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1. The role of soil carbon sequestration in enhancing human resilience in tackling global crises including pandemics

Author: Cornelia Rumpel, Farshad Amiraslani, Deborah Bossio, Claire Chenu, Beverley Henry, Alejandro Fuentes Espinoza, Lydie-Stella Koutika, Jagdish Ladha, Beata Madari, Budiman Minasny, A.O. Olaleye, Yasuhito Shirato, Saidou Nourou Sall, Jean-François Soussana, and Consuelo Varela-Ortega
Subjects: Soil health, Human health, Covid, Socio-economy, Multi-stakeholder collaboration, Sustainability, Geology, QE1-996.5
Abstract: Soils have recently received attention in the policy area due to their various connections to climate change, human health and their key role in sustaining human societies in general. In this context, agricultural production and healthy nutritious food are linked to soil health and the diversity of their (micro-)biome, which depend on organic carbon materials as an energy and nutrient source. In this paper, we review the evidence showing that carbon-rich soils improve the resilience of human societies to pandemics and other crises. We indicate pathways for how the loss of soil carbon due to farming could be reversed by transformations within our food systems. Moreover, we argue that soil carbon has a strong role to play in enhancing environmental and human health in addition to mitigating and adapting to climate change. This multifaceted role requires a transdisciplinary dialogue and multi-stakeholder collaboration.
Published: 2022
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2. Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance

Author: Jinfeng Chang, Philippe Ciais, Nicolas Viovy, Jean-François Soussana, Katja Klumpp, and Benjamin Sultan
Subjects: European grassland, Grassland management, Phenology, Warming levels, Climate change, Environmental sciences, GE1-350
Abstract: Abstract Background Europe has warmed more than the global average (land and ocean) since pre-industrial times, and is also projected to continue to warm faster than the global average in the twenty-first century. According to the climate models ensemble projections for various climate scenarios, annual mean temperature of Europe for 2071–2100 is predicted to be 1–5.5 °C higher than that for 1971–2000. Climate change and elevated CO2 concentration are anticipated to affect grassland management and livestock production in Europe. However, there has been little work done to quantify the European-wide response of grassland to future climate change. Here we applied ORCHIDEE-GM v2.2, a grid-based model for managed grassland, over European grassland to estimate the impacts of future global change. Results Increases in grassland productivity are simulated in response to future global change, which are mainly attributed to the simulated fertilization effect of rising CO2. The results show significant phenology shifts, in particular an earlier winter-spring onset of grass growth over Europe. A longer growing season is projected over southern and southeastern Europe. In other regions, summer drought causes an earlier end to the growing season, overall reducing growing season length. Future global change allows an increase of management intensity with higher than current potential annual grass forage yield, grazing capacity and livestock density, and a shift in seasonal grazing capacity. We found a continual grassland soil carbon sink in Mediterranean, Alpine, North eastern, South eastern and Eastern regions under specific warming level (SWL) of 1.5 and 2 °C relative to pre-industrial climate. However, this carbon sink is found to saturate, and gradually turn to a carbon source at warming level reaching 3.5 °C. Conclusions This study provides a European-wide assessment of the future changes in productivity and phenology of grassland, and their consequences for the management intensity and the carbon balance. The simulated productivity increase in response to future global change enables an intensification of grassland management over Europe. However, the simulated increase in the interannual variability of grassland productivity over some regions may reduce the farmers’ ability to take advantage of the increased long-term mean productivity in the face of more frequent, and more severe drops of productivity in the future.
Published: 2017
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3. Development of a functional approach in a grassland vegetation sub-model = Desenvolvimento de uma abordagem funcional em um submodelo vegetal campestre

Author: Jean-François Soussana, Frédérique Louault, Pascal Carrère, and Enio Egon Sosinski Júnior
Subjects: extensification, grassland vegetation, models, simulation, functional attributes, vegetation communities, extensificação, vegetação campestre, modelos, simulação, atributos funcionais, comunidades vegetais, Animal culture, SF1-1100
Abstract: To improve our understanding of grassland dynamics under different levels of utilization, a functional description of the vegetation was introduced in a deterministic model. The selected traits and their parameterization were based on the results of a longtermexperiment in which temperate grasslands were managed for 12 years with three levels of herbage use: high, medium and low. The integration of functional attributes of the community species within the model’s parameters can be seen as a new step in the study ofthe grassland ecosystem. With this tool, it is possible to decrease the number of interconnections in the system and consequently decrease the complexity. In this work a, functional definition of three different grassland communities was introduced into the subvegetation model. This was done by interchanging the model’s parameters with the functional attributes of the communities. From the conceptual point of view, the subvegetation model works adequately and it seems suitable to simulate the dynamic ofgrassland vegetation described by functional traits. The model fits experimental data well for high levels of utilization, but was poorly adjusted at medium and low levels of herbage use. We believe this is due to a better simulation of green biomass fluxes than forsenescence or reproductive fluxes. Some possible improvements of the model are discussed.Para aumentar a nossa compreensão sobre a dinâmica da vegetação campestre em diferentes níveis de utilização, foi introduzido num modelo determinístico uma descrição funcional da vegetação. Os atributos funcionais escolhidos e suas parametrizações foram baseadosem resultados de experimento de longo prazo, no qual pastagens temperadas foram manejadas por 12 anos com três níveis de utilização: alto, médio e baixo. A integração de atributos funcionais da comunidade vegetal nos parâmetros do modelo pode ser vista como um novo passo no estudo de ecossistemas pastoris. Com essa ferramenta, é possível reduzir o número de interconexões no sistema e consequentemente diminuir sua complexidade. Neste trabalho uma definição funcional de três diferentes comunidades vegetais campestres foi introduzida num submodelo vegetal. Isso foi feito pelo intercambio de parâmetros do modelo com atributos funcionais dacomunidade. Do ponto de vista conceitual, o submodelo vegetal funciona bem e parece adequado para simular a dinâmica da vegetação campestre descrita por atributos funcionais. Os resultados do modelo mostram bom ajuste destes aos dados experimentais para o alto nível deutilização mas não para o médio ou baixo nível de utilização de forragem. Nós acreditamos que isto se deve a melhor simulação dos fluxos de biomassa verde do que da senescência ou dos fluxos reprodutivos. Algumas possibilidades de melhorias do modelo são discutidas.
Published: 2008

4. Modeled Changes in Potential Grassland Productivity and in Grass-Fed Ruminant Livestock Density in Europe over 1961-2010.

Author: Jinfeng Chang, Nicolas Viovy, Nicolas Vuichard, Philippe Ciais, Matteo Campioli, Katja Klumpp, Raphaël Martin, Adrian Leip, and Jean-François Soussana
Subjects: Medicine, Science
Abstract: About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage. However, besides management, grassland productivity is highly vulnerable to climate (i.e., temperature, precipitation, CO2 concentration), and spatial information about European grassland productivity in response to climate change is scarce. The process-based vegetation model ORCHIDEE-GM, containing an explicit representation of grassland management (i.e., herbage mowing and grazing), is used here to estimate changes in potential productivity and potential grass-fed ruminant livestock density across European grasslands over the period 1961-2010. Here "potential grass-fed ruminant livestock density" denotes the maximum density of livestock that can be supported by grassland productivity in each 25 km × 25 km grid cell. In reality, livestock density could be higher than potential (e.g., if additional feed is supplied to animals) or lower (e.g., in response to economic factors, pedo-climatic and biotic conditions ignored by the model, or policy decisions that can for instance reduce livestock numbers). When compared to agricultural statistics (Eurostat and FAOstat), ORCHIDEE-GM gave a good reproduction of the regional gradients of annual grassland productivity and ruminant livestock density. The model however tends to systematically overestimate the absolute values of productivity in most regions, suggesting that most grid cells remain below their potential grassland productivity due to possible nutrient and biotic limitations on plant growth. When ORCHIDEE-GM was run for the period 1961-2010 with variable climate and rising CO2, an increase of potential annual production (over 3%) per decade was found: 97% of this increase was attributed to the rise in CO2, -3% to climate trends and 15% to trends in nitrogen fertilization and deposition. When compared with statistical data, ORCHIDEE-GM captures well the observed phase of climate-driven interannual variability in grassland production well, whereas the magnitude of the interannual variability in modeled productivity is larger than the statistical data. Regional grass-fed livestock numbers can be reproduced by ORCHIDEE-GM based on its simple assumptions and parameterization about productivity being the only limiting factor to define the sustainable number of animals per unit area. Causes for regional model-data misfits are discussed, including uncertainties in farming practices (e.g., nitrogen fertilizer application, and mowing and grazing intensity) and in ruminant diet composition, as well as uncertainties in the statistical data and in model parameter values.
Published: 2015
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5. Distribuição horizontal e taxas de crescimento, senescência e desfolhação de azevém perene e festuca, puros e em associação

Author: Andréa Machado Groff, Jean-François Soussana, Frédérique Louault, Anibal de Moraes, and Edson Cristiano Groff
Subjects: competição, Festuca arundinacea, Lolium perenne, massa do bocado, profundidade do bocado, seleção, Animal culture, SF1-1100
Abstract: O experimento foi realizado no INRA (Institut National de la Recherche Agronomique) em Theix, França. Duas gramíneas (azevém perene e festuca)foram semeadas em caixas (0,13 m²) usando-se três distribuições horizontais do pasto (pura, linhas alternadas e faixas alternadas) e três intervalos de desfolhações (3,5, 7 e 14 dias), com quatro repetições por tratamento. Quatro meses após a semeadura, a cada data de desfolhação, as caixas foram oferecidas, individualmente, a quatro ovelhas secas e retiradas após a realização de 340 bocados.m-2. Para cada gramínea estudaram-se a densidade populacional e a massa de perfilhos, a altura e a produção de matéria seca, a profundidade e a massa do bocado e as taxas de crescimento, senescência e desfolhação. A maior altura do pasto, gerada por desfolhações menos freqüentes, promoveu a realização de bocados mais profundos e de maior massa. Por outro lado, em desfolhações mais freqüentes a altura do pasto foi mantida mais baixa, e a profundidade e massa do bocado foram menores. A distribuição horizontal das plantas promoveu respostas diferenciadas em relação as taxas de crescimento, senescência e desfolhação. Quando em linhas alternadas a festuca teve a taxa de crescimento limitada, provavelmente desfavorecida pela competição.
Published: 2002

6. Reducing greenhouse gas emissions in agriculture without compromising food security?

Author: Stefan Frank, Petr Havlík, Jean-François Soussana, Antoine Levesque, Hugo Valin, Eva Wollenberg, Ulrich Kleinwechter, Oliver Fricko, Mykola Gusti, Mario Herrero, Pete Smith, Tomoko Hasegawa, Florian Kraxner, and Michael Obersteiner
Subjects: AFOLU, climate change mitigation, food security, soil carbon, partial equilibrium model, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350, Science, Physics, QC1-999
Abstract: To keep global warming possibly below 1.5 °C and mitigate adverse effects of climate change, agriculture, like all other sectors, will have to contribute to efforts in achieving net negative emissions by the end of the century. Cost-efficient distribution of mitigation across regions and economic sectors is typically calculated using a global uniform carbon price in climate stabilization scenarios. However, in reality such a carbon price would substantially affect food availability. Here, we assess the implications of climate change mitigation in the land use sector for agricultural production and food security using an integrated partial equilibrium modelling framework and explore ways of relaxing the competition between mitigation in agriculture and food availability. Using a scenario that limits global warming cost-efficiently across sectors to 1.5 °C, results indicate global food calorie losses ranging from 110–285 kcal per capita per day in 2050 depending on the applied demand elasticities. This could translate into a rise in undernourishment of 80–300 million people in 2050. Less ambitious greenhouse gas (GHG) mitigation in the land use sector reduces the associated food security impact significantly, however the 1.5 °C target would not be achieved without additional reductions outside the land use sector. Efficiency of GHG mitigation will also depend on the level of participation globally. Our results show that if non-Annex-I countries decide not to contribute to mitigation action while other parties pursue their mitigation efforts to reach the global climate target, food security impacts in these non-Annex-I countries will be higher than if they participate in a global agreement, as inefficient mitigation increases agricultural production costs and therefore food prices. Land-rich countries with a high proportion of emissions from land use change, such as Brazil, could reduce emissions with only a marginal effect on food availability. In contrast, agricultural mitigation in high population (density) countries, such as China and India, would lead to substantial food calorie loss without a major contribution to global GHG mitigation. Increasing soil carbon sequestration on agricultural land would allow reducing the implied calorie loss by 65% when sticking to the initially estimated land use mitigation requirements, thereby limiting the impact on undernourishment to 20–75 million people, and storing significant amounts of carbon in soils.
Published: 2017
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7. Disentangling coordination among functional traits using an individual-centred model: impact on plant performance at intra- and inter-specific levels.

Author: Vincent Maire, Nicolas Gross, David Hill, Raphaël Martin, Christian Wirth, Ian J Wright, and Jean-François Soussana
Subjects: Medicine, Science
Abstract: BACKGROUND:Plant functional traits co-vary along strategy spectra, thereby defining trade-offs for resource acquisition and utilization amongst other processes. A main objective of plant ecology is to quantify the correlations among traits and ask why some of them are sufficiently closely coordinated to form a single axis of functional specialization. However, due to trait co-variations in nature, it is difficult to propose a mechanistic and causal explanation for the origin of trade-offs among traits observed at both intra- and inter-specific level. METHODOLOGY/PRINCIPAL FINDINGS:Using the G(EMINI) individual-centered model which coordinates physiological and morphological processes, we investigated with 12 grass species the consequences of deliberately decoupling variation of leaf traits (specific leaf area, leaf lifespan) and plant stature (height and tiller number) on plant growth and phenotypic variability. For all species under both high and low N supplies, simulated trait values maximizing plant growth in monocultures matched observed trait values. Moreover, at the intraspecific level, plastic trait responses to N addition predicted by the model were in close agreement with observed trait responses. In a 4D trait space, our modeling approach highlighted that the unique trait combination maximizing plant growth under a given environmental condition was determined by a coordination of leaf, root and whole plant processes that tended to co-limit the acquisition and use of carbon and of nitrogen. CONCLUSION/SIGNIFICANCE:Our study provides a mechanistic explanation for the origin of trade-offs between plant functional traits and further predicts plasticity in plant traits in response to environmental changes. In a multidimensional trait space, regions occupied by current plant species can therefore be viewed as adaptive corridors where trait combinations minimize allometric and physiological constraints from the organ to the whole plant levels. The regions outside this corridor are empty because of inferior plant performance.
Published: 2013
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8. The coordination of leaf photosynthesis links C and N fluxes in C3 plant species.

Author: Vincent Maire, Pierre Martre, Jens Kattge, François Gastal, Gerd Esser, Sébastien Fontaine, and Jean-François Soussana
Subjects: Medicine, Science
Abstract: Photosynthetic capacity is one of the most sensitive parameters in vegetation models and its relationship to leaf nitrogen content links the carbon and nitrogen cycles. Process understanding for reliably predicting photosynthetic capacity is still missing. To advance this understanding we have tested across C(3) plant species the coordination hypothesis, which assumes nitrogen allocation to photosynthetic processes such that photosynthesis tends to be co-limited by ribulose-1,5-bisphosphate (RuBP) carboxylation and regeneration. The coordination hypothesis yields an analytical solution to predict photosynthetic capacity and calculate area-based leaf nitrogen content (N(a)). The resulting model linking leaf photosynthesis, stomata conductance and nitrogen investment provides testable hypotheses about the physiological regulation of these processes. Based on a dataset of 293 observations for 31 species grown under a range of environmental conditions, we confirm the coordination hypothesis: under mean environmental conditions experienced by leaves during the preceding month, RuBP carboxylation equals RuBP regeneration. We identify three key parameters for photosynthetic coordination: specific leaf area and two photosynthetic traits (k(3), which modulates N investment and is the ratio of RuBP carboxylation/oxygenation capacity (V(Cmax)) to leaf photosynthetic N content (N(pa)); and J(fac), which modulates photosynthesis for a given k(3) and is the ratio of RuBP regeneration capacity (J(max)) to V(Cmax)). With species-specific parameter values of SLA, k(3) and J(fac), our leaf photosynthesis coordination model accounts for 93% of the total variance in N(a) across species and environmental conditions. A calibration by plant functional type of k(3) and J(fac) still leads to accurate model prediction of N(a), while SLA calibration is essentially required at species level. Observed variations in k(3) and J(fac) are partly explained by environmental and phylogenetic constraints, while SLA variation is partly explained by phylogeny. These results open a new avenue for predicting photosynthetic capacity and leaf nitrogen content in vegetation models.
Published: 2012
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9. Diversity promotes temporal stability across levels of ecosystem organization in experimental grasslands.

Author: Raphaël Proulx, Christian Wirth, Winfried Voigt, Alexandra Weigelt, Christiane Roscher, Sabine Attinger, Jussi Baade, Romain L Barnard, Nina Buchmann, François Buscot, Nico Eisenhauer, Markus Fischer, Gerd Gleixner, Stefan Halle, Anke Hildebrandt, Esther Kowalski, Annely Kuu, Markus Lange, Alex Milcu, Pascal A Niklaus, Yvonne Oelmann, Stephan Rosenkranz, Alexander Sabais, Christoph Scherber, Michael Scherer-Lorenzen, Stefan Scheu, Ernst-Detlef Schulze, Jens Schumacher, Guido Schwichtenberg, Jean-François Soussana, Vicky M Temperton, Wolfgang W Weisser, Wolfgang Wilcke, and Bernhard Schmid
Subjects: Medicine, Science
Abstract: The diversity-stability hypothesis states that current losses of biodiversity can impair the ability of an ecosystem to dampen the effect of environmental perturbations on its functioning. Using data from a long-term and comprehensive biodiversity experiment, we quantified the temporal stability of 42 variables characterizing twelve ecological functions in managed grassland plots varying in plant species richness. We demonstrate that diversity increases stability i) across trophic levels (producer, consumer), ii) at both the system (community, ecosystem) and the component levels (population, functional group, phylogenetic clade), and iii) primarily for aboveground rather than belowground processes. Temporal synchronization across studied variables was mostly unaffected with increasing species richness. This study provides the strongest empirical support so far that diversity promotes stability across different ecological functions and levels of ecosystem organization in grasslands.
Published: 2010
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10. Development of a functional approach in a grassland vegetation - DOI: 10.4025/actascianimsci.v30i2.4679

Author: Enio Egon Sosinski Junior, Pascal Carrère, Frédérique Louault, and Jean-François Soussana
Subjects: extensification, grassland vegetation, models, simulation, functional attributes, vegetation communities., Animal culture, SF1-1100
Abstract: To improve our understanding of grassland dynamics under different levels of utilization, a functional description of the vegetation was introduced in a deterministic model. The selected traits and their parameterization were based on the results of a long-term experiment in which temperate grasslands were managed for 12 years with three levels of herbage use: high, medium and low. The integration of functional attributes of the community species within the model’s parameters can be seen as a new step in the study of the grassland ecosystem. With this tool, it is possible to decrease the number of interconnections in the system and consequently decrease the complexity. In this work a, functional definition of three different grassland communities was introduced into the sub-vegetation model. This was done by interchanging the model’s parameters with the functional attributes of the communities. From the conceptual point of view, the sub-vegetation model works adequately and it seems suitable to simulate the dynamic of grassland vegetation described by functional traits. The model fits experimental data well for high levels of utilization, but was poorly adjusted at medium and low levels of herbage use. We believe this is due to a better simulation of green biomass fluxes than for senescence or reproductive fluxes. Some possible improvements of the model are discussed.
Published: 2008
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11. Intervalo e intensidade de desfolhação nas taxas de crescimento, senescência e desfolhação e no equilíbrio de gramíneas em associação Interval and intensity of defoliation on the growth, senescence and defoliation fluxes and equilibrium of associated grasses

Author: Andréa Machado Groff, Anibal de Moraes, Jean-François Soussana, Paulo César de Faccio Carvalho, and Frédérique Louault
Subjects: densidade de perfilhos, Festuca arundinacea, Lolium perenne, massa do bocado, massa do perfilho, profundidade do bocado, tiller density, bite mass, tiller mass, bite depth, Animal culture, SF1-1100
Abstract: O experimento foi realizado no INRA (Institut National de la Recherche Agronomique) em Theix, França. Duas gramíneas (azevém perene e festuca)foram semeadas em caixas (0,13 m²) e submetidas a três intervalos (3,5, 7 e 14 dias) e três intensidades (160, 320 e 640 bocados.m-2 a cada desfolhação) de desfolhação, com quatro repetições por tratamento. Quatro meses após a semeadura, a cada data de desfolhação, as caixas foram oferecidas, individualmente, a quatro ovelhas secas e retiradas após a realização de um determinado número de bocados. Para cada gramínea foram estudadas as taxas de crescimento, senescência e desfolhação. Os resultados mostraram que o intervalo e a intensidade de desfolhação tiveram efeitos diferenciados nas taxas de crescimento, senescência e desfolhação e no equilíbrio da associação.The experiment was carried in INRA (Institut National de la Recherche Agronomique) at Theix, France. Two grasses (perennial ryegrass and tall fescue) were grown in sward boxes (0,13 m²) and submitted to three defoliation intervals (3,5, 7 and 14 days between two successive defoliation) and three defoliation intensities (160, 320 and 640 bites.m-2 at each defoliation). Four months after sowing, at defoliation date, sward boxes were offered to four individual dry ewes and removed after a given number of bites had been taken. For each grass species, the growth, senescence and defoliation fluxes were studied. The results showed that the interval and the intensity of grazing had distinct effects on the growth, senescence and defoliation fluxes as well as on the equilibrium of grass mixtures.
Published: 2002
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12. Quantification of the impact of cover crops on Net Ecosystem Exchange using AgriCarbon-EOv0.1.

Author: Ahmad Al Bitar, Taeken Wijmer, Ludovic Arnaud, Rémy Fieuzal, Jean-François Soussana, Hervé Gibrin, Morgane Ferlicop, Jean-François Dejoux, and Eric Ceschia
Published: 2022
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13. Residual correlation and ensemble modelling to improve crop and grassland models.

Author: Renata Sándor, Fiona Ehrhardt, Peter Grace, Sylvie Recous, Pete Smith, Val Snow, Jean-François Soussana, Bruno Basso, Arti Bhatia, Lorenzo Brilli, Jordi Doltra, Christopher D. Dorich, Luca Doro, Nuala Fitton, Brian Grant, Matthew Tom Harrison, Ute Skiba, Miko U. F. Kirschbaum, Katja Klumpp, Patricia Laville, Joël Léonard, Raphaël Martin, Raia Silvia Massad, Andrew D. Moore, Vasileios Myrgiotis, Elizabeth Pattey, Susanne Rolinski, Joanna Sharp, Ward N. Smith, Lianhai Wu, Qing Zhang, and Gianni Bellocchi
Published: 2023
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14. Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems

Author: Sheryl Hendriks, Jean-François Soussana, Martin Cole, Andrew Kambugu, and David Zilberman
Abstract: Action Track 1 of the Food Systems Summit offers an opportunity to bring together the crucial elements of food safety, nutrition, poverty and inequalities in the framework of food systems within the context of climate and environmental change to ensure that all people have access to a safe and nutritious diet. Achieving Action Track 1’s goal is essential to achieving the goals of the other Action Tracks. With less than a decade left to achieve the Sustainable Development Goals (SDGs), most countries are not on a course to hit either the World Health Organisation’s nutrition targets or the SDG 2 targets. The COVID-19 pandemic has exacerbated malnutrition and highlighted the need for food safety. The pandemic has also exposed the deep inequalities in both food systems and societies as a whole. Nonetheless, future food systems can address many of these failings and ensure safe and nutritious food for all. However, structural change is necessary to address the socio-economic drivers behind malnutrition, inequalities and the climate and environmental impacts of food. Adopting a whole-system approach in policy, research and monitoring and evaluation is crucial for managing trade-off and externalities from farm-level to national scales and across multiple sectors and agencies. Supply chain failures will need to be overcome and technology solutions adopted and adapted to specific contexts. A transformation of food systems requires coordinating changes in supply and demand in differentiated ways across world regions: bridging yield gaps and improving livestock feed conversion, largely through agro-ecological practices, deploying soil carbon sequestration and greenhouse gas mitigation at scale, and reducing food loss and waste, as well as addressing over-nourishment and shifting the diets of wealthy populations. The sustainability of global food systems also requires halting the expansion of agriculture into fragile ecosystems, while restoring degraded forests, fisheries, rangelands, peatlands and wetlands. Shifting to more sustainable consumption and production patterns within planetary boundaries will require efforts to influence food demand and diets, diversify food systems, and develop careful land-use planning and management. Integrative policies need to ensure that food prices reflect real costs (including major externalities caused by climate change, land degradation and biodiversity loss, and the public health impacts of malnutrition), reduce food waste and, at the same time, ensure the affordability of safe and healthy food and decent incomes and wages for farmers and food system workers. The harnessing of science and technology solutions and the sharing of actionable knowledge with all players in the food system offer many opportunities. Greater coordination of food system stakeholders is crucial for greater inclusion, greater transparency and more accountability. Sharing lessons and experiences will foster adaptive learning and responsive actions. Careful consideration of the trade-offs, externalities and costs of not acting is needed to ensure that the changes we make benefit all, and especially the most vulnerable in society.
Published: 2023
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15. The True Cost of Food: A Preliminary Assessment

Author: Sheryl Hendriks, Adrian de Groot Ruiz, Mario Herrero Acosta, Hans Baumers, Pietro Galgani, Daniel Mason-D’Croz, Cecile Godde, Katharina Waha, Dimitra Kanidou, Joachim von Braun, Mauricio Benitez, Jennifer Blanke, Patrick Caron, Jessica Fanzo, Friederike Greb, Lawrence Haddad, Anna Herforth, Danie Jordaan, William Masters, Claudia Sadoff, Jean-François Soussana, Maria Cristina Tirado, Maximo Torero, and Matthew Watkins
Abstract: Ensuring sustainable food systems requires vastly reducing their environmental and health costs while making healthy and sustainable food affordable to all. One of the central problems of current food systems is that many of the costs of harmful foods are externalized, i.e., are not reflected in market prices. At the same time, the benefits of healthful foods are not appreciated. Due to externalities, sustainable and healthy food is often less affordable to consumers and less profitable for businesses than unsustainable and unhealthy food. Externalities and other market failures lead to unintended consequences for present and future generations, destroying nature and perpetuating social injustices such as underpay for workers, food insecurity, illness, premature death and other harms. We urgently need to address the fundamental causes of these problems. This chapter sets out the results of an analysis to determine the current cost of externalities in food systems and the potential impact of a shift in diets to more healthy and sustainable production and consumption patterns. The current externalities were estimated to be almost double (19.8 trillion USD) the current total global food consumption (9 trillion USD). These externalities accrue from 7 trillion USD (range 4–11) in environmental costs, 11 trillion USD (range 3–39) in costs to human life and 1 trillion USD (range 0.2–1.7) in economic costs. This means that food is roughly a third cheaper than it would be if these externalities were included. More studies are needed to quantify the costs and benefits of food systems that would support a global shift to more sustainable and healthy diets. However, the evidence presented in this chapter points to the urgent need for a system reset to account for these ‘hidden costs’ in food systems and calls for bold actions to redefine the incentives for producing and consuming healthier and more sustainable diets. The first step to correct for these ‘hidden costs’ is to redefine the value of food through true-cost accounting (TCA) so as to address externalities and other market failures. TCA reveals the true value of food by making the benefits of affordable and healthy food visible and revealing the costs of damage to the environment and human health 3.
Published: 2023
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16. Global environmental climate change, covid-19, and conflict threaten food security and nutrition

Author: Sheryl L Hendriks, Hugh Montgomery, Tim Benton, Ousmane Badiane, Gonzalo Castro de la Mata, Jessica Fanzo, Ramon R Guinto, and Jean-François Soussana
Subjects: Food Security, Climate Change, COVID-19, Humans, Nutritional Status, General Medicine
Published: 2022

17. There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and netecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in 'trial-and-error' calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details

Author: Fabrizio Albanito, David McBey, Matthew Harrison, Pete Smith, Fiona Ehrhardt, Arti Bhatia, Gianni Bellocchi, Lorenzo Brilli, Marco Carozzi, Karen Christie, Jordi Doltra, Christopher Dorich, Luca Doro, Peter Grace, Brian Grant, Joël Léonard, Mark Liebig, Cameron Ludemann, Raphael Martin, Elizabeth Meier, Rachelle Meyer, Massimiliano De Antoni Migliorati, Vasileios Myrgiotis, Sylvie Recous, Renáta Sándor, Val Snow, Jean-François Soussana, Ward N. Smith, Nuala Fitton, Producció Vegetal, Cultius Extensius Sostenibles, University of Aberdeen, School of Biological Sciences, University of Aberdeen, Aberdeen, UK, Tasmanian Institute of Agriculture, University of Tasmania [Hobart, Australia] (UTAS), RITTMO Agroenvironnement (RITTMO), Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Indian Council of Agricultural Research (ICAR), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institute for BioEconomy [Sesto Fiorentino] (IBE | CNR), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Recerca i Tecnologia Agroalimentàries = Institute of Agrifood Research and Technology (IRTA), Natural Resource Ecology Laboratory [Fort Collins] (NREL), Colorado State University [Fort Collins] (CSU), Texas A and M AgriLife Research, Texas A&M University System, Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Queensland University of Technology [Brisbane] (QUT), Ottawa Research and Development Center, Agriculture and Agri-Food (AAFC), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), USDA-ARS, Northern Plains Agricultural Research Laboratory, Sidney, Montana, Cameron Ludemann Consulting, CSIRO Agriculture and Food (CSIRO), Faculty of Veterinary & Agricultural Sciences, University of Melbourne, Parkville, Victoria, School of Geosciences, University of Edimburgh, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre for Agricultural Research [Budapest] (ATK), Hungarian Academy of Sciences (MTA), AgResearch Ltd, and Institute of Biological and Environmental Sciences, University of Aberdeen
Subjects: model ensembles, biogeochemical models, model calibration, Nitrogen, [SDE.MCG]Environmental Sciences/Global Changes, Uncertainty, General Chemistry, Carbon, Soil, model intercomparison, climate change, greenhouse gases, AgMIP, Environmental Chemistry, multi-criteria decision-making, Humans, soil carbon, Ecosystem
Abstract: There is a growing realization that the complexity of model ensemble studies depends not only on the models used but also on the experience and approach used by modelers to calibrate and validate results, which remain a source of uncertainty. Here, we applied a multi-criteria decision-making method to investigate the rationale applied by modelers in a model ensemble study where 12 process-based different biogeochemical model types were compared across five successive calibration stages. The modelers shared a common level of agreement about the importance of the variables used to initialize their models for calibration. However, we found inconsistency among modelers when judging the importance of input variables across different calibration stages. The level of subjective weighting attributed by modelers to calibration data decreased sequentially as the extent and number of variables provided increased. In this context, the perceived importance attributed to variables such as the fertilization rate, irrigation regime, soil texture, pH, and initial levels of soil organic carbon and nitrogen stocks was statistically different when classified according to model types. The importance attributed to input variables such as experimental duration, gross primary production, and net ecosystem exchange varied significantly according to the length of the modeler’s experience. We argue that the gradual access to input data across the five calibration stages negatively influenced the consistency of the interpretations made by the modelers, with cognitive bias in “trial-and-error” calibration routines. Our study highlights that overlooking human and social attributes is critical in the outcomes of modeling and model intercomparison studies. While complexity of the processes captured in the model algorithms and parameterization is important, we contend that (1) the modeler’s assumptions on the extent to which parameters should be altered and (2) modeler perceptions of the importance of model parameters are just as critical in obtaining a quality model calibration as numerical or analytical details. info:eu-repo/semantics/acceptedVersion
Published: 2022
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18. A new method to determine soil organic carbon equilibrium.

Author: Romain Lardy, Gianni Bellocchi, and Jean-François Soussana
Published: 2011
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19. Current NPP cannot predict future soil organic carbon sequestration potential. Comment on 'Photosynthetic limits on carbon sequestration in croplands'

Author: Budiman Minasny, Dominique Arrouays, Rémi Cardinael, Abad Chabbi, Mark Farrell, Beverley Henry, Lydie-Stella Koutika, Jagdish K. Ladha, Alex. B. McBratney, Jose Padarian, Mercedes Román Dobarco, Cornelia Rumpel, Pete Smith, Jean-François Soussana, The University of Sydney, InfoSol (InfoSol), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Zimbawe [Harare] (UZ), University of Zimbawe, Unité de Recherche Pluridisciplinaire Prairies et Plantes Fourragères (P3F), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CSIRO Agriculture and Food (CSIRO), Queensland University of Technology [Brisbane] (QUT), Centre de Recherche sur la Durabilité et la Productivité des Plantations Industrielles (CRDPI), University of California [Davis] (UC Davis), University of California (UC), Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris ), Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and University of Aberdeen
Subjects: [SDE]Environmental Sciences, Soil Science
Abstract: International audience
Published: 2022
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20. La chimie et la nature

Author: Jacques Amouroux, Jean-François Soussana, Clément Sanchez, Christophe Rupp-Dahlem
Published: 2012

21. How to measure, report and verify soil carbon change to realize the potential of soil carbon sequestration for atmospheric greenhouse gas removal

Author: Alberto Sanz-Cobena, Pete Smith, Katja Klumpp, Eva K. Wollenberg, Cristina Arias-Navarro, Stephen McNeill, Ngonidzashe Chirinda, Matthias Kuhnert, Jorge Álvaro-Fuentes, Claire Chenu, Louis A. Schipper, Jean-François Soussana, Niels H. Batjes, Denis A. Angers, Jørgen E. Olesen, Fenny van Egmond, Dario A. Fornara, Daniel P. Rasse, University of Aberdeen, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Agriculture and Agri-Food [Ottawa] (AAFC), University of Waikato [Hamilton], Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Norwegian Institute of Bioeconomy Research (NIBIO), World Soil Information (ISRIC), Manaaki Whenua – Landcare Research [Lincoln], Aarhus University [Aarhus], International Center for Tropical Agriculture [Colombie] (CIAT), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Agri Food and Biosciences Institute, University of Vermont [Burlington], Universidad Politécnica de Madrid (UPM), European Project: 774378,Horizon 2020,CIRCASA(2017), Agriculture and Agri-Food (AAFC), and Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO)
Subjects: 0106 biological sciences, Carbon Sequestration, 010504 meteorology & atmospheric sciences, Water en Landgebruik, [SDV]Life Sciences [q-bio], Climate change, Carbon sequestration, MRV, 010603 evolutionary biology, 01 natural sciences, GeneralLiterature_MISCELLANEOUS, 12. Responsible consumption, Greenhouse Gases, Soil, Soil, Water and Land Use, Bodem, soil organic matter, Greenhouse gas removal, Invited Research Reviews, Environmental Chemistry, Land use, land-use change and forestry, 0105 earth and related environmental sciences, General Environmental Science, 2. Zero hunger, Global and Planetary Change, reporting, Ecology, business.industry, Agricultura, Water and Land Use, Environmental resource management, Agriculture, Soil carbon, 15. Life on land, Bodem, Water en Landgebruik, Carbon, soil organic carbon, Invited Research Review, monitoring, Climate change mitigation, 13. Climate action, Greenhouse gas, [SDE]Environmental Sciences, Environmental science, Emissions trading, measurement, business, verification, ISRIC - World Soil Information
Abstract: There is growing international interest in better managing soils to increase soil organic carbon (SOC) content to contribute to climate change mitigation, to enhance resilience to climate change and to underpin food security, through initiatives such as international ‘4p1000’ initiative and the FAO's Global assessment of SOC sequestration potential (GSOCseq) programme. Since SOC content of soils cannot be easily measured, a key barrier to implementing programmes to increase SOC at large scale, is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms, both for national reporting and for emissions trading. Without such platforms, investments could be considered risky. In this paper, we review methods and challenges of measuring SOC change directly in soils, before examining some recent novel developments that show promise for quantifying SOC. We describe how repeat soil surveys are used to estimate changes in SOC over time, and how long‐term experiments and space‐for‐time substitution sites can serve as sources of knowledge and can be used to test models, and as potential benchmark sites in global frameworks to estimate SOC change. We briefly consider models that can be used to simulate and project change in SOC and examine the MRV platforms for SOC change already in use in various countries/regions. In the final section, we bring together the various components described in this review, to describe a new vision for a global framework for MRV of SOC change, to support national and international initiatives seeking to effect change in the way we manage our soils., Since soil organic carbon (SOC) changes are difficult to measure, a key barrier to implementing programmes to increase SOC is the need for credible and reliable measurement/monitoring, reporting and verification (MRV) platforms. We review methods for measuring SOC change directly in soils, examine novel developments for quantifying SOC change and describe how surveys, long‐term experiments and chronosequences can be used for testing models and as benchmark sites in global frameworks to estimate SOC change. We review MRV platforms for soil organic carbon change already in use and describe a new vision for a global framework for MRV of SOC change.
Published: 2020
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22. Potential of grazing management to improve beef cattle production and mitigate methane emissions in native grasslands of the Pampa biome

Author: William de Souza Filho, Jean Victor Savian, Paulo César de Faccio Carvalho, Teresa Cristina Moraes Genro, Marcelo Ritzel Tischler, Jean-François Soussana, Ian M. Cezimbra, Olivier Jean François Bonnet, Pedro Arthur de Albuquerque Nunes, Cimélio Bayer, Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), Brazilian Agricultural Research Corporation (Embrapa), Instituto Nacional de Investigación Agropecuaria (INIA), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: Environmental Engineering, Livestock, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Forage, 010501 environmental sciences, Beef cattle, 01 natural sciences, Grassland, Animal science, Stocking, Ruminant, Grazing intensity, Grazing, Environmental Chemistry, Animals, Climate change, Dry matter, Waste Management and Disposal, Ecosystem, 0105 earth and related environmental sciences, 2. Zero hunger, geography, geography.geographical_feature_category, biology, business.industry, 15. Life on land, biology.organism_classification, Pollution, Animal Feed, Diet, Greenhouse gases, Environmental science, Cattle, business, Methane, Brazil
Abstract: International audience; We tested the hypothesis that improving sward structure through adjustments in forage allowance re-sults in greater forage intake and live weight (LW) gains by beef cattle and lower CH4emissions perunit LW gain and unit area in a native grassland ecosystem of the Pampa biome. The experiment wascarried out during 2012 and 2013 in southern Brazil.The experimental design was a randomized com-plete block with two replicates. Treatments consisted offive contrasting forage allowances of a nativegrassland managed under continuous stocking: 4, 8, 8–12, 12, and 16 kg of dry matter (DM) 100 kgLW−1day−1(or % LW). The 8–12% LW treatment had a variable forage allowance of 8% LW in springand 12% LW in summer, autumn, and winter. Forage allowance was controlled by changes in stockingrate (kg LW ha−1). Average daily gain (kg LW day−1) was high for forage allowances of 12 and16% LW but decreased at 8%, reaching the lowest value at 4% LW treatment (p
Published: 2021
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23. PREZODE: preventing zoonotic disease emergence

Author: Thierry Lefrançois, Gwenaël Vourc'h, Jean-François Soussana, Benjamin Roche, Yves Martin-Prével, Marie-Isabelle Peyre, Animal, Santé, Territoires, Risques et Ecosystèmes (UMR ASTRE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Systèmes Biologiques (Cirad-BIOS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Montpellier Interdisciplinary center on Sustainable Agri-food systems (Social and nutritional sciences) (UMR MoISA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Montpellier (CIHEAM-IAMM), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Nutrition et Alimentation des Populations aux Suds (NutriPass), Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Maladies infectieuses et vecteurs : écologie, génétique, évolution et contrôle (MIVEGEC), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Unité Mixte de Recherche d'Épidémiologie des maladies Animales et zoonotiques (UMR EPIA), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: 0106 biological sciences, zoonose, 2019-20 coronavirus outbreak, MESH: Pandemics, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), International Cooperation, [SDV]Life Sciences [q-bio], MESH: Global Health, L73 - Maladies des animaux, Global Health, 010603 evolutionary biology, 01 natural sciences, Zoonotic disease, 03 medical and health sciences, Système de surveillance, Prévention des maladies, Zoonoses, Pandemic, Correspondence, Global health, Animals, Humans, MESH: COVID-19, Surveillance épidémiologique, MESH: Animals, MESH: SARS-CoV-2, Pandemics, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, MESH: Humans, SARS-CoV-2, COVID-19, General Medicine, Virology, MESH: International Cooperation, S50 - Santé humaine, Maladie infectieuse, Gestion des connaissances, Business, MESH: Zoonoses
Abstract: International audience
Published: 2021
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24. Les émissions de N2O peuvent-elles compenser les avantages du stockage du carbone organique dans le sol ?

Author: David S. Powlson, Frédéric Rees, Victoria Naipal, Jérôme Balesdent, Rémi Cardinael, Julien Fouché, Emanuele Lugato, Elisa Bruni, Stefan Frank, Philippe Ciais, Dominique Arrouays, Catherine Hénault, Benoit Gabrielle, Hanqin Tian, Thomas Nesme, Sylvain Pellerin, Hugo Valin, Bertrand Guenet, Jean-Pierre Caliman, Michael Obersteiner, Claire Chenu, Feng Zhou, Yang Su, Jean-François Soussana, Dominique Desbois, Songchao Chen, Daniel P. Rasse, Martial Bernoux, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), InfoSol (InfoSol), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE), Institut de Recherche pour le Développement (IRD)-Aix Marseille Université (AMU)-Collège de France (CdF (institution))-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Food and Agriculture Organization of the United Nations [Rome, Italie] (FAO), Smart Research Institute [Indonésie] (SMARTRI), SMART agribusiness and food [Jakarta] (SMART), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), University of Zimbawe [Harare] (UZ), University of Zimbawe, ICOS-ATC (ICOS-ATC), Economie Publique (ECO-PUB), Laboratoire d'étude des Interactions Sol - Agrosystème - Hydrosystème (UMR LISAH), Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), International Institute for Applied Systems Analysis [Laxenburg] (IIASA), Agroécologie [Dijon], Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), European Commission - Joint Research Centre [Ispra] (JRC), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Rothamsted Research, Norwegian Institute of Bioeconomy Research (NIBIO), Auburn University (AU), Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University [Beijing], This paper stemmed from a workshop 'Emerging challenges in large scale soil carbon sequestration' held in Paris on 8-10 October 2018. The workshop was financially supported by the French government under the ANR 'Investissements d'avenir' program with the reference CLAND ANR-16-CONV-0003. F.Z. acknowledges support from the National Natural Science Foundation of China (grant no. 41671464), ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Biotechnology and Biological Sciences Research Council (BBSRC), Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO), Support from the National Natural Science Foundation of China (grant no. 41671464), Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Centre National d'Études Spatiales [Toulouse] (CNES)
Subjects: 0106 biological sciences, Atténuation de l'effet de serre, 010504 meteorology & atmospheric sciences, Travail du sol, [SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy, greenhouse gases emissions, Agroforesterie, Carbone dans le sol, 7. Clean energy, 01 natural sciences, agroforestry, Interactions biologiques, Environmental protection, Biochar, organic amendment, General Environmental Science, 2. Zero hunger, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, Ecology, greenhouse gas emissions, land based mitigation, erosion, [SHS.ECO]Humanities and Social Sciences/Economics and Finance, Tillage, Gaz a effet de serre, séquestration du carbone, Cycle de l'azote, réduction des émissions, [SDE]Environmental Sciences, tillage, Culture de couverture, P33 - Chimie et physique du sol, Labour, Land management, Climate change, érosion, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 010603 evolutionary biology, 12. Responsible consumption, Matière organique du sol, Fertilité du sol, Environmental Chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, biochar, Occupation des sols, émissions de gaz à effet de serre, 0105 earth and related environmental sciences, cover crops agroforestry, Oxyde nitreux, Global warming, Soil carbon, 15. Life on land, soil organic carbon, land-based mitigation, Amendement organique, 13. Climate action, Greenhouse gas, Soil water, Environmental science, cover crops, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Cycle du carbone
Abstract: This paper stemmed from a workshop 'Emerging challenges in large scale soil carbon sequestration' held in Paris on 8-10 October 2018; International audience; To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5°C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large‐scale deployment of other climate mitigation strategies are also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N$_2$O), a powerful greenhouse gas, and increasing SOC may influence N$_2$O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here, we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N$_2$O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta‐analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N$_2$O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g, biochar or non‐pyrogenic C amendment application) may even decrease N$_2$O emissions.; Pour respecter l'accord de Paris visant à limiter le réchauffement climatique à moins de 2°C d'ici 2100, et éventuellement à moins de 1,5°C, des réductions drastiques des émissions de gaz à effet de serre sont obligatoires mais pas suffisantes. Le déploiement à grande échelle d'autres stratégies d'atténuation du climat est également nécessaire. Parmi celles-ci, l'augmentation des stocks de carbone organique du sol (SOC) est un levier important car le carbone dans les sols peut être stocké pendant de longues périodes et les options de gestion des terres pour y parvenir existent déjà et ont été largement testées. Toutefois, les sols agricoles sont également une source importante d'oxyde nitreux (N$_2$O), un puissant gaz à effet de serre, et l'augmentation du SOC peut influer sur les émissions de N$_$O, provoquant probablement une augmentation dans de nombreux cas, tendant ainsi à compenser le bénéfice du changement climatique résultant du stockage accru du SOC. Nous passons ici en revue les principales options de gestion agricole pour l'augmentation des stocks de SOC. Nous évaluons la quantité de SOC qui peut être stockée ainsi que les changements qui en résultent dans les émissions de N$_2$O afin de mieux estimer les avantages climatiques de ces options de gestion. Sur la base des données quantitatives obtenues à partir de méta-analyses publiées et de notre niveau de compréhension actuel, nous concluons que l'atténuation du climat induite par un stockage accru du SOC est généralement surestimée si l'on ne tient pas compte des émissions de N$_2$O associées, mais, à l'exception du travail réduit du sol, n'est jamais totalement compensée. Certaines options (par exemple, le biochar ou l'application d'un amendement C non pyrogène) peuvent même réduire les émissions de N$_2$O.
Published: 2021
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25. Feasibility of the 4 per 1000 aspirational target for soil carbon: A case study for France

Author: Manuel P. Martin, Bassem Dimassi, Mercedes Román Dobarco, Bertrand Guenet, Dominique Arrouays, Denis A. Angers, Fabrice Blache, Frédéric Huard, Jean‐François Soussana, Sylvain Pellerin
Published: 2021
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26. Evaluating the Potential of Legumes to Mitigate N 2 O Emissions From Permanent Grassland Using Process‐Based Models

Author: Lutz Merbold, Pete Smith, Katja Klumpp, Nuala Fitton, Paul C. D. Newton, Sylvie Recous, Fiona Ehrhardt, Peter Grace, Raphaël Martin, Mark Lieffering, Cairistiona F. E. Topp, Marco Bindi, Christopher D. Dorich, Richard T. Conant, Gianni Bellocchi, Kathrin Fuchs, Mark A. Liebig, Lorenzo Brilli, Jean-François Soussana, Russell McAuliffe, Robert M. Rees, Nina Buchmann, Val Snow, Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology (KIT), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Agriculture, Food, Environment and Forestry (DAGRI), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Natural Resource Ecology Laboratory [Fort Collins] (NREL), Colorado State University [Fort Collins] (CSU), Collège de Direction (CODIR), Institute of Biological, Environmental and Rural Sciences (IBERS), Aberystwyth University, Institute for Future Environments, Queensland University of Technology, NGPRL, USDA-ARS : Agricultural Research Service, AgResearch Ltd, Scotland's Rural College (SRUC), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Aberdeen, Swiss National Science Foundation (SNSF)Department for Environment, Food & Rural Affairs (DEFRA) RCUK projectsNew Zealand Government Ministry of Primary Industries, and ANR-13-JFAC-0001,CN-MIP,C and N Models Intercomparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide(2013)
Subjects: 0106 biological sciences, Atmospheric Science, Research program, biological nitrogen fixation, greenhouse gas mitigation, legumes, 010504 meteorology & atmospheric sciences, [SDE.MCG]Environmental Sciences/Global Changes, Public administration, 01 natural sciences, Political science, Agency (sociology), ddc:550, Environmental Chemistry, media_common.cataloged_instance, European union, 0105 earth and related environmental sciences, General Environmental Science, media_common, Investment fund, Global and Planetary Change, Government, Food security, business.industry, 010604 marine biology & hydrobiology, 15. Life on land, Earth sciences, 13. Climate action, Agriculture, Primary sector of the economy, business
Abstract: Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE-JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE-JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N-Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN-MIP project funded by the French National Research Agency (ANR-13-JFAC-0001) and from ADEME (no. 12-60-C0023). Open access funding enabled and organized by Projekt DEAL Funding Information: This modeling study was a joint effort of the Models4Pastures project within the framework of FACCE‐JPI. Lutz Merbold and Kathrin Fuchs acknowledge funding received for the Swiss contribution to Models4Pastures (FACCE‐JPI project, SNSF funded contract: 40FA40_154245/1) and for the Doc. Mobility fellowship (SNSF funded project: P1EZP2_172121). Lutz Merbold further acknowledges the support received for CGIAR Fund Council, Australia (ACIAR), Irish Aid, the European Union, the Netherlands, New Zealand, Switzerland, UK, USAID, and Thailand for funding to the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) as well as for the CGIAR Research Program on Livestock. The NZ contributors acknowledge funding from the New Zealand Government Ministry of Primary Industries to support the aims of the Livestock Research Group of the Global Research Alliance on Agricultural Greenhouse Gases and from AgResearch's Strategic Science Investment Fund (the Forages for Reduced Nitrate Leaching (FRNL) research program). The UK partners acknowledge funding by DEFRA and the RCUK projects: N‐Circle (BB/N013484/1), UGRASS (NE/M016900/1), and GREENHOUSE (NE/K002589/1). R.M. Rees and C.F.E. Topp also received funding from the Scottish Government Strategic Research Programme. Lorenzo Brilli, Camilla Dibari, and Marco Bindi received funding from the Italian Ministry of Agricultural Food and Forestry Policies (MiPAAF). The FR partners acknowledge funding from CN‐MIP project funded by the French National Research Agency (ANR‐13‐JFAC‐0001) and from ADEME (no. 12‐60‐C0023). Open access funding enabled and organized by Projekt DEAL Publisher Copyright: ©2020. The Authors. Open access funding enabled and organized by Projekt DEAL
Published: 2020
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27. La chimie et la nature

Author: ChristopheVE Rupp-Dahlem, Jean-François Soussana, and Clément Sanchez
Published: 2020
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28. Chapitre 3 : Biogéochimie et écologie des sols

Author: Jean-François Soussana
Published: 2020
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29. The impact of interventions in the global land and agri‐food sectors on Nature’s Contributions to People and the UN Sustainable Development Goals

Author: Pete Smith, Giacomo Grassi, Francesco Cherubini, Jean-François Soussana, Donovan Campbell, Anh Le Hoang, Dorothy Kalule Nampanzira, Nobuko Saigusa, Shuaib Lwasa, Johnson Nkem, Vladimir Korotkov, Frances Manning, Pamela McElwee, Miguel Angel Taboada, Katherine Calvin, Ephraim Nkonya, Rutgers, The State University of New Jersey [New Brunswick] (RU), Rutgers University System (Rutgers), Joint Global Change Research Institute, Pacific Northwest National Laboratory (PNNL)-University of Maryland [College Park], University of Maryland System-University of Maryland System, The University of the West Indies, Norwegian University of Science and Technology [Aalesund] (NTNU), Norwegian University of Science and Technology (NTNU), European Commission - Joint Research Centre [Ispra] (JRC), Yu. A. Izrael Institute of Global Climate and Ecology (IGCE), the Russian Academy of Sciences [Moscow, Russia] (RAS), Ministry of Agriculture and Rural Development [Hanoï] (MARD), Makerere University [Kampala, Ouganda] (MAK), United Nations Economic Commission for Africa (UNECA), United Nations, International Food Policy Research Institute [India] (IFPRI), International Food Policy Research Institute [Washington] (IFPRI), Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), National Institute for Environmental Studies [Tsukuba, Japan] (NIES), Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Instituto Nacional de Tecnología Agropecuaria (INTA), University of Aberdeen, and School of Environmental and Biological Sciences, Rutgers University Research Council of NorwayEuropean Commission CGIAR
Subjects: 0106 biological sciences, Sustainable land management, Conservation of Natural Resources, 010504 meteorology & atmospheric sciences, United Nations, Natural resource economics, Land management, adaptation, 010603 evolutionary biology, 01 natural sciences, 12. Responsible consumption, mitigation, Soil, 11. Sustainability, Environmental Chemistry, Animals, Humans, sustainable land management, 0105 earth and related environmental sciences, General Environmental Science, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 2. Zero hunger, Global and Planetary Change, Food security, Ecology, Land use, land degradation, Integrated water resources management, Agriculture, food security, 15. Life on land, Sustainable Development, Carbon, trade-offs, Nature's Contribution to People, 13. Climate action, Sustainability, Land degradation, Food systems, Business, ecosystem services, Goals
Abstract: International audience; Interlocked challenges of climate change, biodiversity loss, and land degradation require transformative interventions in the land management and food production sectors to reduce carbon emissions, strengthen adaptive capacity, and increase food security. However, deciding which interventions to pursue and understanding their relative co-benefits with and trade-offs against different social and environmental goals have been difficult without comparisons across a range of possible actions. This study examined 40 different options, implemented through land management, value chains, or risk management, for their relative impacts across 18 Nature's Contributions to People (NCPs) and the 17 Sustainable Development Goals (SDGs). We find that a relatively small number of interventions show positive synergies with both SDGs and NCPs with no significant adverse trade-offs; these include improved cropland management, improved grazing land management, improved livestock management, agroforestry, integrated water management, increased soil organic carbon content, reduced soil erosion, salinization, and compaction, fire management, reduced landslides and hazards, reduced pollution, reduced post-harvest losses, improved energy use in food systems, and disaster risk management. Several interventions show potentially significant negative impacts on both SDGs and NCPs; these include bioenergy and bioenergy with carbon capture and storage, afforestation, and some risk sharing measures, like commercial crop insurance. Our results demonstrate that a better understanding of co-benefits and trade-offs of different policy approaches can help decision-makers choose the more effective, or at the very minimum, more benign interventions for implementation.
Published: 2020
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30. Can N

Author: Bertrand, Guenet, Benoit, Gabrielle, Claire, Chenu, Dominique, Arrouays, Jérôme, Balesdent, Martial, Bernoux, Elisa, Bruni, Jean-Pierre, Caliman, Rémi, Cardinael, Songchao, Chen, Philippe, Ciais, Dominique, Desbois, Julien, Fouche, Stefan, Frank, Catherine, Henault, Emanuele, Lugato, Victoria, Naipal, Thomas, Nesme, Michael, Obersteiner, Sylvain, Pellerin, David S, Powlson, Daniel P, Rasse, Frédéric, Rees, Jean-François, Soussana, Yang, Su, Hanqin, Tian, Hugo, Valin, and Feng, Zhou
Subjects: Greenhouse Gases, Paris, Soil, Nitrous Oxide, Agriculture, Carbon
Abstract: To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5°C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large-scale deployment of other climate mitigation strategies is also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N
Published: 2020

31. Ensemble modelling, uncertainty and robust predictions of organic carbon in long-term bare-fallow soils

Author: Hugues Clivot, Donna Giltrap, Ward Smith, Katrin Kuka, Renáta Sándor, Bertrand Guenet, Mohamed Abdalla, Matthew T. Harrison, Rosa Francaviglia, Fernando Moyano, Brian Grant, Fabien Ferchaud, Gianni Bellocchi, Claire Chenu, Liisa Kulmala, Tommaso Stella, Christopher D. Dorich, Roberta Farina, Jari Liski, Nuala Fitton, Nils Reibold, Anita Shepherd, Elizabeth A. Meier, Sylvie Recous, Claas Nendel, Luca Bechini, Matthew J. McGrath, Pete Smith, Massimiliano De Antoni Migliorati, Arezoo Taghizadeh-Toosi, Miko U. F. Kirschbaum, Fiona Ehrhardt, Elena Tsutskikh, Uwe Franko, Lorenzo Menichetti, Martin A. Bolinder, Jorge Álvaro-Fuentes, Lorenzo Brilli, Jean-François Soussana, Claudia Di Bene, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA), Biological Research Center [Hungarian Academy of Sciences], Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Aberdeen, Fisica de Sistemas Pequenos, Consejo Superior de Investigaciones Cientificas, Universidad Autónoma de Madrid (UAM), Università degli Studi di Milano = University of Milan (UNIMI), Swedish University of Agricultural Sciences (SLU), Consiglio Nazionale delle Ricerche [Bologna] (CNR), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire Agronomie et Environnement - Antenne Colmar (LAE-Colmar ), Laboratoire Agronomie et Environnement (LAE), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Queensland University of Technology [Brisbane] (QUT), Colorado State University [Fort Collins] (CSU), Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Helmholtz-Gemeinschaft = Helmholtz Association, Manaaki Whenua – Landcare Research [Lincoln], University of Ottawa [Ottawa], Laboratoire de géologie de l'ENS (LGENS), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), University of Tasmania [Hobart, Australia] (UTAS), Julius Kühn-Institut - Federal Research Centre for Cultivated Plants (JKI), Finnish Meteorological Institute (FMI), Commonwealth Scientific and Industrial Research Organisation Energy Technology (CSIRO Energy Technology), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Göttingen State and University Library (SUB Göttingen), Georg-August-University = Georg-August-Universität Göttingen, Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research (ZALF), University of Potsdam = Universität Potsdam, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Biotechnology and Biological Sciences Research Council (BBSRC), Aarhus University [Aarhus], Humboldt University Of Berlin, DEVIL, SUPER-G, French-Italian Galileo program-CLIMSOC project, Joint Programming Initiative 'FACCE', Soils-R-GRREAT, Agriculture & Agri Food Canada, Miljo- og Fodevareministeriet, ANR-16-CONV-0003,CLAND,CLAND : Changement climatique et usage des terres(2016), ANR-13-JFAC-0001,CN-MIP,C and N Models Intercomparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide(2013), European Project: 774378,Horizon 2020,CIRCASA(2017), Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), Universidad Autonoma de Madrid (UAM), University of Milan, Transfrontalière BioEcoAgro (Transfrontalière BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Georg-August-University [Göttingen], University of Potsdam, Biotechnology and Biological Sciences Research Council, and Humboldt-Universität zu Berlin
Subjects: 0106 biological sciences, 010504 meteorology & atmospheric sciences, soil organic carbon dynamics, [SDE.MCG]Environmental Sciences/Global Changes, Soil science, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 010603 evolutionary biology, 01 natural sciences, Standard deviation, protocol for model comparison, Russia, Soil, Calibration, Environmental Chemistry, process based models, 0105 earth and related environmental sciences, General Environmental Science, Total organic carbon, Sweden, Global and Planetary Change, Ecology, bare-fallow soils, Simulation modeling, Uncertainty, Agriculture, Soil carbon, 15. Life on land, European region, Carbon, United Kingdom, process-based models, Term (time), 13. Climate action, Soil water, [SDE]Environmental Sciences, Environmental science, France, bare fallow soils, model parametrization
Abstract: International audience; Simulation models represent soil organic carbon (SOC) dynamics in global carbon (C) cycle scenarios to support climate-change studies. It is imperative to increase confidence in long-term predictions of SOC dynamics by reducing the uncertainty in model estimates. We evaluated SOC simulated from an ensemble of 26 process-based C models by comparing simulations to experimental data from seven long-term bare-fallow (vegetation-free) plots at six sites: Denmark (two sites), France, Russia, Sweden and the United Kingdom. The decay of SOC in these plots has been monitored for decades since the last inputs of plant material, providing the opportunity to test decomposition without the continuous input of new organic material. The models were run independently over multi-year simulation periods (from 28 to 80 years) in a blind test with no calibration (Bln) and with the following three calibration scenarios, each providing different levels of information and/or allowing different levels of model fitting: (a) calibrating decomposition parameters separately at each experimental site (Spe); (b) using a generic, knowledge-based, parameterization applicable in the Central European region (Gen); and (c) using a combination of both (a) and (b) strategies (Mix). We addressed uncertainties from different modelling approaches with or without spin-up initialization of SOC. Changes in the multi-model median (MMM) of SOC were used as descriptors of the ensemble performance. On average across sites, Gen proved adequate in describing changes in SOC, with MMM equal to average SOC (and standard deviation) of 39.2 (+/- 15.5) Mg C/ha compared to the observed mean of 36.0 (+/- 19.7) Mg C/ha (last observed year), indicating sufficiently reliable SOC estimates. Moving to Mix (37.5 +/- 16.7 Mg C/ha) and Spe (36.8 +/- 19.8 Mg C/ha) provided only marginal gains in accuracy, but modellers would need to apply more knowledge and a greater calibration effort than in Gen, thereby limiting the wider applicability of models
Published: 2020
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32. Ensemble modelling of carbon fluxes in grasslands and croplands

Author: Elizabeth Pattey, Ute Skiba, Brian Grant, Gianni Bellocchi, Katja Klumpp, Pete Smith, Matthew T. Harrison, Val Snow, Sylvie Recous, Joanna Sharp, Fiona Ehrhardt, Arti Bhatia, Joël Léonard, Raphaël Martin, Andrew D. Moore, Jordi Doltra, Renata Sándor, Lorenzo Brilli, Jean-François Soussana, Peter Grace, Susanne Rolinski, Ward Smith, Vasileios Myrgiotis, Raia Silvia Massad, Qing Zhang, Miko U. F. Kirschbaum, Lianhai Wu, Nuala Fitton, Luca Doro, Bruno Basso, Christopher D. Dorich, Patricia Laville, Producció Vegetal, Cultius Extensius Sostenibles, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Direction scientifique Environnement, Forêt et Agriculture, Institut National de la Recherche Agronomique (INRA), Queensland University of Technology, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Aberdeen, AgResearch Grasslands, Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Indian Agricultural Research Institute (IARI), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Catabrian Agricultural Research and Training Center (CIFA), Università degli Studi di Sassari, Agriculture and Agri-Food [Ottawa] (AAFC), British Geological Survey (BGS), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Transfrontalière BioEcoAgro (Transfrontalière BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Computer Laboratory [Cambridge], University of Cambridge [UK] (CAM), Scotland's Rural College (SRUC), Potsdam Institute for Climate Impact Research (PIK), Plant & Food Research, Natural Environment Research Council (NERC), Rothamsted Research, CN-MIP by Joint Programming Initiative 'FACCE' Models4Pastures by Joint Programming Initiative 'FACCE' MACSUR by Joint Programming Initiative 'FACCE' COMET-Global by Joint Programming Initiative 'FACCE' MAGGNET by Joint Programming Initiative 'FACCE' French Embassy in Budapest (Hungary) by way of 'Make Our Planet Great Again' programme Federal Ministry of Education & Research (BMBF)01LN1317AEuropean Union (EU)EC EVK2-CT2001-00105GOCE-CT-2003-505572017841SRUC, Queensland University of Technology [Brisbane] (QUT), Università degli Studi di Firenze = University of Florence (UniFI), Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Agriculture and Agri-Food (AAFC), Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), and Biotechnology and Biological Sciences Research Council (BBSRC)
Subjects: 0106 biological sciences, [SDE.MCG]Environmental Sciences/Global Changes, Soil Science, Growing season, Atmospheric sciences, 01 natural sciences, Grassland, Temperate climate, 2. Zero hunger, Biomass (ecology), geography, geography.geographical_feature_category, Primary production, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Crop rotation, 13. Climate action, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Ecosystem respiration, Agronomy and Crop Science, 010606 plant biology & botany
Abstract: Croplands and grasslands are agricultural systems that contribute to land–atmosphere exchanges of carbon (C). We evaluated and compared gross primary production (GPP), ecosystem respiration (RECO), net ecosystem exchange (NEE) of CO2, and two derived outputs - C use efficiency (CUE=-NEE/GPP) and C emission intensity (IntC= -NEE/Offtake [grazed or harvested biomass]). The outputs came from 23 models (11 crop-specific, eight grassland-specific, and four models covering both systems) at three cropping sites over several rotations with spring and winter cereals, soybean and rapeseed in Canada, France and India, and two temperate permanent grasslands in France and the United Kingdom. The models were run independently over multi-year simulation periods in five stages (S), either blind with no calibration and initialization data (S1), using historical management and climate for initialization (S2), calibrated against plant data (S3), plant and soil data together (S4), or with the addition of C and N fluxes (S5). Here, we provide a framework to address methodological uncertainties and contextualize results. Most of the models overestimated or underestimated the C fluxes observed during the growing seasons (or the whole years for grasslands), with substantial differences between models. For each simulated variable, changes in the multi-model median (MMM) from S1 to S5 was used as a descriptor of the ensemble performance. Overall, the greatest improvements (MMM approaching the mean of observations) were achieved at S3 or higher calibration stages. For instance, grassland GPP MMM was equal to 1632 g C m−2 yr-1 (S5) while the observed mean was equal to 1763 m-2 yr-1 (average for two sites). Nash-Sutcliffe modelling efficiency coefficients indicated that MMM outperformed individual models in 92.3 % of cases. Our study suggests a cautious use of large-scale, multi-model ensembles to estimate C fluxes in agricultural sites if some site-specific plant and soil observations are available for model calibration. The further development of crop/grassland ensemble modelling will hinge upon the interpretation of results in light of the way models represent the processes underlying C fluxes in complex agricultural systems (grassland and crop rotations including fallow periods). info:eu-repo/semantics/acceptedVersion
Published: 2020
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33. The changing faces of soil organic matter research

Author: Pete Smith, Margaret S. Torn, Suzanne Lutfalla, Jean-François Soussana, William J. Riley, Michael W. I. Schmidt, Institute of Biological and Environmental Sciences [Aberdeen], University of Aberdeen, Collège de Direction (CODIR), Institut National de la Recherche Agronomique (INRA), Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Department of Geography, University of Zurich, Universität Zürich [Zürich] = University of Zurich (UZH), project N-Circle [BB/N013484/1], project DEVIL [NE/M021327/1], project U-GRASS [NE/M017125/1], U.S. Department of Energy [DE-AC02-05CH11231], and Smith, Pete
Subjects: Crop and Pasture Production, 010504 meteorology & atmospheric sciences, Life on Land, UFSP13-8 Global Change and Biodiversity, [SDV]Life Sciences [q-bio], Biodiversity, Plant Biology, Soil Science, Climate change, 01 natural sciences, 910 Geography & travel, 1111 Soil Science, 0105 earth and related environmental sciences, 2. Zero hunger, Soil health, Agroforestry, business.industry, Soil organic matter, Agronomy & Agriculture, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Soil quality, 10122 Institute of Geography, 13. Climate action, Agriculture, Soil Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Soil fertility, business
Abstract: © 2017 British Society of Soil Science For the 70th Anniversary of the establishment of the British Society of Soil Science, this short paper explores the idea that research on soil organic matter has remained a central theme within soil science over the past 70 years, albeit with changing emphasis and application. The number of publications on soil organic matter has increased greatly in recent decades; for example, there were almost 35 000 journal papers with this theme in the decade 2007–2016. Several topics in research on soil organic matter, such as soil fertility, have endured for a number of decades, with publications found on soil organic matter and fertility in the decade 1947–1956. A search with other keywords occurring with soil, such as climate change, biodiversity, fertility, quality, health and security, showed that several topics did not appear before the 1970s and 1980s, but since then the sub-topics and applications have diversified. Carbon is a keyword that has become more associated with publications on soil organic matter; carbon is in over half of soil organic matter publications of the last decade. A closer examination of research on agricultural soil carbon sequestration since 1990 reveals that the focus of papers in the literature has changed over this period. A closer examination of papers on modelling shows that the next generation of soil organic matter models is developing from pseudo first-order decay models using conceptual pools and prescribed controls of turnover time to vertically resolved, microbially explicit models representing mineral surface and plant interactions. Given its higher policy profile during the last 2 years, research on soil organic matter and soil carbon sequestration is predicted to have a bright future. Highlights: The number of publications on soil organic matter has increased greatly in recent decades. Soil fertility research has endured for many decades, whereas other topics have diversified. Soil organic matter has been increasingly associated with carbon, which has changed the focus of papers since 1990. Expanding policy attention to soil organic matter research during the last 2 years suggests a bright future.
Published: 2017
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34. L’agroécologie : des recherches pour la transition des filières et des territoires

Author: Thierry Caquet, Chantal Gascuel, Michèle Tixier-Boichard, Benoit Dedieu, Cécile Détang-Dessendre, Pierre Dupraz, Philippe Hinsinger, Françoise Médale, Xavier Reboud, Jean-François Soussana, Alban THOMAS, INRAE, directeur scientifique Environnement, INRAE, Sol-Hydrologie, directrice scientifique adjointe Environnement et UMR SAS Rennes, INRAE, Génétique animale, UMR GABI Jouy-en-Josas, INRAE, chef du département Terra, INRAE, Économie, directrice scientifique adjointe Agriculture, INRAE, Économie, UMR Smart, Rennes, Département agronomie et sciences de l'environnement pour les agroécosystèmes (AgroEcoSystem), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), INRAE, cheffe du département Physiologie animale et système d’élevage, Agroécologie [Dijon], Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, INRAE, vice-président International, INRAE, chef du département Éco Socio, Thierry Caquet, Chantal Gascuel, Michèle Tixier-Boichard, Sol Agro et hydrosystème Spatialisation (SAS), AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Génétique Animale et Biologie Intégrative (GABI), Université Paris-Saclay-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département Physiologie Animale et Systèmes d'Elevage (PHASE), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National de la Recherche Agronomique (INRA), and EL Mjiyad, Noureddine
Subjects: [SDE] Environmental Sciences, [SDE]Environmental Sciences
Abstract: International audience; L’agroécologie a été choisie par l’Inra comme l’un des chantiers de prospective interdisciplinaire destiné à identifier les fronts de recherche en réponse à de grands défis sociétaux. Quatre-vingt chercheurs ont dressé un bilan, et proposé des pistes de recherche pour l’agroécologie, et cet ouvrage en synthétise les principales conclusions. L’agroécologie, en tant que discipline scientifique, remettant l’écologie au centre de la conception des systèmes agricoles, est maintenant bien présente. Diversifier le vivant dans des agroécosystèmes est une visée à large spectre, pour les rendre plus robustes, plus résilients. Les recherches en génétique et en écologie du paysage sont mobilisées pour que l’agroécologie utilise des leviers de la parcelle au paysage. La modélisation des systèmes agroécologiques se développe pour mieux comprendre les interactions biotiques et abiotiques multiples, les prédire, et commencer à piloter certains systèmes. La diversification du vivant dans la production agricole (espèces, variétés, successions culturales, etc.) conduit à des produits plus variés. Les conséquences seront importantes sur les filières, ou plus exactement sur les systèmes agri-alimentaires, allant du mode de production aux produits consommés. Ces changements s’inscrivent sur le long terme. La transition agroécologique, adaptative, se coconstruisant avec les acteurs, est en soi un sujet de recherche, et pourra s’appuyer sur des dispositifs expérimentaux, des exploitations agricoles, des territoires d’innovation.
Published: 2020

35. The 4p1000 initiative: Opportunities, limitations and challenges for implementing soil organic carbon sequestration as a sustainable development strategy

Author: Lydie-Stella Koutika, David Whitehead, Pete Smith, Martin Kaonga, Eva K. Wollenberg, Claire Chenu, Jagdish K. Ladha, Beata Emoke Madari, Jean-François Soussana, Brahim Soudi, Magaly García Cardenas, Cornelia Rumpel, Yasuhito Shirato, Farshad Amiraslani, Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris), Institut National de la Recherche Agronomique (INRA)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), University of Tehran, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Université Paris Saclay (COmUE), Universidad Mayor de San Andrés (UMSA), Cambridge Center for Environment, Centre de Recherche sur la Durabilité et la Productivité des Plantations Industrielles (CRDPI), Department of Plant Sciences, University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Empresa Brasileira de Pesquisa Agropecuária (Embrapa), Ministério da Agricultura, Pecuária e Abastecimento [Brasil] (MAPA), Governo do Brasil-Governo do Brasil, National Agriculture and Food Research Organization (NARO), Institute of Biological and Environmental Sciences [Aberdeen], University of Aberdeen, Rabat, Morocco, Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Manaaki Whenua – Landcare Research [Lincoln], University of Vermont [Burlington], Consultative Group on International Agricultural Research (CGIAR), and University of California-University of California
Subjects: Carbon sequestration, [SDV]Life Sciences [q-bio], Geography, Planning and Development, 010501 environmental sciences, 01 natural sciences, 12. Responsible consumption, Soil, 11. Sustainability, Environmental Chemistry, Climate change, Environmental planning, 0105 earth and related environmental sciences, 2. Zero hunger, Sustainable development, Ecology, 04 agricultural and veterinary sciences, General Medicine, Soil carbon, Food security, 15. Life on land, 13. Climate action, Perspective, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Business
Abstract: International audience; Climate change adaptation, mitigation and food security may be addressed at the same time by enhancing soil organic carbon (SOC) sequestration through environmentally sound land management practices. This is promoted by the “4 per 1000” Initiative, a multi-stakeholder platform aiming at increasing SOC storage through sustainable practices. The scientific and technical committee of the Initiative is working to identify indicators, research priorities and region-specific practices needed for their implementation. The Initiative received its name due to the global importance of soils for climate change, which can be illustrated by a thought experiment showing that an annual growth rate of only 0.4% of the standing global SOC stocks would have the potential to counterbalance the current increase in atmospheric CO2. However, there are numerous barriers to the rise in SOC stocks and while SOC sequestration can contribute to partly offsetting greenhouse gas emissions, its main benefits are related to increased soil quality and climate change adaptation. The Initiative provides a collaborative platform for policy makers, practitioners, scientists and stakeholders to engage in finding solutions. Criticism of the Initiative has been related to the poor definition of its numerical target, which was not understood as an aspirational goal. The objective of this paper is to present the aims of the initiative, to discuss critical issues and to present challenges for its implementation. We identify barriers, risks and trade-offs and advocate for collaboration between multiple parties in order to stimulate innovation and to initiate the transition of agricultural systems toward sustainability.
Published: 2020
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36. Which practices co‐deliver food security, climate change mitigation and adaptation, and combat land degradation and desertification?

Author: Pete Smith, Giacomo Grassi, Cristina Arias-Navarro, Mark Rounsevell, Donovan Campbell, Dorothy Kalule Nampanzira, Nobuko Saigusa, Katherine Calvin, Vladimir Korotkov, Almut Arneth, Johnson Nkem, Ephraim Nkonya, Anh Le Hoang, Jo House, Francesco Cherubini, Frances Manning, Miguel Angel Taboada, Annette Cowie, Pamela McElwee, Stephanie Roe, Jean-François Soussana, Matteo Vizzarri, Shuaib Lwasa, Institute of Biological & Environmental Sciences, University of Aberdeen, Joint Global Change Research Institute, Pacific Northwest National Laboratory (PNNL)-University of Maryland [College Park], University of Maryland System-University of Maryland System, United Nations Economic Commission for Africa (UNECA), United Nations, The University of the West Indies, Department of Energy and Process Engineering [Trondheim] (EPT NTNU), Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU)-Norwegian University of Science and Technology (NTNU), European Commission - Joint Research Centre [Ispra] (JRC), Yu. A. Izrael Institute of Global Climate and Ecology (IGCE), the Russian Academy of Sciences [Moscow, Russia] (RAS), Ministry of Agriculture and Rural Development [Hanoï] (MARD), Department of Geography, Makerere University [Kampala, Ouganda] (MAK), Department of Human Ecology, Rutgers, The State University of New Jersey [New Brunswick] (RU), Rutgers University System (Rutgers)-Rutgers University System (Rutgers), International Food Policy Research Institute [Washington] (IFPRI), Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Center for Global Environmental Research, National Institute for Environmental Studies, Collège de Direction (CODIR), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Natural Resources Research Center (CIRN), National Agricultural Technology Institute (INTA), Ciudad Autónoma de Buenos Aires-Ciudad Autónoma de Buenos Aires, Department of Livestock and Industrial Resources, School of Geographical Sciences [Bristol], University of Bristol [Bristol], Department of Environmental Sciences, University of Virginia, Climate Focus B.V., New South Wales Department of Primary Industries (NSW DPI), Karlsruhe Institute of Technology (KIT), Institute of Geography, University of Edinburgh, UKRI NE/M021327/1EP/M013200/1NE/M016900/1UKERC NE/P019455/1BB/N013484/1European Union (EU)774378773901774124776810Wellcome Trust Research Council of Norway286773257622281113294534IPCC Trust Fund, European Project: 774378,Horizon 2020,CIRCASA(2017), and University of Virginia [Charlottesville]
Subjects: 0106 biological sciences, Invited Primary Research Article, Conservation of Natural Resources, 010504 meteorology & atmospheric sciences, media_common.quotation_subject, Acclimatization, Climate Change, demand management, Land management, adaptation, 010603 evolutionary biology, 01 natural sciences, risk management, 12. Responsible consumption, Ecosystem services, Food Supply, mitigation, co‐benefits, 11. Sustainability, ddc:550, co-benefits, Environmental Chemistry, Environmental planning, Risk management, 0105 earth and related environmental sciences, General Environmental Science, media_common, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, 2. Zero hunger, Global and Planetary Change, Food security, Ecology, business.industry, land degradation, land management, Agriculture, food security, 15. Life on land, desertification, practice, Earth sciences, Climate change mitigation, Desertification, 13. Climate action, adverse side effects, Land degradation, Business
Abstract: There is a clear need for transformative change in the land management and food production sectors to address the global land challenges of climate change mitigation, climate change adaptation, combatting land degradation and desertification, and delivering food security (referred to hereafter as “land challenges”). We assess the potential for 40 practices to address these land challenges and find that: Nine options deliver medium to large benefits for all four land challenges. A further two options have no global estimates for adaptation, but have medium to large benefits for all other land challenges. Five options have large mitigation potential (>3 Gt CO2eq/year) without adverse impacts on the other land challenges. Five options have moderate mitigation potential, with no adverse impacts on the other land challenges. Sixteen practices have large adaptation potential (>25 million people benefit), without adverse side effects on other land challenges. Most practices can be applied without competing for available land. However, seven options could result in competition for land. A large number of practices do not require dedicated land, including several land management options, all value chain options, and all risk management options. Four options could greatly increase competition for land if applied at a large scale, though the impact is scale and context specific, highlighting the need for safeguards to ensure that expansion of land for mitigation does not impact natural systems and food security. A number of practices, such as increased food productivity, dietary change and reduced food loss and waste, can reduce demand for land conversion, thereby potentially freeing‐up land and creating opportunities for enhanced implementation of other practices, making them important components of portfolios of practices to address the combined land challenges., There is a clear need for transformative change in the land management and food production sectors to address the global land challenges of climate change mitigation, climate change adaptation, combatting land degradation and desertification, and delivering food security (referred to hereafter as “land challenges”). We assess the potential for 40 practices to address these land challenges and find that most practices deliver across all land challenges. Some practices could result in competition for land, but those that reduce demand for land conversion potentially free‐up land, creating opportunities for enhanced implementation of other practices, making them important for addressing combined land challenge.
Published: 2020
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37. Response to 'The '4p1000' initiative: A new name should be adopted' by Baveye and White (2019)

Author: Pete Smith, Beata Emoke Madari, Yasuhito Shirato, Jagdish K. Ladha, Farshad Amiraslani, Cornelia Rumpel, David Whitehead, Brahim Soudi, Magali García Cárdenas, Claire Chenu, Martin Kaonga, Jean-François Soussana, Eva K. Wollenberg, Lydie-Stella Koutika, Institut d'écologie et des sciences de l'environnement de Paris (IEES (UMR_7618 / UMR_D_242 / UMR_A_1392 / UM_113) ), Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Tehran, Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Paris-Saclay, Universidad Mayor de San Andrés (UMSA), Cambridge Center for Environment, Centre de Recherche sur la Durabilité et la Productivité des Plantations Industrielles (Dispositif en Partenariat) (CRDPI), UR Génétique Amélioration Diversité-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of California [Davis] (UC Davis), University of California, Brazilian Agricultural Research Corporation (Embrapa), National Agriculture and Food Research Organization, University of Aberdeen, Institut Agronomique et Vétérinaire Hassan II - IAV (MOROCCO) (IAV), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Manaaki Whenua-Landcare Research, University of Vermont [Burlington], Institut d'écologie et des sciences de l'environnement de Paris (iEES Paris ), Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), AgroParisTech-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), National Agriculture and Food Research Organization (NARO), Manaaki Whenua – Landcare Research [Lincoln], Sorbonne Université (SU), Institut de Recherche pour le Développement (IRD), Université de loraine, Technical University of Munich (TUM), Institut national de la recherche agronomique [Maroc] (INRA Maroc), Centre National de la Recherche Scientifique (CNRS), Institute of Software Chinese Academy of Sciences [Beijing], Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-UR Génétique Amélioration Diversité, University of California (UC), and Institut Agronomique et Vétérinaire Hassan II (IAV Hassan II)
Subjects: [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Carbon Sequestration, White (horse), 010504 meteorology & atmospheric sciences, Ecology, [SDE.MCG]Environmental Sciences/Global Changes, Ecology (disciplines), [SDV]Life Sciences [q-bio], Geography, Planning and Development, Comment, Environmental ethics, General Medicine, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, 010501 environmental sciences, Sustainable Development, 01 natural sciences, Carbon, Soil, Geography, [SDE]Environmental Sciences, Environmental Chemistry, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences
Abstract: Response to “The “4p1000” initiative: A new name should be adopted” by Baveye and White (2019)
Published: 2020
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38. Elevated CO 2 maintains grassland net carbon uptake under a future heat and drought extreme

Author: Sébastien Devidal, Christophe Escape, Jean-François Soussana, Lionel Thiery, Nathalie Fromin, Jacques Roy, Catherine Picon-Cochard, Clément Piel, Marc Defossez, Angela Augusti, Alexandru Milcu, Olivier Darsonville, Marie-Lise Benot, Florence Volaire, Damien Landais, Michael Bahn, Olivier Ravel, Écotron Européen de Montpellier - UPS 3248, Centre National de la Recherche Scientifique (CNRS), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Biodiversité, Gènes et Communautés, Institut National de la Recherche Agronomique (INRA), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Universität Innsbruck [Innsbruck], Collège de Direction, Écotron Européen de Montpellier, Unité de recherche sur l'Ecosystème Prairial (UREP), Biodiversité, Gènes & Communautés (BioGeCo), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Collège de Direction (CODIR), ANR VALIDATE project, ECOTRONS Research Infrastructure ('Investissement d'Avenir' AnaEE-France ANR-11-INBS-0001), European FP7 ExpeER Transnational Access program, OAD WTZ-programme Austria-France, FWF Project P28572-B22., ANR-07-VULN-0011,VALIDATE,Vulnérabilité des prairies et des élevages au changement climatique et aux événements extrêmes.(2007), ANR-11-INBS-0001,ANAEE-FR,ANAEE-Services(2011), European Project: 266018,EC:FP7:KBBE,FP7-KBBE-2010-4,ANIMALCHANGE(2011), European Project: 262060,EC:FP7:INFRA,FP7-INFRASTRUCTURES-2010-1,EXPEER(2010), Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Paul-Valéry - Montpellier 3 (UM3), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud])
Subjects: 0106 biological sciences, Hot Temperature, 010504 meteorology & atmospheric sciences, Atmospheric sciences, 01 natural sciences, Grassland, Soil, chemistry.chemical_compound, Climate change, Milieux et Changements globaux, ComputingMilieux_MISCELLANEOUS, 2. Zero hunger, changement climatique, Multidisciplinary, geography.geographical_feature_category, écotron, Biological Sciences, Droughts, Carbon dioxide, élevation du gaz carbonique, [SDE.MCG]Environmental Sciences/Global Changes, chemistry.chemical_element, [object Object], Carbon Cycle, Carbon cycle, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, climat extrème, Carbon fluxes, Grassland ecosystem, Ecosystem, 0105 earth and related environmental sciences, Hydrology, geography, flux de carbone, Carbon Dioxide, Extreme events, 15. Life on land, écosystème prairial, Carbon, Plant Leaves, croissance racinaire, chemistry, 13. Climate action, Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Plant nutrition, Intensity (heat transfer), [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis, 010606 plant biology & botany
Abstract: International audience; Extreme climatic events (ECEs) such as droughts and heat waves are predicted to increase in intensity and frequency and impact the terrestrial carbon balance. However, we lack direct experimental evidence of how the net carbon uptake of ecosystems is affected by ECEs under future elevated atmospheric CO2 concentrations (eCO2). Taking advantage of an advanced controlled environment facility for ecosystem research (Ecotron), we simulated eCO2 and extreme cooccurring heat and drought events as projected for the 2050s and analyzed their effects on the ecosystem-level carbon and water fluxes in a C3 grassland. Our results indicate that eCO2 not only slows down the decline of ecosystem carbon uptake during the ECE but also enhances its recovery after the ECE, as mediated by increases of root growth and plant nitrogen uptake induced by the ECE. These findings indicate that, in the predicted near future climate, eCO2 could mitigate the effects of extreme droughts and heat waves on ecosystem net carbon uptake.
Published: 2016
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39. Matching policy and science: Rationale for the '4 per 1000-soils for food security and climate' initiative

Author: Suzanne Lutfalla, Pete Smith, Meryl Richards, Emmanuel Torquebiau, Philippe Ciais, Jean-Luc Chotte, Fiona Ehrhardt, Rattan Lal, Jean-François Soussana, Petr Havlik, Christine Lamanna, Eva K. Wollenberg, Todd S. Rosenstock, Collège de Direction (CODIR), Institut National de la Recherche Agronomique (INRA), Consultative Group on International Agricultural Research (CGIAR), International Institute for Applied Systems Analysis (IIASA), University of Vermont [Burlington], Institut de Recherche pour le Développement (IRD), Agroécologie et Intensification Durables des cultures annuelles (UPR AIDA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), University of Aberdeen, Ohio State University [Columbus] (OSU), French Ministry for Research and Higher Education, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Subjects: P33 - Chimie et physique du sol, S01 - Nutrition humaine - Considérations générales, Carbon sequestration, Carbone, P40 - Météorologie et climatologie, Natural resource economics, [SDV]Life Sciences [q-bio], Soil Science, Climate change, 7. Clean energy, 12. Responsible consumption, Matière organique du sol, United Nations Framework Convention on Climate Change, 11. Sustainability, Earth-Surface Processes, Changement climatique, 2. Zero hunger, Sustainable development, Food security, business.industry, Soil organic carbon, Global warming, 1. No poverty, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, séquestration du carbone, sécurité alimentaire, 13. Climate action, Agriculture, Greenhouse gas, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, business, Agronomy and Crop Science
Abstract: International audience; At the 21st session of the United Nations Framework Convention on Climate Change (UNFCCC, COP21), a voluntary action plan, the '4 per 1000 Initiative: Soils for Food Security and Climate' was proposed under the Agenda for Action. The Initiative underlines the role of soil organic matter (SOM) in addressing the three-fold challenge of food and nutritional security, adaptation to climate change and mitigation of human-induced greenhouse gases (GHGs) emissions. It sets an ambitious aspirational target of a 4 per 1000 (i.e. 0.4%) rate of annual increase in global soil organic carbon (SOC) stocks, with a focus on agricultural lands where farmers would ensure the carbon stewardship of soils, like they manage day-to-day multipurpose production systems in a changing environment. In this paper, the opportunities and challenges for the 4 per 1000 initiative are discussed. We show that the 4 per 1000 target, calculated relative to global top soil SOC stocks, is consistent with literature estimates of the technical potential for SOC sequestration, though the achievable potential is likely to be substantially lower given socio-economic constraints. We calculate that land-based negative emissions from additional SOC sequestration could significantly contribute to reducing the anthropogenic CO2 equivalent emission gap identified from Nationally Determined Contributions pledged by countries to stabilize global warming levels below 2 degrees C or even 1.5 degrees C under the Paris agreement on climate. The 4 per 1000 target could be implemented by taking into account differentiated SOC stock baselines, reversing the current trend of huge soil CO2 losses, e.g. from agriculture encroaching peatland soils. We further discuss the potential benefits of SOC stewardship for both degraded and healthy soils along contrasting spatial scales (field, farm, landscape and country) and temporal (year to century) horizons. Last, we present some of the implications relative to non-CO2 GHGs emissions, water and nutrients use as well as co-benefits for crop yields and climate change adaptation. We underline the considerable challenges associated with the non-permanence of SOC stocks and show how the rates of adoption and the duration of improved soil management practices could alter the global impacts of practices under the 4 per 1000 initiative. We conclude that the 4 per 1000 initiative has potential to support multiple sustainable development goals (SDGs) of the 2030 Agenda. It can be regarded as no-regret since increasing SOC in agricultural soils will contribute to food security benefits that will enhance resilience to climate change. However, social, economic and environmental safeguards will be needed to ensure an equitable and sustainable implementation of the 4 per 1000 target.
Published: 2019
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40. What fluxes are telling us so far ? A naïve reanalysis of CO2 fluxes over the past 18 years

Author: Virginie Moreaux, Paul Berbigier, Daniel Berveiller, Jean-Marc Bonnefond, Christophe Chipeaux, Nicolas Delpierre, Olivier Darsonville, Eric Dufrene, André Granier, Richard Joffre, Katja Klumpp, sebastien lafont, Jean-Michel Limousin, Bernhard Longdoz, Denis Loustau, Kamel Piquemal, Jean-Yves Pontarlier, Serge Rambal, Jean-François Soussana, Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Université Paris-Sud - Paris 11 (UP11), Ecologie des Forêts Méditerranéennes (URFM), Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), Université de Liège, Ecole nationale supérieure des ingénieurs en arts chimiques et technologiques, Collège de Direction (CODIR), Université Paris-Saclay, Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL), Université Paul-Valéry - Montpellier 3 (UPVM)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Ecole nationale supérieure des ingénieurs en arts chimiques et technologiques (ENSIACET), Institut National Polytechnique (Toulouse) (Toulouse INP), and Université de Toulouse (UT)-Université de Toulouse (UT)
Subjects: [SDV]Life Sciences [q-bio], [SDE]Environmental Sciences, ComputingMilieux_MISCELLANEOUS
Abstract: National audience
Published: 2018

41. Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe

Author: Jean-François Soussana, Philippe Ciais, Tao Wang, Raphaël Martin, Romain Lardy, Anne Cozic, Katja Klumpp, Nicolas Viovy, Nicolas Vuichard, Jinfeng Chang, Anne-Isabelle Graux, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Modélisation des Surfaces et Interfaces Continentales (MOSAIC), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), ICOS-ATC (ICOS-ATC), Calcul Scientifique (CALCULS), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), Institut National de la Recherche Agronomique (INRA), CarboEurope IP, Nitroeurope project, Commissariat à l'Energie Atomique, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), and Unité de recherche sur l'Ecosystème Prairial (UREP)
Subjects: 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Eddy covariance, modèle, Atmospheric sciences, 01 natural sciences, modèle orchidée, Grassland, Hydrology (agriculture), Ecosystem model, Grazing, gestion de la prairie, Ecosystem, pasim, Leaf area index, 0105 earth and related environmental sciences, 2. Zero hunger, geography, geography.geographical_feature_category, flux de carbone, Agroforestry, lcsh:QE1-996.5, prairie, 04 agricultural and veterinary sciences, 15. Life on land, lcsh:Geology, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Ecosystem respiration
Abstract: This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland–atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal–vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m−2 yr−1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.
Published: 2018
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42. The greenhouse gas balance of European grasslands

Author: Martin Wattenbach, Philippe Ciais, Rene Dechow, Pete Smith, Sebastiaan Luyssaert, S. L. Piao, E.-D. Schulze, Fabienne Maignan, Jean-François Soussana, Christof Ammann, Ivan A. Janssens, J. Lathière, Annette Freibauer, A. Don, and Nicolas Vuichard
Subjects: geography, geography.geographical_feature_category, Agronomy, Ecosystem model, Grazing, Eddy covariance, Environmental science, Carbon sink, Primary production, Ecosystem, Carbon sequestration, Atmospheric sciences, Grassland
Abstract: The long-term carbon balance (NBP) of grasslands is estimated by combining scarce multi-year eddy-covariance observations at ecosystem observation sites where information on carbon inputs and harvesting removals is available. Following accounting for carbon leached to rivers, we estimated grasslands to be net carbon sinks of 74±10 g C m−2 yr−1. Uncertainties arise from the small number of sites and the short measurement period. Only 11 sites, out of a total of 20 grassland sites in Europe where eddy covariance systems are installed, were set-up for estimating NBP. These 11 selected sites are representative of intensive management practice and we lack information on disturbance history, such as plowing. This suggests that the grassland NBP estimate is likely biased towards overestimating the sink, compared to the European average. Direct measurements of Net Primary Productivity (NPP) are not possible in grasslands given permanent biomass removal by grazing and mowing, uncertainties in rhizodeposition and production of volatile organic carbon compounds lost to the atmosphere. Therefore, the grassland process-based ecosystem model PASIM was used to estimate the spatial-temporal distribution of NPP, providing a European average value of 750±150 g C across extensively grazed, intensively grazed pastures, and forage production systems. In Europe the NPP of grasslands seems higher than that of croplands and forests. The carbon sequestration efficiency of grasslands, defined as the ratio of NBP to NPP, amounts to 0.09±0.10. Therefore, per unit of carbon input, grasslands sequester 3–4 times more carbon in the soil than forests do, making them a good candidate for managing onsite carbon sinks. When using the 100 yr greenhouse warming potential for CH4 and N2O, their emissions due to management of grasslands together offset roughly 70–80% of the carbon sink. Uncertainties on the European grassland greenhouse gas balance, including CO2, CH4 and N2O fluxes are likely to be reduced in the near future, with data being collected from more sites, and improved up-scaling methods.
Published: 2018

43. Long-term impacts of season of grazing on soil carbon sequestration and selected soil properties in the arid Eastern Cape, South Africa

Author: Abubeker Hassen, J.C.O. Du Toit, Katja Klumpp, Deribe G. Talore, Eyob Habte Tesfamariam, Jean-François Soussana, University of Pretoria [South Africa], Grootfontein Agricultural Development Institute, Partenaires INRAE, UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), and Institut National de la Recherche Agronomique (INRA)
Subjects: Soil biodiversity, [SDE.MCG]Environmental Sciences/Global Changes, Soil Science, Plant Science, 010501 environmental sciences, 01 natural sciences, Soil compaction (agriculture), Nutrient, saison de pâturage, Grazing, carbone organique du sol, azote total, 0105 earth and related environmental sciences, 2. Zero hunger, Agroforestry, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Infiltration (hydrology), écosystème aride, Agronomy, matière organique, Soil water, Exclosure, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract: The Karoo biomes of South Africa are major feed resources for livestock farming, yet soil nutrient depletion and degradation is a major problem. The objective of this study was to assess impacts of long-term (> 75 years) grazing during spring (SPG), summer (SUG), winter (WG) and exclosure (non-grazed control) treatments on soil nutrients, penetration resistance and infiltration tests. A soil sampling campaign was carried out to collect soil to a depth of 60 cm to analyse bulk density, soil physical and chemical parameters as well as soil compaction and infiltration. Generally, grazing treatments reduced soil organic C (SOC) stocks and C:N ratios, and modified soil properties. There was higher SOC stock (0.128 Mg ha(-1) yr(-1)) in the exclosure than in the SPG (0.096 Mg ha(-1) yr(-1)), SUG (0.099 Mg ha(-1) yr(-1)) and WG (0.105 Mg ha(-1) yr(-1)). The C:N ratios exhibited similar pattern to that of C. From the grazing treatments, the WG demonstrated 7 to 10 % additional SOC stock over the SPG and SUG, respectively. Short period animal exclusion could be an option to be considered to improve plant nutrients in sandy soils of South Africa. However, this may require a policy environment which supports stock exclusion from such areas vulnerable to land degradation, nutrient and C losses by grazing-induced vegetation and landscape changes.
Published: 2015
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44. The use of biogeochemical models to evaluate mitigation of greenhouse gas emissions from managed grasslands

Author: Marco Carozzi, Lutz Merbold, Kate Gongadze, Susanne Rolinski, Pete Smith, Christopher D. Dorich, Paul C. D. Newton, Kathrin Fuchs, Mark A. Liebig, Nuala Fitton, Renáta Sándor, Robert M. Rees, Val Snow, Katja Klumpp, Sylvie Recous, Fiona Ehrhardt, Raphaël Martin, Gianni Bellocchi, Lorenzo Brilli, Jean-François Soussana, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Centre for Agricultural Research [Budapest] (ATK), Hungarian Academy of Sciences (MTA), Collège de Direction, Institut National de la Recherche Agronomique (INRA), Dipartimento di Scienze delle Produzioni Agroalimentari e dell’Ambiente (DISPAA ), Climate Agriculture Group, Agroscope, Fractionnement des AgroRessources et Environnement - UMR-A 614 (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), School of Biological Sciences [Aberdeen], University of Aberdeen, Lincoln Research Centre, AgResearch Ltd, Colorado State University [Fort Collins] (CSU), Department of Environmental Systems Science, Institute Agricultural Science (ETH Zurich), Sustanaible soils and grassland Department, Rothamsted Research, NGPRL, United States Department of Agriculture - Agricultural Research Service, Scotland's Rural College (SCUR), Postdam Institute for Climate Impact Research (PIK), ADEME, Collège de Direction (CODIR), Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), USDA-ARS : Agricultural Research Service, Scotland's Rural College (SRUC), and Potsdam Institute for Climate Impact Research (PIK)
Subjects: 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], chargement en betail, GHG emision intensity, simulation models, 01 natural sciences, Grassland, cycle de l'azote, Grazing, gaz à effet de serre, méthane, Waste Management and Disposal, 2. Zero hunger, geography.geographical_feature_category, Livestock density, prairie, nitrogen fertilization, 04 agricultural and veterinary sciences, Pollution, fertilisation azotée, Process-based model, France, Sensitivity analysis, Cycling, GHG emission intensity, cycle du carbone, Biogeochemical cycle, Environmental Engineering, modèle de simulation, suisse, Nitrogen fertilization, greenhouse gases, carbon cycle, nitrogen cycle, Environmental Chemistry, Ecosystem, 0105 earth and related environmental sciences, geography, royaume uni, Primary production, 15. Life on land, états-unis, united kingdom, Arid, grazing intensity, Agronomy, 13. Climate action, marsh gas, Greenhouse gas, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, intensité de pâturage, grassland, usa
Abstract: Simulation models quantify the impacts on carbon (C) and nitrogen (N) cycling in grassland systems caused by changes in management practices. To support agricultural policies, it is however important to contrast the responses of alternative models, which can differ greatly in their treatment of key processes and in their response to management. We applied eight biogeochemical models at five grassland sites (in France, New Zealand, Switzerland, United Kingdom and United States) to compare the sensitivity of modelled C and N fluxes to changes in the density of grazing animals (from 100% to 50% of the original livestock densities), also in combination with decreasing N fertilization levels (reduced to zero from the initial levels). Simulated multi-model median values indicated that input reduction would lead to an increase in the C sink strength (negative net ecosystem C exchange) in intensive grazing systems: −64 ± 74 g C m−2 yr−1 (animal density reduction) and −81 ± 74 g C m−2 yr−1 (N and animal density reduction), against the baseline of −30.5 ± 69.5 g C m−2 yr−1 (LSU [livestock units] ≥ 0.76 ha−1 yr−1). Simulations also indicated a strong effect of N fertilizer reduction on N fluxes, e.g. N2O-N emissions decreased from 0.34 ± 0.22 (baseline) to 0.1 ± 0.05 g N m−2 yr−1 (no N fertilization). Simulated decline in grazing intensity had only limited impact on the N balance. The simulated pattern of enteric methane emissions was dominated by high model-to-model variability. The reduction in simulated offtake (animal intake + cut biomass) led to a doubling in net primary production per animal (increased by 11.6 ± 8.1 t C LSU−1 yr−1 across sites). The highest N2O-N intensities (N2O-N/offtake) were simulated at mown and extensively grazed arid sites. We show the possibility of using grassland models to determine sound mitigation practices while quantifying the uncertainties associated with the simulated outputs.
Published: 2018
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45. Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N2O emissions

Author: Fiona Ehrhardt, Mark A. Liebig, Raphaël Martin, Jordi Doltra, Russel McAuliffe, Val Snow, Joël Léonard, Andrew D. Moore, Stephanie K. Jones, Lutz Merbold, Pete Smith, Lianhai Wu, Elizabeth A. Meier, Paul C. D. Newton, Arti Bhatia, Gianni Bellocchi, Massimiliano De Antoni Migliorati, Miko U. F. Kirschbaum, Ward Smith, Brian Grant, Renáta Sándor, Joanna Sharp, Lorenzo Brilli, Nuala Fitton, Jean-François Soussana, Elizabeth Pattey, Luca Doro, Katja Klumpp, Christopher D. Dorich, Bruno Basso, Raia Silvia Massad, Sylvie Recous, Patricia Laville, Qing Zhang, Matthew T. Harrison, Sandro José Giacomini, Susanne Rolinski, Mark Lieffering, Peter Grace, Vasileios Myrgiotis, Collège de Direction (CODIR), Institut National de la Recherche Agronomique (INRA), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Queensland University of Technology, Agresearch Ltd, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), University of Aberdeen, Michigan State University [East Lansing], Michigan State University System, Indian Agricultural Research Institute (IARI), Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Catabrian Agricultural Research and Training Center (CIFA), Colorado State University [Fort Collins] (CSU), Università degli Studi di Sassari, Universidade Federal de Santa Maria = Federal University of Santa Maria [Santa Maria, RS, Brazil] (UFSM), Agriculture and Agri-Food [Ottawa] (AAFC), Tasmanian Institute of Agriculture, Scotland's Rural College (SRUC), Manaaki Whenua – Landcare Research [Lincoln], Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Agroressources et Impacts environnementaux (AgroImpact), USDA-ARS : Agricultural Research Service, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Potsdam Institute for Climate Impact Research (PIK), New Zealand Institute for Crop and Food Research, Partenaires INRAE, Rothamsted Research, Chinese Academy of Sciences (CAS), ANR, European Project: 277610,EC:FP7:KBBE,FP7-JPROG-2011-RTD,FACCE CSA(2011), Queensland University of Technology [Brisbane] (QUT), Università degli Studi di Firenze = University of Florence (UniFI), Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Agriculture and Agri-Food (AAFC), Biotechnology and Biological Sciences Research Council (BBSRC), and Universidade Federal de Santa Maria (UFSM)
Subjects: biogeochemical models, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], Climate change, Atmospheric sciences, 01 natural sciences, Grassland, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Environmental Chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, Agricultural productivity, 0105 earth and related environmental sciences, General Environmental Science, agriculture, 2. Zero hunger, Global and Planetary Change, geography, geography.geographical_feature_category, Ecology, Ensemble forecasting, nitrous oxide, Crop yield, Simulation modeling, 04 agricultural and veterinary sciences, benchmarking, climate change, greenhouse gases, soil, yield, Climate change mitigation, Agronomy, 13. Climate action, greenhouse gas, Greenhouse gas, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science
Abstract: International audience; Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N2O)emissions for wheat, maize, rice and temperate grasslands. Using a multi-stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process-based biogeochemical models were assessed individually or as an ensemble against long-term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents.Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grass-land growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E-median for crop grain yields(from 36% at stage 1 down to 4% on average) and grassland productivity (from 44%to 27%) and to a lesser and more variable extent for N2O emissions. Yield-scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three-model ensembles across crop species and field sites. The potential of using process-based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed.
Published: 2018
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46. The '4 per 1 000': Soils for food security and climate Research Program Symposium Soil organic matter management in agriculture – assessing the potential of the 4 per 1000 initiative (https://www.som-management.org/)

Author: Demenois, Julien, Chotte, Jean-Luc, Verger, Charlotte, Jean-François Soussana, and Weill, Claire
Published: 2018
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47. Response to Editor to the comment by SchipperSmith to our paper entitled 'Continuous soil carbon storage of old permanent pastures in Amazonia'

Author: Sébastien Fontaine, Lilian Blanc, Jean-François Soussana, Lise Ponchant, Catherine Picon-Cochard, Vincent Freycon, Clément Stahl, Camille Dezécache, Katja Klumpp, Benoit Burban, Vincent Blanfort, Gaël Alvarez, Damien Bonal, Marcia Mascarenhas Grise, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Ecologie des forêts de Guyane (UMR ECOFOG), Université des Antilles (UA)-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA), Empresa Brasileira de Pesquisa Agropecuária (Embrapa), Ministério da Agricultura, Pecuária e Abastecimento [Brasil] (MAPA), Governo do Brasil-Governo do Brasil, Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agrosystèmes tropicaux (ASTRO), Institut National de la Recherche Agronomique (INRA), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Ecologie et Ecophysiologie Forestières [devient SILVA en 2018] (EEF), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), and ANR-14-EBID-0002,BASIL,Landscape-scale biodiversity and the balancing of provisioning, regulating and supporting ecosystem services(2014)
Subjects: L01 - Elevage - Considérations générales, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], 01 natural sciences, Grassland, [SHS]Humanities and Social Sciences, Soil, K01 - Foresterie - Considérations générales, chronosequence study, General Environmental Science, 2. Zero hunger, Global and Planetary Change, geography.geographical_feature_category, Ecology, Amazon rainforest, Pâturages, 04 agricultural and veterinary sciences, séquestration du carbone, Forêt, [SDE]Environmental Sciences, Écosystème, P33 - Chimie et physique du sol, China, Eddy covariance, chemistry.chemical_element, deep soil c, eddy covariance, Environmental Chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [INFO]Computer Science [cs], 0105 earth and related environmental sciences, geography, continuous c accumulation, Forestry, Soil carbon, 15. Life on land, Déboisement, Carbon, chemistry, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Cycle du carbone
Abstract: International audience; First of all, we recall that the message conveyed in our paper is that Amazonian forest and old tropical pastures act as C sinks by accumulating recurrently (continuously) C in biomass and soil. We do not support the idea that deforestation increases soil C as suggested in the title of Schipper and Smith comment. In our study, pasture C sink was estimated by two independent methods: eddy covariance measurements (Eddy) and a 36-years chronosequence analyzing soil organic C stock to a depth of 100 cm (Chrono). Both methods provide evidence that pastures ≥24 years can restore all or part of C sink of Amazonian forest if sustainable management is applied. Realizing that old pastures accumulate C is crucial in the Amazonian context where pastures are currently replaced by intensive crops (e.g. soybean) inducing a possible loss of this C sink.
Published: 2017
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48. 8.6. Emissions de gaz à effet de serre et changement climatique : conséquences pour l’agriculture

Author: Jean-François Soussana
Published: 2017
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49. Assessing uncertainties in crop and pasture ensemble model simulations of productivity and N

Author: Fiona, Ehrhardt, Jean-François, Soussana, Gianni, Bellocchi, Peter, Grace, Russel, McAuliffe, Sylvie, Recous, Renáta, Sándor, Pete, Smith, Val, Snow, Massimiliano, de Antoni Migliorati, Bruno, Basso, Arti, Bhatia, Lorenzo, Brilli, Jordi, Doltra, Christopher D, Dorich, Luca, Doro, Nuala, Fitton, Sandro J, Giacomini, Brian, Grant, Matthew T, Harrison, Stephanie K, Jones, Miko U F, Kirschbaum, Katja, Klumpp, Patricia, Laville, Joël, Léonard, Mark, Liebig, Mark, Lieffering, Raphaël, Martin, Raia S, Massad, Elizabeth, Meier, Lutz, Merbold, Andrew D, Moore, Vasileios, Myrgiotis, Paul, Newton, Elizabeth, Pattey, Susanne, Rolinski, Joanna, Sharp, Ward N, Smith, Lianhai, Wu, and Qing, Zhang
Subjects: Crops, Agricultural, Nitrous Oxide, Uncertainty, Agriculture, Computer Simulation, Models, Biological, Food Supply
Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi-species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi-model ensembles to predict productivity and nitrous oxide (N
Published: 2017

50. C and N models Intercomparison – benchmark and ensemble model estimates for grassland production

Author: Pete Smith, Sandro José Giacomini, Gianni Bellocchi, Joël Léonard, M. de Antoni Migliorati, Renata Sándor, Chris Dorich, Arti Bhatia, Ward Smith, Paul C. D. Newton, Jordi Doltra, Raia Silvia Massad, Fiona Ehrhardt, Miko U. F. Kirschbaum, Elizabeth Pattey, Matthew T. Harrison, Qing Zhang, Andrew D. Moore, Russell McAuliffe, Mark A. Liebig, Susanne Rolinski, Raphaël Martin, Brian Grant, Vasileios Myrgiotis, Mark Lieffering, Lorenzo Brilli, Jean-François Soussana, Luca Doro, Katja Klumpp, Bruno Basso, Elizabeth A. Meier, Patricia Laville, Sylvie Recous, Val Snow, Peter Grace, Lutz Merbold, Joanna Sharp, Nuala Fitton, Stephanie K. Jones, Lianhai Wu, Institute for Soil Sciences and Agricultural Chemistry (ATK TAKI), Centre for Agricultural Research [Budapest] (ATK), Hungarian Academy of Sciences (MTA)-Hungarian Academy of Sciences (MTA), UR 0874 Unité de recherche sur l'Ecosystème Prairial, Institut National de la Recherche Agronomique (INRA)-Unité de recherche sur l'Ecosystème Prairial (UREP)-Ecologie des Forêts, Prairies et milieux Aquatiques (EFPA), Institut National de la Recherche Agronomique (INRA), Collège de Direction (CODIR), Department of Geological Sciences, Michigan State University [East Lansing], Michigan State University System-Michigan State University System, Indian Agricultural Research Institute (IARI), DISPAA, Università degli Studi di Firenze = University of Florence [Firenze] (UNIFI), Queensland University of Technology, Cantabrian Agricultural Research and Training Centre, Natural Resource Ecology Laboratory [Fort Collins] (NREL), Colorado State University [Fort Collins] (CSU), Desertification Research Group, University of Sassari, Institute of Biological and Environmental Sciences, University of Aberdeen, Soil Department, Federal University of Santa Maria, Agriculture and Agri-Food [Ottawa] (AAFC), Tasmanian Institute of Agriculture, Scotland's Rural College (SRUC), Manaaki Whenua – Landcare Research [Lincoln], Ecologie fonctionnelle et écotoxicologie des agroécosystèmes (ECOSYS), Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Agroressources et Impacts environnementaux (AgroImpact), United States Department of Agriculture, Lincoln Research Centre, AgResearch Ltd, Grasslands Research Centre, Agriculture and Food, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Department of Environmental Systems Science [ETH Zürich] (D-USYS), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Mazingira Centre, International Livestock Research Institute, Black Mountain Laboratories, CSIRO Agriculture Flagship, Fractionnement des AgroRessources et Environnement (FARE), Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA), Potsdam Institute for Climate Impact Research (PIK), Plant & Food Research, Sustainable Soils and Grassland Systems, Rothamsted Research, Institute of Atmospheric Physics [Beijing] (IAP), Chinese Academy of Sciences [Beijing] (CAS), ANR, European Project: 277610, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Collège de Direction, University of Florence (UNIFI), Scotland's Rural College (SCUR), Landcare Research, Unité d'Agronomie de Laon-Reims-Mons (AGRO-LRM), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Fractionnement des AgroRessources et Environnement - UMR-A 614 (FARE), Université de Reims Champagne-Ardenne (URCA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Recherche Agronomique (INRA), New Zealand Institute for Plant and Food Research Limited, Université de Reims Champagne-Ardenne (URCA)-Institut National de la Recherche Agronomique (INRA)-SFR Condorcet, Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS)-Université de Reims Champagne-Ardenne (URCA)-Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Unité de recherche sur l'Ecosystème Prairial (UREP), Università degli Studi di Firenze = University of Florence (UniFI), Queensland University of Technology [Brisbane] (QUT), Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Agriculture and Agri-Food (AAFC), and Biotechnology and Biological Sciences Research Council (BBSRC)-Biotechnology and Biological Sciences Research Council (BBSRC)
Subjects: 010504 meteorology & atmospheric sciences, Calibration (statistics), [SDV]Life Sciences [q-bio], ANPP, Context (language use), Atmospheric sciences, 01 natural sciences, Grassland, Physics::Geophysics, Benchmark (surveying), C-N MIP, Quantitative Biology::Populations and Evolution, model intercomparaison, 0105 earth and related environmental sciences, 2. Zero hunger, geography, geography.geographical_feature_category, Ensemble forecasting, Ecology, Simulation modeling, 04 agricultural and veterinary sciences, General Medicine, 15. Life on land, grassland production, 13. Climate action, Greenhouse gas, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental science, Arable land
Abstract: Much of the uncertainty in crop and grassland model predictions of how arable and grassland systems respond to changes in management and environmental drivers can be attributed to differences in the structure of these models. This has created an urgent need for international bench- marking of models, in which uncertainties are estimated by running several models that simulate the same physical and management conditions (ensemble modelling) to generate expanded envelopes of uncertainty in model predictions (Asseng et al. , 2013). Simulations of C and N fluxes, in particular, are inherently uncertain because they are driven by complex interactions (Sandor et al. , 2016) and complicated by considerable spatial and temporal variability in the measurements. In this context, the Integrative Research Group of the Global Research Alliance (GRA) on Agricultural Greenhouse Gases promotes a coordinated activity across multiple international projects (e.g. C and N Models Inter-comparison and Improvement to assess management options for GHG mitigation in agrosystems worldwide (C-N MIP) and Models4Pastures of the FACCE-JPI, https://www.faccejpi.com) to benchmark and compare simulation models that estimate C – N related outputs (including greenhouse gas emissions) from arable crop and grassland systems (http://globalresearchalliance.org/e/model- intercomparison-on-agricultural-ghg-emissions). This study presents some preliminary results on the uncertainty of outputs from 12 grassland models, whereas exploring differences in model response when increasing data resources are used for model calibration.
Published: 2016
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