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In Europe, implementation of sustainable fisheries management has been reinforced in the latest common fisheries policy, and presently marine fish stocks are mostly managed through assessment of their exploitation and ecological status compared to reference points such as Maximum Sustainable Yield (MSY). However, MSY and its associated fishing mortality rate FMSY are sensitive to both stock characteristics and environment conditions. In parallel, climate change impacts are increasingly affecting fish stocks directly and indirectly but might also change the exploitation reference points and the associated level of catch. Here we explored the variability of MSY reference points under climate change by using a multi-species model applied to the Eastern English Channel, a highly exploited semi-continental sea. The spatial individual-based OSMOSE explicitly represents the entire fish life cycle of 14 species interacting through size-based opportunistic predation. The model was first parameterized and run to fit the historical situation (2000-2009) and then used to assess the ecosystem state for the 2050-2059 period, using two contrasting climate change scenarios (RCP 4.5 and RCP 8.5). For each condition, a monospecific MSY estimation routine was performed by varying species fishing mortality independently and allowed estimation of reference points for each species. The FMSY estimated with OSMOSE were mostly in accordance with available values derived from stock assessment and used for fishing advice. Evolution of reference points with climate change was compared across species and highlighted that overexploited cold-water species are likely to have both MSY and FMSY declining with climate warming. Considering all species together, MSY under RCP scenarios was expected to be higher than historical MSY for half of them, with no clear link with species temperature preferences, exploitation status or trophic level, but in relation with expected change of species biomass under climate change. By contrast, for 80% of cases FMSY projections showed consistent decreasing pattern as climate conditions changed from historical to RCP scenarios in the Eastern English Channel. This result constitutes a risk for fisheries management, and anticipation of climate change impacts on fish community would require targeting a smaller fishing mortality than FMSY to ensure sustainable exploitation of marine stocks.

The management and conservation of biodiversity relies on information on both the abundance of species and the potential impact of threats. Globally, one of the largest threats towards marine biodiversity is bycatch in fisheries. Under the Marine Strategy Framework Directive (MSFD), EU Member States are required to assess the status of species, such as the harbour porpoise ( Phocoena phocoena ), in relation to their abundance and mortality due to bycatch every six years. The Vulnerable (HELCOM) Belt Sea population of harbour porpoise has been surveyed to determine its abundance six times using dedicated aerial or ship-based line-transect distance sampling surveys. Here, we estimated the first trend in population abundance over an 18 year period (2005-2022). Using the most recent abundance estimate, we computed a mortality limit applying the modified Potential Biological Removal (mPBR) method based on the regionally agreed conservation objective to restore or maintain 80% of carrying capacity over 100 years with an 80% probability. Over the past 18 years there has been a strong negative trend (-2.7% p.a.; 95% CI: -4.1%; + 1.3%) in abundance, with a 90.5% probability. The mortality limit was estimated to be 24 animals, which the current bycatch estimates (~900 porpoises/year from the commercial Danish and Swedish set net fishery fleets, with no data from Germany and other fishery types) exceed by far. The frequency and quality of data available on abundance for this population are higher than those available for the majority of marine species. Given the observed population decline and likely unsustainable levels of bycatch, the results presented here provide a strong basis to make informed, evidence-based management decisions for action for this population. Such action is needed urgently, before the dire situation of other porpoise species and populations around the globe is repeated.

Human activities in the oceans are increasing and can result in additional mortality on many marine Protected, Endangered or Threatened Species (PETS). It is necessary to implement ambitious measures that aim to restore biodiversity at all nodes of marine food webs and to manage removals resulting from anthropogenic activities. We developed a stochastic surplus production model (SPM) linking abundance and removal processes under the assumption that variations in removals reflect variations in abundance. We then consider several ‘harvest’ control rules, included two candidate ones derived from this SPM (which we called ‘Anthropogenic Removals Threshold’, or ART), to manage removals of PETS. The two candidate rules hinge on the estimation of a stationary removal rate. We compared these candidate rules to other existing control rules ( e.g. potential biological removal or a fixed percentage rule) in three scenarios: (i) a base scenario whereby unbiased but noisy data are available, (ii) scenario whereby abundance estimates are overestimated and (iii) scenario whereby abundance estimates are underestimated. The different rules were tested on a simulated set of data with life-history parameters close to a small-sized cetacean species of conservation interest in the North-East Atlantic, the harbour porpoise ( Phocoena phocoena ), and in a management strategy evaluation framework. The effectiveness of the rules were assessed by looking at performance metrics, such as time to reach the conservation objectives, the removal limits obtained with the rules or temporal autocorrelation in removal limits. Most control rules were robust against biases in data and allowed to reach conservation objectives with removal limits of similar magnitude when averaged over time. However, one of the candidate rule (ART) displayed greater alignment with policy requirements for PETS such as minimizing removals over time.

Bycatch, the undesirable and non-intentional catch of non-target species in marine fisheries, is one of the main causes of mortality of marine mammals worldwide. When quantitative conservation objectives and management goals are clearly defined, computer-based procedures can be used to explore likely population dynamics under different management scenarios and estimate the levels of anthropogenic removals, including bycatch, that marine mammal populations may withstand. Two control rules for setting removal limits are the Potential Biological Removal (PBR) established under the US Marine Mammal Protection Act and the Removals Limit Algorithm (RLA) inspired from the Catch Limit Algorithm (CLA) developed under the Revised Management Procedure of the International Whaling Commission. The PBR and RLA control rules were tested in a Management Strategy Evaluation (MSE) framework. A key feature of PBR and RLA is to ensure conservation objectives are met in the face of the multiple uncertainties or biases that plague real-world data on marine mammals. We built a package named RLA in the R software to carry out MSE of control rules to set removal limits in marine mammal conservation. The package functionalities are illustrated by two case studies carried out under the auspices of the Oslo and Paris convention (OSPAR) (the Convention for the Protection of the Marine Environment of the North-East Atlantic) Marine Mammal Expert Group (OMMEG) in the context of the EU Marine Strategy Framework Directive. The first case study sought to tune the PBR control rule to the conservation objective of restoring, with a probability of 0.8, a cetacean population to 80% of carrying capacity after 100 years. The second case study sought to further develop a RLA to set removals limit on harbor porpoises in the North Sea with the same conservation objective as in the first case study. Estimation of the removals limit under the RLA control rule was carried out within the Bayesian paradigm. Outputs from the functions implemented in the package RLA allows the assessment of user-defined performance metrics, such as time to reach a given fraction of carrying capacity under a given level of removals compared to the time needed given no removals.

Marine megafauna plays an important functional role in marine ecosystems as top predators but are threatened by a wide range of anthropogenic activities. Bycatch, the incidental capture of non-targeted species in commercial and recreational fisheries, is of particular concern for small cetacean species, such as dolphins and porpoises. In the North-East Atlantic, common dolphin ( Delphinus delphis , Linné 1758) bycatch has been increasing and associated with large numbers of animals stranding during winter on the French Atlantic seashore since at least 2017. However, uncertainties around the true magnitude of common dolphin bycatch and the fisheries involved have led to delays in the implementation of mitigation measures. Current data collection on dolphin bycatch in France is with non-dedicated observers deployed on vessels for the purpose of national fisheries sampling programmes. These data cannot be assumed representative of the whole fisheries' bycatch events. This feature makes it difficult to use classic ratio estimators since they require a truly randomised sample of the fishery by dedicated observers. We applied a newly developed approach, regularised multilevel regression with post-stratification, to estimate total bycatch from unrepresentative samples and total fishing effort. The latter is needed for post-stratification and the former is analysed in a Bayesian framework with multilevel regression to regularise and better predict bycatch risk. We estimated the number of bycaught dolphins for each week and 10 International Council for the Exploration of the Sea (ICES) divisions from 2004 to 2020 by estimating jointly bycatch risk, haul duration, and the number of hauls per days at sea (DaS). Bycatch risk in pair trawlers flying the French flag was the highest in winter 2017 and 2019 and was associated with the longest haul durations. ICES divisions 8.a and 8.b (shelf part of the Bay of Biscay) were estimated to have the highest common dolphin bycatch. Our results were consistent with independent estimates of common dolphin bycatch from strandings. Our method show cases how non-representative observer data can nevertheless be analysed to estimate fishing duration, bycatch risk and, ultimately, the number of bycaught dolphins. These weekly-estimates improve upon current knowledge of the nature of common dolphin bycatch and can be used to inform management and policy decisions at a finer spatio-temporal scale than has been possible to date. Our results suggest that limiting haul duration, especially in winter, could serve as an effective mitigation strategy.