Résumé
Commission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, p. 4–10. The Commission may consult the group on any matter relating to marine and fisheries biology, fishing gear technology, fisheries economics, fisheries governance, ecosystem effects of fisheries, aquaculture or similar disciplines. This report is the 11th of a suite of STECF EWG reports dedicated to the evaluation of the implementation of the Western Mediterranean Sea Multi-Annual management Plan (hereafter, MAP), following EWG reports 18-09, 18-13, 19-01, 19-14, 20-13, 21-01, 21- 13, 22-01, 22- 11 and 23-01. The group was requested to update the graphical representation of fishing effort time series evolution by MS, GSA, vessel length and gear with the latest data obtained from the FDI datacall (TOR 1). Together with the fishing effort time series the group was requested to update the F-E analysis by stock and gear using the outputs from STECF EWG 23-09 (TOR 2). The group was also requested to collect qualitative information on the fuel related situation to potentially estimate cost changes in 2022-2023 (TOR2). Finally, the group was requested to implement mixed fisheries bio-economic models to run a number of different scenarios up to 2030 to test a combination of measures taking into account all the effort reductions, closure areas and maximum catch limits (MCLs) introduced in the western Mediterranean MAP since 2020 (TOR 3-4). Within the scenarios a combination of effort reductions and MSLs were tested, together with the introduction of spatio-temporal closures and selectivity restrictions to obtain compensation mechanisms by MSs. A total number of 13 scenarios were requested, 6 of which were considered priority scenarios. For TOR 1 time series of fishing effort in fishing days, days at sea, hours at sea, GT x fishing days, and kW x fishing days by Country (Spain, France, Italy), EMU (1 and 2), GSA (1, 5, 6, 7, 8, 9, 10, 11), gear (OTB, OTT, GNS, GTR, LLS, other), and fleet segment (<12m, 12-18m, 18-24m, >24m) were produced. Graphs for fishing days are reported in the report while the rest of the data are submitted in Annex I as an Excel table. The comparison of fishing days for trawlers (OTB, OTM, OTT, PTB, PTM and TBB as per EU regulation 2019/2236) declared in the FDI official datacall and reported in the 2020, 2021, 2022 and 2023 regulations were reported this year as well. Across fleet segments, the fishing effort from the regulation is greater, for most segments, than that estimated through the FDI database. This could be due to the regulation values being calculated considering the maximum fishing days possible for the year and also difficult to estimate the possible transfer among fleet segments. An additional analysis (section 2.3) was added to provide a broad context of the state and evolution of the fishery in EMU-1 (encompassing GSAs 1,5,6,7), through the detailed examination of weights, values and prices landed by stocks and fleet segments using the FDI data submitted to the group. It was observed that during the implementation of the MAP, all fleet segments have not evolved in the same way. If all demersal trawlers seem to face a substantial contraction of their landed values, deep-water trawlers are increasing their landed value, most likely thanks to an increased ARA price. Still, for many other fleets, the transition rates before and during the plan remains similar. For TOR 2 the F-E analysis was updated and as in previous years a linear relationship consistent across GSAs and stocks was not found for any gear. Those stocks were there seem to be a linear relationship, such as HKE, ARA, DPS (except for DPS 1), it was shown that there is an effect of the GSA level which should be accounted for in future modelling exercises potentially using mixed effect models. Concerning fuel prices the group noted that marine fuel prices are significantly influenced by global oil prices which are driven by factors like international agreements, supply disruptions, or changes in demand. Geopolitical tensions and conflicts, sanctions or embargoes on certain countries can affect the availability and cost of marine fuels. Technology and efficiency improvements can impact fuel efficiency and investments in energy-efficient vessels and propulsion systems can lead to cost savings. Also, environmental concerns, such as reducing carbon emissions and promoting sustainable fishing practices, are affecting fuel usage and prices. It's also important to consider that marine fuel prices can vary significantly by region and port, depending on local factors, taxes, subsidies, transportation costs and regulations. In particular, governments may provide subsidies or financial incentives to the fishing industry to mitigate the impact of high fuel prices or promote environmentally friendly practices. Within the group the EUMOFA and AER data are used to parameterize the models. On these data the group highlighted two issues for a correct interpretation of the model results: 1. The financial situation which the bio-economic models present for the year 2022 and beyond depend a lot on the assumptions regarding the development of fuel prices but include no mitigation measures for the fishing companies (like de minimis payments to cover parts of the increase in fuel costs 2022). STECF plenary (22-03) agreed not to include those support payments to allow distinguishing between the impacts of the MAP from external economic shocks. 2. STECF PLEN (22-03) observed that the nowcast for 2023 (that are now used as input data for the models) should be interpreted with caution due to the fact that the development in the second half of the year (energy and fish prices, inflation, interest rates etc.) is unknown and highly uncertain. FOR TOR 3 results for EMU 1 are obtained from the IAM and the ISIS-Fish models: from the IAM model only scenarios adjusting trawler fishing effort to reach Fmsy of Hake (i.e. scenarios A and D) foresee exploitation levels in line with the objectives of the plan, i.e. all stocks at Fmsy in 2025. With the two other simulated scenarios, in which only maximum catch limit on ARA was applied, with or without selectivity measures on deep water trawls, i.e. scenarios Status Quo and L, respectively, the stocks of Hake in GSA1567, red mullet in GSA1, red mullet in GSA6, Nephrops in GSA 6, and Blue and red shrimp in GSA 5 do not reach the objective of Fmsy in 2025. Scenarios allowing to reach Fmsy for all stocks foresee some significant negative socio-economic impacts for French and Spanish trawlers in the short and medium term, with a reduction in their Gross Value Added, Gross Profit, employment in terms of Full Time Equivalent (FTE), and average wages. From the ISIS-Fish model results showed that the SQ scenario did not achieve the objective of the plan regarding HKE, as fishing mortality stays way above Fmsy and the SSB below Blim. The four other scenarios, A, B, C and E, on the contrary succeeded in reaching Fmsy at the latest in 2028 and Hake SSB was above Blim but below Bpa starting in 2029. The determinant factor was the adjustment of effort to reach Fmsy, which implied reductions in effort level of more than 60% compared to 2022 FDI values. Economic indicators for ISIS- Fish could not be reported. In EMU 2 results are obtained from models BEMTOOL and SMART: from the BEMTOOL model for ARS, MUT9 and DPS the Fmsy level is reached by 2025 for all the scenarios explored. For DPS an increase in F is expected in 2024 for scenario L, due to the reallocation of the effort induced by the catch limit, but in 2025 the value is below Fmsy. For HKE and NEP9 only scenarios A, C and D (which are forced to reach Fmsy by 2025) allow to reach Fmsy in 2025, while SQ and L have F well above the reference point. It should be noticed that the change in selectivity implemented in scenario L show a slight improvement in respect to the SQ scenario for HKE, but it does not allow to reach Fmsy in 2025. As a general consideration, the scenarios most impacting on the effort highlight the risk of underutilization of the stocks that currently already are close or in line with the reference point. Results for the stock of MUT 10 and ARA in 9-10-11 should be taken with caution as no analytical assessment was available for these two stocks in the last two years. The results of the economic indicators showed that in the short term for all the alternative scenarios is expected a decrease, which generally is followed by an increase in the medium-long term. For the SMART model for four of the five stocks (ARS, DPS, HKE, and MUT) the scenarios associated with the best effect on the stock are A, C, D, E and L. For NEP, the situation seems to be much more complex and only scenario A allows you to get close to the BPA (Precautionary Biomass Level) value. However, all the simulated scenarios show a substantial reduction in Gross profit margin. Results suggest that in EMU 1 and 2 Fmsy in 2025 is reached for all stocks only when effort is decreased as much as 60% to 85% depending on the fleet segment observed, with bigger segments suffering a higher reduction. Scenarios accounting for an MCL on ARA and ARS do not allow to reach Fmsy for all stocks including HKE. In EMU 2, the ARS, MUT and DPS stocks are already close or at Fmsy becoming underutilized due to the reductions to bring HKE and NEP at Fmsy.