The present dataset is based on a nine site study of fine seabed topography in intertidal zones. Four coral sites (Maupiti A, B and C and Niau islands) and five rocky sites (Ars en Ré, Socoa, Parlementia A and B and Banneg island) have been explored. The data has been gathered using on-foot GNSS RTK for all sites (Trimble R8/R8S and Leica sytems) except Banneg island, where aerial Lidar data from Litto3D program has been used. The horizontal resolution varies between 3.8 and 12cm allowing to describe a wide range of spatial scales (generally over 3 spectral decades). The data has been processed to explore the statistical and spectral metrics which can be used to characterize the architectural complexity of seabeds. Owners: - Topographic survey on Ars-en-Ré : profile X, Z in meter along a transec was operated on 10-15 Jan 2021 with On-foot Trimble R8/R8S GNSS RTK by Shom, Gladys and Univ. de Montpellier - Topographic survey on Maupiti Hoe: profile X, Z in meter along a transec was operated on 5-10 July 2018 with on-foot Trimble R8/R8S GNSS RTK by GLADYS and Université de Montpellier - Topographic survey on Niau : profile X, Z in meter along a transec operated on 10 Nov. 2021 with On-foot Trimble R8/R8S GNSS RTK - by CEREGE and MIO (OSU Pytheas) - Topographic survey on Parlementia A, and B : profile X, Z in meter along a transec was operated on 22 Fev 2023 with on-foot Leica GNSS RTK by SIAME, UPPA - Topographic survey on Socoa : profile X, Z in meter along a transec was operated on 21 Fev 2023 with on-foot Leica GNSS RTK by SIAME, UPPA and Shom - Topographic survey in high resolution of Banneg island (X, Y, Z) is made by aerial lidar litto3D on spring 2012/2013 by Shom and IGN

The bathymetric DEM of the atlantic facade with a resolution of 0.001° (~ 100 m) was prepared as part of the HOMONIM project. It encompasses part of the North Sea, the Channel and the Bay of Biscay. Offshore, this DTM extends beyond the slope to approximately 4800 m depth. The DEM is designed to be used in hydrodynamic models in order to produce high-precision forecasts for coastal water levels and sea conditions and therefore improve the pertinence of the Waves-Submersion monitoring programme. This product is available with the Lowest Astronomic Tide (LAT) or the Mean Sea Level (MSL) as a vertical datum.

"Towards an integrated prediction of Land & Sea Responses to global change in the Mediterranean Basin" The LaSeR-Med project aims at investigating the effects of climate change and of mediterranean population growth on some major indicators of the Mediterranean Sea (primary production, carbon export, zooplankton biomass available for small pelagic fishes, pH, dissolved oxygen) using and integrated model encompassing a socio-economic model, a continental model of agro-ecosystems, and a physical ocean-atmosphere model coupled to a biogeochemical model of the ocean. Last, a model for the widespread species of jellyfish Pelagia Noctiluca (Berline et al., 2013) uses biogeochemical outputs as food forcing for the jellyfish. In this project, our aim was first to investigate the large-scale and long-term impacts of variations in river inputs on the biogeochemistry of the Mediterranean Sea over the last decades (see Pages et al., 2020a). In the second phase, a climate scenario (RCP8.5) alone (Pages et al., 2020b) or combined with a “land-use” scenario derived to ensure the same level of food availability as today in 2050 have been run to investigate its effect on these indicators and to analyze the observed changes on the structure and the functioning of planktonic food web. This interdisciplinary project provided the framework for joint discussions on each of the sub-models that constitute the integrated model, namely the socio-economic model (Ami et al., in prep., Mardesic et al., in prep.) created ex nihilo by researchers from AMSE, INRA and GREQAM, the continental agro-ecosystem model LPJmL (Bondeau et al., 2007) worked on at IMBE so as to include the nitrogen and phosphorous cycles in the frame of the present project, and the ocean biogeochemical model Eco3M-Med developed at MIO (Baklouti et al., 2006; Alekseenko et al. 2014, Guyennon et al., 2015; Pagès et al., 2020a), forced by ocean physics, either using the ocean model NEMO-Med12 forced by atmosphere at IPSL (simulation NM12-FREE run with the NEMO-MED12 model and used for our hindcast simulation, see below) or a coupled ocean-atmosphere model at CNRM (physical forcing provided by CNRM-RCSM4, see below). Details on the CNRM-RCSM4 model The CNRM-RCSM4 simulates the main components of the Mediterranean regional climate system and their interactions. It includes four different components: (i) The atmospheric regional model ALADIN-Climate (Radu et al., 2008; Colin et al., 2010; Herrmann et al., 2011) characterized by a 50 km horizontal resolution, 31 vertical levels, and a time step of 1800 s, (ii) the ISBA (Interaction between Soil Biosphere and Atmosphere) land-surface model (Noilhan and Mahfouf, 1996) at a 50 km horizontal resolution, (iii) the TRIP (Total Runoff Integrating Pathways) river routing model (Oki and Sud, 1998), used to convert the runoff simulated by ISBA into rivers (Decharme et al., 2010; Szczypta et al., 2012; Voldoire et al., 2013), and (iv) the Ocean general circulation model NEMO (Nucleus for European Modeling of the Ocean, Madec and NEMO-Team, 2016) in its NEMO-MED8 regional configuration (Beuvier et al., 2010). NEMO-MED8 is characterized by a horizontal resolution of 1/8° (grid cells size from 6 to 12 km), a vertical resolution of 43 vertical levels (cell height ranging from 6 to 200 m), and a time step of 1200 s. More details about the CNRM-RCSM4 model can be found in Sevault et al. (2014). Keywords: - Mediterranean Sea, river inputs, chlorophyll, nutrients, phytoplankton, bacteria, zooplankton, dissolved and particulate organic detrital matter Citation: Pagès, R., Baklouti, M., Barrier, N., Richon, C., Dutay, J.-C., and Moutin, T. (2020a). Changes in rivers inputs during the last decades significantly impacted the biogeochemistry of the eastern Mediterranean basin: a modelling study. Prog. Oceanogr. 181:102242. doi:10.1016/j.pocean.2019.102242 Pagès, R., Baklouti, M., Barrier, N., Ayache, M., Sevault, F., Somot, S. and Moutin, T. (2020b). Projected Effects of Climate-Induced Changes in Hydrodynamics on the Biogeochemistry of the Mediterranean Sea Under the RCP 8.5 Regional Climate Scenario. Front. Mar. Sci. 7:563615. doi:10.3389/fmars.2020.563615 Ayache, M., Bondeau, A., Pagès, R., Barrier, N., Ostberg, S. and Baklouti, M. (2020). LPJmL-Med – Modelling the dynamics of the land-sea nutrient transfer over the Mediterranean region–version 1: Model description and evaluation. Geoscientific Model Development Discussions, Copernicus Publ.

This metadata corresponds to the EUNIS Coastal habitat types, predicted distribution of habitat suitability dataset. Coastal habitats are those above spring high tide limit (or above mean water level in non-tidal waters) occupying coastal features and characterised by their proximity to the sea, including coastal dunes and wooded coastal dunes, beaches and cliffs. Includes free-draining supralittoral habitats adjacent to marine habitats which are normally only very rarely subject to any type of salt water, in as much as they may be inhabited predominantly by terrestrial species, strandlines characterised by terrestrial invertebrates and moist and wet coastal dune slacks and dune-slack pools. Supralittoral sands and wracks may be found also in marine habitats (M). Excludes supralittoral rock pools and habitats, the splash zone immediately above the the mean water line, as well the spray zone and zone subject to sporadic inundation with salt water in as much as it may be inhabited predominantly by marine species, which are included in marine (M). The modelled suitability for EUNIS coastal habitat types is an indication of where conditions are favourable for the habitat type based on sample plot data (Braun-Blanquet database) and the Maxent software package. The modelled suitability map may be used as a proxy for the geographical distribution of the habitat type. Note however that it is not representing the actual distribution of the habitat type. As predictors for the suitability modelling not only climate and soil parameters have been taken into account, but also so-called RS-EVB's, Remote Sensing-enabled Essential Biodiversity Variables, like land use, vegetation height, phenology, and LAI (Leaf Area Index). Because the EBV's are restricted by the extent of the remote sensing data (EEA38 countries and the United Kingdom) the modelling result does also not go beyond this boundary. The dataset is provided both in Geodatabase and Geopackage formats.