{"type": "FeatureCollection", "features": [{"id": "10.1007/s11104-015-2625-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:15:13Z", "type": "Journal Article", "created": "2015-08-08", "title": "Long-Term Impacts Of Season Of Grazing On Soil Carbon Sequestration And Selected Soil Properties In The Arid Eastern Cape, South Africa", "description": "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\u00a0years) 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\u00a0cm 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\u00a0Mg\u00a0ha\u22121\u00a0yr\u22121) in the exclosure than in the SPG (0.096\u00a0Mg\u00a0ha\u22121\u00a0yr\u22121), SUG (0.099\u00a0Mg\u00a0ha\u22121\u00a0yr\u22121) and WG (0.105\u00a0Mg\u00a0ha\u22121\u00a0yr\u22121). The C:N ratios exhibited similar pattern to that of C. From the grazing treatments, the WG demonstrated 7 to 10\u00a0% 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.", "keywords": ["2. Zero hunger", "Soil organic carbon", "[SDE.MCG]Environmental Sciences/Global Changes", "Exclosure", "04 agricultural and veterinary sciences", "Total nitrogen", "15. Life on land", "630", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "[SDE.MCG] Environmental Sciences/Global Changes", "Grazing season", "\u00e9cosyst\u00e8me aride", "13. Climate action", "Arid ecosystem", "mati\u00e8re organique", "saison de p\u00e2turage", "carbone organique du sol", "0401 agriculture", " forestry", " and fisheries", "Organic matter", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "azote total"]}, "links": [{"href": "https://doi.org/10.1007/s11104-015-2625-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11104-015-2625-z", "name": "item", "description": "10.1007/s11104-015-2625-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-015-2625-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-08-09T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2020.114237", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:16:35Z", "type": "Journal Article", "created": "2020-02-06", "title": "Model averaging for mapping topsoil organic carbon in France", "description": "Abstract   The soil organic carbon (SOC) pool is the largest terrestrial carbon (C) pool and is two to three times larger than the C stored in vegetation and the atmosphere. SOC is a crucial component within the C cycle, and an accurate baseline of SOC is required, especially for biogeochemical and earth system modelling. This baseline will allow better monitoring of SOC dynamics due to land use change and climate change. However, current estimates of SOC stock and its spatial distribution have large uncertainties. In this study, we test whether we can improve the accuracy of the three existing SOC maps of France obtained at national (IGCS), continental (LUCAS), and global (SoilGrids) scales using statistical model averaging approaches. Soil data from the French Soil Monitoring Network (RMQS) were used to calibrate and evaluate five model averaging approaches, i.e., Granger-Ramanathan, Bias-corrected Variance Weighted (BC-VW), Bayesian Modelling Averaging, Cubist and Residual-based Cubist. Cross-validation showed that with a calibration size larger than 100 observations, the five model averaging approaches performed better than individual SOC maps. The BC-VW approach performed best and is recommended for model averaging. Our results show that 200 calibration observations were an acceptable calibration strategy for model averaging in France, showing that a fairly small number of spatially stratified observations (sampling density of 1 sample per 2500\u00a0km2) provides sufficient calibration data. We also tested the use of model averaging in data-poor situations by reproducing national SOC maps using various sized subsets of the IGCS dataset for model calibration. The results show that model averaging always performs better than the national SOC map. However, the Modelling Efficiency dropped substantially when the national SOC map was excluded in model averaging. This indicates the necessity of including a national SOC map for model averaging, even if produced with a small dataset (i.e., 200 samples). This study provides a reference for data-poor countries to improve national SOC maps using existing continental and global SOC maps.", "keywords": ["Soil organic carbon", "[SDV]Life Sciences [q-bio]", "cartographie num\u00e9rique des sols", "04 agricultural and veterinary sciences", "Data-poor countries", "cartographie num\u00e9rique du sol", "15. Life on land", "01 natural sciences", "soil sciences", "sciences du sol", "[SDV] Life Sciences [q-bio]", "Digital soil mapping", "Sample size requirement", "13. Climate action", "Bias-corrected Variance Weighted", "carbone organique du sol", "0401 agriculture", " forestry", " and fisheries", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://hal.science/hal-02473703/file/revised%20accepted%20version%20Chen%20et%20al.pdf"}, {"href": "https://doi.org/10.1016/j.geoderma.2020.114237"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2020.114237", "name": "item", "description": "10.1016/j.geoderma.2020.114237", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2020.114237"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-01T00:00:00Z"}}, {"id": "10.1038/srep15991", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:18:03Z", "type": "Journal Article", "created": "2015-11-04", "title": "Forest soil carbon is threatened by intensive biomass harvesting", "description": "Abstract<p>Forests play a key role in the carbon cycle as they store huge quantities of organic carbon, most of which is stored in soils, with a smaller part being held in vegetation. While the carbon storage capacity of forests is influenced by forestry, the long-term impacts of forest managers\uffe2\uff80\uff99 decisions on soil organic carbon (SOC) remain unclear. Using a meta-analysis approach, we showed that conventional biomass harvests preserved the SOC of forests, unlike intensive harvests where logging residues were harvested to produce fuelwood. Conventional harvests caused a decrease in carbon storage in the forest floor, but when the whole soil profile was taken into account, we found that this loss in the forest floor was compensated by an accumulation of SOC in deeper soil layers. Conversely, we found that intensive harvests led to SOC losses in all layers of forest soils. We assessed the potential impact of intensive harvests on the carbon budget, focusing on managed European forests. Estimated carbon losses from forest soils suggested that intensive biomass harvests could constitute an important source of carbon transfer from forests to the atmosphere (142\uffe2\uff80\uff93497 Tg-C), partly neutralizing the role of a carbon sink played by forest soils.</p>", "keywords": ["2. Zero hunger", "0106 biological sciences", "Carbon Sequestration", "[SDE.MCG]Environmental Sciences/Global Changes", "Forestry", "04 agricultural and veterinary sciences", "Forests", "15. Life on land", "forest soil", "01 natural sciences", "Article", "Carbon", "Carbon Cycle", "Trees", "[SDE.MCG] Environmental Sciences/Global Changes", "Soil", "13. Climate action", "carbone organique du sol", "0401 agriculture", " forestry", " and fisheries", "Biomass", "Milieux et Changements globaux", "sol forestier", "Ecosystem", "Environmental Monitoring"]}, "links": [{"href": "https://hal.science/hal-01594440/file/2015_Achat_Scientific%20Reports_1.pdf"}, {"href": "https://doi.org/10.1038/srep15991"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/srep15991", "name": "item", "description": "10.1038/srep15991", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/srep15991"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-11-04T00:00:00Z"}}, {"id": "20.500.11850/548479", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:54Z", "type": "Journal Article", "title": "A well-established fact: Rapid mineralization of organic inputs is an important factor for soil carbon sequestration", "description": "Open AccessISSN:1365-2389", "keywords": ["P33 - Chimie et physique du sol", "2. Zero hunger", "http://aims.fao.org/aos/agrovoc/c_1374571087594", "P40 - M\u00e9t\u00e9orologie et climatologie", "P34 - Biologie du sol", "04 agricultural and veterinary sciences", "15. Life on land", "min\u00e9ralisation du carbone", "http://aims.fao.org/aos/agrovoc/c_331583", "carbon sequestration", "soil", "sciences du sol", "s\u00e9questration du carbone", "http://aims.fao.org/aos/agrovoc/c_36244", "climate change", "carbon sequestration; climate change; mineralization; soil", "13. Climate action", "carbone organique du sol", "0401 agriculture", " forestry", " and fisheries", "http://aims.fao.org/aos/agrovoc/c_389fe908", "mineralization", "min\u00e9ralisation", "http://aims.fao.org/aos/agrovoc/c_15999", "http://aims.fao.org/aos/agrovoc/c_7188", "att\u00e9nuation des effets du changement climatique"], "contacts": [{"organization": "Angers, Denis, Arrouays, Dominique, Cardinael, R\u00e9mi, Chenu, Claire, Corbeels, Marc, Demenois, Julien, Farrell, Mark, Martin, Manuel, Minasny, Budiman, Recous, Sylvie, Six, Johan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/20.500.11850/548479"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Soil%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.11850/548479", "name": "item", "description": "20.500.11850/548479", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11850/548479"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "3005528129", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:26:35Z", "type": "Journal Article", "created": "2020-02-06", "title": "Model averaging for mapping topsoil organic carbon in France", "description": "Abstract   The soil organic carbon (SOC) pool is the largest terrestrial carbon (C) pool and is two to three times larger than the C stored in vegetation and the atmosphere. SOC is a crucial component within the C cycle, and an accurate baseline of SOC is required, especially for biogeochemical and earth system modelling. This baseline will allow better monitoring of SOC dynamics due to land use change and climate change. However, current estimates of SOC stock and its spatial distribution have large uncertainties. In this study, we test whether we can improve the accuracy of the three existing SOC maps of France obtained at national (IGCS), continental (LUCAS), and global (SoilGrids) scales using statistical model averaging approaches. Soil data from the French Soil Monitoring Network (RMQS) were used to calibrate and evaluate five model averaging approaches, i.e., Granger-Ramanathan, Bias-corrected Variance Weighted (BC-VW), Bayesian Modelling Averaging, Cubist and Residual-based Cubist. Cross-validation showed that with a calibration size larger than 100 observations, the five model averaging approaches performed better than individual SOC maps. The BC-VW approach performed best and is recommended for model averaging. Our results show that 200 calibration observations were an acceptable calibration strategy for model averaging in France, showing that a fairly small number of spatially stratified observations (sampling density of 1 sample per 2500\u00a0km2) provides sufficient calibration data. We also tested the use of model averaging in data-poor situations by reproducing national SOC maps using various sized subsets of the IGCS dataset for model calibration. The results show that model averaging always performs better than the national SOC map. However, the Modelling Efficiency dropped substantially when the national SOC map was excluded in model averaging. This indicates the necessity of including a national SOC map for model averaging, even if produced with a small dataset (i.e., 200 samples). This study provides a reference for data-poor countries to improve national SOC maps using existing continental and global SOC maps.", "keywords": ["Soil organic carbon", "[SDV]Life Sciences [q-bio]", "cartographie num\u00e9rique des sols", "04 agricultural and veterinary sciences", "cartographie num\u00e9rique du sol", "Data-poor countries", "15. Life on land", "01 natural sciences", "soil sciences", "sciences du sol", "[SDV] Life Sciences [q-bio]", "Digital soil mapping", "Sample size requirement", "13. Climate action", "carbone organique du sol", "Bias-corrected Variance Weighted", "0401 agriculture", " forestry", " and fisheries", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://hal.science/hal-02473703/file/revised%20accepted%20version%20Chen%20et%20al.pdf"}, {"href": "https://doi.org/3005528129"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3005528129", "name": "item", "description": "3005528129", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3005528129"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-01T00:00:00Z"}}, {"id": "10.57745/HRCQL8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:24:39Z", "type": "Dataset", "title": "Unite Exp\u00e9rimentale RGCO de Ploudaniel  : Donn\u00e9es collect\u00e9es dans le cadre des \u00e9tudes de sol du r\u00e9seau CAREX", "description": "Ces donn\u00e9es ont \u00e9t\u00e9 cr\u00e9\u00e9es pour la caract\u00e9risation des sols et de leurs propri\u00e9t\u00e9s de l'Unit\u00e9 Exp\u00e9rimentale INRAE RGCO de Ploudaniel. L\u2019\u00e9tude a port\u00e9 sur 67 ha. Les donn\u00e9es contiennent des informations ponctuelles issues d\u2019observations et d\u2019analyses sur 69 sondages et 14 profils p\u00e9dologiques. Le jeu de donn\u00e9es contient \u00e9galement des donn\u00e9es surfaciques : r\u00e9sistivit\u00e9s \u00e9lectriques spatiales, carte des types de sols classifi\u00e9s par Unit\u00e9s Typologiques de Sols (UTS).", "keywords": ["pH du sol", "structure du sol", "potentiel matriciel", "masse volumique du sol", "horizon", "type de sol", "carbonate", "carbone organique du sol", "propriet\u00e9s physico-chimiques du sol", "g\u00e9ologie", "phosphore du sol", "azote total", "point de fl\u00e9trissement permanent", "carte p\u00e9dologique", "r\u00e9tention hydrique du sol", "propriet\u00e9 hydrique du sol", "capacit\u00e9 au champ", "teneur en argile", "carbone total", "granulom\u00e9trie du sol", "hydromorphie", "Earth and Environmental Sciences", "r\u00e9f\u00e9rentiel p\u00e9dologique", "unit\u00e9 typologique de sol UTS", "r\u00e9sisitivit\u00e9 \u00e9l\u00e9ctrique", "capacit\u00e9 d'\u00e9change cationique", "texture", "occupation du sol"], "contacts": [{"organization": "Mistou Marie-Noel, Girot Ghislain, Seger Maud, Laloua Didier, Le Lay Christian, Gaillard Herv\u00e9, Heller Renaud, Sherif Rehanna, Kermarrec Dominique, Levardois Kevin, Chauvin Jean-Eric,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.57745/HRCQL8"}, {"rel": "self", "type": "application/geo+json", "title": "10.57745/HRCQL8", "name": "item", "description": "10.57745/HRCQL8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.57745/HRCQL8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.57745/2V46MF", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:24:39Z", "type": "Dataset", "title": "Unit\u00e9 Exp\u00e9rimentale d'Epoisses : Donn\u00e9es collect\u00e9es dans le cadre des \u00e9tudes de sol du r\u00e9seau CAREX", "description": "Ces donn\u00e9es ont \u00e9t\u00e9 cr\u00e9\u00e9es pour la caract\u00e9risation des sols et de leurs propri\u00e9t\u00e9s de l'Unit\u00e9 Exp\u00e9rimentale INRAE d'Epoisse (commune de Breteni\u00e8re, C\u00f4te d'Or, France). L\u2019\u00e9tude a port\u00e9 sur 120 ha. Les donn\u00e9es contiennent des informations ponctuelles issues d\u2019observations et d\u2019analyses sur 92 sondages et 12 profils p\u00e9dologiques. Le jeu de donn\u00e9es contient \u00e9galement des donn\u00e9es surfaciques : r\u00e9sistivit\u00e9s \u00e9lectriques spatiales, carte des types de sols classifi\u00e9s par Unit\u00e9s Typologiques de Sols (UTS).", "keywords": ["Earth and Environmental Science", "pH du sol", "structure du sol", "potentiel matriciel", "masse volumique du sol", "horizon", "type de sol", "carbonate", "granulometrie du sol", "carbone organique du sol", "propriet\u00e9s physico-chimiques du sol", "g\u00e9ologie", "azote total", "r\u00e9sisitivit\u00e9 \u00e9lectrique", "carte p\u00e9dologique", "r\u00e9tention hydrique du sol", "propriet\u00e9 hydrique du sol", "capacit\u00e9 au champ", "teneur en argile", "capacit\u00e9 d \u00e9change cationique", "carbone total", "hydromorphie", "point fl\u00e9trissement permanent", "Earth and Environmental Sciences", "propriet\u00e9s physico chimiques du sol", "r\u00e9f\u00e9rentiel p\u00e9dologique", "unit\u00e9 typologique de sol UTS", "Environmental Research", "Natural Sciences", "capacit\u00e9 d'\u00e9change cationique", "texture", "occupation du sol", "Geosciences"], "contacts": [{"organization": "Seger, Maud, Girot, Ghislain, Mistou, Marie-No\u00ebl, Laloua, Didier, Le Lay, Christian, Gaillard, Herv\u00e9, Ubertosi, Marjorie, Coffin, Arnaud, Hugard, Rodolphe,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.57745/2V46MF"}, {"rel": "self", "type": "application/geo+json", "title": "10.57745/2V46MF", "name": "item", "description": "10.57745/2V46MF", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.57745/2V46MF"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "11250/3082084", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:25Z", "type": "Journal Article", "created": "2023-05-08", "title": "Soil organic carbon models need independent time-series validation for reliable prediction", "description": "Abstract<p>Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.</p", "keywords": ["P33 - Chimie et physique du sol", "[SDE] Environmental Sciences", "P40 - M\u00e9t\u00e9orologie et climatologie", "analyse de s\u00e9ries chronologiques", "01 natural sciences", "2300 General Environmental Science", "http://aims.fao.org/aos/agrovoc/c_3041", "carbone organique du sol", "http://aims.fao.org/aos/agrovoc/c_389fe908", "GE1-350", "910 Geography & travel", "mod\u00e9lisation", "0105 earth and related environmental sciences", "QE1-996.5", "http://aims.fao.org/aos/agrovoc/c_230ab86c", "U10 - Informatique", " math\u00e9matiques et statistiques", "1900 General Earth and Planetary Sciences", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "technique de pr\u00e9vision", "http://aims.fao.org/aos/agrovoc/c_28778", "Environmental sciences", "10122 Institute of Geography", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "U30 - M\u00e9thodes de recherche"]}, "links": [{"href": "https://www.nature.com/articles/s43247-023-00830-5.pdf"}, {"href": "https://doi.org/11250/3082084"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Communications%20Earth%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11250/3082084", "name": "item", "description": "11250/3082084", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11250/3082084"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-05-08T00:00:00Z"}}, {"id": "50|od______3631::788b68858ed6ceec284f239e36d1e6eb", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:27:26Z", "type": "Report", "title": "A marginal abatement cost curve for greenhouse gases attenuation by additional carbon storage in french agricultural land", "description": "Following the Paris agreement in 2015, the European Union (EU) set a carbon neutrality objective by 2050, and so did France. The French agricultural sector can contribute as a carbon sink through carbon storage in biomass and soil, in addition to reducing GHG emissions. The objective of this study is to quantitatively assess the additional storage potential and cost of a set of eight carbon-storing practices. The impacts of these agricultural practices on soil organic carbon storage and crop production are assessed at a very fine spatial scale, using crop and grassland models. The associated area base, GHG budget, and implementation costs are assessed and aggregated at the region level. The economic model BANCO uses this information to derive the marginal abatement cost curve for France and identify the combination of carbon storing practices that minimizes the total cost of achieving a given national net GHG mitigation target. We find that a substantial amount of carbon, 36.2 to 52.9 MtCO2e yr\u22121, can be stored in soil and biomass for reasonable carbon prices of 55 and 250 \u20ac tCO2e\u22121, respectively (corresponding to current and 2030 French carbon value for climate action), mainly by developing agroforestry and hedges, generalising cover crops, and introducing or extending temporary grasslands in crop sequences. This finding questions the 3\u20135 times lower target of 10 MtCO2e.yr\u22121 retained for the agricultural carbon sink by the French climate neutrality strategy. Overall, this would decrease total French GHG emissions by 9.2\u201313.8%, respectively (reference year 2019).", "keywords": ["2. Zero hunger", "P33 - Chimie et physique du sol", "http://aims.fao.org/aos/agrovoc/c_1374571087594", "P40 - M\u00e9t\u00e9orologie et climatologie", "F08 - Syst\u00e8mes et modes de culture", "\u00e9mission de gaz", "terre agricole", "co\u00fbt marginal", "http://aims.fao.org/aos/agrovoc/c_331597", "15. Life on land", "http://aims.fao.org/aos/agrovoc/c_28725", "7. Clean energy", "http://aims.fao.org/aos/agrovoc/c_331583", "http://aims.fao.org/aos/agrovoc/c_0d4560a5", "http://aims.fao.org/aos/agrovoc/c_2808", "s\u00e9questration du carbone", "13. Climate action", "r\u00e9duction des \u00e9missions", "11. Sustainability", "carbone organique du sol", "http://aims.fao.org/aos/agrovoc/c_3081", "gaz \u00e0 effet de serre", "http://aims.fao.org/aos/agrovoc/c_389fe908", "http://aims.fao.org/aos/agrovoc/c_34841", "att\u00e9nuation des effets du changement climatique"], "contacts": [{"organization": "Bamiere, Laure, Bellassen, Valentin, Angers, Denis, Cardinael, R\u00e9mi, Ceschia, Eric, Chenu, Claire, Constantin, Julie, Delame, Nathalie, Diallo, A., Graux, Anne-Isabelle, Houot, Sabine, Klumpp, Katja, Launay, Camille, Letort, Elodie, Martin, Raphael, Meziere, Delphine, Mosnier, Claire, R\u00e9chauch\u00e8re, Olivier, Schiavo, Michele, Th\u00e9rond, Olivier, Pellerin, Sylvain,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______3631::788b68858ed6ceec284f239e36d1e6eb"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______3631::788b68858ed6ceec284f239e36d1e6eb", "name": "item", "description": "50|od______3631::788b68858ed6ceec284f239e36d1e6eb", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______3631::788b68858ed6ceec284f239e36d1e6eb"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "9b81642374175d90e0b717deca64ff67", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:28:30Z", "type": "Report", "title": "Satellite time series contribution to organic carbon mapping in cultivated soils at various regional scales", "description": "Open AccessLe carbone organique du sol (COS) dans les zones agricoles joue un r\u00f4le cl\u00e9 dans la s\u00e9curit\u00e9 alimentaire et l'att\u00e9nuation du changement climatique. La quantification du COS est n\u00e9cessaire pour mettre en \u0153uvre des techniques et des pratiques de stockage. Cependant, l'\u00e9chantillonnage du COS dans un monde qui couvre environ 1,5 milliard d'hectares de sols agricoles est un v\u00e9ritable d\u00e9fi. C'est pourquoi l'utilisation de technologies telles que les capteurs satellitaires constitue une alternative prometteuse pour quantifier et cartographier le COS dans diff\u00e9rents types d'agro\u00e9cosyst\u00e8mes \u00e0 travers le monde. L'objectif de cette th\u00e8se est d'\u00e9valuer le potentiel des images satellitaires Sentinel-2 (S2) et Sentinel-1 (S1) pour la cartographie du COS dans les agro-\u00e9cosyst\u00e8mes de la France m\u00e9tropolitaine en utilisant des mod\u00e8les spectraux et spatio-spectraux. Le chapitre 1 aborde l'\u00e9tat d'avancement de la cartographie du COS en France et pr\u00e9sente les principales limitations et m\u00e9thodes actuellement utilis\u00e9es avec les donn\u00e9es d'images satellitaires pour la pr\u00e9diction du COS. Le chapitre 2 pr\u00e9sente les zones d'\u00e9tude situ\u00e9es dans les r\u00e9gions Bretagne, Occitanie et Centre Val de Loire. De plus, les principaux ensembles de donn\u00e9es utilis\u00e9s sont d\u00e9crits et une analyse pr\u00e9liminaire de l'une des zones d'\u00e9tude est pr\u00e9sent\u00e9e. Le troisi\u00e8me chapitre \u00e9value le potentiel des images S2 et des produits d\u00e9riv\u00e9s de S1 et S2 pour pr\u00e9dire le SOC \u00e0 l'aide d'images \u00e0 date unique. Dans ce chapitre comme dans le second, des limitations li\u00e9es principalement aux conditions de surface du sol ont \u00e9t\u00e9 observ\u00e9es ; et les meilleures dates d'image pour d\u00e9tecter le SOC ont \u00e9t\u00e9 identifi\u00e9es. Dans la quatri\u00e8me au lieu d'images \u00e0 date unique, l'utilisation de mosa\u00efques temporelles S2 de sol nu (S2Bsoil) par p\u00e9riodes est abord\u00e9e comme l'utilisation de covariables d\u00e9riv\u00e9es de l'imagerie satellitaire et du terrain. Ce chapitre traite de l'importance de la s\u00e9lection des p\u00e9riodes de production de S2Bsol et de l'utilisation de covariables pertinentes pour comprendre la variabilit\u00e9 spatiale du COS \u00e0 l'\u00e9chelle r\u00e9gionale. Enfin, le dernier chapitre aborde les principaux constats et perspectives \u00e0 envisager dans un futur proche.", "keywords": ["[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy", "[SDE.MCG] Environmental Sciences/Global Changes", "S\u00e9ries satellitaires Sentinel", "Digital soil mapping", "Soil organic carbon", "Carbone organique du sol", "Bare soil", "Sentinel time series", "Sol nu", "Croplands", "Terres agricoles", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "Cartographie num\u00e9rique des sols"], "contacts": [{"organization": "Urbina Salazar, Diego Fernando", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/9b81642374175d90e0b717deca64ff67"}, {"rel": "self", "type": "application/geo+json", "title": "9b81642374175d90e0b717deca64ff67", "name": "item", "description": "9b81642374175d90e0b717deca64ff67", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/9b81642374175d90e0b717deca64ff67"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "oai:HAL:tel-04622576v1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:34:11Z", "type": "Report", "title": "Satellite time series contribution to organic carbon mapping in cultivated soils at various regional scales", "description": "Open AccessLe carbone organique du sol (COS) dans les zones agricoles joue un r\u00f4le cl\u00e9 dans la s\u00e9curit\u00e9 alimentaire et l'att\u00e9nuation du changement climatique. La quantification du COS est n\u00e9cessaire pour mettre en \u0153uvre des techniques et des pratiques de stockage. Cependant, l'\u00e9chantillonnage du COS dans un monde qui couvre environ 1,5 milliard d'hectares de sols agricoles est un v\u00e9ritable d\u00e9fi. C'est pourquoi l'utilisation de technologies telles que les capteurs satellitaires constitue une alternative prometteuse pour quantifier et cartographier le COS dans diff\u00e9rents types d'agro\u00e9cosyst\u00e8mes \u00e0 travers le monde. L'objectif de cette th\u00e8se est d'\u00e9valuer le potentiel des images satellitaires Sentinel-2 (S2) et Sentinel-1 (S1) pour la cartographie du COS dans les agro-\u00e9cosyst\u00e8mes de la France m\u00e9tropolitaine en utilisant des mod\u00e8les spectraux et spatio-spectraux. Le chapitre 1 aborde l'\u00e9tat d'avancement de la cartographie du COS en France et pr\u00e9sente les principales limitations et m\u00e9thodes actuellement utilis\u00e9es avec les donn\u00e9es d'images satellitaires pour la pr\u00e9diction du COS. Le chapitre 2 pr\u00e9sente les zones d'\u00e9tude situ\u00e9es dans les r\u00e9gions Bretagne, Occitanie et Centre Val de Loire. De plus, les principaux ensembles de donn\u00e9es utilis\u00e9s sont d\u00e9crits et une analyse pr\u00e9liminaire de l'une des zones d'\u00e9tude est pr\u00e9sent\u00e9e. Le troisi\u00e8me chapitre \u00e9value le potentiel des images S2 et des produits d\u00e9riv\u00e9s de S1 et S2 pour pr\u00e9dire le SOC \u00e0 l'aide d'images \u00e0 date unique. Dans ce chapitre comme dans le second, des limitations li\u00e9es principalement aux conditions de surface du sol ont \u00e9t\u00e9 observ\u00e9es ; et les meilleures dates d'image pour d\u00e9tecter le SOC ont \u00e9t\u00e9 identifi\u00e9es. Dans la quatri\u00e8me au lieu d'images \u00e0 date unique, l'utilisation de mosa\u00efques temporelles S2 de sol nu (S2Bsoil) par p\u00e9riodes est abord\u00e9e comme l'utilisation de covariables d\u00e9riv\u00e9es de l'imagerie satellitaire et du terrain. Ce chapitre traite de l'importance de la s\u00e9lection des p\u00e9riodes de production de S2Bsol et de l'utilisation de covariables pertinentes pour comprendre la variabilit\u00e9 spatiale du COS \u00e0 l'\u00e9chelle r\u00e9gionale. 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