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1. Small temperature variations are a key regulator of reproductive growth and assimilate storage in oil palm (Elaeis guineensis).

Author

Tani N, Abdul Hamid ZA, Joseph N, Sulaiman O, Hashim R, Arai T, Satake A, Kondo T, and Kosugi A

Subjects
Rain, Seasons, Temperature, Arecaceae growth & development, Arecaceae metabolism, Carbohydrate Metabolism, Climate Change, Palm Oil, Reproduction, Starch metabolism
Abstract

Oil palm is an important crop for global vegetable oil production, and is widely grown in the humid tropical regions of Southeast Asia. Projected future climate change may well threaten palm oil production. However, oil palm plantations currently produce large amounts of unutilised biological waste. Oil palm stems - which comprise two-thirds of the waste - are especially relevant because they can contain high levels of non-structural carbohydrates (NSC) that can serve as feedstock for biorefineries. The NSC in stem are also considered a potent buffer to source-sink imbalances. In the present study, we monitored stem NSC levels and female reproductive growth. We then applied convergent cross mapping (CCM) to assess the causal relationship between the time-series. Mutual causal relationships between female reproductive growth and the stem NSC were detected, with the exception of a relationship between female reproductive organ growth and starch levels. The NSC levels were also influenced by long-term cumulative temperature, with the relationship showing a seven-month time lag. The dynamic between NSC levels and long-term cumulative rainfall showed a shorter time lag. The lower temperatures and higher cumulative rainfall observed from October to December identify this as a period with maximum stem NSC stocks.

Published
2020
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2. Change in the wind.

Author

Paper, Wendy

Subjects
*CLIMATE change, *GREENHOUSE gases, *CARBON dioxide & the environment
Abstract

Presents an overview of efforts to curb climate change in Australia. Agreement to reduce greenhouse gas emissions; Withdrawal of the United States from the initiative; Stabilization of carbon dioxide.

Published
2001

3. Effects of elevated CO2 on the water hyacinth-biocontrol agent Megamelus scutellaris (Hemiptera: Delphacidae) and its yeast-like symbiotes.

Author

Righetti, Tomás, de la Fuente, Daniela, Paper, Matthew K., Brentassi, María E., Hill, Martin P., Coetzee, Julie A., Salinas, Nicolás A., Bruzzone, Octavio A., and Sosa, Alejandro J.

Subjects
*ATMOSPHERIC carbon dioxide, *CHEMICAL composition of plants, *HEMIPTERA, *WATER hyacinth, *BIOLOGICAL pest control agents, *INVASIVE plants
Abstract

[Display omitted] • Some invasive plant species, like Pontederia crassipes , could be possibly affected by climate change. • Megamelus scutellaris is one of the most commonly used biocontrol agents for P. crassipes. • As other planthoppers, M. scutellaris is expected to host obligate mutualistic organisms, known as Yeast-like symbiotes (YLS). • YLS are first reported in M. scutellaris species and their numbers are positively correlated with their host's weight. • YLS numbers increased under elevated CO 2 , in heavier females. Water hyacinth, Pontederia crassipes , is a highly invasive plant native to South America and one of the most invasive aquatic plants in the world. For its control, the planthopper Megamelus scutellaris Berg (Hemiptera: Delphacidae), a phloem feeder also native to South America has been introduced to the USA and South Africa. Considering predicted climate change scenarios, understanding their impacts on biological control agents is crucial. An intriguing yet scarcely explored subject, is the effect of climatic changes on the obligate endosymbionts associated with sap-sucking feeders. Planthoppers establish an obligate relationship with yeast-like symbiotes (YLS), unicellular fungal microorganisms that play an important role in their development, providing missing nutrients in their diet. Considering that increased atmospheric CO 2 affects plant chemical composition, this might have a direct impact on their insect host and on their number of YLS. We evaluated the effect of two different CO 2 environments: current (cCO 2 − 400 ppm) and elevated (eCO 2 − 800 ppm) on the abundance of YLS (number of YLS cells/insect) of M. scutellaris , as well as the, age structure, sex, and weight of insects. Heavier females harbored more YLS under eCO 2 which underscores the importance of the interaction of CO 2 levels and insects' weight in shaping the abundance of YLS. Additionally, there was a significant increase in the total abundance of insects for instars III to V and adults under eCO 2 conditions. However, male number significantly exceeded that of females under both CO 2 conditions. Our results suggest a potential positive impact of eCO 2 on M. scutellaris populations, which could, in turn, enhance the control of P. crassipes. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Quantifying CMIP6 model uncertainties in extreme precipitation projections

Author

John, Amal, Douville, Hervé, Ribes, Aurélien, Yiou, Pascal, Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), 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), Horizon 2020 Framework Programme, H2020, H2020 Marie Skłodowska-Curie Actions, MSCA: 813844, Center for Agriculture, Food and the Environment, University of Massachusetts Amherst, CAFE, Horizon 2020, This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project, which has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 813844. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output to CMIP. We also thank the Institut Pierre-Simon Laplace (ISPL) Mésocentre for Climate Sciences for the CMIP6 data acquisition, storage space, and intensive computing resources for this paper., This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project, which has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 813844 . We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output to CMIP. We also thank the Institut Pierre-Simon Laplace (ISPL) Mésocentre for Climate Sciences for the CMIP6 data acquisition, storage space, and intensive computing resources for this paper., Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), 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
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Atmospheric Science, [SDU]Sciences of the Universe [physics], [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, [SDE.MCG]Environmental Sciences/Global Changes, Geography, Planning and Development, Extremes, Uncertainty, Climate change, Precipitation, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, Management, Monitoring, Policy and Law
Abstract

International audience; Projected changes in precipitation extremes and their uncertainties are evaluated using an ensemble of global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP). They are scaled by corresponding changes either in global mean surface temperature (ΔGSAT) or in local surface temperature (ΔT) and are expressed in terms of 20-yr return values (RV20) of annual maximum one-day precipitation. Our main objective is to quantify the model response uncertainty and to highlight the regions where changes may not be consistent with the widely used assumption of a Clausius–Clapeyron (CC) rate of ≈7%/K. When using a single realization for each model, as in the latest report from the Intergovernmental Panel on Climate Change (IPCC), the assessed inter-model spread includes both model uncertainty and internal variability, which can be however assessed separately using a large ensemble. Despite the overestimated inter-model spread, our results show a robust enhancement of extreme precipitation with more than 90% of models simulating an increase of RV20. Moreover, this increase is consistent with the CC rate of ≈7%/K over about 83% of the global land domain when scaled by (ΔGSAT). Our results also advocate for producing multiple single model initial condition ensembles in the next CMIP projections, to better filter internal variability out in estimating the response of extreme events.

Published
2022

5. Water Use Efficiency (WUE) across scales: From genes to landscape

Author

Vincent Vadez, Raphael Pilloni, Alexandre Grondin, Amir Hajjarpoor, Hatem Belhouchette, Youssef Brouziyne, Ghani Chehbouni, Mohamed Hakim Kharrou, Rim Zitouna-Chebbi, Insaf Mekki, Jérôme Molénat, Frédéric Jacob, Jérôme Bossuet, Diversité, adaptation, développement des plantes (UMR DIADE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Université de Montpellier (UM), International Crops Research Institute for the Semi-Arid Tropics [Inde] (ICRISAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Centre d'Etude Regional Pour l'Amelioration de l'Adaptation A la Secheresse (CERAAS), Institut Sénégalais de Recherches Agricoles [Dakar] (ISRA), LMI Adaptation des Plantes et microorganismes associés aux Stress Environnementaux [Dakar] (LAPSE), Institut de Recherche pour le Développement (IRD), Agrosystèmes Biodiversifiés (UMR ABSys), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, 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), International Water Management Institute, MENA Office (IWMI), Université Mohammed VI Polytechnique [Ben Guerir] (UM6P), International Water Research Institute (IWRI), Institut National de Recherche en Génie Rural Eaux et Forêts (INRGREF), Ecole Nationale du Génie Rural, des Eaux et des Forêts (ENGREF)-Institution de la Recherche et de l'Enseignement Supérieur Agricoles [Tunis] (IRESA), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Independent Consultant, The paper was written and supported under the Make Our Planet Great Again (MOPGA) ICARUS project (Improve Crops in Arid Regions and future climates) funded by the Agence Nationale de la Recherche (ANR, grant ANR-17-MPGA-0011), and written in the scope and with the support of the ClimBeR initiative of the CGIAR, itself supported by the France-CGIAR action plan on Climate Change., ANR-17-MPGA-0011,ICARUS,Improve Crops in Arid Regions and future climates(2017), Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM), and Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro

Subjects
CLIMATIC CHANGE, Physiology, PAYSAGE AGRICOLE, WATER MANAGEMENT, MODELS, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, CROPPING SYSTEMS, UTILISATION DE L'EAU, Plant Science, drought, GESTION DES EAUX, EXPLOITATION AGRICOLE, AGRICULTURAL LANDSCAPE, MODELE, FARMS, farming systems, WUE, ECHELLE SPATIALE, SECHERESSE, [SDE.IE]Environmental Sciences/Environmental Engineering, SYSTEME DE CULTURE, TRANSPIRATION, [SDV.SA.AEP]Life Sciences [q-bio]/Agricultural sciences/Agriculture, economy and politics, food security, WATER USE, landscape, WATER USE EFFICIENCY, landscapewater use efficiency, EFFICIENCE D'UTILISATION DE L'EAU, climate change, CHANGEMENT CLIMATIQUE, breeding, SPATIAL SCALE, farming system, crop breeding, [SDV.EE.BIO]Life Sciences [q-bio]/Ecology, environment/Bioclimatology
Abstract

International audience; Highlights:This paper reviews ways to improve water use efficiency beyond the plant level, across time and space scales, from cells, organs, and plants, to field, farm, and landscape.Abstract:Water scarcity will be one of the main issues of the 21 st century, because of competing needs between civil, industrial, and agriculture use. While agriculture is the largest user of water, its share is bound to decrease as societies develop. Clearly, agriculture needs to become more water efficient. Improving water use efficiency (WUE) at the plant level is important although there is a long way into translating this at the farm/landscape level. As we move up from a cell/organ/plant scale to more integrated scales such as plot, field, farm system, and landscape, other factors need to be considered, including trade-offs, to possibly improve WUE. These include choices of crop variety/species, farm management, landscape design, infrastructure development, ecosystem functions, where human decisions matter. This review is a cross-disciplinary attempt to analyze ways to address WUE at these different scales where metrics of analysis are defined and trade-offs considered. The equations in this perspective paper use similar metrics across scales for an easier connection and are developed to highlight which levers, at different scales, can improve WUE. We also refer to models operating at these different scales to assess WUE. While our entry point is plants and crops, we scale up the analysis of WUE to farm systems and landscapes.

Published
2023

6. Les émissions de N2O peuvent-elles compenser les avantages du stockage du carbone organique dans le sol ?

Author

David S. Powlson, Frédéric Rees, Victoria Naipal, Jérôme Balesdent, Rémi Cardinael, Julien Fouché, Emanuele Lugato, Elisa Bruni, Stefan Frank, Philippe Ciais, Dominique Arrouays, Catherine Hénault, Benoit Gabrielle, Hanqin Tian, Thomas Nesme, Sylvain Pellerin, Hugo Valin, Bertrand Guenet, Jean-Pierre Caliman, Michael Obersteiner, Claire Chenu, Feng Zhou, Yang Su, Jean-François Soussana, Dominique Desbois, Songchao Chen, Daniel P. Rasse, Martial Bernoux, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), 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), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), 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), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), InfoSol (InfoSol), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Smart Research Institute [Indonésie] (SMARTRI), SMART agribusiness and food [Jakarta] (SMART), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), University of Zimbawe [Harare] (UZ), University of Zimbawe, ICOS-ATC (ICOS-ATC), Economie Publique (ECO-PUB), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-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 National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Commission - Joint Research Centre [Ispra] (JRC), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rothamsted Research, Norwegian Institute of Bioeconomy Research (NIBIO), Auburn University (AU), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], This paper stemmed from a workshop 'Emerging challenges in large scale soil carbon sequestration' held in Paris on 8-10 October 2018. The workshop was financially supported by the French government under the ANR 'Investissements d'avenir' program with the reference CLAND ANR-16-CONV-0003. F.Z. acknowledges support from the National Natural Science Foundation of China (grant no. 41671464), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), 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)-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), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - 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), Biotechnology and Biological Sciences Research Council (BBSRC), Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO), Support from the National Natural Science Foundation of China (grant no. 41671464), Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre National d'Études Spatiales [Toulouse] (CNES)

Subjects
0106 biological sciences, Atténuation de l'effet de serre, 010504 meteorology & atmospheric sciences, Travail du sol, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, greenhouse gases emissions, Agroforesterie, Carbone dans le sol, 7. Clean energy, 01 natural sciences, agroforestry, Interactions biologiques, Environmental protection, Biochar, organic amendment, General Environmental Science, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, Ecology, greenhouse gas emissions, land based mitigation, erosion, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Tillage, Gaz a effet de serre, séquestration du carbone, Cycle de l'azote, réduction des émissions, [SDE]Environmental Sciences, tillage, Culture de couverture, P33 - Chimie et physique du sol, Labour, Land management, Climate change, érosion, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 010603 evolutionary biology, 12. Responsible consumption, Matière organique du sol, Fertilité du sol, Environmental Chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, biochar, Occupation des sols, émissions de gaz à effet de serre, 0105 earth and related environmental sciences, cover crops agroforestry, Oxyde nitreux, Global warming, Soil carbon, 15. Life on land, soil organic carbon, land-based mitigation, Amendement organique, 13. Climate action, Greenhouse gas, Soil water, Environmental science, cover crops, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Cycle du carbone
Abstract

This paper stemmed from a workshop 'Emerging challenges in large scale soil carbon sequestration' held in Paris on 8-10 October 2018; International audience; To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5°C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large‐scale deployment of other climate mitigation strategies are also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N$_2$O), a powerful greenhouse gas, and increasing SOC may influence N$_2$O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here, we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N$_2$O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta‐analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N$_2$O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g, biochar or non‐pyrogenic C amendment application) may even decrease N$_2$O emissions.; Pour respecter l'accord de Paris visant à limiter le réchauffement climatique à moins de 2°C d'ici 2100, et éventuellement à moins de 1,5°C, des réductions drastiques des émissions de gaz à effet de serre sont obligatoires mais pas suffisantes. Le déploiement à grande échelle d'autres stratégies d'atténuation du climat est également nécessaire. Parmi celles-ci, l'augmentation des stocks de carbone organique du sol (SOC) est un levier important car le carbone dans les sols peut être stocké pendant de longues périodes et les options de gestion des terres pour y parvenir existent déjà et ont été largement testées. Toutefois, les sols agricoles sont également une source importante d'oxyde nitreux (N$_2$O), un puissant gaz à effet de serre, et l'augmentation du SOC peut influer sur les émissions de N$_$O, provoquant probablement une augmentation dans de nombreux cas, tendant ainsi à compenser le bénéfice du changement climatique résultant du stockage accru du SOC. Nous passons ici en revue les principales options de gestion agricole pour l'augmentation des stocks de SOC. Nous évaluons la quantité de SOC qui peut être stockée ainsi que les changements qui en résultent dans les émissions de N$_2$O afin de mieux estimer les avantages climatiques de ces options de gestion. Sur la base des données quantitatives obtenues à partir de méta-analyses publiées et de notre niveau de compréhension actuel, nous concluons que l'atténuation du climat induite par un stockage accru du SOC est généralement surestimée si l'on ne tient pas compte des émissions de N$_2$O associées, mais, à l'exception du travail réduit du sol, n'est jamais totalement compensée. Certaines options (par exemple, le biochar ou l'application d'un amendement C non pyrogène) peuvent même réduire les émissions de N$_2$O.

Published
2021

7. Pathways and pitfalls in extreme event attribution

Author

Roop Singh, Julie Arrighi, Karin van der Wiel, Andrew D. King, Sarah F. Kew, Robert Vautard, Fraser C. Lott, Friederike E. L. Otto, Sjoukje Philip, Geert Jan van Oldenborgh, Maarten van Aalst, Royal Netherlands Meteorological Institute (KNMI), University of Oxford, 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), School of Earth Sciences [Melbourne], Faculty of Science [Melbourne], University of Melbourne-University of Melbourne, Met Office Hadley Centre for Climate Change (MOHC), United Kingdom Met Office [Exeter], Red Cross Red Crescent Climate Centre, University of Twente, Australian Research Council, ARC: DE180100638 European Commission, EC, This paper builds on results from the Copernicus COP 039 and C3S 62 contracts lead by KNMI, which focused on the development of a prototype for extreme events and attribution service within the context of the Copernicus Climate Change Service (C3S) implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) and funded by the European Union. The Red Cross Red Crescent Climate Centre authors were partly supported by the Partners for Resilience program. AK was funded by the Australian Research Council (DE180100638)., University of Oxford [Oxford], 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), University of Twente [Netherlands], Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation, and UT-I-ITC-4DEarth

Subjects
Atmospheric Science, Global and Planetary Change, Extreme weather, 010504 meteorology & atmospheric sciences, Computer science, Vulnerability, Climate change, 010501 environmental sciences, Extreme event attribution, 01 natural sciences, Hazard, Data science, Public interest, ITC-HYBRID, Detection and attribution, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, ITC-ISI-JOURNAL-ARTICLE, Meteorology & Atmospheric Sciences, Climate model, Attribution, 0105 earth and related environmental sciences, Event (probability theory)
Abstract

The last few years have seen an explosion of interest in extreme event attribution, the science of estimating the influence of human activities or other factors on the probability and other characteristics of an observed extreme weather or climate event. This is driven by public interest, but also has practical applications in decision-making after the event and for raising awareness of current and future climate change impacts. The World Weather Attribution (WWA) collaboration has over the last 5 years developed a methodology to answer these questions in a scientifically rigorous way in the immediate wake of the event when the information is most in demand. This methodology has been developed in the practice of investigating the role of climate change in two dozen extreme events world-wide. In this paper, we highlight the lessons learned through this experience. The methodology itself is documented in a more extensive companion paper. It covers all steps in the attribution process: the event choice and definition, collecting and assessing observations and estimating probability and trends from these, climate model evaluation, estimating modelled hazard trends and their significance, synthesis of the attribution of the hazard, assessment of trends in vulnerability and exposure, and communication. Here, we discuss how each of these steps entails choices that may affect the results, the common problems that can occur and how robust conclusions can (or cannot) be derived from the analysis. Some of these developments also apply to other attribution methodologies and indeed to other problems in climate science.

Published
2021

8. 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

9. Additive genetic variance for traits least related to fitness increases with environmental stress in the desert locust, Schistocerca gregaria

Author

Marie‐Pierre Chapuis, Benjamin Pélissié, Cyril Piou, Floriane Chardonnet, Christine Pagès, Antoine Foucart, Elodie Chapuis, Hélène Jourdan‐Pineau, Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-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 National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Nebraska [Kearney] (UNK), Plant Health Institute of Montpellier (UMR PHIM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Peuplements végétaux et bioagresseurs en milieu tropical (UMR PVBMT), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de La Réunion (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), This work was supported by research funds from the French Agricultural Research Centre for International Development (CIRAD) and the project ANR-18-CE32-0010 (PEPPER). The authors acknowledge the South Green Platform for providing computational resources that have contributed to the research results reported within this paper., ANR-18-CE32-0010,PEPPER,Etude de l'émergence du polyphénisme de phase et des risques associés(2018), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - 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), and Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Université de Montpellier (UM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro

Subjects
life history evolution, growth, [SDV]Life Sciences [q-bio], Stress abiotique, stress, morphology, pest insects, pigmentation, Variation phénotypique, QH540-549.5, Schistocerca gregaria, Ecology, viability, Stress thermique, temperature, L10 - Génétique et amélioration des animaux, L40 - Anatomie et morphologie des animaux, climate change, Plasticité phénotypique, Variance génétique
Abstract

International audience; Under environmental stress, previously hidden additive genetic variation can be unmasked and exposed to selection. The amount of hidden variation is expected to be higher for life history traits, which strongly correlate to individual fitness, than for morphological traits, in which fitness effects are more ambiguous. However, no consensual pattern has been recovered yet, and this idea is still debated in the literature. Here, we hypothesize that the classical categorization of traits (i.e., life history and morphology) may fail to capture their proximity to fitness. In the desert locust, Schistocerca gregaria, a model organism for the study of insect polyphenism, we quantified changes in additive genetic variation elicited by lifetime thermal stress for ten traits, in which evolutionary significance is known. Irrespective of their category, traits under strong stabilizing selection showed genetic invariance with environmental stress, while traits more loosely associated with fitness showed a marked increase in additive genetic variation in the stressful environment. Furthermore, traits involved in adaptive phenotypic plasticity (growth compensation) showed either no change in additive genetic variance or a change of moderate magnitude across thermal environments. We interpret this mitigated response of plastic traits in the context of integrated evolution to adjust the entire phenotype in heterogeneous environments (i.e., adaptiveness of initial plasticity, compromise of phenotypic compensation with stress, and shared developmental pathway). Altogether, our results indicate, in agreement with theoretical expectations, that environmental stress can increase available additive genetic variance in some desert locust traits, but those closely linked to fitness are largely unaffected. Our study also highlights the importance of assessing the proximity to fitness of a trait on a case-by-case basis and in an ecologically relevant context, as well as considering the processes of canalization and plasticity, involved in the control of phenotypic variation.

Published
2021

10. Climate change impact on future wildfire danger and activity in southern Europe: a review

Author

Javier Madrigal, Jean-Luc Dupuy, Carmen Hernando, Julien Ruffault, François Pimont, Nicolas Martin-StPaul, Hélène Fargeon, Paulo Fernandes, Mercedes Guijarro, Ecologie des Forêts Méditerranéennes (URFM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centro de Investigacion Forestal (INIA-CIFOR), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria = National Institute for Agricultural and Food Research and Technology (INIA), Universidade de Trás-os-Montes e Alto Douro (UTAD), Universidade do Trás-os-Montes e Alto Douro, Centro de Investigação e de Tecnologias Agro-Ambientais e Biológicas (CITAB), University of Trás-os-Montes and Alto Douro [Portugal] (UTAD), This paper has been prepared under the framework of the project MedWildFireLab (‘Global Change Impacts on Wildland Fire Behaviour and Uses in Mediterranean Forest Ecosystems, towards a «wall less» Mediterranean Wildland Fire Laboratory’) funded by ERANET FORESTERRA, and project UID/AGR/04033/2019 funded by the FCT (Fundação para a Ciência e a Tecnologia)., European Project: 138533,FCT::,FORESTERRA/2014,FORESTERRA/0001/2014(2014), Spanish National Research Council [Madrid] (CSIC), and Portuguese Foundation for Science and TechnologyUID/AGR/04033/2019

Subjects
environmental_sciences, 0106 biological sciences, Mediterranean climate, Forest management, Climate change, Climate-fire relationship, FWI, 010603 evolutionary biology, 01 natural sciences, Forest fuels, Mediterranean forests, Burnt areas, [SDV.SA.SF]Life Sciences [q-bio]/Agricultural sciences/Silviculture, forestry, 11. Sustainability, Ecosystem, Projections, Ecology, Global warming, Forestry, 15. Life on land, Arid, Disturbance (ecology), 13. Climate action, Greenhouse gas, Environmental science, Physical geography, 010606 plant biology & botany
Abstract

Wildfire is the main disturbance in forested ecosystems of southern Europe and is due to complex interactions between climate-weather, fuels and people. Warmer and drier conditions projected in this region are expected to profoundly affect wildfires, which will impact ecosystems and humans. We review the scientific literature addressing the assessment of climate change impacts on wildfires in southern Europe, with a twofold objective: (i) report the trends in wildfire danger and activity projected under warming climate in southern Europe and (ii) discuss the limitations of wildfire projections under the specific biogeographical context of southern Europe.We identified 22 projection studies that examined future wildfire danger or wildfire activity at local, regional or continental scale. Under the scenario with the highest greenhouse gas emissions, we found that projections studies estimate an increase in future fire danger and burnt areas varying, on average, from 2 to 4 % and from 15 to 25 % per decade, respectively. Fire-prone area expansion to the north and to Mediterranean mountains is a concern, while climate-induced burnt area increase might be limited by fuel availability in the most arid areas. While all studies agreed on the direction of changes, further comparisons on the magnitude of increase remained challenging because of heterogeneous methodological choices between projections studies (climate models, projection period, spatial scale and fire metrics). We then described three main sources of uncertainty that may affect the reliability of wildfire projections: climate projections, climate-fire models, and the influences of fuel load/structure and human related factors on the climate-fire relationships. We finally suggest research directions to address some of these issues for the purpose of refining fire danger and fire activity projections in southern Europe.

Published
2020

11. The Pliocene Model Intercomparison Project Phase 2: Large-scale climate features and climate sensitivity

Author

A. M. Haywood, J. C. Tindall, H. J. Dowsett, A. M. Dolan, K. M. Foley, S. J. Hunter, D. J. Hill, W.-L. Chan, A. Abe-Ouchi, C. Stepanek, G. Lohmann, D. Chandan, W. R. Peltier, N. Tan, C. Contoux, G. Ramstein, X. Li, Z. Zhang, C. Guo, K. H. Nisancioglu, Q. Zhang, Q. Li, Y. Kamae, M. A. Chandler, L. E. Sohl, B. L. Otto-Bliesner, R. Feng, E. C. Brady, A. S. von der Heydt, M. L. J. Baatsen, D. J. Lunt, 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), Modélisation du climat (CLIM), 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), 17189 University of Toronto, U of T Vetenskapsrådet, VR: 2013-06476, 2017-04232 Engineering and Physical Sciences Research Council, EPSRC: EP/M008.363/1 University of Leeds Natural Sciences and Engineering Research Council of Canada, NSERC: A9627 Government of Ontario Ministerio de Educación, Cultura y Deporte, MECD: 024.002.001 National Science Foundation, NSF: 1418411, 1852977 National Center for Atmospheric Research, NCAR Seventh Framework Programme, FP7 China Scholarship Council, CSC: 201804910023 China Postdoctoral Science Foundation: 2015M581154 Netherlands Earth System Science Centre, NESSC European Research Council, ERC: 278636 Japan Society for the Promotion of Science, KAKEN: 17H06104 Ministry of Education, Culture, Sports, Science and Technology, Monbusho: 17H06323 Canada Foundation for Innovation U.S. Geological Survey, USGS Engineering and Physical Sciences Research Council, EPSRC: EP/M008.363/1, Acknowledgements. We acknowledge the use of NOAA_ERSST_V5 data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at https://www.esrl.noaa.gov/psd/ (last access: 12 September 2019). Alan M. Haywood, Julia C. Tindall, Aisling M. Dolan, Stephen J. Hunter and Daniel J. Hill acknowledge the FP7 Ideas programme: European Research Council (grant no. PLIO-ESS, 278636), the Past Earth Network (EPSRC grant no. EP/M008.363/1) and the University of Leeds Advanced Research Computing service. Julia C. Tindall was also supported through the Centre for Environmental Modelling and Computation (CEMAC), University of Leeds. Harry J. Dowsett and Kevin M. Foley acknowledge support from the USGS Climate Research and Development Program. This research used samples and/or data provided by the Ocean Drilling Program (ODP) and International Ocean Discovery Program (IODP). Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Bette L. Otto-Bliesner, Esther C. Brady and Ran Feng acknowledge that material for their participation is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation (NSF) (cooperative agreement no. 1852977 and NSF OPP grant no. 1418411). The CESM project is supported primarily by the National Science Foundation. Computing and data storage resources, including the Cheyenne supercomputer (https://doi.org/10.5065/D6RX99HX), were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. NCAR is sponsored by the National Science Foundation. Ning Tan, Camille Contoux and Gilles Ramstein were granted access to the HPC resources of TGCC under the allocations 2016-A0030107732, 2017-R0040110492 and 2018-R0040110492 (gencmip6) and 2019-A0050102212 (gen2212) provided by GENCI. The IPSL-CM6 team of the IPSL Climate Modelling Centre (https://cmc.ipsl.fr, last access: 16 September 2020) is acknowledged for having developed, tested, evaluated and tuned the IPSL climate model, as well as per- formed and published the CMIP6 experiments. Christian Stepanek acknowledges funding from the Helmholtz Climate Initiative REKLIM. Christian Stepanek and Gerrit Lohmann acknowledge funding via the Alfred Wegener Institute’s research programme Marine, Coastal and Polar Systems. Qiong Zhang acknowledge support from the Swedish Research Council (2013-06476 and 2017-04232). Simulations with EC-Earth were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at the National Supercomputer Centre (NSC). Wing-Le Chan and Ayako Abe-Ouchi acknowledge funding from JSPS (KAKENHI grant no. 17H06104 and MEXT KAKENHI grant no. 17H06323). Their simulations with MIROC4m were performed on the Earth Simulator at JAMSTEC, Yokohama, Japan. The work by Anna S. von der Heydt and Michiel L. J. Baatsen was carried out under the program of the Netherlands Earth System Science Centre (NESSC), financially supported by the Ministry of Education, Culture and Science (OCW grant no. 024.002.001). Simulations with CCSM4-Utr were performed at the SURFsara Dutch national computing facilities and were sponsored by NWO-EW (Netherlands Organisation for Scientific Research, Exact Sciences) (project no. 17189). W. Richard Peltier and Deepak Chandan were supported by Canadian NSERC Discovery Grant A9627, and they wish to acknowledge the support of SciNet HPC Consortium for providing computing facilities. SciNet is funded by the Canada Foundation for Innovation under the auspices of Compute Canada, the Government of Ontario, the Ontario Research Fund – Research Excellence, and the University of Toronto. Xiangyu Li acknowledges financial support from the China Scholarship Council (201804910023) and the China Postdoctoral Science Foundation (project no. 2015M581154). The NorESM simulations benefitted from resources provided by UNINETT Sigma2 – the National Infrastructure for High Performance Computing and Data Storage in Norway. The authors would also like to thank Tim Herbert and an anonymous reviewer for helpful comments on an earlier version of this paper., Financial support. This research has been supported by the Past Earth Network (EPSRC grant no. EP/M008.363/1)., 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), 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)-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
010504 meteorology & atmospheric sciences, lcsh:Environmental protection, Stratigraphy, Climate change, Zonal and meridional, 010502 geochemistry & geophysics, Atmospheric sciences, 01 natural sciences, lcsh:Environmental pollution, Pliocene climate, lcsh:TD169-171.8, Precipitation, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, Global and Planetary Change, geography, geography.geographical_feature_category, Paleontology, 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, lcsh:TD172-193.5, Polar amplification, Environmental science, Climate sensitivity, Climate model, Ice sheet
Abstract

The Pliocene epoch has great potential to improve our understanding of the long-term climatic and environmental consequences of an atmospheric CO2 concentration near ∼400 parts per million by volume. Here we present the large-scale features of Pliocene climate as simulated by a new ensemble of climate models of varying complexity and spatial resolution based on new reconstructions of boundary conditions (the Pliocene Model Intercomparison Project Phase 2; PlioMIP2). As a global annual average, modelled surface air temperatures increase by between 1.7 and 5.2 ∘C relative to the pre-industrial era with a multi-model mean value of 3.2 ∘C. Annual mean total precipitation rates increase by 7 % (range: 2 %–13 %). On average, surface air temperature (SAT) increases by 4.3 ∘C over land and 2.8 ∘C over the oceans. There is a clear pattern of polar amplification with warming polewards of 60∘ N and 60∘ S exceeding the global mean warming by a factor of 2.3. In the Atlantic and Pacific oceans, meridional temperature gradients are reduced, while tropical zonal gradients remain largely unchanged. There is a statistically significant relationship between a model's climate response associated with a doubling in CO2 (equilibrium climate sensitivity; ECS) and its simulated Pliocene surface temperature response. The mean ensemble Earth system response to a doubling of CO2 (including ice sheet feedbacks) is 67 % greater than ECS; this is larger than the increase of 47 % obtained from the PlioMIP1 ensemble. Proxy-derived estimates of Pliocene sea surface temperatures are used to assess model estimates of ECS and give an ECS range of 2.6–4.8 ∘C. This result is in general accord with the ECS range presented by previous Intergovernmental Panel on Climate Change (IPCC) Assessment Reports.

Published
2020

12. Influence of past and future climate changes on the distribution of three Southeast Asian murine rodents

Author

Serge Morand, Christine N. Meynard, Johan Michaux, Vincent Herbreteau, Alice Latinne, Surachit Waengsothorn, Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Institut de Botanique, Université de Liège, Centre de Biologie pour la Gestion des Populations (UMR CBGP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), UMR 228 Espace-Dev, Espace pour le développement, Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM)-Université de Guyane (UG)-Université des Antilles (UA), Thailand Institute of Scientific and Technological Research (TISTR), Thailand Institute of Scientific and Technological Research, Animal et gestion intégrée des risques (UPR AGIRs), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), This work was supported by a Belgian FRS-FNRS fellowship to A.L. (mandat ‘aspirant’) and to J.R.M. (mandat ‘Ma^ıtre de recherches’) and financial grants from the Belgian FRS-FNRS [‘credits pour brefs sejours a l’etranger’ to A.L. and J.R.M. and credits from the ‘Fonds de la Recherche Fondamentale Collective (FRFC)’ to J.R.M.], the University of Li ege and the Communaute franc aise de Belgique. A.L. was funded by a Marie Curie COFUND postdoctoral fellowship when writing this paper. This study is part of the ‘CERoPath project’, ANR Biodiversity ANR07 BDIV012, and the ‘BiodivHealthSEA project’, ANR CP&ES11 CPEL002, funded by the French National Agency for Research. Th, ANR-07-BDIV-0012,CEROPATH,Ecologie des communautés rongeurs - pathogènes en Asie du Sud-Est : effets des changements de biodiversité et implications pour l'écologie de la santé(2007), ANR-11-CEPL-0002,BiodivHealthSEA,Impacts et perceptions locales des changements globaux : santé, biodiversité et zoonoses en Asie du Sud-Est(2011), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE), Université de Guyane (UG)-Université des Antilles (UA)-Institut de Recherche pour le Développement (IRD)-Université de Perpignan Via Domitia (UPVD)-Avignon Université (AU)-Université de La Réunion (UR)-Université de Montpellier (UM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS), Université des Antilles (UA)-Université de Guyane (UG)-Université de Montpellier (UM)-Université de La Réunion (UR)-Avignon Université (AU)-Université de Perpignan Via Domitia (UPVD)-Institut de Recherche pour le Développement (IRD), Animal et gestion intégrée des risques (Cirad-Bios-UPR 22 AGIRs), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), ANR-07-BDIV-0012,BDIV,Ecologie des communautés rongeurs - pathogènes en Asie du Sud-Est : effets des changements de biodiversité et implications pour l'écologie de la santé(2007), and 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)

Subjects
0106 biological sciences, 01 natural sciences, Species distribution modelling, Dynamique des populations, Climate change, Leopoldamys sabanus, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 0303 health sciences, Ecology, biology, Last Glacial Maximum, [SHS.GEO]Humanities and Social Sciences/Geography, Southeast Asia, Pleistocene, Geography, rodents, Interglacial, L20 - Écologie animale, Leopoldamys neilli, P40 - Météorologie et climatologie, Distribution géographique, Évaluation du risque, Froid, Southeast asian, 010603 evolutionary biology, Last Interglacial, Rodents, modelling, 03 medical and health sciences, Leopoldamys, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Changement climatique, L60 - Taxonomie et géographie animales, Modèle de simulation, 15. Life on land, biology.organism_classification, Environmental niche modelling, 13. Climate action, Écologie animale, species distribution, Rongeur, Murinae, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

International audience; Aim We tested the influence of Pleistocene climatic fluctuations and the potential effect of future climate change on Southeast Asian small mammal dis- tributions using two forest-dwelling (Leopoldamys herberti and Leopoldamys sabanus) and one karst (Leopoldamys neilli) endemic rodent species as models.Location Southeast Asia.Methods We used presence–absence data of genetically identified individuals, bioclimatic variables and species distribution modelling techniques to predict potential distributions of the three studied species under current, past [Last Interglacial (LIG) and Last Glacial Maximum (LGM)] and future conditions. We applied a variety of modelling techniques and then used consensus tech- niques to draw up robust maps of potential distribution ranges at all stages.Results According to our models, these three Leopoldamys species did not experience significant range contraction during the LGM. Our models revealed substantial range contraction during the LIG for L. herberti in northern Indo- china, while its distribution expanded in southern Indochina. Evidence of a southward range expansion during that period was also obtained for L. neilli, whereas L. sabanus remained widely distributed in insular Southeast Asia but experienced a range contraction on the Thai-Malay Peninsula. The two future climate change scenarios used predicted that large climatically suitable areas would still be available in the future for the three species.Main conclusions Our model predictions contradict the well-established hypothesis that Southeast Asian forest-dwelling species were confined to small refugia during the LGM. Moreover, our results suggest that some Southeast Asian taxa may have been distributed in their refugial state during the LIG rather than the LGM. This could be because of vegetation changes that may have occurred at that time as a result of the increased seasonality observed dur- ing the LIG. These Pleistocene refugia may have been localized in northern Indochina but our study also revealed that southern Indochina could provide major potential refugia.

Published
2015