"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 document is a state of the art on marine dunes and their ecosystems. A first part details the characteristics of marine dunes, a second part summarizes the methods of in situ analysis and modeling of these marine dunes, a third part describes the ecosystems that compose them, a fourth part describes the human activities that impact them. In appendix, an atlas of marine dunes in France and in the world is established.

"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 first aim was 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). 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 simulation NM12-free: The historical simulation used in this work is referred to as the NM12-FREE (no reanalysis no data assimilation) which started in October 1979 and ended in June 2013 (Hamon et al., 2016). It has been run with the general circulation model NEMO in its regional configuration NEMO-MED12 based on a horizontal resolution of 1/12 de degree (6.5 to 8 km cells) and a 75-level vertical resolution (of 1 m width at the surface to 135 m at the seabed). For this simulation, runoff and river inputs in the NM12 domain came from the inter-annual data of Ludwig et al. (2009) and the atmospheric forcing was based on the dynamical downscaling of the ERA-INTERIM reanalysis, i.e. ALDERA which has a 12 km spatial resolution and a 3 h temporal resolution. More details on the NM12-FREE simulation are given in Hamon et al. (2016). 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 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.

This metadata corresponds to the EUNIS Littoral biogenic habitat (salt marshes) types, predicted distribution of habitat suitability dataset. Littoral habitats are those formed by animals such as worms and mussels or plants (salt marshes). The verified littoral biogenic habitat samples used are derived from the Braun-Blanquet database (http://www.sci.muni.cz/botany/vegsci/braun_blanquet.php?lang=en) which is a centralised database of vegetation plots and comprises copies of national and regional databases using a unified taxonomic reference database. The geographic extent of the distribution data are all European countries except Armenia and Azerbaijan. The modelled suitability for EUNIS saltmarsh 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. However, note that it is not representing the actual distribution of the habitat type. As predictors for the suitabilty 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 Landuse, Vegetation height, Phenology, LAI(Leave Area Index) and Population density. 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. The Training map files show the modelled suitable distribution, omitting the 10% of occurrence records in the least suitable environment under the assumption that they are not representative of the overall suitable habitat distribution. The 10 percentile training presence is an arbitrary threshold which omits all regions with habitat suitability lower than the suitability values for the lowest 10% of occurrence records.