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This study evaluates the relationship between both commercial and scientific spatial fisheries data and a new satellite-based estimate of potential fish production (Ocean Productivity available to Fish, OPFish) in the European Seas. To construct OPFish, we used productivity frontal features derived from chlorophyll-a horizontal gradients, which characterize 10%–20% of the global phytoplankton production that effectively fuels higher trophic levels. OPFish is relatively consistent with the spatial distribution of both pelagic and demersal fish landings and catches per unit of effort (LPUEs and CPUEs, respectively). An index of harvest relative to ocean productivity (HP index) is calculated by dividing these LPUEs or CPUEs with OPFish. The HP index reflects the intensity of fishing by gear type with regard to local fish production. Low HP levels indicate lower LPUEs or CPUEs than expected from oceanic production, suggesting over-exploitation, while high HP levels imply more sustainable fishing. HP allows comparing the production-dependent suitability of local fishing intensities. Our results from bottom trawl data highlight that over-exploitation of demersal species from the shelves is twice as high in the Mediterranean Sea than in the North-East Atlantic. The estimate of HP index by dominant pelagic and demersal gears suggests that midwater and bottom otter trawls are associated with the lowest and highest overfishing, respectively. The contrasts of fishing intensity at local scales captured by the HP index suggest that accounting for the local potential fish production can promote fisheries sustainability in the context of ecosystem-based fisheries management as required by international marine policies.

Un groupe de travail a été créé en 2017 face à la problématique des nombreux échouages de dauphins communs sur la côte Atlantique avec pour objectifs d’améliorer la connaissance sur les interactions entre la pêche et les mammifères marins, sens limiter les captures accidentelles de cétacés. Deux programmes de sur-échantillonnage du programme ObsMer ont été mis en place, dans le golfe de Gascogne, durant les hivers 2018/19 et 2019/20 temps et sur la flottille des fileyeurs dans un second temps. Dans ce contexte, cette saisine de la DPMA demande la réalisation d’une description détaillée de l’activité des flottilles “à risque” VIII, une actualisation de la typologie des fileyeurs pour le golfe de Gascogne construite dans le cadre de la saisine de la DPMA du 16 avril 2019 puis l’analyse des données ObsMer colle derniers. En ce qui concerne l’analyse des données ObsMer et notamment l’observation des captures accidentelles, le très faible taux de couverture associé à la rareté des évènements rapportés demande d’affiner l’utilisation de ces inf l’échelle des flottilles. Ce travail est toujours en cours. Enfin, une procédure d’estimation du risque de captures accidentelles de delphinidés dans le golfe de Gascogne a été établie dans présentés en Annexe 2.

WGCATCH contributes to ensure the quality of commercial catch data, which underpins stock assessments and advice. At this year’s WGCATCH meeting all the proposed ToRs were covered and objectives were met. The group started documenting the national estimation procedures (Section 3.2). Most of the countries use ratio estimators for their estimation. Recent discussions at WGCATCH and other EGs have increasingly highlighted that estimation techniques currently used by many countries to process commercial catch data may not be the most up-to-date and/or ignore sampling design and/or are far from transparent and/or involve significant levels of adhoc decisions. Therefore, WGCATCH recommends a series of practical workshops on estimation procedures for the next 3 years to produce best practice guidelines for choosing methods and variables used to raise commercial sampling data. Under ToR a.3, the sample size thresholds used for national data provision were documented. WGCATCH discussed extensively use of specific thresholds, however, it is not possible to come up with a single universal rule to be applied across all countries and stocks. Instead, WGCATCH advises that specific analytical steps are taken during the benchmark process to test and evaluate the impacts of applying or not thresholds to national data before providing the data to the assessment. Intersessional work was carried out to develop tools to be used by the data submitters and stock coordinators to understand and summarise the quality and quantity of the data provided to Intercatch (Section 3.3). The work developed under SSF, ToR b), continued to develop best practice guidelines on SSF data collection, with quantitative analyses on the coverage/completeness of fishing activity. PCA analysis was carried out of data incompleteness issue or over-declaration to build a risk’ map where each country*area is positioned (Section 4.2). The sub-group reviewed the proposed CL and CE data formats from RDBES cor

The RDBES is the new Regional DataBase and Estimation System. The RDBES is expected to replace the previous RDB and InterCatch by the end of 2021 and will bring significant improvements and transparency in the provision of estimates from commercial fisheries to stock assessment and other end-users. The developments of the RDBES meet the EU-MAP requirements of progress towards statistically sound sampling schemes. The RDBES data model and associated database are able to store, among other, sampling data alongside the elements required to describe the sampling design used in data collection. Upload of data to and estimation within the RDBES will require significant adaptation of the data collection processes of national institutes in several areas, including data storage, but also sampling design, field protocols, estimation and data provision to end-users. To secure a soft transition there is a need to intensify internal planning of these adaptations from 2020. The Workshop on Estimation with the RDBES data model (WKRDB-EST) prepared data for 8 of the 13 upper hierarchies of the RDBES and developed a first set of R-scripts that handles designbased estimation in the RDBES data model. Developments and tests were positive and confirmed the usefulness of the data model for design-based estimation. These developments are publically available in the ICES GitHub (https://GitHub.com/ices-eg/WK_RDBES/tree/master/WKRDBEST). The RDBES core group will continue the development and produce an R-package that aggregates a) a generic set of estimation functions and b) vignettes documenting design-based estimation in each type of sampling hierarchy. WKRDB-EST examined and tested version v.1.17 of the RDBES model with feedback being obtained from 15 countries on 8 of the 13 upper hierarchies of the RDBES. The data model can now be considered relatively stable with mostly minor issues being identified. The RDBES core group will discuss these issues and incorporate in a future

As global change becomes a major concern, the need to contextualize discrete observations to highlight long-term evolutions also becomes more relevant. In response to this challenge, Marine Historical Ecology (MHE) has recently emerged as a new discipline within the marine sciences, dedicated to studying the relationship between long-term evolution of marine ecosystems and temporal variations of external predictors such as meteorological parameters, or descriptors of human activities. In recent years, therefore, considerable effort has been devoted to study long-term time series on fisheries and environmental data. This approach has increased our knowledge about natural variability and functioning of marine environments and has helped us to characterize breaking points and baseline shifts in these systems. However, MHE studies were rarely planned when data acquisition has begun, and some information about the critical components of ecosystem functioning, although helpful, could be missing without turning back. In particular, very few long-term datasets on mollusk bivalves have been released, although these species are cultivated worldwide, could account for a large part of the biomass and also act as ecosystem engineers. From an ecological point of view, oysters also have the advantage to exhibit great phenotypic plasticity in response to environmental variability and to be sessile, making them perfect sentinels of the environment. In this context, we have compiled dataset from three monitoring networks of oyster production coordinated by IFREMER, named REMORA, RESCO, and ECOSCOPA. These networks have monitored growth and mortalities rates for spat and adult Crassostrea gigas oysters reared in 13 locations along the French coastline during the 1993-2017 period. We modeled the evolution of mean individual weights and mortality rates as a function of time to cope with changes in data frequency acquisition during annual monitoring campaigns. We have thus produced stand

L’estuaire de Seine est un habitat essentiel pour les espèces halieutiques emblématiques de la façade Manche-Mer du Nord en sa qualité de nourricerie. Cet estuaire a connu de profondes modifications morphologiques au cours des 30 dernières années des suites d’une forte anthropisation de ces rives. Cet habitat estuarien-côtier, comptant parmi les habitats les plus productifs du milieu marin, joue un rôle central dans le renouvellement des stocks de pêche, en favorisant la croissance et la survie des juvéniles des espèces dites « nourricerie-dépendantes ». Malgré une couverture temporelle très inégale dans les campagnes depuis 30 ans, les suivis des communautés de juvéniles et les observations biotiques (communautés benthiques), abiotiques (hydrodynamisme, biogéochimie …) et anthropiques (pression de pêche, polluants) associées sont aujourd’hui assez longs pour permettre une approche statistique spatio-temporelle des nourriceries de baie de Seine. Ces travaux s’inscrivent dans une thèse dont l’objectif est de détecter et comprendre les liens entre les descripteurs de la nourricerie et les populations exploitées en Manche. Pour répondre à cette problématique, le jeu de données, rassemblant 13 années d’observations et 131 taxons, est exploré au travers d’analyses géostatistiques et multivariées. Ici sont présentées les premières analyses, dont l’objectif est de décrire dans un premier temps les patrons et dynamiques d’occupations de l’estuaire par les juvéniles de différentes espèces de poissons plats. Ces derniers sont les mieux échantillonnés dans le programme de suivi de la nourricerie. Cette description passe par le calcul d’indices spatiaux permettant de décrire la dynamique spatiale et une analyse en composante principale, EOFs, (Empirical Orthogonal Functions) pour décrire les structures spatiales de chaque espèce. La recherche de ces structures est valorisée par leur mise en relation avec des données environnementales disponible en ligne (EMODnet, Copernicus). C

The Working Group on Widely Distributed Stocks (WGWIDE) reports on the status and considerations for management of Northeast-Atlantic mackerel, blue whiting, Western and North Sea horse mackerel, Northeast-Atlantic boarfish, Norwegian spring-spawning herring, striped red mullet (Subareas 6, 8 and Divisions 7.a-c, e-k and 9.a), and red gurnard (Subareas 3, 4, 5, 6, 7, and 8) stocks. Northeast-Atlantic (NEA) Mackerel. This species is widely distributed throughout the ICES area and currently supports one of the most valuable European fisheries. Mackerel is fished by a variety of fleets from many countries (ranging from open boats using handlines on the Iberian coasts to large freezer trawlers and Refrigerated Sea Water (RSW) vessels in the Northern Area). The assessment methodology was modified during the 2019 inter-benchmark process. The 2019 WGWIDE assessment was an update of the benchmarked assessment incorporating a new year for the catch information, for all surveys (egg survey, IESSNS survey and recruitment index) and for the RFID tagging recapture. After a strong increase from the late 2000s to 2014, the SSB has been declining since 2015, but remains at high levels (well above MSY Btrigger), The estimated fishing mortality has been steadily declining since the mid-2000s, and is now estimated to be close to FMSY. This decrease of the fishing mortality, while the stock has been sustaining high catches (consistently in excess to ICES advice) is explained by a succession of good recruitments, indicating a current high productivity for this stock. Blue Whiting. This pelagic gadoid is widely distributed in the eastern part of the North Atlantic. The assessment this year followed the Stock Annex based the conclusions from the Inter-Benchmark Protocol of Blue Whiting (IBPBLW 2016). The method for calculating mean weight at age for the preliminary (2019) was however changed, such that the observed values were used. Previously, a three year average

Ce document est une synthèse des informations collectées en 2017 à bord des navires de pêche professionnelle dans le cadre de l'action ObsMer. Cette action vise à observer in situ l’activité de pêche et l'ensemble de la capture, particulièrement la partie non retenue, en identifiant les espèces capturées, les tonnages par espèce et en prenant des mesures de tailles. Ce travail s'inscrit dans le cadre d'un partenariat entre le Comite National des Pêches Maritimes et des Élevages Marins (CNPMEM), la Direction des Pêches Maritimes et de l'Aquaculture (DPMA) du Ministère de l’Agriculture et de l'Alimentation, et l'Ifremer.

1. The behaviour of individuals affect their distributions and is therefore fundamental in determining ecological patterns. While, the direct observation of behaviour is often limited due to logistical constraints, collection of movement data has been greatly facilitated through the development of bio-logging. Movement data obtained through tracking instrumentation may potentially constitute a relevant proxy to infer behaviour. 2. To infer behaviour from movement data is a key focus within the "movement ecology" discipline. Statistical learning constitutes a number of methods that can be used to assess the link between given variables from a fully informed training dataset and then predict the values on a non-informed variable. We chose the random forest algorithm for its high prediction accuracy and its ease of implementation. The strength of random forest partly lies in its ability to handle a very large number of variables. Our methodology is accordingly based on the derivation of multiple predictor variables from movement data over various temporal scales, to capture as much information as possible from changes and variations in movement. 3. The methodology is described in four steps, using examples on foraging seabirds and fishing vessels for illustration. The models showed very high prediction accuracy (92%-97%), thereby confirming the influence of behaviour on movement decisions and demonstrating the ability to derive multiple variables from movement data to predict behaviour with random forests. 4. The codes developed for this methodology are published in the "M2B" (Movement to Behaviour) R package, available at https://CRAN.R-project.org/package=m2b. They can be used and adapted to datasets where movement was sampled from a wide range of taxa, sampling schemes or tracking devices. Observations are needed for a subset of the data, but once the model is trained, it can be used on any dataset with similar movement data.

Ce document est une synthèse des informations collectées en 2016 à bord des navires de pêche professionnelle dans le cadre de l'action ObsMer. Cette action vise à observer in situ l’activité de pêche et l'ensemble de la capture, particulièrement la partie non retenue, en identifiant les espèces capturées, les tonnages par espèce et en prenant des mesures de tailles. Ce travail s'inscrit dans le cadre d'un partenariat entre le Comite National des Pêches Maritimes et des Élevages Marins (CNPMEM), la Direction des Pêches Maritimes et de l'Aquaculture (DPMA) du Ministère de l’Agriculture et de l'alimentation, et l'Ifremer.

FishPi is a pilot project financed through an European grant (MARE/2014/19) aiming to strengthen regional coordination in the area of fisheries data collection. This project includes four case studies, one of which aims at analyzing alternative sampling plans for fisheries operating on Northern & Southern hake stocks. The case study analyzes a variety of sampling design scenarios, from Simple Random Sampling to combinations of stratified sampling designs (by country, by port, by quarter…), using anonymised landings data from logbooks and sales notes (2013-2014). The results were compared regarding bias and precision to evaluate the best approach. The most precise estimates of total catch were obtained in scenarios stratified by port and, secondly, by port and country and by port and quarter. The general conclusion was that regional sampling designs stratified by port provided improved precision in this fishery. Apart from statistical considerations, this conclusion was also discussed under other points of view to give a feasibility perspective showing that coverage by country, and also by domain (stock), would be compromised if regional design is simply based on statistical analyses. Efficiency and precision of sampling were found to be highly sensitive to the sampling assumptions and in general countries with smaller contributions to overall landings of hake would see their sampling plans reduced, compromising other requirements for advice such as those related to other stocks or local management measures established by National governments. Hence further analyses are being considered that integrate biometrics, cost-benefit aspects, and concurrent or single-stock sampling strategies.

European hake (Merluccius merluccius) is widely distributed over the Northeast Atlantic shelf, from Norway to Mauritania, with a larger density from the British Islands to the south of Spain and in the Mediterranean and Black sea (ICES, 2015a). Hake is commercially exploited since the eighteenth century (Casey and Pereiro, 1995) but, unlike other gadoids as cod and haddock that supported important fisheries for centuries, large‐scale hake fishery began during the first half of the twentieth century. The European hake is a demersal and benthopelagic species, found mainly between 70 and 370 m depth; however, it also occurs in inshore waters (30 m) and down to depths of 1000 m (Cohen et al., 1990). Juvenile and small Europe hake usually live on muddy beds on the continental shelf, whereas large adult individuals are found on the shelf slope, where the bottom is rough and associated with canyons and cliffs. These biological characteristics make hake catches appears in most of metiers. Fleets involved use a variety of gears including otter trawlers, pair‐trawlers, gillnetters, longliners and, mainly in the southern case, a very heterogeneous small scale fleet –where also gears as traps, hand lines and small trammel nets are present—. Hake is caught in mixed fisheries together with megrim, monkfish, Nephrops, blue whiting, horse mackerel and mackerel depending in all cases on the area and the gear used.

The last multiannual Community program for the collection, management and use of data in the fisheries sector (Commission Decision 2008/949/EC) stated the provision of precision levels and sampling intensities of the estimates at national level. However, the unequal compliance of this standard has hindered its application in stock assessment and the consequent scientific advice. The cost-benefit analysis of a sampling program, besides addressing logistical and economic constraints, should deepen the potential of the tools currently available. This article proposes to test the calculation, provision and use in stock assessment of extensively collected precision parameters. First, sampling intensities and coefficients of variation of fisheries-dependent parameters are calculated using the COST software, a statistical tool specifically designed to quantify uncertainty in marine sampled data. Secondly, alternative ways are explored to provide precision parameters to the stock assessment coordinators by using InterCatch, the existing ICES web-based system to submit national data and compile international catch matrices. Finally, the incorporation of these precision parameters in the assessment model is tested, through a stock assessed by statistical assessment models (such as SS3) which can account for sampling errors. Thus, it will be possible to quantify how errors in input data propagate through stock assessment models to affect harvest rules, and also to help identify the most cost-effective data collections that adequately support the advisory process.

Environmental changes and human activities can have strong impacts on biodiversity and ecosystem functioning. This study investigates how, from a quantitative point of view, simultaneously both environmental and anthropogenic factors affect species composition and abundance of exploited groundfish assemblages (i.e. target and non-target species) at large spatio-temporal scales. We aim to investigate (1) the spatial and annual stability of groundfish assemblages, (2) relationships between these assemblages and structuring factors in order to better explain the dynamic of the assemblages’ structure. The Mauritanian Exclusive Economic Zone (MEEZ) is of particular interest as it embeds a productive ecosystem due to upwelling, producing abundant and diverse resources which constitute an attractive socio-economic development. We applied the multi-variate and multi-table STATICO method on a data set consisting of 854 hauls collected during 14-years (1997–2010) from scientific trawl surveys (species abundance), logbooks of industrial fishery (fishing effort), sea surface temperature and chlorophyll a concentration as environmental variables. Our results showed that abiotic factors drove four main persistent fish assemblages. Overall, chlorophyll a concentration and sea surface temperature mainly influenced the structure of assemblages of coastal soft bottoms and those of the offshore near rocky bottoms where upwellings held. While highest levels of fishing effort were located in the northern permanent upwelling zone, effects of this variable on species composition and abundances of assemblages were relatively low, even if not negligible in some years and areas. The temporal trajectories between environmental and fishing conditions and assemblages did not match for all the entire time series analyzed in the MEEZ, but interestingly for some specific years and areas. The quantitative approach used in this work may provide to stakeholders, scientists and fishers a useful assess

The Mediterranean and Black Seas are semi-enclosed basins characterized by high environmental variability and growing anthropogenic pressure. This has led to an increasing need for a bioregionalization of the oceanic environment at local and regional scales that can be used for managerial applications as a geographical reference. We aim to identify biogeochemical subprovinces within this domain, and develop synthetic indices of the key oceanographic dynamics of each subprovince to quantify baselines from which to assess variability and change. To do this, we compile a data set of 101 months (2002-2010) of a variety of both "classical'' (i.e., sea surface temperature, surface chlorophyll-a, and bathymetry) and "mesoscale'' (i.e., eddy kinetic energy, finite-size Lyapunov exponents, and surface frontal gradients) ocean features that we use to characterize the surface ocean variability. We employ a k-means clustering algorithm to objectively define biogeochemical subprovinces based on classical features, and, for the first time, on mesoscale features, and on a combination of both classical and mesoscale features. Principal components analysis is then performed on the oceanographic variables to define integrative indices to monitor the environmental changes within each resultant subprovince at monthly resolutions. Using both the classical and mesoscale features, we find five biogeochemical subprovinces for the Mediterranean and Black Seas. Interestingly, the use of mesoscale variables contributes highly in the delineation of the open ocean. The first axis of the principal component analysis is explained primarily by classical ocean features and the second axis is explained by mesoscale features. Biogeochemical subprovinces identified by the present study can be useful within the European management framework as an objective geographical framework of the Mediterranean and Black Seas, and the synthetic ocean indicators developed here can be used to monitor variability and

© 2014 Nieblas et al. The Mediterranean and Black Seas are semi-enclosed basins characterized by high environmental variability and growing anthropogenic pressure. This has led to an increasing need for a bioregionalization of the oceanic environment at local and regional scales that can be used for managerial applications as a geographical reference. We aim to identify biogeochemical subprovinces within this domain, and develop synthetic indices of the key oceanographic dynamics of each subprovince to quantify baselines from which to assess variability and change. To do this, we compile a data set of 101 months (2002-2010) of a variety of both >classical> (i.e., sea surface temperature, surface chlorophyll-a, and bathymetry) and >mesoscale> (i.e., eddy kinetic energy, finite-size Lyapunov exponents, and surface frontal gradients) ocean features that we use to characterize the surface ocean variability. We employ a k-means clustering algorithm to objectively define biogeochemical subprovinces based on classical features, and, for the first time, on mesoscale features, and on a combination of both classical and mesoscale features. Principal components analysis is then performed on the oceanographic variables to define integrative indices to monitor the environmental changes within each resultant subprovince at monthly resolutions. Using both the classical and mesoscale features, we find five biogeochemical subprovinces for the Mediterranean and Black Seas. Interestingly, the use of mesoscale variables contributes highly in the delineation of the open ocean. The first axis of the principal component analysis is explained primarily by classical ocean features and the second axis is explained by mesoscale features. Biogeochemical subprovinces identified by the present study can be useful within the European management framework as an objective geographical framework of the Mediterranean and Black Seas, and the synthetic ocean indicators developed here can be used to mon

Carbon stable isotopes and fatty acids were measured in the suspended particulate organic matter (POM) of the Thau lagoon to study its qualitative temporal changes in relation to environmental factors and to identify the food sources of bivalves over a one-yr-cycle in relation to their growth. Reciprocally, the impact of shellfish farming on POM was also studied. Oysters and mussels were sampled and measured for biometry, stable isotopes and fatty acid composition. Water samples were collected at two sites, both inside and outside of the shellfish farming area, to determine concentrations in POM, chlorophyll a (Chl a) and stable isotopes. Carbon isotopes and fatty acids in bivalves reflected seasonal changes in food sources, which varied consistently with the environment. Seasonal changes in delta C-13 and fatty acids in the bivalves suggested that dietary phytoplankton contribution varied according to season. Terrestrial organic matter and bacteria can contribute to the diet of bivalves during non-bloom periods. Mussels seemed to rely more on diatoms and less on terrestrial organic matter and bacteria than oysters did, particularly when phytoplankton biomass was low during the summer. Although one- and two-yr-old oysters showed similar delta C-13, their fatty acid dynamics differed slightly. Periods of high growth rate in bivalves were mainly fuelled by diatoms, thus highlighting the importance of seasonal blooms of microphytoplankton during the critical period of bivalve growth and gamete production. Although there was no significant effect of shellfish farms on Chl a and POM delta C-13, consistent differences indicate that stable isotopes could be used successfully to investigate the effects of bivalve aquaculture. (C) 2011 Elsevier B.V. All rights reserved.