Revisiting rebuilding options of European fisheries

Abstract

Overfishing remains widespread in European seas, and the 2020 sustainability objectives under the Common Fisheries Policy (CFP) have not been fully met, leaving many stocks outside safe biological limits. At the same time, management must also ensure economic viability for fishing fleets, highlighting the need to quantify trade-offs between stock recovery and fleet profitability. Building on previous research, we assess 220 fish and invertebrate stocks across eight ecoregions, providing higher spatial resolution than previous analyses. Using a surplus-production framework, we model biomass and profitability trajectories under alternative exploitation scenarios. Results show that reducing fishing mortality to moderate exploitation patterns produces the most robust improvements in profitability across regions, while also supporting biomass rebuilding. However, the magnitude and timing of these effects vary geographically: northeast Atlantic regions start from higher baseline stock status but exhibit more modest marginal gains, whereas Mediterranean and Black Sea regions, despite poorer initial conditions, display stronger rebuilding potential and larger relative improvements once fishing pressure is reduced, with pronounced heterogeneity among subregions. These findings suggest that moderate exploitation reductions can yield long-term economic gains, though transitional costs and ecosystem constraints may limit near-term feasibility. Our results have direct relevance for region-specific European Union (EU) management, indicating where existing multiannual plans may require complementary measures to align biological sustainability with fleet profitability. We conclude that spatially resolved bioeconomic assessments can inform adaptive management and support progress toward both ecological and socioeconomic objectives under the CFP and associated frameworks.

Introduction

Fisheries are vital for food security, livelihoods, and economic stability for European countries bordering the Mediterranean Sea and northeast Atlantic Ocean (FAO, 2024). Yet, overfishing remains widespread in these waters, and current management, focused on achieving maximum sustainable yield, has generally failed to rebuild depleted stocks (Froese et al., 2018; Froese et al., 2025). Ensuring the sustainability of marine resources and fishing activities, especially in ecosystems that are both overexploited (Tsikliras et al., 2015; Froese et al., 2018) and increasingly affected by rising temperatures (Blanchet et al., 2019; Lamine et al., 2023), requires science-based management (Zimmermann and Werner, 2019).

The 2013 reform of the Common Fisheries Policy (CFP) legally obliged European Union (EU) Member States (MS) to ensure that all stocks were exploited at or below levels consistent with the Maximum Sustainable Yield (MSY) “by 2015 where possible and on a progressive basis by 2020” (CFP, 2013). While some progress toward this objective has been observed in the northeast Atlantic Ocean (Froese et al., 2021) and partially in the Mediterranean (FAO, 2023a), the 2020 MSY goal was not fully achieved, with many targeted stocks throughout the European seas remaining overfished and outside safe biological limits (Tsikliras et al., 2015; Froese et al., 2018; Froese et al., 2025). Now that the 2020 MSY deadline has passed, EU policy priorities have shifted toward broader 2030 targets outlined in the Biodiversity Strategy (EU, 2021), including expanding marine protected areas to at least 30% of EU seas, yet this transition risks leaving an unaddressed gap in evaluating ongoing progress toward stock sustainability and economic performance under MSY-consistent exploitation pathways.

The CFP also requires economic sustainability and long-term profitability of EU fleets, ensuring that environmental objectives are met alongside socio-economic benefits (CFP, 2013). Indeed, management that fails to ensure long-term financial stability for fishers is likely to fail (Worm et al., 2009; Dichmont et al., 2010). Fishers respond strongly to economic incentives, particularly price dynamics (Lancker et al., 2023), though behavior is constrained by regulatory measures such as Total Allowable Catch (TAC), quota allocations, and effort restrictions under EU management frameworks (Batsleer et al., 2013). Where such mechanisms are in place (noting, for example, that TACs are generally absent in the Mediterranean Sea), they limit the ability of fleets to freely increase effort or access resources, thereby ensuring that fishing activity remains within biologically and legally defined boundaries. Evaluating trade-offs between short-term revenue impacts and long-term profitability requires quantitative tools and scenario-based assessments (Peterson et al., 2003; Grafton et al., 2007).

Although some measures have been proposed to mitigate short-term losses for fishers, robust models remain essential for evaluating trade-offs and guiding strategic decisions. Stock assessments are central to this process, providing the scientific foundation for sustainable exploitation. As the core of fisheries management, they offer biological reference points and indicators to inform policymakers and stakeholders (Hilborn and Walters, 1992; Beddington et al., 2007). State-of-the-art approaches range from demanding, data-rich models that integrate detailed biological information such as age, length, and maturity (e.g., Methot and Wetzel, 2013) to low-cost, data-poor methods that use routinely collected catch data and parameter priors to estimate stock indicators and reference points (e.g., Froese et al., 2017). The latter are particularly valuable in regions with limited resources for data collection and low management capacity (Lancker et al., 2023).

Froese et al. (2018) evaluated the status and exploitation level of fish and invertebrate stocks in the northeast Atlantic and the Mediterranean Sea, along with projected catch and profitability. Among other findings, they concluded that regionalized management under the CFP, including multiannual plans, designated fish stock recovery areas, and targeted conservation measures, is essential for the long-term sustainability of stocks and fisheries. Taking this into account, we revisit the Froese et al. (2018) study, aiming to predict stock rebuilding and future fisheries profitability at a finer spatial scale across European seas, based on 220 fish and invertebrate stock assessments. Specifically, rather than treating the northeast Atlantic and the Mediterranean as single units, here we analyze eight separate subregions within these larger areas (Figure 1). Using an advanced implementation of a surplus production model, we simulate profitability under a range of alternative exploitation scenarios. Viewing fisheries as social–ecological systems, our aim is to provide insights at a finer regional scale, to support fisheries managers in identifying exploitation levels that are biologically and economically sustainable, profitable, ecologically responsible, and consistent with the objectives of the CFP.

Figure 1

Materials and methods

Dataset

A total of 220 fish and invertebrate stocks from eight ecoregions across European seas were assessed and used to simulate future profitability under different exploitation scenarios. Three ecoregions were located in the northeast Atlantic Ocean (Baltic Sea, Greater North Sea, and Bay of Biscay), four in the Mediterranean Sea (Balearic Sea, Adriatic Sea, Aegean Sea, and Levantine Sea), while the Black Sea was treated as a single ecoregion (Figure 1).

For the northeast Atlantic Ocean, biomass trajectories or relative abundance indices were extracted from formal stock assessment reports published by the International Council for the Exploration of the Seas (ICES) and catch or landings data were obtained from the ICES database (1970–2021). For the Mediterranean Sea, landings data for each ecoregion (1970–2021) were obtained from the Food and Agriculture Organization–General Fisheries Commission for the Mediterranean (FAO–GFCM) database (FAO, 2023b), while biomass and relative abundance data were drawn from the Data Collection Framework (DCF) program. More specifically, biomass indices were estimated as kg/km² using data from the international bottom trawl survey in the Mediterranean (MEDITS) following the methodology outlined in Spedicato et al. (2019). The mean length of the available catch time series was 40.3 years (range: 11–70 years). For 134 stocks, catch data were available through 2020, while the remaining stocks had data only up to 2019.

Reference points

We estimated stock status using the open-source CMSY++ stock assessment tool (Froese et al., 2023). The CMSY++ approach applies advanced Monte Carlo filtering within a Bayesian framework to produce proxies for the maximum sustainable yield (MSY), fishing pressure that can produce the MSY (F_msy), biomass that can produce the MSY (B_msy), and indicators such as relative stock size (B/B_msy) and exploitation (F/F_msy), based on catch data and resilience information. Full details on the CMSY++ framework are provided in Froese et al. (2023).

Exploitation scenarios

To simulate the future fisheries profitability, we followed a similar approach with Froese et al. (2018). The stock status projected for 2021 based on the CMSY++ analyses was used to apply four different exploitation scenarios until the year 2035:

The 0.5 scenario: B_lim is a biomass threshold under which stocks are considered to be endangered by impaired recruitment and considered outside of safe biological limits (sensu CFP, 2013). For the purposes of this study, a precautionary approach was followed by setting B_lim to half of B_msy, a threshold that corresponds to fishing pressure 0.5 F_msy. Below that level, fishing mortality is linearly reduced to zero with decrease in biomass (F_reduced), like the harvest control rule of ICES (2016) based on the following equation:

Also, F_msy was reduced as a linear function of biomass below 0.5 B_msy using Equation 1 adjusted to F_msy.

• The 0.6 scenario: if stock size is at or above half of B_msy, fishing mortality of 0.6 F_msy is applied.

• The 0.8 scenario: if stock size is at or above half of B_msy, fishing mortality of 0.8 F_msy is applied.

• The 0.95 scenario: fishing mortality of 0.95 F_msy is applied throughout, regardless of stock size.

The different scenarios or harvest control rules applied and the trajectories resulting from the four exploitation scenarios for rebuilding time, catch, and profitability are presented separately for each region. Trajectories for rebuilding and catch start in 2020 or 2021, the last year for which actual catch data and exploitation rates were available for stocks. Biomass was modeled using the last exploitation rates until 2021. From 2020–1 to 2034-5, the exploitation rates of the four scenarios were applied. Trajectories for profitability start in 2020-1, the last year for which estimates of net profit margins were available. For each scenario, the percentage of stocks at or above B_msy, the estimated Catches, and the percentage of depleted stocks [stocks were considered as depleted if stock size fell below half of B_msy, Froese et al. (2018)] were estimated.

Simulation of profitability

When the average effort and profitability of current fisheries are known, the profitability of four exploitation scenarios can be compared using the equilibrium curve of yield over effort. Here, we define profitability as the net profit for fisheries, taking into account the income from landings and other sources, minus unpaid labor, crew, energy, repair and other variable/non-variable costs, depreciation, and the opportunity cost of capital (STECF, 2016; section 6.4).

For fisheries in 2020, the mean net profit margin as a percentage of fishing income was μ_mean = 7.2% for the whole region (excluding distant water fleets and UK fisheries). Mean net profit margin for each region was estimated as:

where i refers to the main MS that operate in each area. In Equation 2, for the North Sea, μ_mean was equal to 13.4%, assuming that Belgium, Netherlands, Germany, and Denmark operate in the area. For the Baltic Sea, μ_mean = 13.9% (Germany, Denmark, Estonia, Finland, Lithuania, Latvia, Poland, and Sweden). The μ_mean was equal to 4.58% for the Bay of Biscay (Spain and France), west Mediterranean Sea μ_mean was 5.3% (Spain, France, and Italy), μ_mean = 8.93% for the Adriatic Sea (Italy, Croatia, and Slovenia), μ_mean = 5.6% for the Aegean Sea based on the Greek fleet, μ_mean = 32.1% for the Black Sea (Bulgaria and Romania), and μ_mean = −32.1% for the Levantine Sea based on the Cypriot fleet (Annex of STECF, 2022). In the absence of spatially resolved revenue and profit data, we assumed uniform national net margin profits across areas. The same stands for data on other income were available and thus revenues from fishing were taken as the main income, assuming a constant fish price over time, as is common in the literature (Costello et al., 2016). All variable costs were assumed as proportional to effort, i.e., marginal costs of effort are constant, and fishing mortality was used as a proxy for effort. This means that resource rents are not dissipated in European fisheries, as could be the case, for example, under conditions of regulated open access (Homans and Wilen, 1997). This is consistent with the STECF report of overall positive profit margins in European fisheries (STECF, 2024). Based on the above assumptions, an index of profitability is derived as annual net profit in percentage of fishing revenues at MSY. Using the above data, this index was calculated as shown in the following equation:

where π_t is the profitability index for year t, μ_mean is the observed mean net profit margin (%), (C/MSY)_mean is the observed mean catch relative to MSY and (F/F_msy)_mean is the observed mean fishing mortality relative to F_msy as a proxy for mean effort. F_t and B_t used in Equation 3 are fishing mortality and biomass in the four considered scenarios. For simplicity, discount rates were assumed to be zero for the projected period. To simulate the uncertainty around the projected variables, concerning the main input parameters B/B_msy, B_msy, and F_msy, we used Monte Carlo simulations based on 10,000 samples. Finally, to assess the robustness of the projected profitability outcomes to uncertainty in the economic assumptions, we conducted a sensitivity analysis focusing on the μ_mean. Specifically, for each exploitation scenario, all simulations were repeated after perturbing μ_mean.by −20%, −10%, +10%, and +20% relative to its baseline value. The resulting profitability trajectories were then contrasted with those obtained under the reference μ_mean, to evaluate the degree to which projected economic outcomes depend on this key economic parameter.

Results

Across the eight ecoregions studied, exploitation scenarios produced consistent and predictable effects on biomass rebuilding, catch, depletion risk, and fisheries profitability. Lower fishing mortality (0.5–0.6 F_msy) promoted rapid biomass recovery (Figure 2) and sharply reduced depletion (Supplementary Figure S1; Table 1), whereas higher fishing mortality (0.8–0.95 F_msy) resulted in higher short-term catches but slower or incomplete rebuilding (Supplementary Figure S2; Table 1). Current fishing mortality (F_cur) generally performed poorly across all metrics. Initial stock status differed markedly among ecoregions: the northeast Atlantic (Baltic Sea, North Sea, and Bay of Biscay) showed substantially higher proportions of stocks at or above B_msy compared to the Mediterranean and Black Sea. These initial differences shaped the magnitude of potential gains under all scenarios tested.

Figure 2

Across regions, the 0.5 F_msy scenario consistently resulted in the highest rebuilding, with 60%–90% of stocks projected to be above B_msy by 2034–2035 in most regions. The 0.6 F_msy scenario produced similar but slightly delayed trajectories, while 0.8 F_msy achieved moderate but incomplete rebuilding. By contrast, 0.95 F_msy and F_cur led to the slowest recovery, and in several Mediterranean and Black Sea ecoregions, biomass rebuilding remained minimal. Notably, strong rebuilding responses occurred in the west Mediterranean Sea, Black Sea, and Levantine Sea, where the share of stocks above B_msy increased from <20% today to >80% under 0.5 F_msy. In the Baltic Sea, where stocks are already relatively healthier, gains were more modest but still substantial.

Profitability increased in nearly all regions under all tested scenarios, reflecting the positive economic effect of biomass rebuilding (Figure 3). The 0.8 F_msy scenario enhanced profitability in regions with relatively healthy stocks (e.g., Baltic Sea). The 0.6 F_msy scenario also yielded consistent profitability gains, typically ranking second or first among regions and delivering major increases, even in systems where present-day net margins are negative. The 0.5 F_msy scenario also delivered large profitability improvements, though slightly below the peak performance of 0.6 F_msy in several regions due to more severe short-term reductions in harvest. In contrast, profitability under 0.95 F_msy remained lowest or near lowest in most regions, demonstrating that aggressive exploitation is not economically optimal even where it produces higher short-term catches. Sensitivity analysis of profitability with respect to the μ_mean (Supplementary Figures S3-S10) indicated that results were generally robust across regions. In most ecoregions, perturbations of μ_mean (± 10%–20%) did not alter the qualitative patterns or relative ranking of exploitation scenarios, and profitability trajectories remained consistent with the baseline results. An exception was the Bay of Biscay, where profitability responses to μ_mean were highly variable and sensitive, reflecting substantial underlying uncertainty. Given this instability and the high uncertainty already associated with baseline profitability estimates, no robust inference on profitability can be drawn for this region.

Figure 3

Across regions, higher exploitation rates (0.8–0.95 F_msy) produced the highest near-term catches, while reduced rates (0.5–0.6 F_msy) produced lower initial catches but improved longer-term sustainability. Detailed temporal trajectories of projected catch for each region are presented in Supplementary Figure S2, demonstrating the expected early loss but later gain dynamic, characteristic of rebuilding strategies. Additionally, the proportion of stocks below 0.5 B_msy declined under all tested scenarios of reduced exploitation. Reductions were largest under 0.5 F_msy, which nearly eliminated depleted stocks in most regions by the end of the projection period. Under 0.6 F_msy, depletion also declined substantially, while under 0.8 and especially 0.95 F_msy, a significant fraction of stocks remained depleted. Further regional detail is provided in Supplementary Figure S1.

Comparative metrics across regions and scenarios

Scenario performance exhibited a clear spatial structure, with stronger initial stock status and management outcomes in northeast Atlantic regions (Baltic Sea and North Sea) and weaker initial stock condition but stronger rebound potential in Mediterranean and Black Sea regions (Table 1). Across all regions, the 0.5 and 0.6 F_msy scenarios produced the greatest improvements in biomass and depletion reduction, but their absolute effects differed depending on geographic context. Generally, 0.8 F_msy performed better in areas where stocks were already relatively healthy, such as in northern Europe, providing higher near-term catches while still enabling modest rebuilding. The 0.6 F_msy scenario also delivered reliable profitability outcomes and ranked first or second in nearly all regions, while 0.5 F_msy was the strongest conservation strategy everywhere, and produced the largest relative economic improvement where stocks were initially weakest.

In contrast, Mediterranean and Black Sea stocks began from a far more depleted state, generating larger relative gains under lower-mortality scenarios. Under both 0.5 and 0.6 F_msy, these regions exhibited rapid biomass rebuilding and dramatic improvements in profitability, far exceeding those observed in northern systems. In these more fragile ecosystems, even moderate exploitation (0.8 F_msy) left a substantial proportion of stocks still depleted by the end of the projection period, whereas aggressive exploitation (0.95 F_msy and F_cur) maintained or worsened depletion patterns.

Discussion

Our findings reveal substantial regional differences in stock status and profitability under varying levels of fishing mortality. The contrasting trends between these major regions can be explained by differences in exploitation history, ecosystem and fisheries characteristics, the organization and capacity of fisheries science and management, the economic development, and data availability (Pauly and Maclean, 2003; Froese, 2011; Smith and Garcia, 2014; Cardinale and Scarcella, 2017). In general, a noticeable north–south gradient from the northeast Atlantic Ocean to the Mediterranean Sea has previously been found, with most Mediterranean stocks being overfished (i.e., low biomass) and undergoing overfishing (i.e., high exploitation levels; Tsikliras et al., 2015, 2021), and stocks in the northeast Atlantic being in a better state (Fernandes et al., 2017; Hilborn et al., 2021), a pattern also reflected in the relative profitability of their fisheries (Froese et al., 2018; Carvalho et al., 2021).

However, our findings also demonstrate substantial heterogeneity among and within basins: weak rebuilding potential in the Baltic Sea and the Adriatic, persistent uncertainty and poor performance in sensitivity analysis in the Bay of Biscay, and poor current stock status but high margins of rebuilding for the west Mediterranean, Levantine, and Black Sea stocks. These patterns, which would have been obscured by broader spatial aggregation, potentially reveal constraints and opportunities for the multi-annual management plans adopted in many of these areas, such as the Baltic Multiannual Plan (MAP; 2016), the North Sea MAP (2018), and the West Med MAP (2019). For the Baltic Sea, for example, our results provide evidence that economic performance can diverge across exploitation scenarios even when biomass outcomes are similar. Thus, incorporating profitability trajectories as an additional management consideration within the Baltic Multiannual Plan (EU 2016/1139) could help identify exploitation levels that maximize both long-term stock recovery and fleet viability. On the other hand, poor performance, high rebuilding capacity, and high projected profitability under the 0.6 F_msy exploitation scenario in the west Mediterranean indicate that the progressive reduction in fishing effort, if coupled with spatial closures, will offset costs from lost fishing opportunities, representing a step in the right direction (Hopkins et al., 2024).

Nevertheless, some common patterns emerge across all regions. Consistent with Froese et al. (2018), the 0.5 and 0.6 F_msy scenarios were the most effective in rebuilding biomass and reducing the number of depleted stocks, confirming that lower fishing pressure reduces the risk of overfishing even in severely overexploited systems. Stocks can quickly enhance productivity and sustainable yields, thereby lowering fishing costs and increasing both profitability and net economic benefits (Arnason et al., 2009). Yet, catches depend not only on the productivity of target species but also on fishing effort. Consequently, inconsistencies between catch and profitability trends are linked to variation in fuel and fish prices, stock productivity, and overall fishing costs (Erauskin-Extramiana et al., 2024). At the same time, implementing strict effort controls may negatively affect local employment, market supply, prices, and sector-wide profitability, potentially causing short-term economic losses (Akbari et al., 2021). In such cases, alternative livelihood opportunities are necessary to help fishers cope with reduced catches (Daw et al., 2012).

Our results show that the moderate 0.8 F_msy scenario can enhance profitability while maintaining reasonable catches. This demonstrates a viable trade-off between conservation and near-term economic returns. On the other hand, the poor long-term performance of the 0.95 F_msy and F_cur exploitation scenarios, despite their initially high catches, highlights the risks to long-term sustainability. The high costs associated with maintaining elevated effort, combined with slow and incomplete biomass rebuilding, ultimately lead to reduced catches and revenues. These scenarios should not be considered a viable management option (Froese et al., 2018). As F_cur reflects historical developments rather than deliberate management strategies, it has similarly been shown to be less profitable and far from optimal compared to evidence-based alternatives, particularly in the northwest Mediterranean Sea (Maynou, 2021).

Overall, our results are broadly consistent with those of Froese et al. (2018), particularly with respect to biomass rebuilding, where the lowest exploitation scenarios (0.5–0.6 F_msy) consistently produce the strongest recovery. However, important differences emerge in projected profitability dynamics. In northern European waters, both studies show that higher exploitation rates yield short-term economic gains, while lower and moderate fishing mortality becomes more profitable over time as biomass rebuilds. In our analysis, the timing of this transition differs among subregions, occurring earlier in the North Sea and later in the Baltic Sea compared to Froese et al. (2018). In the Mediterranean Sea, the finer spatial resolution reveals a more heterogeneous response: while the west Mediterranean, Levantine, and Black seas broadly follow patterns reported for the basin as a whole, the Adriatic and Aegean seas exhibit trajectories more comparable to northern European systems. These differences highlight the added value of spatially resolved analyses in revealing region-specific bioeconomic dynamics that are masked in basin-scale assessments.

However, considerable uncertainty is evident in several projected trajectories, even in scenarios that produce consistent mean trends. This uncertainty primarily reflects variability and limited information in key biological inputs; uncertainty tends to be higher in regions (e.g., Bay of Biscay, Levantine, and Aegean) with fewer assessed stocks, shorter or noisier catch time series, or stocks close to biological limits, where small changes in exploitation can generate divergent biomass and profitability responses. Besides that, the CMSY++ and surplus production framework, while well-established for data-limited contexts (Froese et al., 2017), necessarily simplifies biological dynamics and does not incorporate age structure, recruitment variability, trophic interactions, or climate-driven shifts in productivity. Additionally, our profitability metric assumes constant real prices and proportional cost–effort relationships, whereas real fleets face volatility in fuel costs, market demand, and input prices (STECF, 2024). This framework also implicitly assumes that resource rents are not dissipated; however, STECF (2024) documents low profitability and even losses in some EU fleet segments, indicating that this assumption does not always hold. Our profitability index should therefore be interpreted as an idealized economic signal rather than a full representation of fleet-level economic performance. Moreover, the STECF Annual Economic Report on the EU Fishing Fleet (AER) net profit estimates exclude subsidies, which can mask losses or elevate apparent profitability and thus contribute additional uncertainty. Finally, while scenario outputs provide internally consistent relative trajectories, they should not be interpreted as deterministic forecasts of actual future profits or biomass. The overlapping uncertainty, particularly for profitability, limits fine-grained ranking of closely spaced fishing mortality scenarios, which should be better regarded as indicative trends under idealized management implementations. These limitations underscore the need for ongoing refinement of stock assessments, broader data coverage, and sensitivity testing to environmental and socio-economic variability.

In general, fisheries management requires navigating complex trade-offs among ecological, economic, and social objectives, to ensure sustainable stocks while meeting stakeholder needs. Taking this into account and considering regional management priorities, our results indicate that lower to medium (0.6 to 0.8 F_msy) exploitation scenarios emerge as the most realistic choice across the eight regions included in our analyses. These regimes can deliver good catch levels and substantially higher profits within a few years, generating clear economic benefits for the fishing sector (Sumaila and Bellmann, 2016). Overall, transitioning to lower fishing mortality offers the best compromise across regions, advancing sustainability goals while maintaining economic viability. Success stories, such as the recovery of Atlantic bluefin tuna in both the northeast Atlantic and Mediterranean following significant reductions in fishing effort (Bjørndal, 2023), demonstrate that decisive action can enable stock rebuilding and secure long-term gains for ecosystems and fishing communities alike.

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