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OSU Pytheas UMS 3470 CNRS

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    Une infrastructure de recherche européenne de mesure des concentrations atmosphériques des gaz à effet de serre et des flux de carbone sur les écosystèmes et l’océan. La tour ICOS (pour Integrated Carbon Observation System) installée à l'Observatoire de Haute Provence (OHP), haute de 100 m est une antenne régionale du dispositif permettant d’étudier la place de la forêt méditerranéenne dans le bilan de carbone. Elle est équipée d’instruments à trois niveaux (10, 50, 100 m). Le réseau est doté de 3 types de stations réparties sur le territoire : continentales, côtières et de montagne. Chacune de ces stations mesure les paramètres suivants : * température, direction et vitesse du vent, pression atmosphérique, humidité * CO2, CH4, CO, H2O * hauteur de couche limite atmosphérique (lidar) Les objectifs scientifiques de ce programme européen sont de : * tracer les flux de carbone en Europe et dans les régions adjacentes par observation des écosystèmes, de l'atmosphère et des océans à travers des réseaux intégrés, * fournir les observations à long terme nécessaires pour comprendre l'état présent et prévoir le comportement du carbone global et des émissions des gaz à effet de serre, * surveiller et évaluer l'efficacité de la séquestration du carbone et/ou de la réduction des émissions de gaz à effet de serre sur la composition globale de l'atmosphère, en prenant en compte les sources et les puits par région géographique et par secteur d'activité. L'infrastructure ICOS permet d'accueillir des chercheurs pour des campagnes de recherches

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    L’Observatoire du milieu porté par le GIPREB (Groupement d’Intérêt Publique pour la Réhabilitation de l’Etang de Berre) a pour vocation de suivre depuis 1994 l’évolution hydrologique et biologique de l’étang de Berre (France, Méditerranée). Le suivi du benthos dans l’étang de Berre se fait depuis 2005. Il est réalisé par le GIPREB dans sa totalité. Il y a deux échelles temporelles et spatiales distinctes de suivi : 1) Les station centrales : prélèvement mensuel en 3 stations de l’étang de Berre ============================================================= *Date de début de la série : 2005 *Fréquence : Prélèvement mensuel *Coordonnés des points de Prélèvement : B3 Long : 43.3066 ; Lat : 5.0435 ; Profondeur : 5m B4 Long 43.2708 ; Lat : 5.0567 ; Profondeur : 9 m B6 Long 43.2633 ; Lat 5.0644 ; Profondeur : 9m *Protocole : Engin : Benne Orange peel de 1/12 m² Méthode : Triplicata par station et comptage/détermination des espèces présentes *Paramètres : Richesse Spécifique Densité d’individus (nombre par m²) 2) Les station côtières : prélèvement bi annuel en 10 stations de l’étang de Berre ============================================================= *Date de début de la série : 2005 *Fréquence : Prélèvement Bi annuel (Aout ou septembre et décembre ou février) *Coordonnés des points de Prélèvement : B1 Long 43.3075 Lat 5.0039 Profondeur : 4 m B2 Long 43.3027 Lat 5.0659 Profondeur : 4 m B5 Long 43.2544 Lat 5.0386 Profondeur : 4 m B7 Long 43.2562 Lat 5.1074 Profondeur : 4 m B8 Long 43.3246 Lat 5.0146 Profondeur : 4 m B9 Long 43.2746 Lat 5.0889 Profondeur : 4 m B10 Long 43.2879 Lat 5.1171 Profondeur : 4 m B11 Long 43.273 Lat 5.1105 Profondeur : 4 m B12 Long 43.244 Lat 5.0343 Profondeur : 4 m B13 Long 43.2845 Lat 5.0022 Profondeur : 4 m *Protocole : Engin : ¼ d’une benne Benne Orange peel de 1/12 m² Méthode : Triplicata par station et comptage/détermination des espèces présentes *Paramètres : Richesse Spécifique Densité d’individus (nombre par m²)

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    Sortie du modèle atmosphérique WRF et Meso-NH

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    Meteorological data from the Bay of Marseille based on the measurements taken on the site located on the Pomegues island SITE : Iles de Pomègues – Sémaphore du Frioul - Latitude 43°15’59 N - Longitude 5°17’39 W - Hauteur : 25 m PROGRAMME DE RATTACHEMENT : - Mediterranean Oceanic Observing System on Environment : MOOSE - SOMLIT - Labellisation : SOERE - INSU - Financement : SOERE – INSU Read the abstract and supplemental information provided in the Vector template for more details. EQUIPEMENTS: - Station météorologique Auria avec transmission temps réel - Anémomètre et girouette - Baromètre - Pyranomètre - pluviomètre PARAMETRES MESURES : - Vent ( vitesse et direction) - Température et pression atmosphérique - Irradiance - Pluie DISPONIBLITE DES DONNEES : - Visualisation temps réel - Base de données du Service d'Observation du MIO RESPONSABLE : P. Raimbault. PARTICIPANTS : - M. Fornier (Tech Univ) et M. Lafont (Tech Univ) : maintenance - C. Yohia : gestion des données – site web PARTENAIRES : - MOOSE - SOMLIT – MERMEX – CHARMEX -Ville de Marseille - Parc des îles du Frioul -CITATION : Raimbault, P., & Yohia, C. (2017). Météorologie locale en baie de Marseille : Frioul [Data set]. MIO UMR 7294 CNRS. https://doi.org/10.34930/5C9F6377-726B-436B-AA0F-ECC32803EF88

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    L'Observatoire européen multidisciplinaire des fonds marins et des colonnes d'eau baptisé (EMSO) (European Multidisciplinary Seafloor and water column Observatory) est une infrastructure de recherche répartie à l'échelle européenne des observatoires des fonds marins et des colonnes d'eau. Il vise à explorer davantage les océans, à mieux comprendre les phénomènes qui se produisent au fond de la mer, et à élucider le rôle critique que ces phénomènes jouent dans les systèmes terrestres globaux. Cet observatoire repose sur des sites (ou nœuds) d’observation qui ont été déployés dans des endroits stratégiques des mers européennes, de l'Arctique à l'Atlantique, de la Méditerranée à la mer Noire. Il y a actuellement onze nœuds en eau profonde plus quatre nœuds d'essai en eau peu profonde. EMSO Ligure Ouest est l’un de ces observatoires sous-marin permanent situé en mer Ligurienne et est déployé au large de Toulon, en France. Cette région été choisi pour ses intérêts scientifiques particulières tels que : sismicité, topographie, turbidité, biodiversité, dynamique des masses d'eau et flux de matières organiques. Ce réseau d’observation sous-marine fait aussi partie de KM3NeT (https://www.km3net.org/) qui a une topologie modulaire conçue pour connecter jusqu'à 120 unités de détection de neutrinos. L'instrumentation Earth and Sea Science (ESS) connectée à KM3NeT repose sur deux composants complémentaires: un module d'interface instrumenté (MII) et une ligne instrumentée autonome (ALBATROSS). La ligne ALBATROSS est une ligne inductive (2000 m) composée d'un système de communication acoustique, de deux câbles inductifs équipés de capteurs CTD-O2, de courantomètres et de deux bouées instrumentées. Cette ligne est déployée à une distance de 2-3 kilomètres du MII, et la communication à terre est faite par un lien acoustique avec le MII, et câble électro-optique via le nœud KM3NeT. Data 2016 - DOI: https://doi.org/10.17882/47129 Data Albatross inductive line from 2019 to 2020-11 - DOI: https://doi.org/10.17882/74513 Data Albatross inductive line from 2021 - DOI: https://doi.org/10.17882/83244

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    As part of the EUREC4A-OA project (H. Bellenger, S. Speich, LMD), which is the French oceanographic component of the larger EUREC4A field experiments, the “flux mast” national instrument was installed on the Reseach Vessel R/V Atalante from Genavir. The flux mast holds instruments that measure atmospheric turbulence and meteorological variables. The collected data are used to estimate the turbulent fluxes of momentum and heat at the air-sea interface. Specifically, the flux mast instruments measure air pressure, air temperature, humidity, air refraction index, H2O, the three components of the wind vector, and the upward and downward solar and infrared radiation fluxes. The fluxes calculated are the latent and sensible heat fluxes, and the friction velocity. DOI : https://www.seanoe.org/data/00661/77341/

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    "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.

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    "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.

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    The scientific objectives of the project MAUPITI HOE are to understand the hydrodynamics of an archetypal reef-lagoon system of a high volcanic reef island. The physical functioning of the hydrosystem involves a fine coupling between water levels, waves (including wind, infragravity and VLF waves), currents and seabed structure (reef roughness). The present data focuses on the reef barrier dynamics. Citation: - Sous D., Bouchette F., Certain R., Meulé S. (2021). Maupiti Hoe 2018 [Data set]. MIO UMR 7294 CNRS, GLADYS. https://doi.org/10.34930/9DB3BEC4-0BBF-4531-8864-F100C4B8ECED

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    Environmental conditions are a set of physical and biological variables that define an ecosystem. Microorganisms with higher generation times than more complex multicellular organisms are more sensitive to changing environmental conditions. Therefore, microbial growth curves are an important and simple way to understand how environmental conditions affect microorganisms. Growth curves are used in a variety of biological applications. Traditionally in microbiology, the maximum growth rate (µmax) is calculated by fitting a linear model on data of the exponential growth phase. This method is simple to implement, and robust if the exponential phase contains many points. However, this method is very limiting when the curve is described with few points, as we have seen with experiments under high pressure conditions. In order to overcome this limit, recurrent in biology, we propose to use models to estimate growths parameters. Modeling has existed for many years to describe the growth behavior of microorganisms under variable physical and chemical conditions (Zwietering et al., 1990). Here we propose a ready-to-use application that do not require any special coding skills and allow retrieving several essential parameters describing microbial growth. his app aims at estimating the growth rate and maximum cells density using non-linear regression. The method is detailled in Martini et al. (2013). A demo dataset is available in "Download a demo dataset", you can save it in your computer and load it using "Browse", or you can also browse your own dataset. On Plot panel, it is possible to set axes labels, axes range and Smooth. Smooth parameter can compute theorical (downloadable) for to use with other activities. In order to run this application, you have to format your dataset with tabulation separators. Also, remove all spaces in the dataset header (prefer to use "_" when needed). Organise your dataset so that there is only two arrays. The first one being the time and the second one, the cells density (e. g. optic density, cell number, biomass). This application proposes a method to perform a logistic regression to estimate growth rate as well as maximum cells density . Citation: Garel, M., Izard, L., Vienne, M., Nerini, D., Tamburini, C., Martini, S. (2021). R-shiny-microorganisms v2 : A ready-to-use logistic regression implemented in R shiny to estimate growth parameters of microorganisms [Data set]. MIO UMR 7294 CNRS. https://doi.org/10.34930/DC1DAF1C-09E3-4829-8878-91D0BF0E643E