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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Debaeke, Philippe; Abella, Mathieu; Constantin, Julie; Ferrand, Nicolas; +11 Authors

    La pratique d'une deuxième culture dans l’année, soit à la suite d’une récolte en début d’été (culture dérobée), soit par semis dans la culture primaire (culture en relais), permet une production supplémentaire, qu’elle soit destinée à l’alimentation animale ou humaine ou à vocation énergétique. Cette pratique de double culture peut générer un revenu supplémentaire tout en fournissant des services de soutien et de régulation. En tant que telle, elle peut être considérée comme une forme d'agriculture écologiquement intensive, mais aussi comme une opportunité offerte par le changement climatique. Le processus de prise de décision aboutissant à la double culture repose sur de nombreux facteurs liés aux conditions pédoclimatiques, mais aussi à l’espérance de gain et à la perception du risque. Le projet CASDAR "3C2A : Trois cultures en deux ans" (2019-2023) qui a regroupé 15 partenaires (agriculteurs, conseillers de chambres d’agriculture, ingénieurs d’instituts techniques, chercheurs) s'est efforcé de créer des références utiles pour la double culture dans le Sud-Ouest de la France, englobant les régions Nouvelle-Aquitaine et Occitanie. Cet article vise à illustrer l'intérêt potentiel du soja et du tournesol en tant que doubles cultures dans le Sud-Ouest de la France par une analyse qualitative des perceptions des agriculteurs sur les risques et les opportunités de cette pratique, complétée par une évaluation sur 4 ans des performances agronomiques et économiques de la double culture chez les agriculteurs (130 parcelles) ainsi qu’en station expérimentale où des gammes variétales ont été comparées pendant 3 ans. Avec l’appui de la simulation agronomique (SPA1 , STICS2 ), il a été possible d’évaluer la robustesse des conclusions (faisabilité, productivité) sur des séquences climatiques plus longues, pour des pédoclimats et des conduites culturales non expérimentées, et pour des scénarios de changement climatique, mais aussi d’apprécier les impacts environnementaux (besoins en eau, drainage, lixiviation du nitrate) des cultures dérobées dans le Sud-Ouest. Growing a second crop in a year, either following an early summer harvest (catch crop) or by sowing into the previous autumn-sown crop (relay crop), enables additional production, whether for feed, food or energy purposes. This practice of double cropping can generate additional income while providing support and regulation services. As such, it can be seen as an ecologically intensive form of agriculture, but also as an opportunity offered by climate change. The decision-making process leading to double cropping is based on a number of factors linked to soil and climatic conditions, but also to the expectation of gain and the perception of risk. The CASDAR project "3C2A: Three crops in two years" (2019-2023), which gathered 15 partners (farmers, advisors from chambers of agriculture, engineers from technical institutes, researchers), was set up to create useful references for double cropping in south-western France, encompassing the regions of Nouvelle-Aquitaine and Occitanie. The aim of this article is to illustrate the potential interest of soybean and sunflower as second crops in south-western France by means of a qualitative analysis of farmers' perceptions of the risks and opportunities of this practice, enriched by a 4- year on-farm assessment of the agronomic and economic performances of double cropping (130 fields) and at the experimental station, where a range of varieties were compared over a 3-year period. With the support of agronomic simulation (SPA1 , STICS2 ), it was possible to assess the robustness of the conclusions (feasibility, productivity) over longer climatic sequences, for unexperimented soils, climates and cropping practices, and for climate change scenarios. It was also possible to assess the environmental impacts (water requirements, drainage, nitrate leaching) of catch crops in the South-West.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL INRAEarrow_drop_down
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    HAL INRAE
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    Article . 2024
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL INRAEarrow_drop_down
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      Article . 2024
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Debaeke, Philippe; Abella, Mathieu; Constantin, Julie; Ferrand, Nicolas; +11 Authors

    La pratique d'une deuxième culture dans l’année, soit à la suite d’une récolte en début d’été (culture dérobée), soit par semis dans la culture primaire (culture en relais), permet une production supplémentaire, qu’elle soit destinée à l’alimentation animale ou humaine ou à vocation énergétique. Cette pratique de double culture peut générer un revenu supplémentaire tout en fournissant des services de soutien et de régulation. En tant que telle, elle peut être considérée comme une forme d'agriculture écologiquement intensive, mais aussi comme une opportunité offerte par le changement climatique. Le processus de prise de décision aboutissant à la double culture repose sur de nombreux facteurs liés aux conditions pédoclimatiques, mais aussi à l’espérance de gain et à la perception du risque. Le projet CASDAR "3C2A : Trois cultures en deux ans" (2019-2023) qui a regroupé 15 partenaires (agriculteurs, conseillers de chambres d’agriculture, ingénieurs d’instituts techniques, chercheurs) s'est efforcé de créer des références utiles pour la double culture dans le Sud-Ouest de la France, englobant les régions Nouvelle-Aquitaine et Occitanie. Cet article vise à illustrer l'intérêt potentiel du soja et du tournesol en tant que doubles cultures dans le Sud-Ouest de la France par une analyse qualitative des perceptions des agriculteurs sur les risques et les opportunités de cette pratique, complétée par une évaluation sur 4 ans des performances agronomiques et économiques de la double culture chez les agriculteurs (130 parcelles) ainsi qu’en station expérimentale où des gammes variétales ont été comparées pendant 3 ans. Avec l’appui de la simulation agronomique (SPA1 , STICS2 ), il a été possible d’évaluer la robustesse des conclusions (faisabilité, productivité) sur des séquences climatiques plus longues, pour des pédoclimats et des conduites culturales non expérimentées, et pour des scénarios de changement climatique, mais aussi d’apprécier les impacts environnementaux (besoins en eau, drainage, lixiviation du nitrate) des cultures dérobées dans le Sud-Ouest. Growing a second crop in a year, either following an early summer harvest (catch crop) or by sowing into the previous autumn-sown crop (relay crop), enables additional production, whether for feed, food or energy purposes. This practice of double cropping can generate additional income while providing support and regulation services. As such, it can be seen as an ecologically intensive form of agriculture, but also as an opportunity offered by climate change. The decision-making process leading to double cropping is based on a number of factors linked to soil and climatic conditions, but also to the expectation of gain and the perception of risk. The CASDAR project "3C2A: Three crops in two years" (2019-2023), which gathered 15 partners (farmers, advisors from chambers of agriculture, engineers from technical institutes, researchers), was set up to create useful references for double cropping in south-western France, encompassing the regions of Nouvelle-Aquitaine and Occitanie. The aim of this article is to illustrate the potential interest of soybean and sunflower as second crops in south-western France by means of a qualitative analysis of farmers' perceptions of the risks and opportunities of this practice, enriched by a 4- year on-farm assessment of the agronomic and economic performances of double cropping (130 fields) and at the experimental station, where a range of varieties were compared over a 3-year period. With the support of agronomic simulation (SPA1 , STICS2 ), it was possible to assess the robustness of the conclusions (feasibility, productivity) over longer climatic sequences, for unexperimented soils, climates and cropping practices, and for climate change scenarios. It was also possible to assess the environmental impacts (water requirements, drainage, nitrate leaching) of catch crops in the South-West.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL INRAEarrow_drop_down
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    HAL INRAE
    Article . 2024
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    Article . 2024
    License: CC BY NC ND
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ HAL INRAEarrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Levavasseur, Florent; Kouakou, Patrice; Constantin, Julie; Cresson, Romain; +7 Authors

    AbstractEnergy cover crops for biogas production through anaerobic digestion (AD) are inserted between two primary crops. They replace either bare soil or nonharvested cover crops, and their management is usually intensified to produce more biomass. They allow the production of renewable energy as well as digestate, used as an organic fertilizer, without directly competing with food production. Because of the increased biomass production and export and of the return of a digested biomass to the soil, the impact of energy cover crops on soil organic carbon (SOC) is questioned. The objective of this paper was to study the difference in SOC stocks induced by the introduction of energy cover crops for AD coupled with the application of the resulting amount of digestate. We used the AD model Sys‐Metha combined with the soil C model AMG to simulate SOC stocks for 13 case studies in France, with scenarios comparing different intercrop management practices, with or without cover crops, harvested or not. Our results indicated that the higher biomass production of energy cover crops (from 6.7 to 11.1 t DM ha−1) in comparison with nonharvested cover crops (2 t DM ha−1) or bare soil led to higher humified C input (belowground input and digestate), despite the high C fraction exported in AD. This resulted in an increase in SOC stocks in comparison with nonharvested cover crops or bare soil (from 0.01 to 0.12 t C ha−1 year−1 over 30 years). The uncertainties in the model parameters did not modify these results. However, in the case of equal biomass production between energy cover crops and nonharvested cover crops, SOC stocks would be lower with energy cover crops.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Université d'Artois:...arrow_drop_down
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    GCB Bioenergy
    Article . 2022 . Peer-reviewed
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      Article . 2023
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    Authors: Levavasseur, Florent; Kouakou, Patrice; Constantin, Julie; Cresson, Romain; +7 Authors

    AbstractEnergy cover crops for biogas production through anaerobic digestion (AD) are inserted between two primary crops. They replace either bare soil or nonharvested cover crops, and their management is usually intensified to produce more biomass. They allow the production of renewable energy as well as digestate, used as an organic fertilizer, without directly competing with food production. Because of the increased biomass production and export and of the return of a digested biomass to the soil, the impact of energy cover crops on soil organic carbon (SOC) is questioned. The objective of this paper was to study the difference in SOC stocks induced by the introduction of energy cover crops for AD coupled with the application of the resulting amount of digestate. We used the AD model Sys‐Metha combined with the soil C model AMG to simulate SOC stocks for 13 case studies in France, with scenarios comparing different intercrop management practices, with or without cover crops, harvested or not. Our results indicated that the higher biomass production of energy cover crops (from 6.7 to 11.1 t DM ha−1) in comparison with nonharvested cover crops (2 t DM ha−1) or bare soil led to higher humified C input (belowground input and digestate), despite the high C fraction exported in AD. This resulted in an increase in SOC stocks in comparison with nonharvested cover crops or bare soil (from 0.01 to 0.12 t C ha−1 year−1 over 30 years). The uncertainties in the model parameters did not modify these results. However, in the case of equal biomass production between energy cover crops and nonharvested cover crops, SOC stocks would be lower with energy cover crops.

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    GCB Bioenergy
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    Authors: Bamière, Laure; Bellassen, Valentin; Angers, D.; Cardinael, R.; +17 Authors

    Suite aux accords de Paris en 2015, l'Union européenne (UE) s'est fixé un objectif de neutralité carbone d'ici à 2050, tout comme la France. En plus de réduire les émissions de GES, le secteur agricole français peut contribuer à la neutralité carbone en tant que puits de carbone, par le stockage de carbone dans le sol et la biomasse. L'objectif de cette étude est de quantifier le potentiel de stockage additionnel et le coût d'un ensemble de huit pratiques stockantes. Les impacts de ces pratiques agricoles sur le stockage du carbone organique du sol et les rendements des cultures sont évalués à une échelle spatiale très fine, à l'aide de modèles de cultures et de prairies. L'assiette, le bilan GES net et le coût de mise en œuvre associés à chaque pratique sont également évalués et agrégés au niveau régional. Le modèle économique BANCO utilise ces informations pour générer la courbe de coût marginal d'abattement pour la France, et identifier la combinaison de pratiques stockantes qui minimise le coût total pour atteindre un objectif national donné d'atténuation des émissions de GES nettes. Nous montrons qu'une quantité non négligeable de carbone, de 36,2 à 52,9 MtCO2e an-1, peut être stockée dans le sol et la biomasse pour des prix du carbone raisonnables de 55 et 250 € tCO2e-1, respectivement (correspondant à la "valeur de l'action pour le climat" actuelle et 2030, fixée par le gouvernement français), et cela principalement par le développement de l'agroforesterie et des haies, la généralisation des cultures intermédiaires, l'introduction ou l'extension des prairies temporaires dans les séquences de culture. Ce résultat remet en cause l'objectif 3 à 5 fois inférieur retenu pour le puits de carbone agricole (10 MtCO2e.an-1) par la stratégie nationale bas carbone. Globalement, ce stockage additionnel de carbone permettrait de réduire les émissions totales de GES de la France de 9,2 à 13,8 %, respectivement (année de référence 2019). Following the Paris agreement in 2015, the European Union (EU) set a carbon neutrality objective by 2050, and so did France. The French agricultural sector can contribute as a carbon sink through carbon storage in biomass and soil, in addition to reducing GHG emissions. The objective of this study is to quantitatively assess the additional storage potential and cost of a set of eight carbon-storing practices. The impacts of these agricultural practices on soil organic carbon storage and crop production are assessed at a very fine spatial scale, using crop and grassland models. The associated area base, GHG budget, and implementation costs are assessed and aggregated at the region level. The economic model BANCO uses this information to derive the marginal abatement cost curve for France and identify the combination of carbon storing practices that minimizes the total cost of achieving a given national net GHG mitigation target. We find that a substantial amount of carbon, 36.2 to 52.9 MtCO2e yr-1, can be stored in soil and biomass for reasonable carbon prices of 55 and 250 € tCO2e-1, respectively (corresponding to current and 2030 French carbon value for climate action), mainly by developing agroforestry and hedges, generalising cover crops, and introducing or extending temporary grasslands in crop sequences. This finding questions the 3-5 times lower target of 10 MtCO2e.yr-1 retained for the agricultural carbon sink by the French climate neutrality strategy. Overall, this would decrease total French GHG emissions by 9.2 to 13.8%, respectively (reference year 2019).

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    Journal of Cleaner Production
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    Authors: Bamière, Laure; Bellassen, Valentin; Angers, D.; Cardinael, R.; +17 Authors

    Suite aux accords de Paris en 2015, l'Union européenne (UE) s'est fixé un objectif de neutralité carbone d'ici à 2050, tout comme la France. En plus de réduire les émissions de GES, le secteur agricole français peut contribuer à la neutralité carbone en tant que puits de carbone, par le stockage de carbone dans le sol et la biomasse. L'objectif de cette étude est de quantifier le potentiel de stockage additionnel et le coût d'un ensemble de huit pratiques stockantes. Les impacts de ces pratiques agricoles sur le stockage du carbone organique du sol et les rendements des cultures sont évalués à une échelle spatiale très fine, à l'aide de modèles de cultures et de prairies. L'assiette, le bilan GES net et le coût de mise en œuvre associés à chaque pratique sont également évalués et agrégés au niveau régional. Le modèle économique BANCO utilise ces informations pour générer la courbe de coût marginal d'abattement pour la France, et identifier la combinaison de pratiques stockantes qui minimise le coût total pour atteindre un objectif national donné d'atténuation des émissions de GES nettes. Nous montrons qu'une quantité non négligeable de carbone, de 36,2 à 52,9 MtCO2e an-1, peut être stockée dans le sol et la biomasse pour des prix du carbone raisonnables de 55 et 250 € tCO2e-1, respectivement (correspondant à la "valeur de l'action pour le climat" actuelle et 2030, fixée par le gouvernement français), et cela principalement par le développement de l'agroforesterie et des haies, la généralisation des cultures intermédiaires, l'introduction ou l'extension des prairies temporaires dans les séquences de culture. Ce résultat remet en cause l'objectif 3 à 5 fois inférieur retenu pour le puits de carbone agricole (10 MtCO2e.an-1) par la stratégie nationale bas carbone. Globalement, ce stockage additionnel de carbone permettrait de réduire les émissions totales de GES de la France de 9,2 à 13,8 %, respectivement (année de référence 2019). Following the Paris agreement in 2015, the European Union (EU) set a carbon neutrality objective by 2050, and so did France. The French agricultural sector can contribute as a carbon sink through carbon storage in biomass and soil, in addition to reducing GHG emissions. The objective of this study is to quantitatively assess the additional storage potential and cost of a set of eight carbon-storing practices. The impacts of these agricultural practices on soil organic carbon storage and crop production are assessed at a very fine spatial scale, using crop and grassland models. The associated area base, GHG budget, and implementation costs are assessed and aggregated at the region level. The economic model BANCO uses this information to derive the marginal abatement cost curve for France and identify the combination of carbon storing practices that minimizes the total cost of achieving a given national net GHG mitigation target. We find that a substantial amount of carbon, 36.2 to 52.9 MtCO2e yr-1, can be stored in soil and biomass for reasonable carbon prices of 55 and 250 € tCO2e-1, respectively (corresponding to current and 2030 French carbon value for climate action), mainly by developing agroforestry and hedges, generalising cover crops, and introducing or extending temporary grasslands in crop sequences. This finding questions the 3-5 times lower target of 10 MtCO2e.yr-1 retained for the agricultural carbon sink by the French climate neutrality strategy. Overall, this would decrease total French GHG emissions by 9.2 to 13.8%, respectively (reference year 2019).

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    Authors: Launay, Camille; Houot, Sabine; Jean-Baptiste, Vincent; Raynal, Helene; +1 Authors

    Cover crops could be considered either as multi-services crops (MSCC) (Justes at al, 2017) that are included in rotation for different agronomical purposes (N leaching limitations, storage of Carbon …)or as raw materials used to produce biogas in fermenter by an anaerobic digestion process (AD)). In this latter case, we considered them as energy cover crop (ECC). Some European countries areexploring the idea of replacing dedicated crops with ECC for biogas production, accompanied with specific regulation measures in order to avoid competition with food crops for land use and tosustain crop services such as limitation of N leaching. In France, some studies (ADEME 2018B, 2021) gave an estimation of 18 and 23 Mt covering 11 to 30% of our gas needs by 2050 but based on simpleassumptions and coarse calculations. We present here the methodology and the results of the chapter 5 of C. Launay‘s phD (Launay 2023) about the estimation of the potential production of ECCat France scale and the impacts on food production and on environment. One of the originality of this work has consisted in the design of a modelling chain combining different models in order to represent the different processes from field to energy production. Then, we applied it at France scale.

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    Authors: Launay, Camille; Houot, Sabine; Jean-Baptiste, Vincent; Raynal, Helene; +1 Authors

    Cover crops could be considered either as multi-services crops (MSCC) (Justes at al, 2017) that are included in rotation for different agronomical purposes (N leaching limitations, storage of Carbon …)or as raw materials used to produce biogas in fermenter by an anaerobic digestion process (AD)). In this latter case, we considered them as energy cover crop (ECC). Some European countries areexploring the idea of replacing dedicated crops with ECC for biogas production, accompanied with specific regulation measures in order to avoid competition with food crops for land use and tosustain crop services such as limitation of N leaching. In France, some studies (ADEME 2018B, 2021) gave an estimation of 18 and 23 Mt covering 11 to 30% of our gas needs by 2050 but based on simpleassumptions and coarse calculations. We present here the methodology and the results of the chapter 5 of C. Launay‘s phD (Launay 2023) about the estimation of the potential production of ECCat France scale and the impacts on food production and on environment. One of the originality of this work has consisted in the design of a modelling chain combining different models in order to represent the different processes from field to energy production. Then, we applied it at France scale.

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    Authors: Constantin, Julie; Beaudoin, Nicolas; Launay, Marie; Duval, Jérôme; +1 Authors

    Abstract The long term effects of repeated catch crops on N dynamics in arable farming were assessed using mid-term experiments and long-term simulations. The soil-crop model STICS (v6.9) was tested against a database provided by three experiments (13–17 years) carried out in Northern France, including treatments with or without repeated catch crops. STICS performance was checked for crop biomass, N uptake, soil water content and mineral N at harvest of main crops, drained water, N leaching and mineralization rates. The model satisfactorily reproduced these variables, except for soil mineral N and N leached at one site. N leached was predicted with a slight bias, between −3 and +7 kg N ha−1 yr−1, and soil N mineralized was simulated with a bias lower than 7 kg N ha−1 yr−1. The model simulated correctly the N uptake by catch crops and the kinetics of extra N mineralization due to catch crops. Seven scenarios varying in the presence of catch crops, fertilization rate and climate were simulated on long-term (60 years); their effects on N uptake, soil N storage, N mineralization and nitrate leaching were compared by difference with a control scenario. Repeated catch crops lead to reduce N leaching, sequester organic N and increase N mineralization. The model indicated that the sequestered N reached a maximum of 430–750 kg N ha−1 after 23–45 years depending on site. The extra-mineralization due to catch crops progressively increased up to 38–65 kg N ha−1 yr−1. A strategy of constant N fertilizer rate resulted in raising the N uptake of main crops and slowing down the abatement of nitrate leaching. Conversely, when N fertilization rates were reduced by 20–24 kg N ha−1 yr−1, crop production remained stable and catch crops reduced N leaching on the long term by 33–55%. Therefore catch crop is a promising technique for controlling the N cascade.

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    Authors: Constantin, Julie; Beaudoin, Nicolas; Launay, Marie; Duval, Jérôme; +1 Authors

    Abstract The long term effects of repeated catch crops on N dynamics in arable farming were assessed using mid-term experiments and long-term simulations. The soil-crop model STICS (v6.9) was tested against a database provided by three experiments (13–17 years) carried out in Northern France, including treatments with or without repeated catch crops. STICS performance was checked for crop biomass, N uptake, soil water content and mineral N at harvest of main crops, drained water, N leaching and mineralization rates. The model satisfactorily reproduced these variables, except for soil mineral N and N leached at one site. N leached was predicted with a slight bias, between −3 and +7 kg N ha−1 yr−1, and soil N mineralized was simulated with a bias lower than 7 kg N ha−1 yr−1. The model simulated correctly the N uptake by catch crops and the kinetics of extra N mineralization due to catch crops. Seven scenarios varying in the presence of catch crops, fertilization rate and climate were simulated on long-term (60 years); their effects on N uptake, soil N storage, N mineralization and nitrate leaching were compared by difference with a control scenario. Repeated catch crops lead to reduce N leaching, sequester organic N and increase N mineralization. The model indicated that the sequestered N reached a maximum of 430–750 kg N ha−1 after 23–45 years depending on site. The extra-mineralization due to catch crops progressively increased up to 38–65 kg N ha−1 yr−1. A strategy of constant N fertilizer rate resulted in raising the N uptake of main crops and slowing down the abatement of nitrate leaching. Conversely, when N fertilization rates were reduced by 20–24 kg N ha−1 yr−1, crop production remained stable and catch crops reduced N leaching on the long term by 33–55%. Therefore catch crop is a promising technique for controlling the N cascade.

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      Agriculture Ecosystems & Environment
      Article . 2012 . Peer-reviewed
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    Authors: Constantin, Julie; Minette, Sébastien; Vericel, Gregory; Jordan-Meille, Lionel; +1 Authors

    Abstract Background and aims Cover crops can efficiently increase nitrogen (N) recycling in agroecosystems. By providing a green-manure effect for the next crop, they allow reduced mineral fertilisation. We developed a decision-support tool, called MERCI, to predict N available from cover crop residues over time, from a single measurement of fresh shoot biomass. Methods We coupled a large experimental database from France with a simulation experiment using the soil-crop model STICS. More than 25 000 measurements of 74 species of cover crops as a sole crop or bispecific mixtures were collected. Linear regression models, at the species, family or entire-database level depending on the data available, were built to predict dry biomass, N amount and C:N ratio. Dynamics of N mineralized and leaching from cover crop residues were predicted at 24 contrasting sites as a function of the biomass, carbon (C):N ratio and termination date. Results Correlations between fresh biomass, dry biomass and N amounts in experimental data were strong (r = 0.80-0.96), and predicted N amounts in fresh shoot biomass were relatively accurate. Percentages of N mineralized and leached simulated by STICS were explained mainly by the C:N ratio, site and number of months after termination, but to different degrees. Conclusion MERCI is an easy and robust decision-support tool for predicting N release in the field, and could thus be adopted by advisors and farmers to improve management of nutrient recycling in temperate arable cropping systems.

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    Plant and Soil
    Article . 2023 . Peer-reviewed
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    Agritrop
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      Plant and Soil
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    Authors: Constantin, Julie; Minette, Sébastien; Vericel, Gregory; Jordan-Meille, Lionel; +1 Authors

    Abstract Background and aims Cover crops can efficiently increase nitrogen (N) recycling in agroecosystems. By providing a green-manure effect for the next crop, they allow reduced mineral fertilisation. We developed a decision-support tool, called MERCI, to predict N available from cover crop residues over time, from a single measurement of fresh shoot biomass. Methods We coupled a large experimental database from France with a simulation experiment using the soil-crop model STICS. More than 25 000 measurements of 74 species of cover crops as a sole crop or bispecific mixtures were collected. Linear regression models, at the species, family or entire-database level depending on the data available, were built to predict dry biomass, N amount and C:N ratio. Dynamics of N mineralized and leaching from cover crop residues were predicted at 24 contrasting sites as a function of the biomass, carbon (C):N ratio and termination date. Results Correlations between fresh biomass, dry biomass and N amounts in experimental data were strong (r = 0.80-0.96), and predicted N amounts in fresh shoot biomass were relatively accurate. Percentages of N mineralized and leached simulated by STICS were explained mainly by the C:N ratio, site and number of months after termination, but to different degrees. Conclusion MERCI is an easy and robust decision-support tool for predicting N release in the field, and could thus be adopted by advisors and farmers to improve management of nutrient recycling in temperate arable cropping systems.

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    Plant and Soil
    Article . 2023 . Peer-reviewed
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      Plant and Soil
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    Authors: Kritika Kothari; Rafael Battisti; Kenneth J. Boote; Sotirios Archontoulis; +24 Authors

    Une estimation précise du rendement des cultures dans les scénarios de changement climatique est essentielle pour quantifier notre capacité à nourrir une population croissante et à développer des adaptations agronomiques pour répondre à la demande alimentaire future. Une évaluation coordonnée des simulations de rendement à partir de modèles écophysiologiques basés sur les processus pour l'évaluation de l'impact du changement climatique fait toujours défaut pour le soja, la légumineuse à grains la plus cultivée et la principale source de protéines dans notre chaîne alimentaire. Dans cette première étude multimodèle sur le soja, nous avons utilisé dix modèles de premier plan capables de simuler le rendement du soja sous différentes températures et concentrations atmosphériques de CO2 [CO2] pour quantifier l'incertitude dans les simulations de rendement du soja en réponse à ces facteurs. Les modèles ont d'abord été paramétrés avec des données mesurées de haute qualité provenant de cinq environnements contrastés. Nous avons trouvé une variabilité considérable entre les modèles dans les réponses de rendement simulées à l'augmentation de la température et du [CO2]. Par exemple, en cas d'augmentation de la température de + 3 °C dans notre endroit le plus frais en Argentine, certains modèles ont simulé que le rendement diminuerait jusqu'à 24 %, tandis que d'autres simulaient une augmentation du rendement allant jusqu'à 29 %. Dans notre emplacement le plus chaud au Brésil, les modèles ont simulé une réduction du rendement allant d'une diminution de 38 % sous + 3 °C à une augmentation de la température sans effet sur le rendement. De même, en augmentant le [CO2] de 360 à 540 ppm, les modèles ont simulé une augmentation du rendement allant de 6% à 31%. L'étalonnage du modèle n'a pas réduit la variabilité entre les modèles, mais a eu un effet inattendu sur la modification des réponses du rendement à la température pour certains des modèles. La forte incertitude dans les réponses des modèles indique l'applicabilité limitée des modèles individuels pour les projections alimentaires du changement climatique. Cependant, la moyenne d'ensemble des simulations à travers les modèles était un outil efficace pour réduire la forte incertitude dans les simulations de rendement du soja associées aux modèles individuels et à leur paramétrage. Les réponses du rendement moyen de l'ensemble à la température et au [CO2] étaient similaires à celles rapportées dans la littérature. Notre étude est la première démonstration des avantages obtenus en utilisant un ensemble de modèles de légumineuses à grains pour les projections alimentaires du changement climatique, et souligne qu'un développement plus poussé du modèle du soja avec des expériences sous des [CO2] et des températures élevées est nécessaire pour réduire l'incertitude des modèles individuels. Una estimación precisa del rendimiento de los cultivos en escenarios de cambio climático es esencial para cuantificar nuestra capacidad para alimentar a una población en crecimiento y desarrollar adaptaciones agronómicas para satisfacer la demanda futura de alimentos. Todavía falta una evaluación coordinada de las simulaciones de rendimiento a partir de modelos ecofisiológicos basados en procesos para la evaluación del impacto del cambio climático para la soja, la leguminosa de grano más cultivada y la principal fuente de proteínas en nuestra cadena alimentaria. En este primer estudio multimodelo de soja, utilizamos diez modelos prominentes capaces de simular el rendimiento de la soja a diferentes temperaturas y concentraciones de CO2 atmosférico [CO2] para cuantificar la incertidumbre en las simulaciones de rendimiento de soja en respuesta a estos factores. Los modelos se parametrizaron por primera vez con datos medidos de alta calidad de cinco entornos contrastantes. Encontramos una variabilidad considerable entre los modelos en las respuestas de rendimiento simuladas al aumento de la temperatura y [CO2]. Por ejemplo, bajo un aumento de temperatura de + 3 ° C en nuestra ubicación más fresca en Argentina, algunos modelos simularon que el rendimiento se reduciría hasta un 24%, mientras que otros simularon aumentos de rendimiento de hasta un 29%. En nuestra ubicación más cálida en Brasil, los modelos simularon una reducción del rendimiento que va desde una disminución del 38% con un aumento de temperatura de + 3 ° C hasta ningún efecto en el rendimiento. Del mismo modo, al aumentar [CO2] de 360 a 540 ppm, los modelos simularon un aumento del rendimiento que osciló entre el 6% y el 31%. La calibración del modelo no redujo la variabilidad entre los modelos, pero tuvo un efecto inesperado en la modificación de las respuestas de rendimiento a la temperatura para algunos de los modelos. La alta incertidumbre en las respuestas de los modelos indica la aplicabilidad limitada de los modelos individuales para las proyecciones alimentarias del cambio climático. Sin embargo, la media del conjunto de simulaciones entre modelos fue una herramienta efectiva para reducir la alta incertidumbre en las simulaciones de rendimiento de soja asociadas con modelos individuales y su parametrización. Las respuestas de rendimiento medio del conjunto a la temperatura y [CO2] fueron similares a las informadas en la literatura. Nuestro estudio es la primera demostración de los beneficios logrados al utilizar un conjunto de modelos de leguminosas de grano para las proyecciones de alimentos del cambio climático, y destaca que se necesita un mayor desarrollo del modelo de soja con experimentos bajo [CO2] y temperatura elevadas para reducir la incertidumbre de los modelos individuales. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. يعد التقدير الدقيق لمحصول المحاصيل في ظل سيناريوهات تغير المناخ أمرًا ضروريًا لتحديد قدرتنا على إطعام عدد متزايد من السكان وتطوير التكيفات الزراعية لتلبية الطلب على الغذاء في المستقبل. لا يزال التقييم المنسق لمحاكاة الغلة من النماذج الفسيولوجية البيئية القائمة على العمليات لتقييم تأثير تغير المناخ مفقودًا بالنسبة لفول الصويا، وهو بقول الحبوب الأكثر زراعة على نطاق واسع والمصدر الرئيسي للبروتين في سلسلتنا الغذائية. في هذه الدراسة الأولى متعددة النماذج لفول الصويا، استخدمنا عشرة نماذج بارزة قادرة على محاكاة محصول فول الصويا تحت درجات حرارة متفاوتة وتركيز ثاني أكسيد الكربون في الغلاف الجوي [CO2] لقياس عدم اليقين في محاكاة محصول فول الصويا استجابة لهذه العوامل. تم قياس النماذج أولاً ببيانات مقاسة عالية الجودة من خمس بيئات متباينة. وجدنا تباينًا كبيرًا بين النماذج في استجابات العائد المحاكاة لزيادة درجة الحرارة و [CO2]. على سبيل المثال، في ظل ارتفاع درجة الحرارة بمقدار + 3 درجات مئوية في أروع موقع لنا في الأرجنتين، قامت بعض النماذج بمحاكاة أن العائد سيقلل بنسبة تصل إلى 24 ٪، بينما يزيد العائد المحاكى الآخر بنسبة تصل إلى 29 ٪. في موقعنا الأكثر دفئًا في البرازيل، قامت النماذج بمحاكاة انخفاض العائد الذي يتراوح بين انخفاض بنسبة 38 ٪ تحت + ارتفاع درجة حرارة 3 درجات مئوية إلى عدم التأثير على العائد. وبالمثل، عند زيادة [ثاني أكسيد الكربون] من 360 إلى 540 جزء في المليون، قامت النماذج بمحاكاة زيادة العائد التي تراوحت من 6 ٪ إلى 31 ٪. لم تقلل معايرة النموذج من التباين عبر النماذج ولكن كان لها تأثير غير متوقع على تعديل استجابات الخضوع لدرجة الحرارة لبعض النماذج. يشير عدم اليقين الشديد في الاستجابات النموذجية إلى التطبيق المحدود للنماذج الفردية للتوقعات الغذائية لتغير المناخ. ومع ذلك، كان المتوسط الجماعي للمحاكاة عبر النماذج أداة فعالة للحد من عدم اليقين العالي في محاكاة غلة فول الصويا المرتبطة بالنماذج الفردية ومعلماتها. كانت استجابات متوسط العائد على درجة الحرارة و [CO2] متشابهة مع تلك الواردة في الأدبيات. دراستنا هي أول عرض توضيحي للفوائد التي تحققت من استخدام مجموعة من نماذج البقوليات لتوقعات تغير المناخ الغذائية، وتسلط الضوء على الحاجة إلى مزيد من تطوير نموذج فول الصويا مع التجارب تحت [CO2] ودرجة الحرارة المرتفعة لتقليل عدم اليقين من النماذج الفردية.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kritika Kothari; Rafael Battisti; Kenneth J. Boote; Sotirios Archontoulis; +24 Authors

    Une estimation précise du rendement des cultures dans les scénarios de changement climatique est essentielle pour quantifier notre capacité à nourrir une population croissante et à développer des adaptations agronomiques pour répondre à la demande alimentaire future. Une évaluation coordonnée des simulations de rendement à partir de modèles écophysiologiques basés sur les processus pour l'évaluation de l'impact du changement climatique fait toujours défaut pour le soja, la légumineuse à grains la plus cultivée et la principale source de protéines dans notre chaîne alimentaire. Dans cette première étude multimodèle sur le soja, nous avons utilisé dix modèles de premier plan capables de simuler le rendement du soja sous différentes températures et concentrations atmosphériques de CO2 [CO2] pour quantifier l'incertitude dans les simulations de rendement du soja en réponse à ces facteurs. Les modèles ont d'abord été paramétrés avec des données mesurées de haute qualité provenant de cinq environnements contrastés. Nous avons trouvé une variabilité considérable entre les modèles dans les réponses de rendement simulées à l'augmentation de la température et du [CO2]. Par exemple, en cas d'augmentation de la température de + 3 °C dans notre endroit le plus frais en Argentine, certains modèles ont simulé que le rendement diminuerait jusqu'à 24 %, tandis que d'autres simulaient une augmentation du rendement allant jusqu'à 29 %. Dans notre emplacement le plus chaud au Brésil, les modèles ont simulé une réduction du rendement allant d'une diminution de 38 % sous + 3 °C à une augmentation de la température sans effet sur le rendement. De même, en augmentant le [CO2] de 360 à 540 ppm, les modèles ont simulé une augmentation du rendement allant de 6% à 31%. L'étalonnage du modèle n'a pas réduit la variabilité entre les modèles, mais a eu un effet inattendu sur la modification des réponses du rendement à la température pour certains des modèles. La forte incertitude dans les réponses des modèles indique l'applicabilité limitée des modèles individuels pour les projections alimentaires du changement climatique. Cependant, la moyenne d'ensemble des simulations à travers les modèles était un outil efficace pour réduire la forte incertitude dans les simulations de rendement du soja associées aux modèles individuels et à leur paramétrage. Les réponses du rendement moyen de l'ensemble à la température et au [CO2] étaient similaires à celles rapportées dans la littérature. Notre étude est la première démonstration des avantages obtenus en utilisant un ensemble de modèles de légumineuses à grains pour les projections alimentaires du changement climatique, et souligne qu'un développement plus poussé du modèle du soja avec des expériences sous des [CO2] et des températures élevées est nécessaire pour réduire l'incertitude des modèles individuels. Una estimación precisa del rendimiento de los cultivos en escenarios de cambio climático es esencial para cuantificar nuestra capacidad para alimentar a una población en crecimiento y desarrollar adaptaciones agronómicas para satisfacer la demanda futura de alimentos. Todavía falta una evaluación coordinada de las simulaciones de rendimiento a partir de modelos ecofisiológicos basados en procesos para la evaluación del impacto del cambio climático para la soja, la leguminosa de grano más cultivada y la principal fuente de proteínas en nuestra cadena alimentaria. En este primer estudio multimodelo de soja, utilizamos diez modelos prominentes capaces de simular el rendimiento de la soja a diferentes temperaturas y concentraciones de CO2 atmosférico [CO2] para cuantificar la incertidumbre en las simulaciones de rendimiento de soja en respuesta a estos factores. Los modelos se parametrizaron por primera vez con datos medidos de alta calidad de cinco entornos contrastantes. Encontramos una variabilidad considerable entre los modelos en las respuestas de rendimiento simuladas al aumento de la temperatura y [CO2]. Por ejemplo, bajo un aumento de temperatura de + 3 ° C en nuestra ubicación más fresca en Argentina, algunos modelos simularon que el rendimiento se reduciría hasta un 24%, mientras que otros simularon aumentos de rendimiento de hasta un 29%. En nuestra ubicación más cálida en Brasil, los modelos simularon una reducción del rendimiento que va desde una disminución del 38% con un aumento de temperatura de + 3 ° C hasta ningún efecto en el rendimiento. Del mismo modo, al aumentar [CO2] de 360 a 540 ppm, los modelos simularon un aumento del rendimiento que osciló entre el 6% y el 31%. La calibración del modelo no redujo la variabilidad entre los modelos, pero tuvo un efecto inesperado en la modificación de las respuestas de rendimiento a la temperatura para algunos de los modelos. La alta incertidumbre en las respuestas de los modelos indica la aplicabilidad limitada de los modelos individuales para las proyecciones alimentarias del cambio climático. Sin embargo, la media del conjunto de simulaciones entre modelos fue una herramienta efectiva para reducir la alta incertidumbre en las simulaciones de rendimiento de soja asociadas con modelos individuales y su parametrización. Las respuestas de rendimiento medio del conjunto a la temperatura y [CO2] fueron similares a las informadas en la literatura. Nuestro estudio es la primera demostración de los beneficios logrados al utilizar un conjunto de modelos de leguminosas de grano para las proyecciones de alimentos del cambio climático, y destaca que se necesita un mayor desarrollo del modelo de soja con experimentos bajo [CO2] y temperatura elevadas para reducir la incertidumbre de los modelos individuales. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. يعد التقدير الدقيق لمحصول المحاصيل في ظل سيناريوهات تغير المناخ أمرًا ضروريًا لتحديد قدرتنا على إطعام عدد متزايد من السكان وتطوير التكيفات الزراعية لتلبية الطلب على الغذاء في المستقبل. لا يزال التقييم المنسق لمحاكاة الغلة من النماذج الفسيولوجية البيئية القائمة على العمليات لتقييم تأثير تغير المناخ مفقودًا بالنسبة لفول الصويا، وهو بقول الحبوب الأكثر زراعة على نطاق واسع والمصدر الرئيسي للبروتين في سلسلتنا الغذائية. في هذه الدراسة الأولى متعددة النماذج لفول الصويا، استخدمنا عشرة نماذج بارزة قادرة على محاكاة محصول فول الصويا تحت درجات حرارة متفاوتة وتركيز ثاني أكسيد الكربون في الغلاف الجوي [CO2] لقياس عدم اليقين في محاكاة محصول فول الصويا استجابة لهذه العوامل. تم قياس النماذج أولاً ببيانات مقاسة عالية الجودة من خمس بيئات متباينة. وجدنا تباينًا كبيرًا بين النماذج في استجابات العائد المحاكاة لزيادة درجة الحرارة و [CO2]. على سبيل المثال، في ظل ارتفاع درجة الحرارة بمقدار + 3 درجات مئوية في أروع موقع لنا في الأرجنتين، قامت بعض النماذج بمحاكاة أن العائد سيقلل بنسبة تصل إلى 24 ٪، بينما يزيد العائد المحاكى الآخر بنسبة تصل إلى 29 ٪. في موقعنا الأكثر دفئًا في البرازيل، قامت النماذج بمحاكاة انخفاض العائد الذي يتراوح بين انخفاض بنسبة 38 ٪ تحت + ارتفاع درجة حرارة 3 درجات مئوية إلى عدم التأثير على العائد. وبالمثل، عند زيادة [ثاني أكسيد الكربون] من 360 إلى 540 جزء في المليون، قامت النماذج بمحاكاة زيادة العائد التي تراوحت من 6 ٪ إلى 31 ٪. لم تقلل معايرة النموذج من التباين عبر النماذج ولكن كان لها تأثير غير متوقع على تعديل استجابات الخضوع لدرجة الحرارة لبعض النماذج. يشير عدم اليقين الشديد في الاستجابات النموذجية إلى التطبيق المحدود للنماذج الفردية للتوقعات الغذائية لتغير المناخ. ومع ذلك، كان المتوسط الجماعي للمحاكاة عبر النماذج أداة فعالة للحد من عدم اليقين العالي في محاكاة غلة فول الصويا المرتبطة بالنماذج الفردية ومعلماتها. كانت استجابات متوسط العائد على درجة الحرارة و [CO2] متشابهة مع تلك الواردة في الأدبيات. دراستنا هي أول عرض توضيحي للفوائد التي تحققت من استخدام مجموعة من نماذج البقوليات لتوقعات تغير المناخ الغذائية، وتسلط الضوء على الحاجة إلى مزيد من تطوير نموذج فول الصويا مع التجارب تحت [CO2] ودرجة الحرارة المرتفعة لتقليل عدم اليقين من النماذج الفردية.

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      European Journal of Agronomy
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      https://dx.doi.org/10.60692/sw...
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    Authors: Tribouillois, Hélène; Constantin, Julie; Justes, Eric;

    AbstractCover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO2e ha−1 year−1 in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N2O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO2e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    Hyper Article en Ligne
    Article . 2018
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Agritrop
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Global Change Biology
    Article . 2018 . Peer-reviewed
    License: Wiley Online Library User Agreement
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    HAL INRAE
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Global Change Biology
      Article . 2018 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Tribouillois, Hélène; Constantin, Julie; Justes, Eric;

    AbstractCover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO2e ha−1 year−1 in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N2O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO2e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Agritrop
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Global Change Biology
    Article . 2018 . Peer-reviewed
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2018
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Global Change Biology
      Article . 2018 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2018
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; +30 Authors

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    PLoS ONE
    Article . 2016 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      PLoS ONE
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    Authors: Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; +30 Authors

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

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    PLoS ONE
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      PLoS ONE
      Article . 2016 . Peer-reviewed
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      PLoS ONE
      Article . 2016
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      IRIS Cnr
      Article . 2016
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Martin, Guillaume; Allain, Sandrine; Bergez, Jacques-Eric; Burger-Leenhardt, Delphine; +10 Authors

    Stakeholders from academic, political or social spheres encourage the development of more sustainable forms of agriculture. Considering the scale and scope of the sustainability transition, it is challenging to the agricultural sector at large. The main question is how to support the transition process? In this communication, we expose how wicked problems related to the sustainability transition of farming systems can be addressed by agricultural science to better understand and support transition processes. We elaborate on the potential for articulation of three research approaches: comprehensive analysis, co-design and simulation modelling that refer to different stances and methodological choices. Comprehensive analysis of the sustainability transition of farming systems provides historical or snapshot perspectives on agricultural and institutional contexts and on the interplay between on one hand, the resources, their management and related performances of farming systems and on the other hand technical, economic and sociocultural dimensions of change. Co-design of the sustainability transition of farming systems stimulates local-scale experiments of transitions in the real world and the identification of alternatives for change from the farming system level to the territorial level. Simulation modelling consists of explorations of scenarios of management at different levels and assessment of their impacts. It offers a future-oriented perspective on transitions. We illustrate this potential for articulation of research approaches by taking the case of two examples of research conducted in our multidisciplinary research group applying to agricultural water management and autonomy in crop-livestock systems. The resulting conceptual framework is the first proposed to organize research to better understand and support sustainability transitions in the agricultural sector.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    ProdInra
    Conference object . 2018
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    HAL INRAE
    Conference object . 2018
    Data sources: HAL INRAE
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Conference object . 2018
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Martin, Guillaume; Allain, Sandrine; Bergez, Jacques-Eric; Burger-Leenhardt, Delphine; +10 Authors

    Stakeholders from academic, political or social spheres encourage the development of more sustainable forms of agriculture. Considering the scale and scope of the sustainability transition, it is challenging to the agricultural sector at large. The main question is how to support the transition process? In this communication, we expose how wicked problems related to the sustainability transition of farming systems can be addressed by agricultural science to better understand and support transition processes. We elaborate on the potential for articulation of three research approaches: comprehensive analysis, co-design and simulation modelling that refer to different stances and methodological choices. Comprehensive analysis of the sustainability transition of farming systems provides historical or snapshot perspectives on agricultural and institutional contexts and on the interplay between on one hand, the resources, their management and related performances of farming systems and on the other hand technical, economic and sociocultural dimensions of change. Co-design of the sustainability transition of farming systems stimulates local-scale experiments of transitions in the real world and the identification of alternatives for change from the farming system level to the territorial level. Simulation modelling consists of explorations of scenarios of management at different levels and assessment of their impacts. It offers a future-oriented perspective on transitions. We illustrate this potential for articulation of research approaches by taking the case of two examples of research conducted in our multidisciplinary research group applying to agricultural water management and autonomy in crop-livestock systems. The resulting conceptual framework is the first proposed to organize research to better understand and support sustainability transitions in the agricultural sector.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ProdInra
    Conference object . 2018
    License: CC BY SA
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    Conference object . 2018
    Data sources: HAL INRAE
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      ProdInra
      Conference object . 2018
      License: CC BY SA
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      Conference object . 2018
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Debaeke, Philippe; Abella, Mathieu; Constantin, Julie; Ferrand, Nicolas; +11 Authors

    La pratique d'une deuxième culture dans l’année, soit à la suite d’une récolte en début d’été (culture dérobée), soit par semis dans la culture primaire (culture en relais), permet une production supplémentaire, qu’elle soit destinée à l’alimentation animale ou humaine ou à vocation énergétique. Cette pratique de double culture peut générer un revenu supplémentaire tout en fournissant des services de soutien et de régulation. En tant que telle, elle peut être considérée comme une forme d'agriculture écologiquement intensive, mais aussi comme une opportunité offerte par le changement climatique. Le processus de prise de décision aboutissant à la double culture repose sur de nombreux facteurs liés aux conditions pédoclimatiques, mais aussi à l’espérance de gain et à la perception du risque. Le projet CASDAR "3C2A : Trois cultures en deux ans" (2019-2023) qui a regroupé 15 partenaires (agriculteurs, conseillers de chambres d’agriculture, ingénieurs d’instituts techniques, chercheurs) s'est efforcé de créer des références utiles pour la double culture dans le Sud-Ouest de la France, englobant les régions Nouvelle-Aquitaine et Occitanie. Cet article vise à illustrer l'intérêt potentiel du soja et du tournesol en tant que doubles cultures dans le Sud-Ouest de la France par une analyse qualitative des perceptions des agriculteurs sur les risques et les opportunités de cette pratique, complétée par une évaluation sur 4 ans des performances agronomiques et économiques de la double culture chez les agriculteurs (130 parcelles) ainsi qu’en station expérimentale où des gammes variétales ont été comparées pendant 3 ans. Avec l’appui de la simulation agronomique (SPA1 , STICS2 ), il a été possible d’évaluer la robustesse des conclusions (faisabilité, productivité) sur des séquences climatiques plus longues, pour des pédoclimats et des conduites culturales non expérimentées, et pour des scénarios de changement climatique, mais aussi d’apprécier les impacts environnementaux (besoins en eau, drainage, lixiviation du nitrate) des cultures dérobées dans le Sud-Ouest. Growing a second crop in a year, either following an early summer harvest (catch crop) or by sowing into the previous autumn-sown crop (relay crop), enables additional production, whether for feed, food or energy purposes. This practice of double cropping can generate additional income while providing support and regulation services. As such, it can be seen as an ecologically intensive form of agriculture, but also as an opportunity offered by climate change. The decision-making process leading to double cropping is based on a number of factors linked to soil and climatic conditions, but also to the expectation of gain and the perception of risk. The CASDAR project "3C2A: Three crops in two years" (2019-2023), which gathered 15 partners (farmers, advisors from chambers of agriculture, engineers from technical institutes, researchers), was set up to create useful references for double cropping in south-western France, encompassing the regions of Nouvelle-Aquitaine and Occitanie. The aim of this article is to illustrate the potential interest of soybean and sunflower as second crops in south-western France by means of a qualitative analysis of farmers' perceptions of the risks and opportunities of this practice, enriched by a 4- year on-farm assessment of the agronomic and economic performances of double cropping (130 fields) and at the experimental station, where a range of varieties were compared over a 3-year period. With the support of agronomic simulation (SPA1 , STICS2 ), it was possible to assess the robustness of the conclusions (feasibility, productivity) over longer climatic sequences, for unexperimented soils, climates and cropping practices, and for climate change scenarios. It was also possible to assess the environmental impacts (water requirements, drainage, nitrate leaching) of catch crops in the South-West.

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    Authors: Debaeke, Philippe; Abella, Mathieu; Constantin, Julie; Ferrand, Nicolas; +11 Authors

    La pratique d'une deuxième culture dans l’année, soit à la suite d’une récolte en début d’été (culture dérobée), soit par semis dans la culture primaire (culture en relais), permet une production supplémentaire, qu’elle soit destinée à l’alimentation animale ou humaine ou à vocation énergétique. Cette pratique de double culture peut générer un revenu supplémentaire tout en fournissant des services de soutien et de régulation. En tant que telle, elle peut être considérée comme une forme d'agriculture écologiquement intensive, mais aussi comme une opportunité offerte par le changement climatique. Le processus de prise de décision aboutissant à la double culture repose sur de nombreux facteurs liés aux conditions pédoclimatiques, mais aussi à l’espérance de gain et à la perception du risque. Le projet CASDAR "3C2A : Trois cultures en deux ans" (2019-2023) qui a regroupé 15 partenaires (agriculteurs, conseillers de chambres d’agriculture, ingénieurs d’instituts techniques, chercheurs) s'est efforcé de créer des références utiles pour la double culture dans le Sud-Ouest de la France, englobant les régions Nouvelle-Aquitaine et Occitanie. Cet article vise à illustrer l'intérêt potentiel du soja et du tournesol en tant que doubles cultures dans le Sud-Ouest de la France par une analyse qualitative des perceptions des agriculteurs sur les risques et les opportunités de cette pratique, complétée par une évaluation sur 4 ans des performances agronomiques et économiques de la double culture chez les agriculteurs (130 parcelles) ainsi qu’en station expérimentale où des gammes variétales ont été comparées pendant 3 ans. Avec l’appui de la simulation agronomique (SPA1 , STICS2 ), il a été possible d’évaluer la robustesse des conclusions (faisabilité, productivité) sur des séquences climatiques plus longues, pour des pédoclimats et des conduites culturales non expérimentées, et pour des scénarios de changement climatique, mais aussi d’apprécier les impacts environnementaux (besoins en eau, drainage, lixiviation du nitrate) des cultures dérobées dans le Sud-Ouest. Growing a second crop in a year, either following an early summer harvest (catch crop) or by sowing into the previous autumn-sown crop (relay crop), enables additional production, whether for feed, food or energy purposes. This practice of double cropping can generate additional income while providing support and regulation services. As such, it can be seen as an ecologically intensive form of agriculture, but also as an opportunity offered by climate change. The decision-making process leading to double cropping is based on a number of factors linked to soil and climatic conditions, but also to the expectation of gain and the perception of risk. The CASDAR project "3C2A: Three crops in two years" (2019-2023), which gathered 15 partners (farmers, advisors from chambers of agriculture, engineers from technical institutes, researchers), was set up to create useful references for double cropping in south-western France, encompassing the regions of Nouvelle-Aquitaine and Occitanie. The aim of this article is to illustrate the potential interest of soybean and sunflower as second crops in south-western France by means of a qualitative analysis of farmers' perceptions of the risks and opportunities of this practice, enriched by a 4- year on-farm assessment of the agronomic and economic performances of double cropping (130 fields) and at the experimental station, where a range of varieties were compared over a 3-year period. With the support of agronomic simulation (SPA1 , STICS2 ), it was possible to assess the robustness of the conclusions (feasibility, productivity) over longer climatic sequences, for unexperimented soils, climates and cropping practices, and for climate change scenarios. It was also possible to assess the environmental impacts (water requirements, drainage, nitrate leaching) of catch crops in the South-West.

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    Authors: Levavasseur, Florent; Kouakou, Patrice; Constantin, Julie; Cresson, Romain; +7 Authors

    AbstractEnergy cover crops for biogas production through anaerobic digestion (AD) are inserted between two primary crops. They replace either bare soil or nonharvested cover crops, and their management is usually intensified to produce more biomass. They allow the production of renewable energy as well as digestate, used as an organic fertilizer, without directly competing with food production. Because of the increased biomass production and export and of the return of a digested biomass to the soil, the impact of energy cover crops on soil organic carbon (SOC) is questioned. The objective of this paper was to study the difference in SOC stocks induced by the introduction of energy cover crops for AD coupled with the application of the resulting amount of digestate. We used the AD model Sys‐Metha combined with the soil C model AMG to simulate SOC stocks for 13 case studies in France, with scenarios comparing different intercrop management practices, with or without cover crops, harvested or not. Our results indicated that the higher biomass production of energy cover crops (from 6.7 to 11.1 t DM ha−1) in comparison with nonharvested cover crops (2 t DM ha−1) or bare soil led to higher humified C input (belowground input and digestate), despite the high C fraction exported in AD. This resulted in an increase in SOC stocks in comparison with nonharvested cover crops or bare soil (from 0.01 to 0.12 t C ha−1 year−1 over 30 years). The uncertainties in the model parameters did not modify these results. However, in the case of equal biomass production between energy cover crops and nonharvested cover crops, SOC stocks would be lower with energy cover crops.

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    Authors: Levavasseur, Florent; Kouakou, Patrice; Constantin, Julie; Cresson, Romain; +7 Authors

    AbstractEnergy cover crops for biogas production through anaerobic digestion (AD) are inserted between two primary crops. They replace either bare soil or nonharvested cover crops, and their management is usually intensified to produce more biomass. They allow the production of renewable energy as well as digestate, used as an organic fertilizer, without directly competing with food production. Because of the increased biomass production and export and of the return of a digested biomass to the soil, the impact of energy cover crops on soil organic carbon (SOC) is questioned. The objective of this paper was to study the difference in SOC stocks induced by the introduction of energy cover crops for AD coupled with the application of the resulting amount of digestate. We used the AD model Sys‐Metha combined with the soil C model AMG to simulate SOC stocks for 13 case studies in France, with scenarios comparing different intercrop management practices, with or without cover crops, harvested or not. Our results indicated that the higher biomass production of energy cover crops (from 6.7 to 11.1 t DM ha−1) in comparison with nonharvested cover crops (2 t DM ha−1) or bare soil led to higher humified C input (belowground input and digestate), despite the high C fraction exported in AD. This resulted in an increase in SOC stocks in comparison with nonharvested cover crops or bare soil (from 0.01 to 0.12 t C ha−1 year−1 over 30 years). The uncertainties in the model parameters did not modify these results. However, in the case of equal biomass production between energy cover crops and nonharvested cover crops, SOC stocks would be lower with energy cover crops.

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    GCB Bioenergy
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    Authors: Bamière, Laure; Bellassen, Valentin; Angers, D.; Cardinael, R.; +17 Authors

    Suite aux accords de Paris en 2015, l'Union européenne (UE) s'est fixé un objectif de neutralité carbone d'ici à 2050, tout comme la France. En plus de réduire les émissions de GES, le secteur agricole français peut contribuer à la neutralité carbone en tant que puits de carbone, par le stockage de carbone dans le sol et la biomasse. L'objectif de cette étude est de quantifier le potentiel de stockage additionnel et le coût d'un ensemble de huit pratiques stockantes. Les impacts de ces pratiques agricoles sur le stockage du carbone organique du sol et les rendements des cultures sont évalués à une échelle spatiale très fine, à l'aide de modèles de cultures et de prairies. L'assiette, le bilan GES net et le coût de mise en œuvre associés à chaque pratique sont également évalués et agrégés au niveau régional. Le modèle économique BANCO utilise ces informations pour générer la courbe de coût marginal d'abattement pour la France, et identifier la combinaison de pratiques stockantes qui minimise le coût total pour atteindre un objectif national donné d'atténuation des émissions de GES nettes. Nous montrons qu'une quantité non négligeable de carbone, de 36,2 à 52,9 MtCO2e an-1, peut être stockée dans le sol et la biomasse pour des prix du carbone raisonnables de 55 et 250 € tCO2e-1, respectivement (correspondant à la "valeur de l'action pour le climat" actuelle et 2030, fixée par le gouvernement français), et cela principalement par le développement de l'agroforesterie et des haies, la généralisation des cultures intermédiaires, l'introduction ou l'extension des prairies temporaires dans les séquences de culture. Ce résultat remet en cause l'objectif 3 à 5 fois inférieur retenu pour le puits de carbone agricole (10 MtCO2e.an-1) par la stratégie nationale bas carbone. Globalement, ce stockage additionnel de carbone permettrait de réduire les émissions totales de GES de la France de 9,2 à 13,8 %, respectivement (année de référence 2019). Following the Paris agreement in 2015, the European Union (EU) set a carbon neutrality objective by 2050, and so did France. The French agricultural sector can contribute as a carbon sink through carbon storage in biomass and soil, in addition to reducing GHG emissions. The objective of this study is to quantitatively assess the additional storage potential and cost of a set of eight carbon-storing practices. The impacts of these agricultural practices on soil organic carbon storage and crop production are assessed at a very fine spatial scale, using crop and grassland models. The associated area base, GHG budget, and implementation costs are assessed and aggregated at the region level. The economic model BANCO uses this information to derive the marginal abatement cost curve for France and identify the combination of carbon storing practices that minimizes the total cost of achieving a given national net GHG mitigation target. We find that a substantial amount of carbon, 36.2 to 52.9 MtCO2e yr-1, can be stored in soil and biomass for reasonable carbon prices of 55 and 250 € tCO2e-1, respectively (corresponding to current and 2030 French carbon value for climate action), mainly by developing agroforestry and hedges, generalising cover crops, and introducing or extending temporary grasslands in crop sequences. This finding questions the 3-5 times lower target of 10 MtCO2e.yr-1 retained for the agricultural carbon sink by the French climate neutrality strategy. Overall, this would decrease total French GHG emissions by 9.2 to 13.8%, respectively (reference year 2019).

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    Journal of Cleaner Production
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    Authors: Bamière, Laure; Bellassen, Valentin; Angers, D.; Cardinael, R.; +17 Authors

    Suite aux accords de Paris en 2015, l'Union européenne (UE) s'est fixé un objectif de neutralité carbone d'ici à 2050, tout comme la France. En plus de réduire les émissions de GES, le secteur agricole français peut contribuer à la neutralité carbone en tant que puits de carbone, par le stockage de carbone dans le sol et la biomasse. L'objectif de cette étude est de quantifier le potentiel de stockage additionnel et le coût d'un ensemble de huit pratiques stockantes. Les impacts de ces pratiques agricoles sur le stockage du carbone organique du sol et les rendements des cultures sont évalués à une échelle spatiale très fine, à l'aide de modèles de cultures et de prairies. L'assiette, le bilan GES net et le coût de mise en œuvre associés à chaque pratique sont également évalués et agrégés au niveau régional. Le modèle économique BANCO utilise ces informations pour générer la courbe de coût marginal d'abattement pour la France, et identifier la combinaison de pratiques stockantes qui minimise le coût total pour atteindre un objectif national donné d'atténuation des émissions de GES nettes. Nous montrons qu'une quantité non négligeable de carbone, de 36,2 à 52,9 MtCO2e an-1, peut être stockée dans le sol et la biomasse pour des prix du carbone raisonnables de 55 et 250 € tCO2e-1, respectivement (correspondant à la "valeur de l'action pour le climat" actuelle et 2030, fixée par le gouvernement français), et cela principalement par le développement de l'agroforesterie et des haies, la généralisation des cultures intermédiaires, l'introduction ou l'extension des prairies temporaires dans les séquences de culture. Ce résultat remet en cause l'objectif 3 à 5 fois inférieur retenu pour le puits de carbone agricole (10 MtCO2e.an-1) par la stratégie nationale bas carbone. Globalement, ce stockage additionnel de carbone permettrait de réduire les émissions totales de GES de la France de 9,2 à 13,8 %, respectivement (année de référence 2019). Following the Paris agreement in 2015, the European Union (EU) set a carbon neutrality objective by 2050, and so did France. The French agricultural sector can contribute as a carbon sink through carbon storage in biomass and soil, in addition to reducing GHG emissions. The objective of this study is to quantitatively assess the additional storage potential and cost of a set of eight carbon-storing practices. The impacts of these agricultural practices on soil organic carbon storage and crop production are assessed at a very fine spatial scale, using crop and grassland models. The associated area base, GHG budget, and implementation costs are assessed and aggregated at the region level. The economic model BANCO uses this information to derive the marginal abatement cost curve for France and identify the combination of carbon storing practices that minimizes the total cost of achieving a given national net GHG mitigation target. We find that a substantial amount of carbon, 36.2 to 52.9 MtCO2e yr-1, can be stored in soil and biomass for reasonable carbon prices of 55 and 250 € tCO2e-1, respectively (corresponding to current and 2030 French carbon value for climate action), mainly by developing agroforestry and hedges, generalising cover crops, and introducing or extending temporary grasslands in crop sequences. This finding questions the 3-5 times lower target of 10 MtCO2e.yr-1 retained for the agricultural carbon sink by the French climate neutrality strategy. Overall, this would decrease total French GHG emissions by 9.2 to 13.8%, respectively (reference year 2019).

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    Authors: Launay, Camille; Houot, Sabine; Jean-Baptiste, Vincent; Raynal, Helene; +1 Authors

    Cover crops could be considered either as multi-services crops (MSCC) (Justes at al, 2017) that are included in rotation for different agronomical purposes (N leaching limitations, storage of Carbon …)or as raw materials used to produce biogas in fermenter by an anaerobic digestion process (AD)). In this latter case, we considered them as energy cover crop (ECC). Some European countries areexploring the idea of replacing dedicated crops with ECC for biogas production, accompanied with specific regulation measures in order to avoid competition with food crops for land use and tosustain crop services such as limitation of N leaching. In France, some studies (ADEME 2018B, 2021) gave an estimation of 18 and 23 Mt covering 11 to 30% of our gas needs by 2050 but based on simpleassumptions and coarse calculations. We present here the methodology and the results of the chapter 5 of C. Launay‘s phD (Launay 2023) about the estimation of the potential production of ECCat France scale and the impacts on food production and on environment. One of the originality of this work has consisted in the design of a modelling chain combining different models in order to represent the different processes from field to energy production. Then, we applied it at France scale.

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    Authors: Launay, Camille; Houot, Sabine; Jean-Baptiste, Vincent; Raynal, Helene; +1 Authors

    Cover crops could be considered either as multi-services crops (MSCC) (Justes at al, 2017) that are included in rotation for different agronomical purposes (N leaching limitations, storage of Carbon …)or as raw materials used to produce biogas in fermenter by an anaerobic digestion process (AD)). In this latter case, we considered them as energy cover crop (ECC). Some European countries areexploring the idea of replacing dedicated crops with ECC for biogas production, accompanied with specific regulation measures in order to avoid competition with food crops for land use and tosustain crop services such as limitation of N leaching. In France, some studies (ADEME 2018B, 2021) gave an estimation of 18 and 23 Mt covering 11 to 30% of our gas needs by 2050 but based on simpleassumptions and coarse calculations. We present here the methodology and the results of the chapter 5 of C. Launay‘s phD (Launay 2023) about the estimation of the potential production of ECCat France scale and the impacts on food production and on environment. One of the originality of this work has consisted in the design of a modelling chain combining different models in order to represent the different processes from field to energy production. Then, we applied it at France scale.

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    Authors: Constantin, Julie; Beaudoin, Nicolas; Launay, Marie; Duval, Jérôme; +1 Authors

    Abstract The long term effects of repeated catch crops on N dynamics in arable farming were assessed using mid-term experiments and long-term simulations. The soil-crop model STICS (v6.9) was tested against a database provided by three experiments (13–17 years) carried out in Northern France, including treatments with or without repeated catch crops. STICS performance was checked for crop biomass, N uptake, soil water content and mineral N at harvest of main crops, drained water, N leaching and mineralization rates. The model satisfactorily reproduced these variables, except for soil mineral N and N leached at one site. N leached was predicted with a slight bias, between −3 and +7 kg N ha−1 yr−1, and soil N mineralized was simulated with a bias lower than 7 kg N ha−1 yr−1. The model simulated correctly the N uptake by catch crops and the kinetics of extra N mineralization due to catch crops. Seven scenarios varying in the presence of catch crops, fertilization rate and climate were simulated on long-term (60 years); their effects on N uptake, soil N storage, N mineralization and nitrate leaching were compared by difference with a control scenario. Repeated catch crops lead to reduce N leaching, sequester organic N and increase N mineralization. The model indicated that the sequestered N reached a maximum of 430–750 kg N ha−1 after 23–45 years depending on site. The extra-mineralization due to catch crops progressively increased up to 38–65 kg N ha−1 yr−1. A strategy of constant N fertilizer rate resulted in raising the N uptake of main crops and slowing down the abatement of nitrate leaching. Conversely, when N fertilization rates were reduced by 20–24 kg N ha−1 yr−1, crop production remained stable and catch crops reduced N leaching on the long term by 33–55%. Therefore catch crop is a promising technique for controlling the N cascade.

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    Authors: Constantin, Julie; Beaudoin, Nicolas; Launay, Marie; Duval, Jérôme; +1 Authors

    Abstract The long term effects of repeated catch crops on N dynamics in arable farming were assessed using mid-term experiments and long-term simulations. The soil-crop model STICS (v6.9) was tested against a database provided by three experiments (13–17 years) carried out in Northern France, including treatments with or without repeated catch crops. STICS performance was checked for crop biomass, N uptake, soil water content and mineral N at harvest of main crops, drained water, N leaching and mineralization rates. The model satisfactorily reproduced these variables, except for soil mineral N and N leached at one site. N leached was predicted with a slight bias, between −3 and +7 kg N ha−1 yr−1, and soil N mineralized was simulated with a bias lower than 7 kg N ha−1 yr−1. The model simulated correctly the N uptake by catch crops and the kinetics of extra N mineralization due to catch crops. Seven scenarios varying in the presence of catch crops, fertilization rate and climate were simulated on long-term (60 years); their effects on N uptake, soil N storage, N mineralization and nitrate leaching were compared by difference with a control scenario. Repeated catch crops lead to reduce N leaching, sequester organic N and increase N mineralization. The model indicated that the sequestered N reached a maximum of 430–750 kg N ha−1 after 23–45 years depending on site. The extra-mineralization due to catch crops progressively increased up to 38–65 kg N ha−1 yr−1. A strategy of constant N fertilizer rate resulted in raising the N uptake of main crops and slowing down the abatement of nitrate leaching. Conversely, when N fertilization rates were reduced by 20–24 kg N ha−1 yr−1, crop production remained stable and catch crops reduced N leaching on the long term by 33–55%. Therefore catch crop is a promising technique for controlling the N cascade.

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      Agriculture Ecosystems & Environment
      Article . 2012 . Peer-reviewed
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    Authors: Constantin, Julie; Minette, Sébastien; Vericel, Gregory; Jordan-Meille, Lionel; +1 Authors

    Abstract Background and aims Cover crops can efficiently increase nitrogen (N) recycling in agroecosystems. By providing a green-manure effect for the next crop, they allow reduced mineral fertilisation. We developed a decision-support tool, called MERCI, to predict N available from cover crop residues over time, from a single measurement of fresh shoot biomass. Methods We coupled a large experimental database from France with a simulation experiment using the soil-crop model STICS. More than 25 000 measurements of 74 species of cover crops as a sole crop or bispecific mixtures were collected. Linear regression models, at the species, family or entire-database level depending on the data available, were built to predict dry biomass, N amount and C:N ratio. Dynamics of N mineralized and leaching from cover crop residues were predicted at 24 contrasting sites as a function of the biomass, carbon (C):N ratio and termination date. Results Correlations between fresh biomass, dry biomass and N amounts in experimental data were strong (r = 0.80-0.96), and predicted N amounts in fresh shoot biomass were relatively accurate. Percentages of N mineralized and leached simulated by STICS were explained mainly by the C:N ratio, site and number of months after termination, but to different degrees. Conclusion MERCI is an easy and robust decision-support tool for predicting N release in the field, and could thus be adopted by advisors and farmers to improve management of nutrient recycling in temperate arable cropping systems.

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    Plant and Soil
    Article . 2023 . Peer-reviewed
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    Agritrop
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      Plant and Soil
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    Authors: Constantin, Julie; Minette, Sébastien; Vericel, Gregory; Jordan-Meille, Lionel; +1 Authors

    Abstract Background and aims Cover crops can efficiently increase nitrogen (N) recycling in agroecosystems. By providing a green-manure effect for the next crop, they allow reduced mineral fertilisation. We developed a decision-support tool, called MERCI, to predict N available from cover crop residues over time, from a single measurement of fresh shoot biomass. Methods We coupled a large experimental database from France with a simulation experiment using the soil-crop model STICS. More than 25 000 measurements of 74 species of cover crops as a sole crop or bispecific mixtures were collected. Linear regression models, at the species, family or entire-database level depending on the data available, were built to predict dry biomass, N amount and C:N ratio. Dynamics of N mineralized and leaching from cover crop residues were predicted at 24 contrasting sites as a function of the biomass, carbon (C):N ratio and termination date. Results Correlations between fresh biomass, dry biomass and N amounts in experimental data were strong (r = 0.80-0.96), and predicted N amounts in fresh shoot biomass were relatively accurate. Percentages of N mineralized and leached simulated by STICS were explained mainly by the C:N ratio, site and number of months after termination, but to different degrees. Conclusion MERCI is an easy and robust decision-support tool for predicting N release in the field, and could thus be adopted by advisors and farmers to improve management of nutrient recycling in temperate arable cropping systems.

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    Plant and Soil
    Article . 2023 . Peer-reviewed
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      Plant and Soil
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    Authors: Kritika Kothari; Rafael Battisti; Kenneth J. Boote; Sotirios Archontoulis; +24 Authors

    Une estimation précise du rendement des cultures dans les scénarios de changement climatique est essentielle pour quantifier notre capacité à nourrir une population croissante et à développer des adaptations agronomiques pour répondre à la demande alimentaire future. Une évaluation coordonnée des simulations de rendement à partir de modèles écophysiologiques basés sur les processus pour l'évaluation de l'impact du changement climatique fait toujours défaut pour le soja, la légumineuse à grains la plus cultivée et la principale source de protéines dans notre chaîne alimentaire. Dans cette première étude multimodèle sur le soja, nous avons utilisé dix modèles de premier plan capables de simuler le rendement du soja sous différentes températures et concentrations atmosphériques de CO2 [CO2] pour quantifier l'incertitude dans les simulations de rendement du soja en réponse à ces facteurs. Les modèles ont d'abord été paramétrés avec des données mesurées de haute qualité provenant de cinq environnements contrastés. Nous avons trouvé une variabilité considérable entre les modèles dans les réponses de rendement simulées à l'augmentation de la température et du [CO2]. Par exemple, en cas d'augmentation de la température de + 3 °C dans notre endroit le plus frais en Argentine, certains modèles ont simulé que le rendement diminuerait jusqu'à 24 %, tandis que d'autres simulaient une augmentation du rendement allant jusqu'à 29 %. Dans notre emplacement le plus chaud au Brésil, les modèles ont simulé une réduction du rendement allant d'une diminution de 38 % sous + 3 °C à une augmentation de la température sans effet sur le rendement. De même, en augmentant le [CO2] de 360 à 540 ppm, les modèles ont simulé une augmentation du rendement allant de 6% à 31%. L'étalonnage du modèle n'a pas réduit la variabilité entre les modèles, mais a eu un effet inattendu sur la modification des réponses du rendement à la température pour certains des modèles. La forte incertitude dans les réponses des modèles indique l'applicabilité limitée des modèles individuels pour les projections alimentaires du changement climatique. Cependant, la moyenne d'ensemble des simulations à travers les modèles était un outil efficace pour réduire la forte incertitude dans les simulations de rendement du soja associées aux modèles individuels et à leur paramétrage. Les réponses du rendement moyen de l'ensemble à la température et au [CO2] étaient similaires à celles rapportées dans la littérature. Notre étude est la première démonstration des avantages obtenus en utilisant un ensemble de modèles de légumineuses à grains pour les projections alimentaires du changement climatique, et souligne qu'un développement plus poussé du modèle du soja avec des expériences sous des [CO2] et des températures élevées est nécessaire pour réduire l'incertitude des modèles individuels. Una estimación precisa del rendimiento de los cultivos en escenarios de cambio climático es esencial para cuantificar nuestra capacidad para alimentar a una población en crecimiento y desarrollar adaptaciones agronómicas para satisfacer la demanda futura de alimentos. Todavía falta una evaluación coordinada de las simulaciones de rendimiento a partir de modelos ecofisiológicos basados en procesos para la evaluación del impacto del cambio climático para la soja, la leguminosa de grano más cultivada y la principal fuente de proteínas en nuestra cadena alimentaria. En este primer estudio multimodelo de soja, utilizamos diez modelos prominentes capaces de simular el rendimiento de la soja a diferentes temperaturas y concentraciones de CO2 atmosférico [CO2] para cuantificar la incertidumbre en las simulaciones de rendimiento de soja en respuesta a estos factores. Los modelos se parametrizaron por primera vez con datos medidos de alta calidad de cinco entornos contrastantes. Encontramos una variabilidad considerable entre los modelos en las respuestas de rendimiento simuladas al aumento de la temperatura y [CO2]. Por ejemplo, bajo un aumento de temperatura de + 3 ° C en nuestra ubicación más fresca en Argentina, algunos modelos simularon que el rendimiento se reduciría hasta un 24%, mientras que otros simularon aumentos de rendimiento de hasta un 29%. En nuestra ubicación más cálida en Brasil, los modelos simularon una reducción del rendimiento que va desde una disminución del 38% con un aumento de temperatura de + 3 ° C hasta ningún efecto en el rendimiento. Del mismo modo, al aumentar [CO2] de 360 a 540 ppm, los modelos simularon un aumento del rendimiento que osciló entre el 6% y el 31%. La calibración del modelo no redujo la variabilidad entre los modelos, pero tuvo un efecto inesperado en la modificación de las respuestas de rendimiento a la temperatura para algunos de los modelos. La alta incertidumbre en las respuestas de los modelos indica la aplicabilidad limitada de los modelos individuales para las proyecciones alimentarias del cambio climático. Sin embargo, la media del conjunto de simulaciones entre modelos fue una herramienta efectiva para reducir la alta incertidumbre en las simulaciones de rendimiento de soja asociadas con modelos individuales y su parametrización. Las respuestas de rendimiento medio del conjunto a la temperatura y [CO2] fueron similares a las informadas en la literatura. Nuestro estudio es la primera demostración de los beneficios logrados al utilizar un conjunto de modelos de leguminosas de grano para las proyecciones de alimentos del cambio climático, y destaca que se necesita un mayor desarrollo del modelo de soja con experimentos bajo [CO2] y temperatura elevadas para reducir la incertidumbre de los modelos individuales. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. يعد التقدير الدقيق لمحصول المحاصيل في ظل سيناريوهات تغير المناخ أمرًا ضروريًا لتحديد قدرتنا على إطعام عدد متزايد من السكان وتطوير التكيفات الزراعية لتلبية الطلب على الغذاء في المستقبل. لا يزال التقييم المنسق لمحاكاة الغلة من النماذج الفسيولوجية البيئية القائمة على العمليات لتقييم تأثير تغير المناخ مفقودًا بالنسبة لفول الصويا، وهو بقول الحبوب الأكثر زراعة على نطاق واسع والمصدر الرئيسي للبروتين في سلسلتنا الغذائية. في هذه الدراسة الأولى متعددة النماذج لفول الصويا، استخدمنا عشرة نماذج بارزة قادرة على محاكاة محصول فول الصويا تحت درجات حرارة متفاوتة وتركيز ثاني أكسيد الكربون في الغلاف الجوي [CO2] لقياس عدم اليقين في محاكاة محصول فول الصويا استجابة لهذه العوامل. تم قياس النماذج أولاً ببيانات مقاسة عالية الجودة من خمس بيئات متباينة. وجدنا تباينًا كبيرًا بين النماذج في استجابات العائد المحاكاة لزيادة درجة الحرارة و [CO2]. على سبيل المثال، في ظل ارتفاع درجة الحرارة بمقدار + 3 درجات مئوية في أروع موقع لنا في الأرجنتين، قامت بعض النماذج بمحاكاة أن العائد سيقلل بنسبة تصل إلى 24 ٪، بينما يزيد العائد المحاكى الآخر بنسبة تصل إلى 29 ٪. في موقعنا الأكثر دفئًا في البرازيل، قامت النماذج بمحاكاة انخفاض العائد الذي يتراوح بين انخفاض بنسبة 38 ٪ تحت + ارتفاع درجة حرارة 3 درجات مئوية إلى عدم التأثير على العائد. وبالمثل، عند زيادة [ثاني أكسيد الكربون] من 360 إلى 540 جزء في المليون، قامت النماذج بمحاكاة زيادة العائد التي تراوحت من 6 ٪ إلى 31 ٪. لم تقلل معايرة النموذج من التباين عبر النماذج ولكن كان لها تأثير غير متوقع على تعديل استجابات الخضوع لدرجة الحرارة لبعض النماذج. يشير عدم اليقين الشديد في الاستجابات النموذجية إلى التطبيق المحدود للنماذج الفردية للتوقعات الغذائية لتغير المناخ. ومع ذلك، كان المتوسط الجماعي للمحاكاة عبر النماذج أداة فعالة للحد من عدم اليقين العالي في محاكاة غلة فول الصويا المرتبطة بالنماذج الفردية ومعلماتها. كانت استجابات متوسط العائد على درجة الحرارة و [CO2] متشابهة مع تلك الواردة في الأدبيات. دراستنا هي أول عرض توضيحي للفوائد التي تحققت من استخدام مجموعة من نماذج البقوليات لتوقعات تغير المناخ الغذائية، وتسلط الضوء على الحاجة إلى مزيد من تطوير نموذج فول الصويا مع التجارب تحت [CO2] ودرجة الحرارة المرتفعة لتقليل عدم اليقين من النماذج الفردية.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kritika Kothari; Rafael Battisti; Kenneth J. Boote; Sotirios Archontoulis; +24 Authors

    Une estimation précise du rendement des cultures dans les scénarios de changement climatique est essentielle pour quantifier notre capacité à nourrir une population croissante et à développer des adaptations agronomiques pour répondre à la demande alimentaire future. Une évaluation coordonnée des simulations de rendement à partir de modèles écophysiologiques basés sur les processus pour l'évaluation de l'impact du changement climatique fait toujours défaut pour le soja, la légumineuse à grains la plus cultivée et la principale source de protéines dans notre chaîne alimentaire. Dans cette première étude multimodèle sur le soja, nous avons utilisé dix modèles de premier plan capables de simuler le rendement du soja sous différentes températures et concentrations atmosphériques de CO2 [CO2] pour quantifier l'incertitude dans les simulations de rendement du soja en réponse à ces facteurs. Les modèles ont d'abord été paramétrés avec des données mesurées de haute qualité provenant de cinq environnements contrastés. Nous avons trouvé une variabilité considérable entre les modèles dans les réponses de rendement simulées à l'augmentation de la température et du [CO2]. Par exemple, en cas d'augmentation de la température de + 3 °C dans notre endroit le plus frais en Argentine, certains modèles ont simulé que le rendement diminuerait jusqu'à 24 %, tandis que d'autres simulaient une augmentation du rendement allant jusqu'à 29 %. Dans notre emplacement le plus chaud au Brésil, les modèles ont simulé une réduction du rendement allant d'une diminution de 38 % sous + 3 °C à une augmentation de la température sans effet sur le rendement. De même, en augmentant le [CO2] de 360 à 540 ppm, les modèles ont simulé une augmentation du rendement allant de 6% à 31%. L'étalonnage du modèle n'a pas réduit la variabilité entre les modèles, mais a eu un effet inattendu sur la modification des réponses du rendement à la température pour certains des modèles. La forte incertitude dans les réponses des modèles indique l'applicabilité limitée des modèles individuels pour les projections alimentaires du changement climatique. Cependant, la moyenne d'ensemble des simulations à travers les modèles était un outil efficace pour réduire la forte incertitude dans les simulations de rendement du soja associées aux modèles individuels et à leur paramétrage. Les réponses du rendement moyen de l'ensemble à la température et au [CO2] étaient similaires à celles rapportées dans la littérature. Notre étude est la première démonstration des avantages obtenus en utilisant un ensemble de modèles de légumineuses à grains pour les projections alimentaires du changement climatique, et souligne qu'un développement plus poussé du modèle du soja avec des expériences sous des [CO2] et des températures élevées est nécessaire pour réduire l'incertitude des modèles individuels. Una estimación precisa del rendimiento de los cultivos en escenarios de cambio climático es esencial para cuantificar nuestra capacidad para alimentar a una población en crecimiento y desarrollar adaptaciones agronómicas para satisfacer la demanda futura de alimentos. Todavía falta una evaluación coordinada de las simulaciones de rendimiento a partir de modelos ecofisiológicos basados en procesos para la evaluación del impacto del cambio climático para la soja, la leguminosa de grano más cultivada y la principal fuente de proteínas en nuestra cadena alimentaria. En este primer estudio multimodelo de soja, utilizamos diez modelos prominentes capaces de simular el rendimiento de la soja a diferentes temperaturas y concentraciones de CO2 atmosférico [CO2] para cuantificar la incertidumbre en las simulaciones de rendimiento de soja en respuesta a estos factores. Los modelos se parametrizaron por primera vez con datos medidos de alta calidad de cinco entornos contrastantes. Encontramos una variabilidad considerable entre los modelos en las respuestas de rendimiento simuladas al aumento de la temperatura y [CO2]. Por ejemplo, bajo un aumento de temperatura de + 3 ° C en nuestra ubicación más fresca en Argentina, algunos modelos simularon que el rendimiento se reduciría hasta un 24%, mientras que otros simularon aumentos de rendimiento de hasta un 29%. En nuestra ubicación más cálida en Brasil, los modelos simularon una reducción del rendimiento que va desde una disminución del 38% con un aumento de temperatura de + 3 ° C hasta ningún efecto en el rendimiento. Del mismo modo, al aumentar [CO2] de 360 a 540 ppm, los modelos simularon un aumento del rendimiento que osciló entre el 6% y el 31%. La calibración del modelo no redujo la variabilidad entre los modelos, pero tuvo un efecto inesperado en la modificación de las respuestas de rendimiento a la temperatura para algunos de los modelos. La alta incertidumbre en las respuestas de los modelos indica la aplicabilidad limitada de los modelos individuales para las proyecciones alimentarias del cambio climático. Sin embargo, la media del conjunto de simulaciones entre modelos fue una herramienta efectiva para reducir la alta incertidumbre en las simulaciones de rendimiento de soja asociadas con modelos individuales y su parametrización. Las respuestas de rendimiento medio del conjunto a la temperatura y [CO2] fueron similares a las informadas en la literatura. Nuestro estudio es la primera demostración de los beneficios logrados al utilizar un conjunto de modelos de leguminosas de grano para las proyecciones de alimentos del cambio climático, y destaca que se necesita un mayor desarrollo del modelo de soja con experimentos bajo [CO2] y temperatura elevadas para reducir la incertidumbre de los modelos individuales. An accurate estimation of crop yield under climate change scenarios is essential to quantify our ability to feed a growing population and develop agronomic adaptations to meet future food demand. A coordinated evaluation of yield simulations from process-based eco-physiological models for climate change impact assessment is still missing for soybean, the most widely grown grain legume and the main source of protein in our food chain. In this first soybean multi-model study, we used ten prominent models capable of simulating soybean yield under varying temperature and atmospheric CO2 concentration [CO2] to quantify the uncertainty in soybean yield simulations in response to these factors. Models were first parametrized with high quality measured data from five contrasting environments. We found considerable variability among models in simulated yield responses to increasing temperature and [CO2]. For example, under a + 3 °C temperature rise in our coolest location in Argentina, some models simulated that yield would reduce as much as 24%, while others simulated yield increases up to 29%. In our warmest location in Brazil, the models simulated a yield reduction ranging from a 38% decrease under + 3 °C temperature rise to no effect on yield. Similarly, when increasing [CO2] from 360 to 540 ppm, the models simulated a yield increase that ranged from 6% to 31%. Model calibration did not reduce variability across models but had an unexpected effect on modifying yield responses to temperature for some of the models. The high uncertainty in model responses indicates the limited applicability of individual models for climate change food projections. However, the ensemble mean of simulations across models was an effective tool to reduce the high uncertainty in soybean yield simulations associated with individual models and their parametrization. Ensemble mean yield responses to temperature and [CO2] were similar to those reported from the literature. Our study is the first demonstration of the benefits achieved from using an ensemble of grain legume models for climate change food projections, and highlights that further soybean model development with experiments under elevated [CO2] and temperature is needed to reduce the uncertainty from the individual models. يعد التقدير الدقيق لمحصول المحاصيل في ظل سيناريوهات تغير المناخ أمرًا ضروريًا لتحديد قدرتنا على إطعام عدد متزايد من السكان وتطوير التكيفات الزراعية لتلبية الطلب على الغذاء في المستقبل. لا يزال التقييم المنسق لمحاكاة الغلة من النماذج الفسيولوجية البيئية القائمة على العمليات لتقييم تأثير تغير المناخ مفقودًا بالنسبة لفول الصويا، وهو بقول الحبوب الأكثر زراعة على نطاق واسع والمصدر الرئيسي للبروتين في سلسلتنا الغذائية. في هذه الدراسة الأولى متعددة النماذج لفول الصويا، استخدمنا عشرة نماذج بارزة قادرة على محاكاة محصول فول الصويا تحت درجات حرارة متفاوتة وتركيز ثاني أكسيد الكربون في الغلاف الجوي [CO2] لقياس عدم اليقين في محاكاة محصول فول الصويا استجابة لهذه العوامل. تم قياس النماذج أولاً ببيانات مقاسة عالية الجودة من خمس بيئات متباينة. وجدنا تباينًا كبيرًا بين النماذج في استجابات العائد المحاكاة لزيادة درجة الحرارة و [CO2]. على سبيل المثال، في ظل ارتفاع درجة الحرارة بمقدار + 3 درجات مئوية في أروع موقع لنا في الأرجنتين، قامت بعض النماذج بمحاكاة أن العائد سيقلل بنسبة تصل إلى 24 ٪، بينما يزيد العائد المحاكى الآخر بنسبة تصل إلى 29 ٪. في موقعنا الأكثر دفئًا في البرازيل، قامت النماذج بمحاكاة انخفاض العائد الذي يتراوح بين انخفاض بنسبة 38 ٪ تحت + ارتفاع درجة حرارة 3 درجات مئوية إلى عدم التأثير على العائد. وبالمثل، عند زيادة [ثاني أكسيد الكربون] من 360 إلى 540 جزء في المليون، قامت النماذج بمحاكاة زيادة العائد التي تراوحت من 6 ٪ إلى 31 ٪. لم تقلل معايرة النموذج من التباين عبر النماذج ولكن كان لها تأثير غير متوقع على تعديل استجابات الخضوع لدرجة الحرارة لبعض النماذج. يشير عدم اليقين الشديد في الاستجابات النموذجية إلى التطبيق المحدود للنماذج الفردية للتوقعات الغذائية لتغير المناخ. ومع ذلك، كان المتوسط الجماعي للمحاكاة عبر النماذج أداة فعالة للحد من عدم اليقين العالي في محاكاة غلة فول الصويا المرتبطة بالنماذج الفردية ومعلماتها. كانت استجابات متوسط العائد على درجة الحرارة و [CO2] متشابهة مع تلك الواردة في الأدبيات. دراستنا هي أول عرض توضيحي للفوائد التي تحققت من استخدام مجموعة من نماذج البقوليات لتوقعات تغير المناخ الغذائية، وتسلط الضوء على الحاجة إلى مزيد من تطوير نموذج فول الصويا مع التجارب تحت [CO2] ودرجة الحرارة المرتفعة لتقليل عدم اليقين من النماذج الفردية.

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      European Journal of Agronomy
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      https://dx.doi.org/10.60692/sw...
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    Authors: Tribouillois, Hélène; Constantin, Julie; Justes, Eric;

    AbstractCover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO2e ha−1 year−1 in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N2O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO2e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    Hyper Article en Ligne
    Article . 2018
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Agritrop
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Global Change Biology
    Article . 2018 . Peer-reviewed
    License: Wiley Online Library User Agreement
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    HAL INRAE
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Global Change Biology
      Article . 2018 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Tribouillois, Hélène; Constantin, Julie; Justes, Eric;

    AbstractCover crops provide ecosystem services such as storing atmospheric carbon in soils after incorporation of their residues. Cover crops also influence soil water balance, which can be an issue in temperate climates with dry summers as for example in southern France and Europe. As a consequence, it is necessary to understand cover crops' long‐term influence on greenhouse gases (GHG) and water balances to assess their potential to mitigate climate change in arable cropping systems. We used the previously calibrated and validated soil–crop model STICS to simulate scenarios of cover crop introduction to assess their influence on rainfed and irrigated cropping systems and crop rotations distributed among five contrasted sites in southern France from 2007 to 2052. Our results showed that cover crops can improve mean direct GHG balance by 315 kg CO2e ha−1 year−1 in the long term compared to that of bare soil. This was due mainly to an increase in carbon storage in the soil despite a slight increase in N2O emissions which can be compensated by adapting fertilization. Cover crops also influence the water balance by reducing mean annual drainage by 20 mm/year but increasing mean annual evapotranspiration by 20 mm/year compared to those of bare soil. Using cover crops to improve the GHG balance may help to mitigate climate change by decreasing CO2e emitted in cropping systems which can represent a decrease from 4.5% to 9% of annual GHG emissions of the French agriculture and forestry sector. However, if not well managed, they also could create water management issues in watersheds with shallow groundwater. Relationships between cover crop biomass and its influence on several variables such as drainage, carbon sequestration, and GHG emissions could be used to extend our results to other conditions to assess the cover crops' influence in a wider range of areas.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Agritrop
    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Global Change Biology
    Article . 2018 . Peer-reviewed
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Article . 2018
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2018
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Global Change Biology
      Article . 2018 . Peer-reviewed
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      Article . 2018
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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    Authors: Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; +30 Authors

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    PLoS ONE
    Article . 2016 . Peer-reviewed
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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      PLoS ONE
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    Authors: Hoffmann, Holger; Zhao, Gang; Asseng, Senthold; Bindi, Marco; +30 Authors

    We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority. This may bias simulated yields at large scales, varying largely across models. Thus, we evaluated the error associated with spatially aggregated soil and climate data for 14 crop models. Yields of winter wheat and silage maize were simulated under water-limited production conditions. We calculated this error from crop yields simulated at spatial resolutions from 1 to 100 km for the state of North Rhine-Westphalia, Germany. Most models showed yields biased by <15% when aggregating only soil data. The relative mean absolute error (rMAE) of most models using aggregated soil data was in the range or larger than the inter-annual or inter-model variability in yields. This error increased further when both climate and soil data were aggregated. Distinct error patterns indicate that the rMAE may be estimated from few soil variables. Illustrating the range of these aggregation effects across models, this study is a first step towards an ex-ante assessment of aggregation errors in large-scale simulations.

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    PLoS ONE
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      PLoS ONE
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    Authors: Martin, Guillaume; Allain, Sandrine; Bergez, Jacques-Eric; Burger-Leenhardt, Delphine; +10 Authors

    Stakeholders from academic, political or social spheres encourage the development of more sustainable forms of agriculture. Considering the scale and scope of the sustainability transition, it is challenging to the agricultural sector at large. The main question is how to support the transition process? In this communication, we expose how wicked problems related to the sustainability transition of farming systems can be addressed by agricultural science to better understand and support transition processes. We elaborate on the potential for articulation of three research approaches: comprehensive analysis, co-design and simulation modelling that refer to different stances and methodological choices. Comprehensive analysis of the sustainability transition of farming systems provides historical or snapshot perspectives on agricultural and institutional contexts and on the interplay between on one hand, the resources, their management and related performances of farming systems and on the other hand technical, economic and sociocultural dimensions of change. Co-design of the sustainability transition of farming systems stimulates local-scale experiments of transitions in the real world and the identification of alternatives for change from the farming system level to the territorial level. Simulation modelling consists of explorations of scenarios of management at different levels and assessment of their impacts. It offers a future-oriented perspective on transitions. We illustrate this potential for articulation of research approaches by taking the case of two examples of research conducted in our multidisciplinary research group applying to agricultural water management and autonomy in crop-livestock systems. The resulting conceptual framework is the first proposed to organize research to better understand and support sustainability transitions in the agricultural sector.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Martin, Guillaume; Allain, Sandrine; Bergez, Jacques-Eric; Burger-Leenhardt, Delphine; +10 Authors

    Stakeholders from academic, political or social spheres encourage the development of more sustainable forms of agriculture. Considering the scale and scope of the sustainability transition, it is challenging to the agricultural sector at large. The main question is how to support the transition process? In this communication, we expose how wicked problems related to the sustainability transition of farming systems can be addressed by agricultural science to better understand and support transition processes. We elaborate on the potential for articulation of three research approaches: comprehensive analysis, co-design and simulation modelling that refer to different stances and methodological choices. Comprehensive analysis of the sustainability transition of farming systems provides historical or snapshot perspectives on agricultural and institutional contexts and on the interplay between on one hand, the resources, their management and related performances of farming systems and on the other hand technical, economic and sociocultural dimensions of change. Co-design of the sustainability transition of farming systems stimulates local-scale experiments of transitions in the real world and the identification of alternatives for change from the farming system level to the territorial level. Simulation modelling consists of explorations of scenarios of management at different levels and assessment of their impacts. It offers a future-oriented perspective on transitions. We illustrate this potential for articulation of research approaches by taking the case of two examples of research conducted in our multidisciplinary research group applying to agricultural water management and autonomy in crop-livestock systems. The resulting conceptual framework is the first proposed to organize research to better understand and support sustainability transitions in the agricultural sector.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ProdInra
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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