Moving 6-year analysis of Water body dissolved inorganic nitrogen in the NorthEast Atlantic for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centred average of each season. 6-year periods span from 1971/1976 until 2019/2024. Observation data span from 1971 to 2024. Depth levels (IODE standard depths): [0.0, 5.0, 10.0, 20.0, 30.0, 40.0, 50.0, 75.0, 100.0, 125.0, 150.0, 200.0, 250.0, 300.0, 400.0, 500.0, 600.0, 700.0, 800.0, 900.0, 1000.0, 1100.0, 1200.0, 1300.0, 1400.0, 1500.0, 1750.0, 2000.0]. Data sources: observational data from SeaDataNet/EMODNet Chemistry Data Network. Description of DIVAnd analysis: the computation was done with DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30 sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps is 0.1 degrees. Horizontal correlation length varies from 400km in open sea regions to 50km at the coast. Vertical correlation length is defined as twice the vertical resolution. Signal-to-noise ratio was fixed to 1 for vertical profiles and 0.1 for time series to account for the redundancy in the time series observations. A logarithmic transformation (DIVAnd.loglin) was applied to the data prior to the analysis. Background field: a vertically-filtered profile of the seasonal data mean value (including all years) is substracted from the data. Detrending of data: no, advection constraint applied: no. Units: umol/l.

The West Gironde Mud Patch (WGMP) is a mud deposit located 25 km from the mouth of the Gironde Estuary in the Bay of Biscay. This 4-metre-thick clay-silt feature, which extends over an area of 420 km2, is found at depths between 30 and 80 meters. The main objectives of the JERICObent7 cruise, in July 2019, were to characterise the evolution of the WGMP’s benthic ecosystem in terms of its sedimentary, biogeochemical and ecological properties and to reconstruct climate variations and identify potential anthropogenic impacts over the last few centuries. To this end, a precise chronological framework was established for the sedimentary archives of the last few decades using 210Pbxs (T1/2 = 22.3 years). Interface cores were collected at stations 1, 3 and 4 along a cross-shelf transect. Twin Kullenberg cores were collected at sites 3 and 4 for geochemical (KGL) and palaeoceanographic (JB7-ST) investigations. Each interface core was carefully extruded at 0.5 cm intervals from the top of the core to 4 cm, and then at 1 cm intervals until the bottom was reached. Kullenberg cores were only collected at sites 3 and 4. Depending on their intended use, the Kullenberg cores were sampled at different resolutions, the depth of each sediment layer corresponded to the depth from the top of the core. These layers were then used to determine the dry bulk density and radioisotope activities of interest (210Pb, 226Ra,  228Th, 137Cs, 40K). Excess 210Pb was used to establish the realignment and chronological framework of the interface and Kullenberg cores.

Particularly suited to the purpose of measuring the sensitivity of benthic communities to trawling, a trawl disturbance indicator (de Juan and Demestre, 2012, de Juan et al. 2009) was proposed based on benthic species life history traits to evaluate the sensibility of mega- and epifaunal community to fishing pressure known to have a physical impact on the seafloor (such as dredging and bottom trawling). The selected biological traits were chosen as they determine vulnerability to trawling: mobility, fragility, position on substrata, average size and feeding mode that can easily be related to the fragility, recoverability and vulnerability ecological concepts. Life history traits of species have been defined from the BIOTIC database (MARLIN, 2014) and from information given by Le Pape et al. (2007), Brindamour et al. (2009) and Garcia (2010). For missing life history traits, additional information from literature has been considered. The five categories retained are life history functional traits that were selected based on the knowledge of the response of benthic taxa to trawling disturbance (de Juan and Demestre, 2012). They reflect respectively the possibility to avoid direct gear impact, to benefit from trawling for feeding, to escape gear, to get caught by the net and to resist trawling/dredging action, each of these characteristics being either advantageous or sensitive to trawling. Then, to allow quantitative analysis, a score was assigned to each category: from low vulnerability (0) to high vulnerability (3). The five categories scores were then summed for each taxon (the highly vulnerable taxon could reach the maximum score is 15) and this value may be considered as a species index of sensitivity to trawling disturbance. The scores of 812 taxa commonly found in bottom trawl by-catch in the southern North Sea, English Channel and north-western Mediterranean were described.

The SOMLIT-Antioche observation station, located at 5 nautical miles from Chef de Baie harbor (La Rochelle) is part of the French monitoring network SOMLIT (https://www.somlit.fr/), accredited by the INSU-CNRS as a national Earth Science Observatory (Service National d’Observation : SNO), which comprises 12 observation stations distributed throughout France in coastal locations. It aims to detect long-term changes  of these ecosystems under both natural and anthropogenic forcings. SOMLIT is part of the national research infrastructure for coastal ocean observation ILICO (https://www.ir-ilico.fr/?PagePrincipale&lang=en). The SOMLIT-Antioche station (46.0842 °N, 1.30833 °W) is located in the north-eastern part of the Bay of Biscay, halfway between the islands of Ré and Oléron, at the centre of what is commonly known as the Pertuis Charentais area, which correspond to a semi-enclosed shallow basin and includes four islands (Ré, Oléron, Aix and Madame) and three Pertuis (i.e., detroit) (Breton, Antioche and Maumusson). This 40m-deep site, with muddy to sandy marine bottoms, is submitted to a macro-tidal regime and is largely open to the prevailing westerly swells. It remains under a dominant oceanic/neritic influence, even though its winter/spring hydrological context is influenced by the diluted plumes of the Charente, Gironde and Loire rivers, but not by those of too small estuaries (Lay, Seudre and Sèvre Niortaise). SOMLIT-Antioche hydrological monitoring has been carried out by the LIENSs/OASU laboratory on a fortnightly basis since June 2011. Surface water samples are collected  at high-tide during intermediate tides (70 ± 10 in SHOM units) on board the research  vessel ‘L’Estran’ owned by La Rochelle University. Samples are analyzed for more than 16 core parameters: temperature, salinity, dissolved oxygen, pH, ammonia, nitrates, nitrites, phosphates, silicates, suspended matter, particulate organic carbone, particulate organic nitrogen, chlorophyll, delta15N, delta13C; pico- and nano- plankton. Measurements are carried out in accordance with the ISO/IEC 17025:2017 standard. Simultaneous monitoring of the micro-phytoplankton community (since 2013, SNO PHYTOBS: https://www.phytobs.fr/en) and monitoring of prokaryotic communities (Bacteria and Archaea) are also carried out on a monthly basis. Since 2019, seasonal observations of benthic invertebrate communities (SNO BenthObs : https://www.benthobs.fr/) have also been carried out. This monitoring is complementary to that carried out at hydrological stations in the pre-existing REPHY and DCE networks, some of which are located near marine farming areas (oyster and mussel farms).

210Pb, 226Ra and 137Cs were measured by non-destructive gamma spectrometry on marine sediment cores, collected during RIKEAU 2002 cruise on board r/v Thalia, on the shelf of the Bay of Biscay

The Southern Ocean plays a fundamental role in regulating the global climate. This ocean also contains a rich and highly productive ecosystem, potentially vulnerable to climate change. Very large national and international efforts are directed towards the modeling of physical oceanographic processes to predict the response of the Southern Ocean to global climate change and the role played by the large-scale ocean climate processes. However, these modeling efforts are greatly limited by the lack of in situ measurements, especially at high latitudes and during winter months. The standard data that are needed to study ocean circulation are vertical profiles of temperature and salinity, from which we can deduce the density of seawater. These are collected with CTD (Conductivity-Temperature-Depth) sensors that are usually deployed on research vessels or, more recently, on autonomous Argo profilers. The use of conventional research vessels to collect these data is very expensive, and does not guarantee access to areas where sea ice is found at the surface of the ocean during the winter months. A recent alternative is the use of autonomous Argo floats. However, this technology is not easy to use in glaciated areas. In this context, the collection of hydrographic profiles from CTDs mounted on marine mammals is very advantageous. The choice of species, gender or age can be done to selectively obtain data in particularly under-sampled areas such as under the sea ice or on continental shelves. Among marine mammals, elephant seals are particularly interesting. Indeed, they have the particularity to continuously dive to great depths (590 ± 200 m, with maxima around 2000 m) for long durations (average length of a dive 25 ± 15 min, maximum 80 min). A Conductivity-Temperature-Depth Satellite Relay Data Logger (CTD-SRDLs) has been developed in the early 2000s to sample temperature and salinity vertical profiles during marine mammal dives (Boehme et al. 2009, Fedak 2013). The CTD-SRDL is attached to the seal on land, then it records hydrographic profiles during its foraging trips, sending the data by satellite ARGOS whenever the seal goes back to the surface.While the principle intent of seal instrumentation was to improve understanding of seal foraging strategies (Biuw et al., 2007), it has also provided as a by-product a viable and cost-effective method of sampling hydrographic properties in many regions of the Southern Ocean (Charrassin et al., 2008; Roquet et al., 2013).

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 4 (L4) data) with a particular focus for use in climate studies. This dataset contains the Version 4 Remote Sensing Significant Wave Height product, gridded over a global regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all available altimeters on a monthly basis (using the L2P products also available). These L4 products are meant for statistics and visualization. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 1992 to 2023 (ERS-1, ERS-2,TOPEX-Poseidon, Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3 A, Sentinel-3 B, Sentinel-6 A), therefore spanning over a wider time range than the previous version 3. The missions already retracked (with WHALES) in version 3 were not reprocessed, but extended when applicable. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

The present repository makes available the model, material and outputs of the ISIS-Fish modeling work showcased in the peer-reviewed scientific article by Bastardie et al. 2025. As part of the SEAwise research project (seawiseproject.org), we used an ISIS-Fish database (Mahevas et al 2003, Pelletier et al. 2009, isis-fish.org) previously developed within the MACCO project which describes the mixed demersal fishery in the Bay of Biscay. For this application, the spatial extent of the fishery is the Bay of Biscay, defined here by ICES divisions 8a, 8b and 8d and the resolution chosen is 1/16 ICES statistical rectangle. The biological module (Vajas et al. 2024) includes 7 species of economic interest in the mixed demersal fishery: European hake (Merluccius merluccius), common sole (Solea solea), Norway lobster (Nephrops norvegicus), megrim (Lepidorhombus whiffiagonis), anglerfish (Lophius piscatorius) and two ray species (Raja clavata, Leucoraja naevus). The fishing activities module (Mahevas et al. 2024) is made up of 41 demersal fleets (including all French vessels < 12 meters and > 12 meters fishing in this area, Spanich, UK and Belgium fleets) and 431 métiers (combination of a gear, location and mix of target species) catching these 7 species, as target or bycatch. Monthly effort of a fleet distributes among the possible métiers (those historically practiced). The biological and fishing activity modules are identical to the published version. The original model used here has been calibrated on historical catch data 2015-2018 by tuning accessibility and catchability parameters. In the present application the Bay of Biscay model is used to investigate the spatial- and effort- based fisheries management strategies. Consistently with for a task of the SEAwise project (Bastardie et al. 2024) simulations were conducted from 2021 onwards, projecting the effect of an implementation of 3 different closures from 2022 to 2050, under current fishing effort conditions or in a context of fishing effort reduction. Outcomes of these simulations are averaged over short/medium (10 year horizon) and long-term period (20 year horizon). The data project includes: 1) the database including the biological module and fishing activity module; 2) 8 .properties files, each corresponding to one combination of management measure and closure, to restore the simulations parameters in the ISIS-Fish interface and reproduce the simulation runs; 3) the .java scripts to force effort dynamics and simulate spatio-temporal closures, as well as generate the main output files - they will be called by the ISIS-Fish software once the simulations restored 4) the .rds containing the main outputs of the simulations and the associated .html document displaying the R code to compute the indices of interest at different levels of aggregation and reproduce the figures in Bastardie et al. 2025. All files are provided in the Zip. Associated with this material, a study summary and a readme .docx are provided. The first one provides context on the present work and describes the model and simulations' design. The second provides guidelines to reproduce the simulations and their derived outcomes from the data project material made available in this repository. They are both directly downloadable from this repository and are also copied to the zipped folder containing the data project. All the data are reproducible using isis-fish-4.4.8.1 (isis-fish.org; available at forge.codelutin.com) and R 4.2.0.

Moving 6-year analysis of Water body dissolved inorganic nitrogen (DIN) in the Mediterranean Sea for each season: - winter: January-March, - spring: April-June, - summer: July-September, - autumn: October-December. Every year of the time dimension corresponds to the 6-year centered average of the season. 6-years periods span from 1990-1995 until 2018-2023. Description of DIVA analysis: The computation was done with the DIVAnd (Data-Interpolating Variational Analysis in n dimensions), version 2.7.12, using GEBCO 30sec topography for the spatial connectivity of water masses. The horizontal resolution of the produced DIVAnd maps grids is dx=dy=0.125 degrees (around 13.5km and 10.9km accordingly). The vertical resolution is 21 depth levels: [0.,5.,10.,20.,30.,50.,75.,100.,125.,150.,200.,250.,300.,400.,500.,600.,700.,800.,900.,1000.,1100.]. The horizontal correlation length is 200km. The vertical correlation length (in meters) was set twices the vertical resolution: [10.,10.,20.,20.,40.,50.,50.,50.,50.,100.,100.,100.,200.,200.,200.,200.,200.,200.,200.,200.,200.]. Duplicates check was performed using the following criteria for space and time: dlon=0.001deg., dlat=0.001deg., ddepth=1m, dtime=1hour, dvalue=0.1. The error variance (epsilon2) was set equal to 1 for profiles and 10 for time series to reduce the influence of close data near the coasts. An anamorphosis transformation was applied to the data (function DIVAnd.Anam.loglin) to avoid unrealistic negative values: threshold value=200. A background analysis field was used for all years (1990-2023) with correlation length equal to 600km and error variance (epsilon2) equal to 20. Quality control of the observations was applied using the interpolated field (QCMETHOD=3). Residuals (differences between the observations and the analysis (interpolated linearly to the location of the observations) were calculated. Observations with residuals outside the minimum and maximum values of the 99% quantile were discarded from the analysis. Originators of Italian data sets-List of contributors: - Brunetti Fabio (OGS) - Cardin Vanessa, Bensi Manuel doi:10.6092/36728450-4296-4e6a-967d-d5b6da55f306 - Cardin Vanessa, Bensi Manuel, Ursella Laura, Siena Giuseppe doi:10.6092/f8e6d18e-f877-4aa5-a983-a03b06ccb987 - Cataletto Bruno (OGS) - Cinzia Comici Cinzia (OGS) - Civitarese Giuseppe (OGS) - DeVittor Cinzia (OGS) - Giani Michele (OGS) - Kovacevic Vedrana (OGS) - Mosetti Renzo (OGS) - Solidoro C.,Beran A.,Cataletto B.,Celussi M.,Cibic T.,Comici C.,Del Negro P.,De Vittor C.,Minocci M.,Monti M.,Fabbro C.,Falconi C.,Franzo A.,Libralato S.,Lipizer M.,Negussanti J.S.,Russel H.,Valli G., doi:10.6092/e5518899-b914-43b0-8139-023718aa63f5 - Celio Massimo (ARPA FVG) - Malaguti Antonella (ENEA) - Fonda Umani Serena (UNITS) - Bignami Francesco (ISAC/CNR) - Boldrini Alfredo (ISMAR/CNR) - Marini Mauro (ISMAR/CNR) - Miserocchi Stefano (ISMAR/CNR) - Zaccone Renata (IAMC/CNR) - Lavezza, R., Dubroca, L. F. C., Ludicone, D., Kress, N., Herut, B., Civitarese, G., Cruzado, A., Lefèvre, D.,Souvermezoglou, E., Yilmaz, A., Tugrul, S., and Ribera d'Alcala, M.: Compilation of quality controlled nutrient profiles from the Mediterranean Sea, doi:10.1594/PANGAEA.771907, 2011.

Moving 6-year analysis and visualization of Water body dissolved oxygen concentration in the North Sea. Four seasons (December-February, March-May, June-August, September-November). Data Sources: observational data from SeaDataNet/EMODnet Chemistry Data Network. Description of DIVA analysis: Geostatistical data analysis by DIVAnd (Data-Interpolating Variational Analysis) tool, version 2.7.12. results were subjected to the minfield option in DIVAnd to avoid negative/underestimated values in the interpolated results; error threshold masks L1 (0.3) and L2 (0.5) are included as well as the unmasked field. The depth dimension allows visualizing the gridded field at various depths.