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1. A high-resolution downscaled CMIP5 projections dataset of essential surface climate variables over the globe coherent with theERA5 reanalysis for climate change impact assessments

Author

Thomas Noël, Mathieu Vrac, Guillaume Levavasseur, Dimitri Defrance, Harilaos Loukos, the Climate Data Factory, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Fondation de l'École Polytechnique, FX Centre National de la Recherche Scientifique, CNRS, The activities described in this paper were funded by the Copernicus Climate Change Service. ECMWF implements the Copernicus Climate Change Service and the Copernicus Atmosphere Monitoring Service on behalf of the European Commission. To process the data, this study benefited from the IPSL mesocenter ESPRI facility that is supported by CNRS , SU , and Ecole Polytechnique partly funded by IS-ENES3 project. We also thank the Institut Pierre Simon Laplace for assistance with the Synda software and the Deutsches Klimarechenzentrum for the Quality Assurance tool., The Climate Data Factory, Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)

Subjects
Science (General), [SDV]Life Sciences [q-bio], Computer applications to medicine. Medical informatics, R858-859.7, Climate change, Wind speed, Q1-390, 03 medical and health sciences, 0302 clinical medicine, Downscaling, CMIP5, Impact modeling, Precipitation, Adaptation, Data Article, 030304 developmental biology, Projections, 0303 health sciences, Multidisciplinary, Impact assessment, 13. Climate action, Greenhouse gas, Climatology, Environmental science, ERA5, Climate model, High-resolution, 030217 neurology & neurosurgery, Quantile
Abstract

International audience; A high-resolution climate projections dataset is obtained by statistically downscaling climate projections from the CMIP5 experiment using the ERA5 reanalysis from the Copernicus Climate Change Service. This global dataset has a spatial resolution of 0.25°x 0.25°, comprises 21 climate models and includes 5 surface daily variables at monthly resolution: air temperature (mean, minimum, and maximum), precipitation, and mean near-surface wind speed. Two greenhouse gas emissions scenarios are available: one with mitigation policy (RCP4.5) and one without mitigation (RCP8.5). The downscaling method is a Quantile Mapping method (QM) called the Cumulative Distribution Function transform (CDF-t) method that was first used for wind values and is now referenced in dozens of peer-reviewed publications. The data processing includes quality control of metadata according to the climate modeling community standards and value checking for outlier detection.

Published
2021

2. Forest production efficiency increases with growth temperature

Author

Alessandro Cescatti, Alessio Collalti, Andreas Ibrom, Giorgio Matteucci, Marcos Fernández-Martínez, Ramdane Alkama, Daniel S. Goll, Julia Pongratz, Philippe Ciais, Anders Stockmarr, Vanessa Haverd, Stephen Sitch, Julia E. M. S. Nabel, Iain Colin Prentice, Pierre Friedlingstein, Almut Arneth, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), FOE-2019 College of Natural Resources, University of California Berkeley, CNR: DTA.AD003.474, We thank R.H. Waring, S. Vicca, M. Campioli, F. Pagani and E. Grieco for early constructive comments and thoughtful suggestions, S. Noce for the map of data points. We thank efforts from all site investigators and their funding agencies. This paper contributes to the AXA Chair Programme in Biosphere and Climate Impacts and the Imperial College initiative Grand Challenges in Ecosystems and the Environment. A.C. and G.M. are partially supported by resources available from the Ministry of University and Research (FOE-2019), under the project 'Climate Change' (CNR DTA.AD003.474), M.F.-M. is a postdoctoral fellow of the Research Foundation—Flanders (FWO), AXA Research Fund, and Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, General Physics and Astronomy, adaptation, Atmospheric sciences, 01 natural sciences, Nutrient, Forest production efficiency, ddc:550, SDG 13 - Climate Action, gpp, lcsh:Science, Plant ecology, chemistry.chemical_classification, forest productivity, Carbon dioxide in Earth's atmosphere, Biomass (ecology), Multidisciplinary, Climate-change ecology, Biogeography, [SDE]Environmental Sciences, Engineering sciences. Technology, primary production, biomass production efficienty, Science, carbon use efficiency, chemistry.chemical_element, General Biochemistry, Genetics and Molecular Biology, Article, Latitude, Organic matter, Ecosystem, Precipitation, Biology, 0105 earth and related environmental sciences, Computer. Automation, npp, Primary production, General Chemistry, 15. Life on land, Earth sciences, chemistry, 13. Climate action, Environmental science, lcsh:Q, Forest ecology, Carbon, 010606 plant biology & botany
Abstract

Forest production efficiency (FPE) metric describes how efficiently the assimilated carbon is partitioned into plants organs (biomass production, BP) or—more generally—for the production of organic matter (net primary production, NPP). We present a global analysis of the relationship of FPE to stand-age and climate, based on a large compilation of data on gross primary production and either BP or NPP. FPE is important for both forest production and atmospheric carbon dioxide uptake. We find that FPE increases with absolute latitude, precipitation and (all else equal) with temperature. Earlier findings—FPE declining with age—are also supported by this analysis. However, the temperature effect is opposite to what would be expected based on the short-term physiological response of respiration rates to temperature, implying a top-down regulation of carbon loss, perhaps reflecting the higher carbon costs of nutrient acquisition in colder climates. Current ecosystem models do not reproduce this phenomenon. They consistently predict lower FPE in warmer climates, and are therefore likely to overestimate carbon losses in a warming climate., Many models assume a universal carbon use efficiency across forest biomes, in contrast to assumptions of other process-based models. Here the authors analyse forest production efficiency across a wide range of climates to show a positive relationship with annual temperature and precipitation, indicating that ecosystem models are overestimating forest carbon losses under warming.

Published
2020

3. Helicobacter pylori Adapts to Chronic Infection and Gastric Disease via pH-Responsive BabA-Mediated Adherence

Author

Verena Königer, D. Scott Merrell, Roman Andriiovych Moskalenko, Rainer Haas, Thomas Borén, Sara Henriksson, Jafar Mahdavi, Abhijit Chowdhury, Johan Ögren, Anders Hofer, Jay V. Solnick, Dan Danielsson, Sara K. Lindén, Dag Ilver, Konstantinos S. Papadakos, Susanne Vikström, Jörgen Ådén, Jan Holgersson, Gerhard Gröbner, Alexej Schmidt, Jeanna Bugaytsova, Oscar Björnham, Göran O. Bylund, Rolf Sjöström, Stefan Oscarson, Dionyssios N. Sgouras, Lori M. Hansen, Yevgen A Chernov, Anders Esberg, Kristof Moonens, Christopher Aisenbrey, Charles Kelly, Ludmilla A. Morozova-Roche, Jeannette M. Whitmire, Beatriz Martinez-Gonzalez, Asish K. Mukhopadhyay, Angela Eldridge, Nicklas Strömberg, Robert H. Gilman, Andre Dubois, Lars Engstrand, Staffan Schedin, Brett A. Chromy, Justine Younson, Matthew Goldman, Anna Shevtsova, Macarena P. Quintana-Hayashi, Hui Liu, Magnus Unemo, Lena Rakhimova, Anna Åberg, Sebastian Suerbaum, Anna Arnqvist, Pär Gideonsson, Maréne Landström, Douglas E. Berg, Kristoffer Brännström, Anders Olofsson, Melissa Mendez, G. Balakrish Nair, Han Remaut, Umeå University, School of Life Sciences, University of Nottingham, UK (UON), Sahlgrenska Academy at University of Gothenburg [Göteborg], Université libre de Bruxelles (ULB), VIB-VUB Center for Structural Biology [Bruxelles], VIB [Belgium], Sumy State University, Max Von Pettenkofer Institute (MVP), Ludwig-Maximilians-Universität München (LMU), Uniformed Services University of the Health Sciences (USUHS), King‘s College London, Johns Hopkins Bloomberg School of Public Health [Baltimore], Johns Hopkins University (JHU), School of Digestive and Liver Diseases [Kolkata] (SDLD), National Institute of Cholera and Enteric Diseases, Translational Health Science and Technology Institute [Faridabad] (THSTI), Institut Pasteur Hellénique, Réseau International des Instituts Pasteur (RIIP), Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Karolinska Institutet [Stockholm], Örebro University Hospital [Örebro, Sweden], Hannover Medical School [Hannover] (MHH), German Center for Infection Research - partner site Hannover-Braunschweig (DZIF), School of Chemistry and Chemical Biology (UCD), University College Dublin [Dublin] (UCD), University of California [Davis] (UC Davis), University of California, German Center for Infection Research, Partnersite Munich (DZIF), Département d'Informatique [Bruxelles] (ULB), Faculté des Sciences [Bruxelles] (ULB), Université libre de Bruxelles (ULB)-Université libre de Bruxelles (ULB), University of California [San Diego] (UC San Diego), This work was supported by grants from Vetenskapsrådet (VR/M) to T.B. and S.K.L., Cancerfonden to T.B. and A.A., VR/NT to A.A. and S. Schedin, Formas to S.K.L., the J.C. Kempe and Seth M. Kempe Memorial Foundation, the Knut and Alice Wallenberg Foundation (2012.0090) to T.B. and M.L., European Union Seventh Framework Program GastricGlycoExplorer ITN grant number 316929 to T.B. and Y.A.C., Magn. Bergvall’s Foundation to S. Schedin, DFG (SFB 900/A1) to S. Suerbaum, DFG (HA2697/16-1) to R.H., FP6 ANR-06-PATHO-00701 ERA-NET and Actions Concertées Inter-Pasteuriennes (ACIP) (2006) to D.N.S., NIH R01DK063041 to D.E.B., NIH CA082312 to D.S.M., NIH AI070803 and AI081037 to J.V.S., CSIR project, India (No. 37(1640)/14/EMR –II) to A.K.M., and VIB and FWO (grants: G033717N and 12H8416N) to K.M. and H.R., This paper is dedicated to the memory of our friend, collaborator, and co-author Dr. Andre Dubois, a great scientist who contributed importantly both intellectually and materially to this project. We thank S. Michopoulos and G. Mantzaris for H. pylori clinical isolates and Ö. Furberg (NoPolo.se), N. Ulander (softplanbangkok.com), S. Lindström, and M. Borén for the digital movie, tech, art, and figure work, respectively., Vrije Universiteit Brussel, Basic (bio-) Medical Sciences, Structural Biology Brussels, and Department of Bio-engineering Sciences

Subjects
0301 basic medicine, MESH: Hydrogen-Ion Concentration, Gastric acidity, MESH: Helicobacter Infections/pathology, MESH: Helicobacter pylori/physiology, Disease, adaptation, Bacterial Adhesion, polymorphism, acid responsiveness, MESH: Bacterial Adhesion, Bacterial, Hydrogen-Ion Concentration, gastric acidity, Adhesins, 3. Good health, Cell and molecular biology, medicine.anatomical_structure, Infectious Diseases, MESH: Gastric Mucosa/microbiology, Medical Microbiology, 030106 microbiology, Immunology, Digestive Diseases - (Peptic Ulcer), Biology, blood group antigen-binding adhesion, Microbiology, Helicobacter Infections, diversity, Vaccine Related, 03 medical and health sciences, Virology, ABO blood group system, Biodefense, Gastric mucosa, medicine, MESH: Helicobacter Infections/microbiology, multimerization, Adhesins, Bacterial, subpopulations, Helicobacter pylori, Prevention, gastric cancer, MESH: Adhesins, Bacterial/metabolism, biology.organism_classification, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, MESH: Gastric Mucosa/pathology, Bacterial adhesin, Chronic infection, 030104 developmental biology, Emerging Infectious Diseases, Gastric Mucosa, Parasitology, Digestive Diseases
Abstract

The BabA adhesin mediates high-affinity binding of Helicobacter pylori to the ABO blood group antigen-glycosylated gastric mucosa. Here we show that BabA is acid responsive-binding is reduced at low pH and restored by acid neutralization. Acid responsiveness differs among strains; often correlates with different intragastric regions and evolves during chronic infection and disease progression; and depends on pH sensor sequences in BabA and on pH reversible formation of high-affinity binding BabA multimers. We propose that BabA's extraordinary reversible acid responsiveness enables tight mucosal bacterial adherence while also allowing an effective escape from epithelial cells and mucus that are shed into the acidic bactericidal lumen andthat bio-selection and changes in BabA bindingproperties through mutation and recombination with babA-related genes are selected by differencesamong individuals and by changes in gastric acidity over time. These processes generate diverse H.pylori subpopulations, in which BabA's adaptive evolution contributes to H.pylori persistence and overt gastric disease.

Published
2017

4. Spatiotemporal dynamics of forage and water resources shape space use of West African savanna buffaloes

Author

Georges Janeau, Nicolas Morellet, Marie-Noël De Visscher, Simon Benhamou, Daniel Cornélis, Moumouni Ouedraogo, Animal et gestion intégrée des risques (UPR AGIRs), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), Unité de recherche Comportement et Ecologie de la Faune Sauvage (CEFS), Institut National de la Recherche Agronomique (INRA), Département Productions Forestières (D.P.F.), INERA-CNRST, This study was funded by the French National Research Agency (ANR Mobility program). Buffalo captures were carried out with the financial support of the European Union (ECOPAS Program) and the International Foundation for the Conservation of Wildlife (IGF-France). We sincerely thank the WRP board for allowing us to conduct this study within the park, veterinarians P. Chardonnet, L. Ouattara, and A. Caron, and J.-M. Angibault, C. Paolini, A. K. Samna, the WRP rangers, and the Niger and Burkina Faso Air Forces for their invaluable support during capture sessions. We also warmly thank G. Cumming, S. Chamaille, and H. Fritz, and associate editor D. Van Vuren and 2 anonymous referees, for their comments on a previous draft of this paper., Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut de l'Environnement et Recherches Agricoles [Ouagadougou] (INERA), Centre national de la recherche scientifique et technologique [Ouagadougou] (CNRST)-Centre national de la recherche scientifique et technologique [Ouagadougou] (CNRST), and Cornelis, Daniel

Subjects
0106 biological sciences, Range (biology), [SDV]Life Sciences [q-bio], habitat, habitat selection, 01 natural sciences, behavioral plasticity, Dry season, Dynamique des populations, foraging, home range, normalized difference vegetation index (NDVI), space use, Syncerus, caffer brachyceros, West African savanna buffalo, zoology, Savane, 2. Zero hunger, Ecology, biology, Fourrage, savane africaine, Système de positionnement global, Variation saisonnière, Geography, Habitat, besoin en eau, L20 - Écologie animale, P01 - Conservation de la nature et ressources foncières, Wet season, Buffle africain, Distribution géographique, Home range, Foraging, Context (language use), 010603 evolutionary biology, Conservation des ressources, eau, Genetics, Adaptation, Ecology, Evolution, Behavior and Systematics, Cape buffalo, Nature and Landscape Conservation, L02 - Alimentation animale, 010604 marine biology & hydrobiology, Migration animale, L60 - Taxonomie et géographie animales, Distribution spatiale, 15. Life on land, biology.organism_classification, masse corporelle, Animal Science and Zoology, Écologie animale, Comportement animal, Index de végétation
Abstract

International audience; We investigated space-use patterns of the West African savanna buffalo (Syncerus caffer brachyceros), a little-studied subspecies occurring at the northern limit of the African buffalo's geographical range. This buffalo generally ranges in small herds (about 45 individuals) and has a low body mass (approximately 400 kg) relative to the Cape buffalo (S. c. caffer). We monitored the movements of 7 breeding herds in W Regional Park (Burkina Faso, Benin, Niger) using global positioning system collars and activity data loggers. Habitat selection was analyzed at both large (interseasonal) and small (intraseasonal) scales in a context where resources are segregated spatially at some times of year. Both biotic (primary production and vegetation types) and abiotic (timing of rainfall and surface water) covariates, and the extent to which neighboring herds shared space, were considered. In the dry season buffalo herds ranged close (within 5.3 +/- 2.0 km, mean +/- SD) to segments of permanent rivers. At the onset of the monsoon all herds but 1 (which had year-round access to suitable resources) performed a large (35 +/- 10 km) directional movement in response to a large-scale gradient of primary production. Spatiotemporal dynamics of forage and water resources thus jointly stimulated interseasonal directional movements and shaped large (335 +/- 167 km(2)) annual home ranges. Furthermore, the establishment of home ranges in the wet season appears to be conditioned by a threshold (about 10%) in the availability of perennial grasses. Habitat-selection analysis at intraseasonal scale also underlines the key role played by perennial grasses for buffaloes. The spatial arrangements of home ranges of neighboring herds also suggest that interherd behavioral avoidance is a high-level constraint on foraging processes. The ability of the African buffalo to cope with contrasting environmental conditions throughout most sub-Saharan ecosystems highlights the high behavioral plasticity of this species.

Published
2011