries (Mace, 2001; Rice and Duplisea, 2014; Trenkel, 2018) is how to fish all stocks at optimal levels simultaneously (e.g. at MSY, Table 4). It is generally accepted that fishing of all stocks at MSY (from SSM estimates) is impossible because less productive stocks tend to be overfished (Table 4, Mace, 2001; Stäbler et al., 2016; Baudron et al., 2019; Craig and Link, 2023). Significantly reduced fishing rates (by 20 - 50%) are required in order to achieve sustainable yield of all species (Stäbler et al., 2019).

An alternative of trying to optimize MSY of all species is to estimate ecosystem reference points (ERPs, Table 4, Morrison et al., 2024) for all exploited stocks that will allow optimal fishing and will simultaneously sustain desirable ecosystem state. The desirable ecosystem state may reflect various objectives defined by the managers. ERPs can be holistic (i.e. an ERP for the whole ecosystem) or individual stocks could each have an ERP to ensure that low productivity stocks are not overfished and other ecosystem components (e.g. PETS) stay healthy (Scotti et al., 2022; Morrison et al., 2024).

Discarding is a practice recognized by the stakeholders to be possibly affected by the EBM (landing obligation, LO, Table 4). Several studies demonstrate that the LO would have negative or modest effects on harvested stocks and that limiting discards may have negative effects on scavenger populations of PETS. However, discarding catch may also have other negative effects on PETS - e.g. increased incidental catch (Darby et al., 2023). A task of the EBM is therefore to accommodate a better balance between avoiding discarding practices and sustaining vulnerable ecosystem components.

The trade-off between contradicting objectives of profitable fishing and PETS protection (mammals, sharks, sea turtles, Table 4) in the California current ecosystem has for instance been accommodated by using spatial model daily forecasts (tuned by weather forecasts) allowing for the fisheries to avoid bycatch of protected PETS.

The current fisheries management frameworks can be challenged by unfavorable climate impacts, and the implementation of EBM is a way to accommodate future changes in the fisheries. There are several studies of impacts of climate on fish stocks and fisheries using MEMs (e.g. Bentley et al., 2017; Serpetti et al., 2017; Papantoniou et al., 2023), and such studies were also performed in EcoScope (e.g. Ofir et al., 2023; Keramidas et al., 2023, 2024). However, none of these describe actual management measures (MM) to mitigate climate impacts.

An EU study that evaluated the resilience of the fisheries managed under the CFP to climate change (Table 4, EU, 2022b; Bastardie et al., 2022) found that healthy and well-assessed stocks are more resilient than stocks in a poor state, and that short-lived species are more impacted, but recover quicker after climate shocks such as heat waves. Bioeconomic models (Bastardie et al., 2014; EU, 2022b) showed that fishing fleets with low profitability will not be resilient to climate-induced shocks. Climate change may lead to situations where management rules are not followed, resource resilience can be jeopardized, or fleets’ constraints are too high, affecting their economic resilience. Low fishing mortality and adaptive management may improve resilience and buffer against climate shocks, but at the cost of reducing short-term profits (Table 4).

The MSFD and the CFP are not harmonized to achieve similar ecosystem goals. Conforming to both EU policies will require the inclusion of the ecosystem effects of fishing (Baudron et al., 2019; Stäbler et al., 2016), as well as the development of specific ecological indicators and reference points that reflect the GES descriptors (Bourdaud et al., 2016; Fu et al., 2019; Ito et al., 2023). While reductions in fishing effort may lead to improvements in both the state of stocks and some GES indicators (e.g. D1-biodiversity, D4-food web; Lynam and Mackinson, 2015), trade-offs between fishery and ecosystem objectives may still occur even when fishing is sustainable (Stäbler et al., 2016; Baudron et al., 2019; Uusitalo et al., 2022). Although MEM (e.g., EwE) simulations can help reconcile conflicting policy objectives of the CFP and the MSFD, there is considerable uncertainty about how to include MSFD conservation objectives into new or existing management frameworks (van Hoof, 2015).

Establishing MPAs has a broader objective to protect marine nature, and therefore on most occasions, it is beyond the specific scope of EBM, spanning into the field of maritime spatial planning and ecosystem management. However, the restrictions on the fisheries and the conflicts between fishing and nature conservation, in general, make the MPAs subject to fisheries management and therefore to EBM (Table 4). Recently, Shabtay et al. (2025) described the efforts to propose a network of MPAs for implementation in the Israeli EEZ. The project revealed and tried to streamline substantial challenges in the MPA implementation process, such as establishing and filling information gaps, solving user conflicts (including fisheries restrictions), generating public interest and encouraging the public to endorse the project, and implementation issues such as convincing the government to accept and apply the master plan (Shabtay et al., 2025).

An example of EBM application in Maritime Spatial Planning (MSP) is the assessment of mutual effects between offshore wind farms (OWFs) and fishing (Punt et al., 2009, Table 4). The negative effects such as increased mortality of migrating marine birds (Furness et al., 2013), and increased noise and vibrations that might change long-distance spatial movement of marine mammals (Teilmann and Carstensen, 2012), are more pronounced during the early development phases. A framework combining EwE modeling, the MSP Challenge tool, and an Environmental Impact Assessment metric has been developed to capture these effects, providing a suitable means to assess ecosystem-level impacts across the construction, operation, and decommissioning phases of OWFs (Nascimento et al., 2025). Positive impacts include a “reserve effect” that increases fish biomass via the spill-over into fishing areas (Halouani et al., 2020), and a “reef effect” colonization of the installations by benthic food organisms contributing to upper trophic levels’ biomass (Raoux et al., 2017). As a result, the construction and operation of OWFs induces trade-offs between fisheries, ocean use sectors, and PETS (Lester et al., 2018).

The demand for research on the socio-economic aspects of EBM to support decision and policy making has increased, with the EU pushing towards transformative change which harnesses the power of citizens, businesses, and communities. In EcoScope, a socio-economic survey was carried out in Bulgaria, Malta, and the UK, in order to get a better understanding of the perceptions, preferences, and expectations of the public for EBM and its economic value (Briguglio et al., 2025a). Overall, the results indicated an insufficient knowledge of specific EBM terminology, yet a positive perception of the values associated with EBM, and a strong support for policy interventions.

The socio-economic analyses conducted in EcoScope demonstrated how including the human dimensions of fisheries systems in EBM can facilitate comparisons and trade-off analyses that can help assess the outcomes of policy objectives (e.g., increasing seafood contribution to national food security, improving fleet profitability, reducing unsafe subsidies, increasing female representation in seafood sector employment, among others), as well as identify which sectors, fleet segments, and countries are most vulnerable to supply side or environmental shocks, and can also help identify data gaps and inform future data collection and monitoring efforts. At present, coupling ecology and economics is a must in the provision of scientific advice for the EBM. Further integration of the biophysical and human dimensions of fisheries systems is on the agenda, needing to bring together new algorithms, mandatory socio-economic data collection, adaptive management, and cross-sector and interdisciplinary collaboration.

5 Toward operational EBM

Effective implementation of EBM requires it to be conceived and structured as an adaptive, iterative process that involves formulating policies and legislation, acquiring knowledge, developing and testing models, applying MMs, and conducting ongoing surveillance (Figure 1). The “pull-push” mechanism of demanding/providing EBM advice that currently exists in the EU cannot satisfy the needs for effective operational EBM (Ramírez-Monsalve et al., 2021). Successful operational EBM requires: 1) well-defined management objectives (Tables 3, 4); 2) a clear management process receptive to the evaluation of trade-offs; 3) a suite of well-documented state-of-the-art models; 4) early and iterative engagement among scientists, stakeholders, and managers; 5) a model development process and fusion of suitable models in a collaborative, interactive, and iterative interdisciplinary team; and 6) a rigorous and iterative review process involving independent reviewers, institutions, and stakeholders (Townsend et al., 2019; Craig and Link, 2023).

Monitoring the outcomes of implementation is critical for the effectiveness of the EBM process (Tallis et al., 2010). It involves designing and establishing monitoring programs that identify how the chosen management actions affect the management targets (Levin et al., 2009). Much of the data collected during the monitoring can be used in future EBM, allowing scientists and managers to move from data poor to data rich situations, improving the rigor and sophistication of their decisions with each iteration. When governance is stable and multiple agencies cooperate, an integrated, coordinated, and efficient monitoring program can be established across agencies. Under less ideal governance situations, where funding for monitoring is questionable or the maintenance of monitoring programs is unlikely, the monitoring program can be designed to target critical time frames or areas, or to take advantage of remote sensing. The interdisciplinary team, together with managers and stakeholders, would establish an adaptive management framework that includes existing monitoring plans. Monitoring and adaptive management plans would be integrated, and their efficiencies would be evaluated (Tallis et al., 2010).

Once the EBM process is operational, its components and subprocesses need constant iterative adaptive updating. Data collection, knowledge base, and models need to be improved and tailored through periodic workshops by interdisciplinary teams of scientists and managers. Models, recommendations, and advice need to be re-evaluated through a series of reviews at different levels (experts and stakeholders). Communication between modelers, managers, and stakeholders is essential, and would enable model and procedure refinement, and ensure their usefulness. Communication with stakeholders would enable scientists to respond to urgent and critical events by providing strategic and tactical advice for holistic planning and operational applications (Townsend et al., 2019).

6 Building of the EBM knowledge base and stakeholder involvement: EcoScope platform, toolbox, academy, app and knowledge exchange forum

To facilitate data preservation, sharing, and usage by interested stakeholders, the EcoScope consortium developed, and will maintain in the future, the EcoScope platform (https://data.ecoscopium.eu, Figure 2), which is a key output of the project. The EcoScope platform is a geographical information system that hosts meteorological, oceanographic, biogeochemical, environmental, biological, fishery, and socio-economic datasets, and homogenizes them into common standard types and formats following international protocols. The environmental data are both historical and forecasts, cover all study areas, and are assembled, compiled, and integrated from multiple external databases and platforms such as CMEMS, EMODnet, NOAA, ECMWF, SMHI, Sentinel 2 and 3, CORDEX, IPCC. These data are combined with data from biological (e.g., FishBase, SeaLifeBase) and fisheries databases providing data on biomass, catches, and discards (e.g. GFCM, ICES, FAO, Sea Around Us project), marine mammal distribution (ACCOBAMS), biodiversity (Marine IBA e-atlas), fish and invertebrate species distributions and observations (AquaMaps, OBIS, GBIF), and fishing effort (Global Fishing Watch). All data are homogenized, georeferenced and quality checked, and form the back-end of the Ecoscope Platform (https://ecoscopium.eu/ecoscope-platform). The EcoScope platform is a modular tool linking data with environmental and human drivers, indicators, and models that couples predictions of changes in marine biogeochemistry with ecosystem productivity within a framework of climate change and increased anthropogenic forcing. The platform is based on state-of-the-art methodologies and adopts an Agile approach to ingest the diverse datasets. A series of user stories was considered for designing and providing shared services required by the external stakeholders. This platform is expected to help European decision makers in the long-term management of fishery activities, addressing pressing challenges like climate change and fisheries economy constraints.

Figure 2

The EcoScope Toolbox features a comprehensive set of standardized fisheries, community, ecosystem, and climate indicators, integrated into two unified scoring indices (one for assessing the health of fisheries and another one for assessing ecosystem health (https://ecoscopium.eu/ecoscope-toolbox, Table 1). To align with EBM principles, the toolbox also incorporates some socio-economic indicators, available as time series and specific to ecosystems rather than countries. Where feasible, the individual indicators are connected to outputs from ecosystem models (EwE), stock assessments, and various datasets on oceanography, climate, environment, and fisheries available within the EcoScope platform. The scoring indices have been co-designed and evaluated by scientists and stakeholders to assist decision-making and EBM implementation. The toolbox can be applied anywhere in the world at various scales depending on the data and boundaries, and has a set of metrics that can be used independently to support international and local policies with the EBM.

In addition, the fisheries and ecosystem information and expertise are used to assess ecosystem status and change through the maritime spatial planning (MSP) challenge simulation platform (https://www.mspchallenge.info/msp-challenge-simulation-platform.html). The MSP Challenge simulation platform is an extension of the pre-existing software platform https://www.mspchallenge.info/ applying MEMs (EwE) and incorporating dynamic ecosystem and climate conditions under deep uncertainty. It aims to engage advisers, managers and other stakeholders to carry out robust decisions and to promote adaptive management in accordance with the EU and national policies and legislation (Nascimento et al., 2025).

The EcoScope academy is the educational pillar of the project and includes a collection of online self-paced chapters contained in a course entitled “Ecocentric fisheries management” (https://ecoscope.getlearnworlds.com). The academy is addressed to postgraduate and undergraduate students, young scientists, and policymakers, building up the required knowledge for understanding the complexity and the necessity of EBM. It is used to disseminate the methodological approach of EcoScope and to transfer knowledge to all relevant stakeholders, as well as to support the proper usage of the developed platform and decision-making toolbox, and to facilitate the development and implementation of EBM policies.

The EcoScope app (https://ecoscopium.eu/ecoscope-app) is designed to empower citizens to contribute to the preservation of marine ecosystems by reporting marine hazards such as fishing in protected areas, sightings of invasive species, or marine pollution incidents.). These reports are transmitted in real time to the relevant authorities, ensuring that each issue is promptly addressed and managed. This mechanism facilitates a continuous flow of valuable data from the field, enabling stakeholders to monitor and respond to critical challenges in marine conservation. By collecting and centralizing information from users across regions, the app helps create a more comprehensive picture of activities impacting the marine environment, such as the spread of invasive species and fishing practices in ecologically sensitive areas. These data are not only instrumental in shaping immediate actions, but also serve as a valuable resource for scientists, policymakers, and governments.

The EcoScope stakeholder knowledge exchange forum (KEF) aims to achieve maximum participation, advice, and support from key ecosystem-based fisheries stakeholders to ensure the tools are useful for them and meet their needs. It comprises all stakeholders that were identified as key EBM players in the initial stakeholder mapping, as well as the stakeholders that have actively signed up via https://ecoscopium.eu/stakeholders. The results from the first stakeholder workshop have been instrumental in understanding stakeholder needs, guiding the design of the tools, and ensuring they are fit for purpose. The last workshop will showcase the final tools to all stakeholders in the KEF, and we will collect further feedback and advice on future challenges for EBM, additional needs, and how to best develop the tools further.

7 Discussion

The main objective of the EcoScope project is to help develop an efficient ecosystem-centered approach to fisheries management by providing the necessary data, tools, and communication media directly to users. With respect to this, the building of the EcoScope applications such as MEMs developed for the different sea basins and their availability for testing and use by stakeholders in the EcoScope platform, toolbox, and app were the project’s most essential outputs. This said, we can ask ourselves whether the achievements of the project are sufficient to help the implementation of EBM in Europe, and what problems and limitations we have encountered, that should be avoided in similar future efforts (Table 5).

The EcoScope project showed clear limitations (Table 4), some of which are inherent to the EBM process itself. One of them is the difficult communication of the EBM concept (Briguglio et al. 2025b). During the EcoScope survey (Rodriguez-Perez et al., 2023), stakeholders identified several barriers in implementing EBM: a lack of clarity of the EBM concept, including no common understanding of what the concept means; no guidelines on how EBM could work and be implemented; and no agreed definition, and therefore different interpretations, perceptions, and expectations among the various stakeholders. Policy and regulatory framework issues were also identified as a problem, including poor policy frameworks for EBM, insufficient inclusion of ecosystem aspects by decision makers, insufficient enforcement of regulations, and the complexity of different regulatory mechanisms in different countries. In addition, stakeholder communication issues were seen as a barrier in implementing EBM, including insufficient coordination, different mindsets, and a lack of common vision. Some of these problems can be traced back to the uncertainty in the formulation of the concepts (see Ch. 1), but others result from the mismatch between the environmental and fisheries regulations and advisory bodies with regard to EBM in the EU and elsewhere (Dolan et al., 2016; Ramírez-Monsalve et al., 2021). For example, the CFP deals mainly with fishing, and aims to sustain maximum yields, while the HD, MSFD, MSPD, and BD target environmental and biodiversity protection, and wider ecosystem management (e.g. achieving GES, setting protected zones and renewable energy projects). By trying to accommodate these diverging goals (creating perhaps impossible trade-offs), the EcoScope project (and possibly other similar efforts) is leaving the field of EBM and entering a wider field where it possibly lacks focus and sufficient expertise. The separation between environmental and fisheries regulations and advisory bodies was acknowledged by the EC, which proposed to address the harmonization of ocean policies in the new European Ocean Pact (EU, 2025).

It is clear that the EcoScope consortium’s communication with stakeholders is only indirect and therefore lacks the potential to acquire knowledge and contribute to management decisions interactively with the main actors. In future, project participants should be directly involved with the dedicated assessment and advice groups. Such involvement, however, needs to be authorized by the advisory administration in the EU, and future consortia must earn their place at the decision-making scene and gain the trust of the main actors responsible for the EBM implementation.

It is a considerable challenge to support the EcoScope products beyond the project’s life span. As mentioned in Ch. 5, operational EBM needs constant interactive updating of its policy plans, data collection and knowledge base. EcoScope aims to solve these problems by putting in place viable business models to ensure sustainable operation and update of its products and services in the future. The business models are aiming at future investments from private and public funds to ensure that the EcoScope platform, toolbox, app, and MSP challenge platform fulfill their tasks with the EBM implementation, stakeholder communication, and education.

The geographical scope of EcoScope includes eight sea basins, which have very different ecosystem, fisheries, and management properties. Although the project consortium tried to cover all areas equally, it was not possible to apply all analyses everywhere. SSM assessments and some of the MEM applications (EwE) were carried out in all areas, but others such as socio-economic value chain models were applied only to the Israeli and Balearic Islands cases, and the MSP Challenge simulations – only to the eastern Mediterranean and western Baltic Sea (Nascimento et al., 2025).

The complex nature and bulk quantity of data and tools needed make the development of EBM challenging and expensive. Data collection, identification, and filling of data gaps are essential for EBM development. Nevertheless, a shortage of certain data cannot be the reason to side step the ecosystem approach. When data are missing, modeling, scenario development, and plausible assumptions could be used to fill the gaps and to take on board ecosystem considerations.

The EcoScope project developed modules ready to be used in the EBM implementation in Europe. We feel, however, that a more direct approach should be taken by the responsible organizations, such as the European Commission and the agencies that advise the EC (ICES, GFCM), to explicitly define and set formal research and managerial frameworks for implementing and coordinating EBM activities. To do so, they need to actively communicate with key stakeholders such as the fishing industry, environmentalists, scientists, and advisors, and further develop the legal and institutional background (e.g. by adding to and/or revising the CFP and MSFD, and others) of EBM.

EBM needs a large and complex suite of concepts and tools to deal with a variety of problems ranging from climate change, through various forms of water pollution, to biological trophic interactions and social-economic sustainability. Despite certain criticisms that have been raised due to slow and sometimes badly coordinated approaches, lack of conceptual clarity, insufficient data, complex methodology, and lack of efficient communication, EBM has been developing and evolving toward operational implementation. To paraphrase W.S. Churchill’s famous quote (https://winstonchurchill.org/resources/quotes/the-worst-form-of-government) about democracy: EBM is probably not the most efficient form of management for fisheries or the ecosystem; however, we have no alternative but to maintain our ecosystems healthy and productive in order to be able to use them sustainably.

References

• 1

  Abucay L. R. Sorongon-Yap P. Kesner-Reyes K. Capuli E. C. Reyes R. B. Daskalaki E. et al . (2023). Scientific knowledge gaps on the biology of non-fish marine species across European Seas. Front. Mar. Sci.10. doi: 10.3389/fmars.2023.1198137

  • CrossRef
  • Google Scholar

• 2

  Akoglu E. Libralato S. Salihoglu B. Oguz T. Solidoro C. (2015). EwE-F 1.0: an implementation of Ecopath with Ecosim in Fortran 95/2003 for coupling and integration with other models. Geoscientific Model. Dev.8, 2687–2699. doi: 10.5194/gmd-8-2687-2015

  • CrossRef
  • Google Scholar

• 3

  Alexander K. A. Meyjes S. A. Heymans J. J. (2016). Spatial ecosystem modelling of marine renewable energy installations: Gauging the utility of Ecospace. Ecol. Model.331, 115–128. doi: 10.1016/j.ecolmodel.2016.01.016

  • CrossRef
  • Google Scholar

• 4

  Bastardie F. Brown E. J. Andonegi E. Arthur R. Beukhof E. Depestele J. et al . (2021). A review characterizing 25 ecosystem challenges to be addressed by an Ecosystem Approach to Fisheries Management in Europe. Front. Mar. Sci.7. doi: 10.3389/fmars.2020.629186

  • CrossRef
  • Google Scholar

• 5

  Bastardie F. Feary D. A. Brunel T. Kell L. T. Döring R. Metz S. et al . (2022). Ten lessons on the resilience of the EU common fisheries policy towards climate change and fuel efficiency - A call for adaptive, flexible and well-informed fisheries management. Front. Mar. Sci.9. doi: 10.3389/fmars.2022.947150

  • CrossRef
  • Google Scholar

• 6

  Bastardie F. Nielsen J. R. Miethe T. (2014). DISPLACE: a dynamic, individual-based model for spatial fishing planning and effort displacement—integrating underlying fish population models. Can. J. Fisheries Aquat. Sci.71, 366–386. doi: 10.1139/cjfas-2013-0126

  • CrossRef
  • Google Scholar

• 7

  Baudron A. R. Serpetti N. Fallon N. G. Heymans J. J. Fernandes P. G. (2019). Can the common fisheries policy achieve good environmental status in exploited ecosystems: The west of Scotland demersal fisheries example. Fisheries Res.211, 217–230. doi: 10.1016/j.fishres.2018.10.024

  • CrossRef
  • Google Scholar

• 8

  Bentley J. W. Serpetti N. Heymans J. J. (2017). Investigating the potential impacts of ocean warming on the Norwegian and Barents Seas ecosystem using a time-dynamic food-web model. Ecol. Model.360, 94–107. doi: 10.1016/j.ecolmodel.2017.07.002

  • CrossRef
  • Google Scholar

• 9

  Beverton R. J. H. Holt S. J. (1957). On the dynamics of exploited fish populations Vol. 19 (London: Ministry of Agriculture, Fisheries and Food, Fishery Investigations), 533 pp. Series II.

  • Google Scholar

• 10

  Bourdaud P. Gascuel D. Bentorcha A. Brind’Amour A. (2016). New trophic indicators and target values for an ecosystem-based management of fisheries. Ecol. Indic.61, 588–601. doi: 10.1016/j.ecolind.2015.10.010

  • CrossRef
  • Google Scholar

• 11

  Briguglio M. Rodriguez Perez A. Bayo Ruiz F. Heymans S.J. J. (2025a). Citizens’ views and preferences for ecosystem-based fisheries management. EcoScope Policy Brief, published by the European Marine Board, Ostend, Belgium. Available online at: https://www.um.edu.mt/library/oar/handle/123456789/137131

  • Google Scholar

• 12

  Briguglio M. Ramírez-Monsalve P. Abela G. Armelloni E. N. (2025b). What do people make of “Ecosystem Based Fisheries Management”? Front. Mar. Sci.12. doi: 10.3389/fmars.2025.1553838

  • CrossRef
  • Google Scholar

• 13

  Celić I. Libralato S. Scarcella G. Raicevich S. Marčeta B. Solidoro C. (2018). Ecological and economic effects of the landing obligation evaluated using a quantitative ecosystem approach: a Mediterranean case study. ICES J. Mar. Sci.75, 1992–2003. doi: 10.1093/icesjms/fsy069

  • CrossRef
  • Google Scholar

• 14

  Chagaris D. Drew K. Schueller A. Cieri M. Brito J. Buchheister A. (2020). Ecological reference points for Atlantic menhaden established using an ecosystem model of intermediate complexity. Front. Mar. Sci.7. doi: 10.3389/fmars.2020.606417

  • CrossRef
  • Google Scholar

• 15

  Chakravorty D. Armelloni E. N. de la Puente S. (2024). A systematic review on the use of food web models for addressing the social and economic consequences of fisheries policies and environmental change. Front. Mar. Sci.11. doi: 10.3389/fmars.2024.1489984

  • CrossRef
  • Google Scholar

• 16

  Christensen V. Steenbeek J. Failler P. (2011). A combined ecosystem and value chain modeling approach for evaluating societal cost and benefit of fishing. Ecol. Model.222, 857–864. doi: 10.1016/j.ecolmodel.2010.09.030

  • CrossRef
  • Google Scholar

• 17

  Christensen V. Steenbeek J. Walters C. J. (2024). User guide for Ecopath with Ecosim (EwE) (Vancouver, BC: University of British Columbia), 294 p. Available online at: https://pressbooks.bccampus.ca/eweguide/ (Accessed April 4, 2025).

  • Google Scholar

• 18

  Christensen V. Walters C. J. (2004). Trade-offs in ecosystem-scale optimizations of fisheries management policies. Bull. Mar. Sci.74, 549–562. Available online at: https://www.ingentaconnect.com/contentone/umrsmas/bullmar/2004/00000074/00000003/art00006 (Accessed April 4, 2025).

  • Google Scholar

• 19

  Chust G. Corrales X. González F. Villarino E. Chifflet M. Fernandes J. A. et al . (2022). Marine biodiversity modelling study ( EU DG Research and Innovation, Fundación AZTI, Luxembourg). doi: 10.2777/213731

  • CrossRef
  • Google Scholar

• 20

  Coro G. Magliozzi C. Ellenbroek A. Kaschner K. Pagano P. (2016). Automatic classification of climate change effects on marine species distributions in 2050 using the AquaMaps model. Environ. Ecol. Stat.23, 155–180. doi: 10.1007/s10651-015-0333-8

  • CrossRef
  • Google Scholar

• 21

  Coro G. Sana L. Bove P. (2024). An open science automatic workflow for multi-model species distribution estimation. Int. J. Data Sci. Anal 20, 1131–1150. doi: 10.1007/s41060-024-00517-w

  • CrossRef
  • Google Scholar

• 22

  Craig J. K. Link J. S. (2023). It is past time to use ecosystem models tactically to support ecosystem-based fisheries management: Case studies using Ecopath with Ecosim in an operational management context. Fish Fisheries24, 381–406. doi: 10.1111/faf.12733

  • CrossRef
  • Google Scholar

• 23

  Cury P. M. Shannon L. J. Roux J.-P. Daskalov G. M. Jarre A. Moloney C. L. et al . (2005). Trophodynamic indicators for an ecosystem approach to fisheries. ICES J. Mar. Sci.62, 430–442. doi: 10.1016/j.icesjms.2004.12.006

  • CrossRef
  • Google Scholar

• 24

  Darby J. H. Clairbaux M. Quinn J. L. Thompson P. Quinn L. Cabot D. et al . (2023). Decadal increase in vessel interactions by a scavenging pelagic seabird across the North Atlantic. Curr. Biol.33, 4225–4231.e3. doi: 10.1016/j.cub.2023.08.033

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 25

  De Mutsert K. Coll M. Steenbeek J. Ainsworth C. Buszowski J. Chagaris D. et al . (2024). “ Advances in spatial-temporal coastal and marine ecosystem modeling using Ecospace,” in Treatise on Estuarine and Coastal Science, 2nd ed. ( Elsevier, Amsterdam), 122–169. doi: 10.1016/B978-0-323-90798-9.00035-4

  • CrossRef
  • Google Scholar

• 26

  Dolan T. E. Patrick W. S. Link J. S. (2016). Delineating the continuum of marine ecosystem-based management: a US fisheries reference point perspective. ICES J. Mar. Sci.73, 1042–1050. doi: 10.1093/icesjms/fsv242

  • CrossRef
  • Google Scholar

• 27

  EU (1970). Regulation (EEC) No 2142/70 of the Council of 20 October 1970 on the common organisation of the market in fishery products. Off. J. Eur. Communities236, 5–20. Available online at: http://data.europa.eu/eli/reg/1970/2142/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 28

  EU (1983a). Council Regulation (EEC) No 170/83 of 25 January 1983 establishing a Community system for the conservation and management of fishery resources. Off. J. Eur. Communities24, 1–13. Available online at: http://data.europa.eu/eli/reg/1983/170/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 29

  EU (1983b). Council Regulation (EEC) No 171/83 of 25 January 1983 laying down certain technical measures for the conservation of fishery resources. Off. J. Eur. Communities24, 14–29. Available online at: http://data.europa.eu/eli/reg/1983/171/oj/eng(Accessed April 16, 2025)

  • Google Scholar

• 30

  EU (1992). Council Directive 92/43/EEC of 21 May 1992 on the conservation of natural habitats and of wild fauna and flora (Habitats Directive). Off. J. Eur. UnionL206, 7–50. Available online at: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:31992L0043:EN:HTML (Accessed April 16, 2025).

  • Google Scholar

• 31

  EU (2000). Directive 2000/60/EC of the European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy (Water Framework Directive). Off. J. Eur. UnionL327, 1–73. Available online at: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32000L0060:EN:HTML (Accessed April 16, 2025).

  • Google Scholar

• 32

  EU (2008). Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (Marine Strategy Framework Directive). Off. J. Eur. UnionL164, 19–40. Available online at: http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32008L0056:EN:HTML (Accessed April 16, 2025).

  • Google Scholar

• 33

  EU (2010). Directive 2009/147/EC of the European Parliament and of the Council of 30 November 2009 on the conservation of wild birds (Birds Directive, codified version). Off. J. Eur. UnionL20, 7–25. Available online at: https://eur-lex.europa.eu/eli/dir/2009/147/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 34

  EU (2013). Regulation (EU) No 1380/2013 of the European Parliament and of the Council of 11 December 2013 on the Common Fisheries Policy, amending Council Regulations (EC) No 1954/2003 and (EC) No 1224/2009 and repealing Council Regulations (EC) No 2371/2002 and (EC) No 639/2004 and Council Decision 2004/585/EC. Off. J. Eur. UnionL354, 22–61. Available online at: http://data.europa.eu/eli/reg/2013/1380/oj (Accessed April 16, 2025).

  • Google Scholar

• 35

  EU (2014a). Regulation (EU) No 508/2014 of the European Parliament and of the Council of 15 May 2014 on the European Maritime and Fisheries Fund and repealing Council Regulations (EC) No 2328/2003, (EC) No 861/2006, (EC) No 1198/2006 and (EC) No 791/2007 and Regulation (EU) No 1255/2011 of the European Parliament and of the Council. Off. J. Eur. Union149, 1–66. Available online at: http://data.europa.eu/eli/reg/2014/508/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 36

  EU (2014b). Directive 2014/89/EU of the European Parliament and of the Council of 23 July 2014 establishing a framework for maritime spatial planning. Off. J. Eur. UnionL257, 135–145. Available online at: https://eur-lex.europa.eu/eli/dir/2014/89/oj/eng.

  • Google Scholar

• 37

  EU (2016). Regulation (EU) 2016/2336 of the European Parliament and of the Council of 14 December 2016 establishing specific conditions for fishing for deep-sea stocks in the north-east Atlantic and provisions for fishing in international waters of the north-east Atlantic and repealing Council Regulation (EC) No 2347/2002. Off. J. Eur. Union354, 1–19. Available online at: https://eur-lex.europa.eu/eli/reg/2016/2336/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 38

  EU (2017a). Regulation (EU) 2017/1004 of the European Parliament and of the Council of 17 May 2017 on the establishment of a Union framework for the collection, management and use of data in the fisheries sector and support for scientific advice regarding the common fisheries policy and repealing Council Regulation (EC) No 199/2008 (recast). Off. J. Eur. Union157, 1–21. Available online at: http://data.europa.eu/eli/reg/2017/1004/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 39

  EU (2017b). Commission Delegated Regulation (EU) 2017/1575 of 23 June 2017 amending Delegated Regulation (EU) 2015/242 laying down detailed rules on the functioning of the Advisory Councils under the common fisheries policy. Off. J. Eur. UnionL239, 1–2. Available online at: https://eur-lex.europa.eu/eli/reg_del/2017/1575/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 40

  EU (2019a). Regulation (EU) 2019/1241 of the European Parliament and of the Council of 20 June 2019 on the conservation of fisheries resources and the protection of marine ecosystems through technical measures, amending Council Regulations (EC) No 1967/2006, (EC) No 1224/2009 and Regulations (EU) No 1380/2013, (EU) 2016/1139, (EU) 2018/973, (EU) 2019/472 and (EU) 2019/1022 of the European Parliament and of the Council, and repealing Council Regulations (EC) No 894/97, (EC) No 850/98, (EC) No 2549/2000, (EC) No 254/2002, (EC) No 812/2004 and (EC) No 2187/2005. Off. J. Eur. Union198, 105–201. Available online at: http://data.europa.eu/eli/reg/2019/1241/oj/eng (Accessed April 16, 2025).

  • Google Scholar

• 41

  EU (2019b). “ Communication from the commission to the European parliament, the European council, the European economic and social committee and the committee of the regions,” in The European Green Deal. ( European Commission, Brussels). Available online at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52019DC0640 (Accessed August 10, 2025).

  • Google Scholar

• 42

  EU (2020). “ Communication from the commission to the European parliament, the council, the European economic and social committee and the committee of the regions,” in EU Biodiversity Strategy for 2030 Bringing nature back into our lives. ( European Commission, Brussels). Available online at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex:52020DC0380 (Accessed August 10, 2025).

  • Google Scholar

• 43

  EU (2022a). The implementation of ecosystem-based approaches applied to fisheries management under the CFP: final report ( Publications Office of the European Union, Luxembourg), 110 p. Available online at: https://data.europa.eu/doi/10.2926/57956 (Accessed August 10, 2025).

  • Google Scholar

• 44

  EU (2022b). Climate change and the common fisheries policy: adaptation and building resilience to the effects of climate change on fisheries and reducing emissions of greenhouse gases from fishing: final report (Luxembourg: Publications Office of the European Union), 129 p. Available online at: https://data.europa.eu/doi/10.2926/155626 (Accessed August 10, 2025).

  • Google Scholar

• 45

  EU (2023). “ Communication from the commission to the European parliament, the council, the European economic and social committee and the committee of the regions,” in EU Action Plan: Protecting and restoring marine ecosystems for sustainable and resilient fisheries. ( European Commission, Brussels). Available online at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52023DC0102 (Accessed August 10, 2025).

  • Google Scholar

• 46

  EU (2024). Regulation (EU) 2024/1991 of the European Parliament and of the Council of 24 June 2024 on nature restoration and amending Regulation (EU) 2022/869 (Text with EEA relevance). Available online at: http://data.europa.eu/eli/reg/2024/1991/oj/eng (Accessed August 10, 2025).

  • Google Scholar

• 47

  EU (2025). “ Communication from the commission to the European parliament, the council, the European economic and social committee and the committee of the regions,” in The European ocean pact. ( European Commission, Brussels). Available online at: https://eur-lex.europa.eu/legal-content/EN/ALL/?uri=comnat:COM_2025_0281_FIN (Accessed August 10, 2025).

  • Google Scholar

• 48

  FAO (2003). “ Fisheries Management - 2,” in The Ecosystem Approach to Fisheries (FAO Fisheries Technical Guidelines for Responsible Fisheries No. No. 4, Suppl. 2) ( FAO, Rome, Italy). Available online at: https://www.fao.org/4/y4470e/y4470e00.htm (Accessed August 10, 2025).

  • Google Scholar

• 49

  FAO (2008). “ Fisheries management. 2. The ecosystem approach to fisheries,” in 2.1 Best practices in ecosystem modelling for informing an ecosystem approach to fisheries (FAO Fisheries Technical Guidelines for Responsible Fisheries No. No. 4, Suppl. 2, Add. 1) ( FAO, Rome, Italy). Available online at: https://openknowledge.fao.org/handle/20.500.14283/i0151e (Accessed March 19, 2025).

  • Google Scholar

• 50

  FAO (2009). “ Fisheries management. 2. The ecosystem approach to fisheries,” in 2.2 The human dimensions of the ecosystem approach to fisheries (FAO Fisheries Technical Guidelines for Responsible Fisheries No. No. 4, Suppl. 2, Add. 2) ( FAO, Rome, Italy). Available online at: https://www.fao.org/4/i1146e/i1146e00.htm (Accessed March 19, 2025).

  • Google Scholar

• 51

  FAO (2021). GFCM 2030 Strategy for sustainable fisheries and aquaculture in the Mediterranean and the Black Sea (Rome, Italy: FAO), 25 p. doi: 10.4060/cb7562en

  • CrossRef
  • Google Scholar

• 52

  Farriols M. T. Ordines F. Hidalgo M. Guijarro B. Massutí E. (2015). N90 index: A new approach to biodiversity based on similarity and sensitive to direct and indirect fishing impact. Ecol. Indic.52, 245–255. doi: 10.1016/j.ecolind.2014.12.009

  • CrossRef
  • Google Scholar

• 53

  Froese R. Winker H. Coro G. Demirel N. Tsikliras A. C. Dimarchopoulou D. et al . (2020). Estimating stock status from relative abundance and resilience. ICES J. Mar. Sci.77, 527–538. doi: 10.1093/icesjms/fsz230

  • CrossRef
  • Google Scholar

• 54

  Froese R. Winker H. Coro G. Palomares M.-L. Tsikliras A. C. Dimarchopoulou D. et al . (2023). New developments in the analysis of catch time series as the basis for fish stock assessments: The CMSY++ method. Acta Ichthyologica Piscatoria53, 173–189. doi: 10.3897/aiep.53.105910

  • CrossRef
  • Google Scholar

• 55

  Fu C. Xu Y. Bundy A. Grüss A. Coll M. Heymans J. J. et al . (2019). Making ecological indicators management ready: Assessing the specificity, sensitivity, and threshold response of ecological indicators. Ecol. Indic.105, 16–28. doi: 10.1016/j.ecolind.2019.05.055

  • CrossRef
  • Google Scholar

• 56

  Fulton E. A. Punt A. E. Dichmont C. M. Harvey C. J. Gorton R. (2019). Ecosystems say good management pays off. Fish Fisheries20, 66–96. doi: 10.1111/faf.12324

  • CrossRef
  • Google Scholar

• 57

  Furness R. W. Wade H. M. Masden E. A. (2013). Assessing vulnerability of marine bird populations to offshore wind farms. J. Environ. Manage.119, 56–66. doi: 10.1016/j.jenvman.2013.01.025

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 58

  Garcia S. M. Zerbi A. Aliaume C. Do Chi T. Lasserre G. (2003). “ The ecosystem approach to fisheries,” in Issues, terminology, principles, institutional foundations, implementation and outlook (FAO Fisheries Technical Paper No. 443) ( FAO, Rome, Italy). Available online at: https://openknowledge.fao.org/handle/20.500.14283/y4773e (Accessed March 19, 2025).

  • Google Scholar

• 59

  González-Irusta J. M. de la Torriente A. Punzón A. Blanco M. Serrano A. (2018). Determining and mapping species sensitivity to trawling impacts: the BEnthos Sensitivity Index to Trawling Operations (BESITO). ICES J. Mar. Sci.75, 1710–1721. doi: 10.1093/icesjms/fsy030

  • CrossRef
  • Google Scholar

• 60

  Gulland J. A. (1971). The Fish Resources of the Oceans ( FAO/Fishing News Books, Ltd, Surrey, London) 255pp.

  • Google Scholar

• 61

  Halouani G. Villanueva C.-M. Raoux A. Dauvin J. C. Ben Rais Lasram F. Foucher E. et al . (2020). A spatial food web model to investigate potential spillover effects of a fishery closure in an offshore wind farm. J. Mar. Syst.212, 103434. doi: 10.1016/j.jmarsys.2020.103434

  • CrossRef
  • Google Scholar

• 62

  Heymans J. J. Bundy A. Christensen V. Coll M. De Mutsert K. Fulton E. A. et al . (2020). The Ocean Decade: A true ecosystem modeling challenge. Front. Mar. Sci.7. doi: 10.3389/fmars.2020.554573

  • CrossRef
  • Google Scholar

• 63

  Ito M. Halouani G. Cresson P. Giraldo C. Girardin R. (2023). Detection of fishing pressure using ecological network indicators derived from ecosystem models. Ecol. Indic.147, 110011. doi: 10.1016/j.ecolind.2023.110011

  • CrossRef
  • Google Scholar

• 64

  Jardim E. Millar C. P. Mosqueira I. Scott F. Osio G. C. Ferretti M. et al . (2015). What if stock assessment is as simple as a linear model? The a4a initiative. ICES J. Mar. Sci.72, 232–236. doi: 10.1093/icesjms/fsu050

  • CrossRef
  • Google Scholar

• 65

  Keramidas I. Dimarchopoulou D. Kokkos N. Sylaios G. Tsikliras A. (2024). Temporal ecotrophic impacts of fisheries and climate change in the Aegean Sea. Mar. Ecol. Prog. Ser.749, 19–45. doi: 10.3354/meps14724

  • CrossRef
  • Google Scholar

• 66

  Keramidas I. Dimarchopoulou D. Ofir E. Scotti M. Tsikliras A. C. Gal G. (2023). Ecotrophic perspective in fisheries management: A review of Ecopath with Ecosim models in European marine ecosystems. Front. Mar. Sci.10, 1182921. doi: 10.3389/fmars.2023.1182921

  • CrossRef
  • Google Scholar

• 67

  Kesner-Reyes K. Capuli E. C. Reyes R. B. Jr. Jansalin J. G. M. Rius-Barile J. Bactong M. et al . (2025). Gap analysis on the biology of marine fishes across European Seas. Rev. Fisheries Sci. Aquaculture33, 416–437. doi: 10.1080/23308249.2024.2446806

  • CrossRef
  • Google Scholar

• 68

  Leopold A. (1949). A sand county almanac and sketches here and there (Oxford, UK: Oxford University Press).

  • Google Scholar

• 69

  Lester S. E. Stevens J. M. Gentry R. R. Kappel C. V. Bell T. W. Costello C. J. et al . (2018). Marine spatial planning makes room for offshore aquaculture in crowded coastal waters. Nat. Commun.9, 945. doi: 10.1038/s41467-018-03249-1

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 70

  Levin P. S. Fogarty M. J. Murawski S. A. Fluharty D. (2009). Integrated ecosystem assessments: Developing the scientific basis for ecosystem-based management of the ocean. PloS Biol.7, e1000014. doi: 10.1371/journal.pbio.1000014

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 71

  Libralato S. Solidoro C. (2009). Bridging biogeochemical and food web models for an End-to-End representation of marine ecosystem dynamics: The Venice lagoon case study. Ecol. Model.220, 2960–2971. doi: 10.1016/j.ecolmodel.2009.08.017

  • CrossRef
  • Google Scholar

• 72

  Link J. S. (2010). Ecosystem-Based Fisheries Management: Confronting Tradeoffs (Cambridge, UK: Cambridge University Press).

  • Google Scholar

• 73

  Link J. S. (2021). Evidence of ecosystem overfishing in U.S. large marine ecosystems. ICES J. Mar. Sci.78, 3176–3201. doi: 10.1093/icesjms/fsab185

  • CrossRef
  • Google Scholar

• 74

  Link J. S. Browman H. I. (2014). Integrating what? Levels of marine ecosystem-based assessment and management. ICES J. Mar. Sci.71, 1170–1173. doi: 10.1093/icesjms/fsu026

  • CrossRef
  • Google Scholar

• 75

  Link J. S. Dickey-Collas M. Rudd M. McLaughlin R. Macdonald N. M. Thiele T. et al . (2019). Clarifying mandates for marine ecosystem-based management. ICES J. Mar. Sci.76, 41–44. doi: 10.1093/icesjms/fsy169

  • CrossRef
  • Google Scholar

• 76

  Link J. S. Watson R. A. (2019). Global ecosystem overfishing: Clear delineation within real limits to production. Sci. Adv.5, eaav0474. doi: 10.1126/sciadv.aav0474

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 77

  Link J.S. Watson R.A. Pranovi F. Libralato S. (2020). Comparative production of fisheries yields and ecosystem overfishing in African Large Marine Ecosystems. Env. Dev.36, 100529. doi: 10.1016/j.envdev.2020.100529

  • CrossRef
  • Google Scholar

• 78

  Linke S. Nielsen K. N. Ramírez-Monsalve P. (2023). Roles for advisory science in the International Council for the Exploration of the Sea (ICES). Mar. Policy148, 105469. doi: 10.1016/j.marpol.2022.105469

  • CrossRef
  • Google Scholar

• 79

  Lynam C. P. Mackinson S. (2015). How will fisheries management measures contribute towards the attainment of Good Environmental Status for the North Sea ecosystem? Global Ecol. Conserv.4, 160–175. doi: 10.1016/j.gecco.2015.06.005

  • CrossRef
  • Google Scholar

• 80

  Mace P. M. (2001). A new role for MSY in single-species and ecosystem approaches to fisheries stock assessment and management. Fish Fisheries2, 2–32. doi: 10.1046/j.1467-2979.2001.00033.x

  • CrossRef
  • Google Scholar

• 81

  Methot R. D. Wetzel C. R. (2013). Stock synthesis: A biological and statistical framework for fish stock assessment and fishery management. Fisheries Res.142, 86–99. doi: 10.1016/j.fishres.2012.10.012

  • CrossRef
  • Google Scholar

• 82

  Morrison W. E. Oakes S. A. Karp M. A. Appelman M. H. Link J. S. (2024). Ecosystem-level reference points: Moving toward ecosystem-based fisheries management. Mar. Coast. Fisheries16, e10285. doi: 10.1002/mcf2.10285

  • CrossRef
  • Google Scholar

• 83

  Moutopoulos D. K. Tsagarakis K. Machias A. (2018). Assessing ecological and fisheries implications of the EU landing obligation in Eastern Mediterranean. J. Sea Res.141, 99–111. doi: 10.1016/j.seares.2018.08.006

  • CrossRef
  • Google Scholar

• 84

  Murawski S. (2007). Size matters, sometimes. Nature450, 794–794. doi: 10.1038/450794a

  • CrossRef
  • Google Scholar

• 85

  Nascimento M. C. Gonçalves M. P. Lieser J. Mayer I. Scotti M. (2025). Extending the human pressures-species response system in the MSP Challenge ecosystem simulation platform. Front. Mar. Sci.12. doi: 10.3389/fmars.2025.1561347

  • CrossRef
  • Google Scholar

• 86

  Ofir E. Corrales X. Coll M. Heymans J. J. Goren M. Steenbeek J. et al . (2023). Evaluation of fisheries management policies in the alien species-rich Eastern Mediterranean under climate change. Front. Mar. Sci.10. doi: 10.3389/fmars.2023.1155480

  • CrossRef
  • Google Scholar

• 87

  Onofri L. Maynou F. (2020). Unwanted catches, quota systems and the EU Landing Obligation: An economic and econometric analysis. Ocean Coast. Manage.189, 105159. doi: 10.1016/j.ocecoaman.2020.105159

  • CrossRef
  • Google Scholar

• 88

  Papantoniou G. Zervoudaki S. Assimakopoulou G. Stoumboudi M. Tsagarakis K. (2023). Ecosystem-level responses to multiple stressors using a time-dynamic food-web model: The case of a re-oligotrophicated coastal embayment (Saronikos Gulf, E Mediterranean). Sci. Total Environ.903, 165882. doi: 10.1016/j.scitotenv.2023.165882

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 89

  Patrick W. S. Link J. S. (2015). Myths that continue to impede progress in ecosystem-based fisheries management. Fisheries40, 155–160. doi: 10.1080/03632415.2015.1024308

  • CrossRef
  • Google Scholar

• 90

  Pikitch E. K. Santora C. Babcock E. A. Bakun A. Bonfil R. Conover D. O. et al . (2004). Ecosystem- based fishery management. Science305, 346–347. doi: 10.1126/science.1098222

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 91

  Pitcher T. J. Kalikoski D. Short K. Varkey D. Pramod G. (2009). An evaluation of progress in implementing ecosystem-based management of fisheries in 33 countries. Mar. Policy33, 223–232. doi: 10.1016/j.marpol.2008.06.002

  • CrossRef
  • Google Scholar

• 92

  Punt M. J. Groeneveld R. A. Van Ierland E. C. Stel J. H. (2009). Spatial planning of offshore wind farms: A windfall to marine environmental protection? Ecol. Econ69, 93–103. doi: 10.1016/j.ecolecon.2009.07.013

  • CrossRef
  • Google Scholar

• 93

  Ramírez-Monsalve P. Nielsen K. N. Ballesteros M. Kirkfeldt T. S. Dickey-Collas M. Delaney A. et al . (2021). Pulling mechanisms and pushing strategies: How to improve Ecosystem Approach Fisheries Management advice within the European Union’s Common Fisheries Policy. Fisheries Res.233, 105751. doi: 10.1016/j.fishres.2020.105751

  • CrossRef
  • Google Scholar

• 94

  Raoux A. Tecchio S. Pezy J.-P. Lassalle G. Degraer S. Wilhelmsson D. et al . (2017). Benthic and fish aggregation inside an offshore wind farm: Which effects on the trophic web functioning? Ecol. Indic.72, 33–46. doi: 10.1016/j.ecolind.2016.07.037

  • CrossRef
  • Google Scholar

• 95

  Rice J. Duplisea D. (2014). Management of fisheries on forage species: the test-bed for ecosystem approaches to fisheries. ICES J. Mar. Sci.71, 143–152. doi: 10.1093/icesjms/fst151

  • CrossRef
  • Google Scholar

• 96

  Rodriguez-Perez A. Tsikliras A. C. Gal G. Steenbeek J. Falk-Andersson J. Heymans J. J. (2023). Using ecosystem models to inform ecosystem-based fisheries management in Europe: a review of the policy landscape and related stakeholder needs. Front. Mar. Sci.10. doi: 10.3389/fmars.2023.1196329

  • CrossRef
  • Google Scholar

• 97

  Scotti M. Opitz S. MacNeil L. Kreutle A. Pusch C. Froese R. (2022). Ecosystem-based fisheries management increases catch and carbon sequestration through recovery of exploited stocks: The western Baltic Sea case study. Front. Mar. Sci.9. doi: 10.3389/fmars.2022.879998

  • CrossRef
  • Google Scholar

• 98

  Serpetti N. Baudron A. R. Burrows M. T. Payne B. L. Helaouët P. Fernandes P. G. et al . (2017). Impact of ocean warming on sustainable fisheries management informs the Ecosystem Approach to Fisheries. Sci. Rep.7, 13438. doi: 10.1038/s41598-017-13220-7

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 99

  Shabtay A. Rothschild A. Makovsky Y. Neuman A. Bialik O. Goren L. et al . (2025). Lessons learned by addressing challenges to deep-sea conservation planning in the Southeastern Mediterranean Sea: linking science to practice. Ocean Coast. Manage.267, 107700. doi: 10.1016/j.ocecoaman.2025.107700

  • CrossRef
  • Google Scholar

• 100

  Sherley R. B. Winker H. Rigby C., L. Kyne P. M. Pollom R. Pacoureau N. et al (2020). Estimating IUCN Red List population reduction: JARA—a decision-support tool applied to pelagic sharks. Conservation Letters13, e12688. doi: 10.1111/conl.12688

  • CrossRef
  • Google Scholar

• 101

  Stäbler M. Kempf A. Mackinson S. Poos J. J. Garcia C. Temming A. (2016). Combining efforts to make maximum sustainable yields and good environmental status match in a food-web model of the southern North Sea. Ecol. Model.331, 17–30. doi: 10.1016/j.ecolmodel.2016.01.020

  • CrossRef
  • Google Scholar

• 102

  Stäbler M. Kempf A. Smout S. Temming A. (2019). Sensitivity of multispecies maximum sustainable yields to trends in the top (marine mammals) and bottom (primary production) compartments of the southern North Sea food-web. PloS One14, e0210882. doi: 10.1371/journal.pone.0210882

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 103

  STECF (2023). Scientific Technical and Economic Committee for Fisheries (STECF) - Stock assessments in the Western Mediterranean Sea (STECF 23-09) (No. JRC135661) (Luxembourg: STECF, JRC). doi: 10.2760/995295

  • CrossRef
  • Google Scholar

• 104

  Steenbeek J. Buszowski J. Chagaris D. Christensen V. Coll M. Fulton E. A. et al . (2021). Making spatial-temporal marine ecosystem modelling better – a perspective. Environ. Model. Software145, 105209. doi: 10.1016/j.envsoft.2021.105209

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 105

  Steenbeek J. Coll M. Gurney L. Mélin F. Hoepffner N. Buszowski J. et al . (2013). Bridging the gap between ecosystem modeling tools and geographic information systems: Driving a food web model with external spatial–temporal data. Ecol. Model.263, 139–151. doi: 10.1016/j.ecolmodel.2013.04.027

  • CrossRef
  • Google Scholar

• 106

  Tallis H. Levin P. S. Ruckelshaus M. Lester S. E. McLeod K. L. Fluharty D. L. et al . (2010). The many faces of ecosystem-based management: Making the process work today in real places. Mar. Pol.34, 340–348. doi: 10.1016/j.marpol.2009.08.003

  • CrossRef
  • Google Scholar

• 107

  Teilmann J. Carstensen J. (2012). Negative long term effects on harbour porpoises from a large scale offshore wind farm in the Baltic - evidence of slow recovery. Environ. Res. Lett.7, 45101. doi: 10.1088/1748-9326/7/4/045101

  • CrossRef
  • Google Scholar

• 108

  Thébaud O. Nielsen J. R. Motova A. Curtis H. Bastardie F. Blomqvist G. E. et al . (2023). Integrating economics into fisheries science and advice: progress, needs, and future opportunities. ICES J. Mar. Sci.80, 647–663. doi: 10.1093/icesjms/fsad005

  • CrossRef
  • Google Scholar

• 109

  Tommasi D. deReynier Y. Townsend H. Harvey C. J. Satterthwaite W. H. Marshall K. N. et al . (2021). A case study in connecting fisheries management challenges with models and analysis to support ecosystem-based management in the California Current Ecosystem. Front. Mar. Sci.8. doi: 10.3389/fmars.2021.624161

  • CrossRef
  • Google Scholar

• 110

  Townsend H. Harvey C. J. deReynier Y. Davis D. Zador S. G. Gaichas S. et al . (2019). Progress on implementing ecosystem-based fisheries management in the United States through the use of ecosystem models and analysis. Front. Mar. Sci.6. doi: 10.3389/fmars.2019.00641

  • CrossRef
  • Google Scholar

• 111

  Trenkel V. M. (2018). How to provide scientific advice for ecosystem-based management now. Fish Fisheries19, 390–398. doi: 10.1111/faf.12263

  • CrossRef
  • Google Scholar

• 112

  Tsikliras A. C. Coro G. Daskalov G. Gremillet D. Scotti M. Sylaios G. (2023). A need for a paradigm shift from anthropocentric to ecocentric fisheries management. Front. Mar. Sci.10. doi: 10.3389/fmars.2023.1295733

  • CrossRef
  • Google Scholar

• 113

  UN (1979). Convention on the conservation of migratory species of wild animals. Available online at: https://www.cms.int/sites/default/files/instrument/CMS-text.en_.PDF (Accessed March 19, 2025).

  • Google Scholar

• 114

  UN (1982). Convention on the law of the sea. Available online at: https://www.refworld.org/legal/agreements/unga/1982/en/40182 (Accessed March 19, 2025).

  • Google Scholar

• 115

  UN (1992). Convention on biological diversity. Available online at: http://www.cbd.int/doc/legal/cbd-en.pdf (Accessed March 19, 2025).

  • Google Scholar

• 116

  UN (1995). Agreement for the implementation of the provisions of the United Nations Convention on the Law of the Sea of 10 December 1982 relating to the conservation and management of straddling fish stocks and highly migratory fish stocks. Available online at: https://treaties.un.org/doc/Treaties/1995/08/19950804%2008-25%20AM/Ch_XXI_07p.pdf (Accessed March 19, 2025).

  • Google Scholar

• 117

  US EPAP (1998). “ Ecosystem-based fishery management: A report to congress by the Ecosystem Principles Advisory Panel (Report to Congress),” in NOAA, National Marine Fisheries Service (NMFS)Gland, Swetzerland. Available online at: https://repository.library.noaa.gov/view/noaa/23730 (Accessed August 25, 2025).

  • Google Scholar

• 118

  Uusitalo L. Blenckner T. Puntila-Dodd R. Skyttä A. Jernberg S. Voss R. et al . (2022). Integrating diverse model results into decision support for good environmental status and blue growth. Sci. Total Environ.806, 150450. doi: 10.1016/j.scitotenv.2021.150450

  • Pubmed Abstract
  • CrossRef
  • Google Scholar

• 119

  van Hoof L. (2015). Fisheries management, the ecosystem approach, regionalisation and the elephants in the room. Mar. Policy60, 20–26. doi: 10.1016/j.marpol.2015.05.011

  • CrossRef
  • Google Scholar

• 120

  Ward T. Tarte D. Hegerl E. Short K. (2002). Ecosystem-based management of marine capture fisheries ( World Wide Fund for Nature Australia, Gland, Swetzerland), 80 pp.

  • Google Scholar