{"type": "FeatureCollection", "features": [{"id": "10.1016/j.scitotenv.2021.152880", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:17:21Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Mathematics"], "contacts": [{"organization": "Zhenwang Li, Lei Ding, Donghui Xu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.152880"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2021.152880", "name": "item", "description": "10.1016/j.scitotenv.2021.152880", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.152880"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "10.1029/2022gl098700", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:18:13Z", "type": "Journal Article", "created": "2022-07-19", "title": "Drought Legacy in Sub\u2010Seasonal Vegetation State and Sensitivity to Climate Over the Northern Hemisphere", "description": "Abstract<p>Droughts affect ecosystems at multiple time scales, but their sub\uffe2\uff80\uff90seasonal legacy effects on vegetation activity remain unclear. Combining the satellite\uffe2\uff80\uff90based enhanced vegetation index MODIS EVI with a novel location\uffe2\uff80\uff90specific definition of the growing season, we quantify drought impacts on sub\uffe2\uff80\uff90seasonal vegetation activity and the subsequent recovery in the Northern Hemisphere. Drought legacy effects are quantified as changes in post\uffe2\uff80\uff90drought greenness and sensitivity to climate. We find that greenness losses under severe drought are partially compensated by a \uffe2\uff88\uffbc+5% greening within 2\uffe2\uff80\uff936 growing\uffe2\uff80\uff90season months following the droughts, both in woody and herbaceous vegetation but at different timings. In addition, post\uffe2\uff80\uff90drought sensitivity of herbaceous vegetation to hydrological conditions increases noticeably at high latitudes compared with the local normal conditions, regardless of the choice of drought time scales. In general, the legacy effects on sensitivity are larger in herbaceous vegetation than in woody vegetation.</p", "keywords": ["580", "570", "Ecology", "QC801-809", "Geophysics. Cosmic physics", "Geovetenskap och milj\u00f6vetenskap", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Geovetenskap och relaterad milj\u00f6vetenskap", "growing season\u2010based analysis", "Physical Geography", "13. Climate action", "sub\u2010seasonal vegetation sensitivity", "ecosystem resilience", "0401 agriculture", " forestry", " and fisheries", "Earth and Related Environmental Sciences", "drought legacy", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pub.epsilon.slu.se/28761/1/wu-m-et-al-20220902.pdf"}, {"href": "https://doi.org/10.1029/2022gl098700"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geophysical%20Research%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2022gl098700", "name": "item", "description": "10.1029/2022gl098700", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2022gl098700"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-08-04T00:00:00Z"}}, {"id": "10.1038/srep34786", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:18:26Z", "type": "Journal Article", "created": "2016-10-10", "title": "Contrasting Effects Of Nitrogen And Phosphorus Addition On Soil Respiration In An Alpine Grassland On The Qinghai-Tibetan Plateau", "description": "Abstract<p>High soil organic carbon content, extensive root biomass, and low nutrient availability make alpine grasslands an important ecosystem for assessing the influence of nutrient enrichment on soil respiration (SR). We conducted a four-year (2009\uffe2\uff80\uff932012) field experiment in an alpine grassland on the Qinghai-Tibetan Plateau to examine the individual and combined effects of nitrogen (N, 100\uffe2\uff80\uff89kg ha\uffe2\uff88\uff921year\uffe2\uff88\uff921) and phosphorus (P, 50\uffe2\uff80\uff89kg ha\uffe2\uff88\uff921year\uffe2\uff88\uff921) addition on SR. We found that both N and P addition did not affect the overall growing-season SR but effects varied by year: with N addition SR increased in the first year but decreased during the last two years. However, while P addition did not affect SR during the first two years, SR increased during the last two years. No interactive effects of N and P addition were observed, and both N addition and P addition reduced heterotrophic respiration during the last year of the experiment. N and P addition affected SR via different processes: N mainly affected heterotrophic respiration, whereas P largely influenced autotrophic respiration. Our results highlight the divergent effects of N and P addition on SR and address the important potential of P enrichment for regulating SR and the carbon balance in alpine grasslands.</p>", "keywords": ["Biomass (ecology)", "0106 biological sciences", "Mechanics and Transport in Unsaturated Soils", "Nitrogen", "Soil Science", "Organic chemistry", "Plant Science", "Thermal Effects on Soil", "01 natural sciences", "Article", "Environmental science", "Agricultural and Biological Sciences", "Engineering", "Soil water", "Genetics", "Biology", "Ecosystem", "Civil and Structural Engineering", "2. Zero hunger", "Soil Fertility", "Ecology", "Bacteria", "Respiration", "Botany", "Life Sciences", "Plant Nutrient Uptake and Signaling Pathways", "Phosphorus", "Soil respiration", "04 agricultural and veterinary sciences", "15. Life on land", "Grassland", "Soil carbon", "Agronomy", "Chemistry", "13. Climate action", "FOS: Biological sciences", "Physical Sciences", "Heterotroph", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Animal science", "Nutrient"]}, "links": [{"href": "https://doi.org/10.1038/srep34786"}, {"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/srep34786", "name": "item", "description": "10.1038/srep34786", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/srep34786"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-10-10T00:00:00Z"}}, {"id": "10.1088/1748-9326/11/5/054004", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:18:57Z", "type": "Journal Article", "created": "2016-04-26", "description": "Open AccessEn este estudio, se examinaron los efectos de la intensidad del pastoreo de ganado en los flujos de \u00f3xido nitroso (N2O) del suelo en la estepa del prado de Hulunber, en el noreste de China. Se establecieron seis tratamientos de tasa de siembra (0, 0.23, 0.34, 0.46, 0.69 y 0.92 AU ha\u22121) con tres r\u00e9plicas, y se realizaron observaciones de 2010 a 2014. Nuestros resultados mostraron que se produjeron fluctuaciones temporales sustanciales en el flujo de N2O entre las diferentes intensidades de pastoreo, con flujos m\u00e1ximos de N2O despu\u00e9s de la lluvia natural. El pastoreo tuvo un efecto a largo plazo en el flujo de N2O del suelo en los pastizales. Despu\u00e9s de 4\u20135 a\u00f1os de pastoreo, los flujos de N2O bajo mayores niveles de intensidad de pastoreo comenzaron a disminuir significativamente en un 31.4%\u201360.2% en 2013 y 32.5%\u201350.5% en 2014 en comparaci\u00f3n con el tratamiento sin pastoreo. Observamos una relaci\u00f3n lineal negativa significativa entre los flujos de N2O del suelo y la intensidad del pastoreo para la media de cinco a\u00f1os. El flujo de N2O del suelo se vio afectado significativamente cada a\u00f1o en todos los tratamientos. Durante los cinco a\u00f1os, el coeficiente de variaci\u00f3n temporal (CV) del flujo de N2O del suelo generalmente disminuy\u00f3 significativamente con el aumento de la intensidad del pastoreo. La tasa de emisi\u00f3n de N2O del suelo se correlacion\u00f3 significativamente de manera positiva con la humedad del suelo (SM), el f\u00f3sforo disponible en el suelo (SAP), la biomasa sobre el suelo (AGB), la cobertura vegetal y la altura y se correlacion\u00f3 negativamente con el nitr\u00f3geno total del suelo (TN). Las regresiones escalonadas mostraron que el flujo de N2O se explicaba principalmente por SM, altura de la planta, TN, pH del suelo y suelo Usando modelos de ecuaciones estructurales, mostramos que el pastoreo influy\u00f3 significativamente directamente en la comunidad de plantas y el entorno del suelo, que luego influy\u00f3 en los flujos de N2O del suelo. Nuestros hallazgos proporcionan una referencia importante para comprender mejor los mecanismos e identificar las v\u00edas de los efectos del pastoreo en las tasas de emisi\u00f3n de N2O del suelo, y los impulsores clave de la comunidad vegetal y el entorno del suelo dentro del ciclo del nitr\u00f3geno que probablemente afecten las emisiones de N2O en las estepas de los prados de Mongolia Interior.", "keywords": ["Biomass (ecology)", "driving factor", "Mechanics and Transport in Unsaturated Soils", "Science", "QC1-999", "Soil Science", "Environmental technology. Sanitary engineering", "Environmental science", "meadow steppe", "Agricultural and Biological Sciences", "Engineering", "GE1-350", "Biology", "TD1-1066", "Civil and Structural Engineering", "2. Zero hunger", "Steppe", "Soil Fertility", "Nitrous oxide", "Ecology", "Physics", "Q", "Life Sciences", "04 agricultural and veterinary sciences", "15. Life on land", "soil N2O fluxes", "Soil Erosion and Agricultural Sustainability", "Agronomy", "6. Clean water", "Environmental sciences", "grazing intensity", "Grazing", "13. Climate action", "FOS: Biological sciences", "response and mechanism", "Physical Sciences", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems"], "contacts": [{"organization": "Ruirui Yan, Huajun Tang, Xiaoping Xin, Baorui Chen, Philip J. Murray, Yunchun Yan, Xu Wang, Guoxiang Yang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1088/1748-9326/11/5/054004"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Research%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1088/1748-9326/11/5/054004", "name": "item", "description": "10.1088/1748-9326/11/5/054004", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1088/1748-9326/11/5/054004"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-04-26T00:00:00Z"}}, {"id": "10.1371/journal.pone.0153415", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:20:18Z", "type": "Journal Article", "created": "2016-04-12", "title": "Seasonality, Rather Than Nutrient Addition Or Vegetation Types, Influenced Short-Term Temperature Sensitivity Of Soil Organic Carbon Decomposition", "description": "Open AccessLa r\u00e9ponse de la respiration microbienne de la d\u00e9composition du carbone organique du sol (COS) aux changements environnementaux joue un r\u00f4le cl\u00e9 dans la pr\u00e9diction des tendances futures de la concentration de CO2 atmosph\u00e9rique. Cependant, il n'est pas certain qu'il existe une tendance universelle dans la r\u00e9ponse de la respiration microbienne \u00e0 l'augmentation de la temp\u00e9rature et \u00e0 l'ajout de nutriments parmi les diff\u00e9rents types de v\u00e9g\u00e9tation. Dans cette \u00e9tude, les sols ont \u00e9t\u00e9 \u00e9chantillonn\u00e9s au printemps, en \u00e9t\u00e9, en automne et en hiver \u00e0 partir de cinq types de v\u00e9g\u00e9tation dominants, y compris les for\u00eats de pins, de m\u00e9l\u00e8zes et de bouleaux, les arbustes et les prairies, dans la r\u00e9gion de Saihanba, dans le nord de la Chine. Les \u00e9chantillons de sol de chaque saison ont \u00e9t\u00e9 incub\u00e9s \u00e0 1, 10 et 20 \u00b0C pendant 5 \u00e0 7 jours. L'azote (N\u00a0; 0,035 mM sous forme de NH4NO3) et le phosphore (P\u00a0; 0,03 mM sous forme de P2O5) ont \u00e9t\u00e9 ajout\u00e9s aux \u00e9chantillons de sol, et les r\u00e9ponses de la respiration microbienne du sol \u00e0 l'augmentation de la temp\u00e9rature et \u00e0 l'ajout de nutriments ont \u00e9t\u00e9 d\u00e9termin\u00e9es. Nous avons constat\u00e9 une tendance universelle selon laquelle la respiration microbienne du sol augmentait avec l'augmentation de la temp\u00e9rature, ind\u00e9pendamment de la saison d'\u00e9chantillonnage ou du type de v\u00e9g\u00e9tation. La sensibilit\u00e9 \u00e0 la temp\u00e9rature (indiqu\u00e9e par Q10, l'augmentation du taux de respiration avec une augmentation de 10\u00b0C de la temp\u00e9rature) de la respiration microbienne \u00e9tait plus \u00e9lev\u00e9e au printemps et en automne qu'en \u00e9t\u00e9 et en hiver, quel que soit le type de v\u00e9g\u00e9tation. Le Q10 \u00e9tait significativement corr\u00e9l\u00e9 positivement avec la biomasse microbienne et le rapport champignon\u00a0: bact\u00e9rie. La respiration microbienne (ou Q10) n'a pas r\u00e9pondu de mani\u00e8re significative \u00e0 l'addition d'azote ou de phosphore. Nos r\u00e9sultats sugg\u00e8rent que l'apport en nutriments \u00e0 court terme pourrait ne pas modifier le taux de d\u00e9composition du COS ou sa sensibilit\u00e9 \u00e0 la temp\u00e9rature, alors que l'augmentation de la temp\u00e9rature pourrait am\u00e9liorer consid\u00e9rablement la d\u00e9composition du COS au printemps et en automne, par rapport \u00e0 l'hiver et \u00e0 l'\u00e9t\u00e9.", "keywords": ["Biomass (ecology)", "Atmospheric Science", "Microbial population biology", "Larix", "Carbon Dynamics in Peatland Ecosystems", "Forests", "Agricultural and Biological Sciences", "Soil", "Soil water", "Pathology", "Carbon Feedback", "Biomass", "Betula", "Soil Microbiology", "2. Zero hunger", "Ecology", "Q10", "Respiration", "Q", "R", "Temperature", "Life Sciences", "Soil respiration", "04 agricultural and veterinary sciences", "Soil carbon", "Grassland", "Earth and Planetary Sciences", "Physical Sciences", "Respiration rate", "Medicine", "Seasons", "Vegetation (pathology)", "Research Article", "China", "Nitrogen", "Science", "Soil Science", "Environmental science", "Shrubland", "Genetics", "Arctic Permafrost Dynamics and Climate Change", "Soil Carbon Sequestration", "Biology", "Ecosystem", "Soil science", "Soil organic matter", "Soil Fertility", "Bacteria", "Fungi", "Botany", "15. Life on land", "Pinus", "Vegetation Change", "Carbon", "Agronomy", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient"], "contacts": [{"organization": "Yu-Qi Qian, Fangliang He, Wei Wang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1371/journal.pone.0153415"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLOS%20ONE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1371/journal.pone.0153415", "name": "item", "description": "10.1371/journal.pone.0153415", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1371/journal.pone.0153415"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-04-12T00:00:00Z"}}, {"id": "10.1371/journal.pone.0102062", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:20:17Z", "type": "Journal Article", "created": "2014-07-15", "title": "Effects Of Biochar On Soil Microbial Biomass After Four Years Of Consecutive Application In The North China Plain", "description": "Open AccessL'effet \u00e0 long terme de l'application de biochar sur la biomasse microbienne du sol n'est pas bien compris. Nous avons mesur\u00e9 le carbone (MBC) et l'azote (MBN) de la biomasse microbienne du sol dans une exp\u00e9rience sur le terrain au cours d'une saison de croissance du bl\u00e9 d'hiver apr\u00e8s quatre ann\u00e9es cons\u00e9cutives sans (CK), 4,5 (B4,5) et 9,0 t de biochar ha\u22121 an\u22121 (B9,0) appliqu\u00e9. \u00c0 titre de comparaison, un traitement avec incorporation de r\u00e9sidus de paille de bl\u00e9 (SR) a \u00e9galement \u00e9t\u00e9 inclus. Les r\u00e9sultats ont montr\u00e9 que l'application de biochar augmentait significativement le MBC du sol par rapport au traitement CK, et que la taille de l'effet augmentait avec le taux d'application de biochar. Le traitement B9.0 a montr\u00e9 le m\u00eame effet sur le CSM que le traitement SR. Les effets des traitements sur la MBN du sol \u00e9taient moins forts que pour le MBC. Le ratio de biomasse microbienne C N a \u00e9t\u00e9 significativement augment\u00e9 par le biochar. Le biochar pourrait diminuer la fraction de la biomasse N min\u00e9ralis\u00e9e (KN), ce qui sous-estimerait le MBN du sol pour les traitements au biochar, et surestimerait les rapports C/N de la biomasse microbienne. La fluctuation saisonni\u00e8re dans le CSM \u00e9tait moins importante pour les sols modifi\u00e9s par le biochar que pour les traitements CK et SR, ce qui sugg\u00e8re que le biochar a induit un environnement moins extr\u00eame pour les micro-organismes tout au long de la saison. Il y avait une corr\u00e9lation positive significative entre le CSM et la teneur en eau du sol (CFS), mais il n'y avait pas de corr\u00e9lation significative entre le CSM et la temp\u00e9rature du sol. Les modifications du biochar peuvent donc r\u00e9duire la variabilit\u00e9 temporelle des conditions environnementales pour la croissance microbienne dans ce syst\u00e8me, r\u00e9duisant ainsi les fluctuations temporelles de la dynamique du C et de l'N.", "keywords": ["Biomass (ecology)", "Carbon sequestration", "China", "Nitrogen", "Science", "Geochemistry and Utilization of Coal and Coal Byproducts", "Soil Science", "Organic chemistry", "Environmental science", "Agricultural and Biological Sciences", "Geochemistry and Petrology", "Soil water", "Development and Impacts of Bioenergy Crops", "Biomass", "Biology", "Ecosystem", "Soil Microbiology", "Biochar Application", "Soil science", "2. Zero hunger", "Analysis of Variance", "Q", "R", "Life Sciences", "Straw", "04 agricultural and veterinary sciences", "15. Life on land", "Soil carbon", "Carbon", "Agronomy", "6. Clean water", "Earth and Planetary Sciences", "Biochar", "Chemistry", "13. Climate action", "Charcoal", "Physical Sciences", "Environmental chemistry", "Medicine", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Agronomy and Crop Science", "Animal science", "Pyrolysis", "Research Article"]}, "links": [{"href": "https://doi.org/10.1371/journal.pone.0102062"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLoS%20ONE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1371/journal.pone.0102062", "name": "item", "description": "10.1371/journal.pone.0102062", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1371/journal.pone.0102062"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-07-15T00:00:00Z"}}, {"id": "10.2136/sssaj2011.0030", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:21:14Z", "type": "Journal Article", "created": "2011-09-15", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "Growing season", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Conventional Tillage", "Nitrogen level factor", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.2136/sssaj2011.0030"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Science%20Society%20of%20America%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2136/sssaj2011.0030", "name": "item", "description": "10.2136/sssaj2011.0030", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2136/sssaj2011.0030"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-09-01T00:00:00Z"}}, {"id": "21.11116/0000-000A-C229-D", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:26:48Z", "type": "Journal Article", "created": "2022-07-19", "title": "Drought Legacy in Sub\u2010Seasonal Vegetation State and Sensitivity to Climate Over the Northern Hemisphere", "description": "Abstract<p>Droughts affect ecosystems at multiple time scales, but their sub\uffe2\uff80\uff90seasonal legacy effects on vegetation activity remain unclear. Combining the satellite\uffe2\uff80\uff90based enhanced vegetation index MODIS EVI with a novel location\uffe2\uff80\uff90specific definition of the growing season, we quantify drought impacts on sub\uffe2\uff80\uff90seasonal vegetation activity and the subsequent recovery in the Northern Hemisphere. Drought legacy effects are quantified as changes in post\uffe2\uff80\uff90drought greenness and sensitivity to climate. We find that greenness losses under severe drought are partially compensated by a \uffe2\uff88\uffbc+5% greening within 2\uffe2\uff80\uff936 growing\uffe2\uff80\uff90season months following the droughts, both in woody and herbaceous vegetation but at different timings. In addition, post\uffe2\uff80\uff90drought sensitivity of herbaceous vegetation to hydrological conditions increases noticeably at high latitudes compared with the local normal conditions, regardless of the choice of drought time scales. In general, the legacy effects on sensitivity are larger in herbaceous vegetation than in woody vegetation.</p", "keywords": ["580", "570", "Ecology", "QC801-809", "Geophysics. Cosmic physics", "Geovetenskap och milj\u00f6vetenskap", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Geovetenskap och relaterad milj\u00f6vetenskap", "growing season\u2010based analysis", "Physical Geography", "13. Climate action", "sub\u2010seasonal vegetation sensitivity", "ecosystem resilience", "0401 agriculture", " forestry", " and fisheries", "Earth and Related Environmental Sciences", "drought legacy", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pub.epsilon.slu.se/28761/1/wu-m-et-al-20220902.pdf"}, {"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2022GL098700"}, {"href": "https://doi.org/21.11116/0000-000A-C229-D"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geophysical%20Research%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "21.11116/0000-000A-C229-D", "name": "item", "description": "21.11116/0000-000A-C229-D", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/21.11116/0000-000A-C229-D"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-08-04T00:00:00Z"}}, {"id": "34998760", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:27:45Z", "type": "Journal Article", "created": "2022-01-06", "title": "Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China", "description": "Open AccessLe d\u00e9veloppement d'un syst\u00e8me pr\u00e9cis de pr\u00e9diction du rendement des cultures \u00e0 grande \u00e9chelle est d'une importance primordiale pour la gestion des ressources agricoles et la s\u00e9curit\u00e9 alimentaire mondiale. L'observation de la Terre fournit une source unique d'informations pour surveiller les cultures \u00e0 partir d'une diversit\u00e9 de gammes spectrales. Cependant, l'utilisation int\u00e9gr\u00e9e de ces donn\u00e9es et de leurs valeurs dans la pr\u00e9diction du rendement des cultures est encore peu \u00e9tudi\u00e9e. Ici, nous avons propos\u00e9 la combinaison de donn\u00e9es environnementales (climat, sol, g\u00e9ographie et topographie) avec de multiples donn\u00e9es satellitaires (indices de v\u00e9g\u00e9tation optiques, fluorescence induite par le soleil (SIF), temp\u00e9rature de surface du sol (LST) et profondeur optique de la v\u00e9g\u00e9tation micro-ondes (VOD)) dans le cadre pour estimer le rendement des cultures de ma\u00efs, de riz et de soja dans le nord-est de la Chine, et leur valeur unique et leur influence relative sur la pr\u00e9diction du rendement ont \u00e9t\u00e9 \u00e9valu\u00e9es. Deux m\u00e9thodes de r\u00e9gression lin\u00e9aire, trois m\u00e9thodes d'apprentissage automatique (ML) et un mod\u00e8le d'ensemble ML ont \u00e9t\u00e9 adopt\u00e9s pour construire des mod\u00e8les de pr\u00e9diction de rendement. Les r\u00e9sultats ont montr\u00e9 que les m\u00e9thodes individuelles de ML surpassaient les m\u00e9thodes de r\u00e9gression lin\u00e9aire, le mod\u00e8le d'ensemble de ML a encore am\u00e9lior\u00e9 les mod\u00e8les de ML uniques. De plus, les mod\u00e8les avec plus d'intrants ont obtenu de meilleures performances, la combinaison de donn\u00e9es satellitaires avec des donn\u00e9es environnementales, qui expliquaient respectivement 72\u00a0%, 69\u00a0% et 57\u00a0% de la variabilit\u00e9 du rendement du ma\u00efs, du riz et du soja, a d\u00e9montr\u00e9 des performances de pr\u00e9diction du rendement sup\u00e9rieures \u00e0 celles des intrants individuels. Alors que les donn\u00e9es satellitaires ont contribu\u00e9 \u00e0 la pr\u00e9diction du rendement des cultures principalement au d\u00e9but de la pointe de la saison de croissance, les donn\u00e9es climatiques ont fourni des informations suppl\u00e9mentaires principalement \u00e0 la pointe de la fin de la saison. Nous avons \u00e9galement constat\u00e9 que l'utilisation combin\u00e9e de l'IVE, du LST et du SIF a am\u00e9lior\u00e9 la pr\u00e9cision du mod\u00e8le par rapport au mod\u00e8le d'IVE de r\u00e9f\u00e9rence. Cependant, les indices de v\u00e9g\u00e9tation bas\u00e9s sur l'optique partageaient des informations similaires et ne fournissaient pas beaucoup d'informations suppl\u00e9mentaires au-del\u00e0 de l'IVE. Les pr\u00e9visions de rendement en cours de saison ont montr\u00e9 que les rendements des cultures peuvent \u00eatre pr\u00e9vus de mani\u00e8re satisfaisante deux \u00e0 trois mois avant la r\u00e9colte. La g\u00e9ographie, la topographie, la VOD, l'IVE, les param\u00e8tres hydrauliques du sol et les param\u00e8tres nutritifs sont plus importants pour la pr\u00e9diction du rendement des cultures.", "keywords": ["Atmospheric sciences", "Climate", "Multi-source satellite data", "Normalized Difference Vegetation Index", "Engineering", "Pathology", "Climate change", "Urban Heat Islands and Mitigation Strategies", "Linear regression", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Ecology", "Geography", "Statistics", "Agriculture", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Aerospace engineering", "Archaeology", "Physical Sciences", "Metallurgy", "Medicine", "Seasons", "Global Vegetation Models", "Biomass Estimation", "Regression analysis", "Vegetation (pathology)", "Crops", " Agricultural", "Environmental Engineering", "Environmental data", "Yield (engineering)", "Zea mays", "Environmental science", "Machine learning", "FOS: Mathematics", "Crop yield", "Biology", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "Predictive modelling", "Food security", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "Materials science", "Yield prediction", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Growing season", "0401 agriculture", " forestry", " and fisheries", "Mathematics"], "contacts": [{"organization": "Zhenwang Li, Lei Ding, Donghui Xu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/34998760"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "34998760", "name": "item", "description": "34998760", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/34998760"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "6caa2183-090d-487a-8636-124f065a7818", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-17.3, -34.6], [-17.3, 38.2], [51.1, 38.2], [51.1, -34.6], [-17.3, -34.6]]]}, "properties": {"themes": [{"concepts": [{"id": "climatologyMeteorologyAtmosphere"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}], "updated": "2023-01-31T08:19:22", "created": "2013-10-01T17:22:00", "language": "eng", "title": "Correlation coefficients between yield and other factors for maize (1981-2050) - ClimAfrica WP4", "description": "The correlation coefficients between yield and other factors have been computed at the zone level for the period 1981-2050 and classified in 5 classes. These correlations allow identifying the causes of a negative or positive impact of climate on maize's yield.\nThis data set has been produced in the framework of the \u201cClimate change predictions in Sub-Saharan Africa: impacts and adaptations (ClimAfrica)\u201d project, Work Package 4 (WP4). More information on ClimAfrica project is provided in the Supplemental Information section of this metadata.", "formats": [{"name": "GeoTIFF"}, {"name": "WWW:LINK-1.0-http--link"}, {"name": "WWW:DOWNLOAD-1.0-http--download"}], "keywords": ["yield", "temperature", "precipitation", "evapotranspiration", "Aridity Index", "Length growing seasons", "soil water content", "total carbon", "Water Use Efficiency", "Water Requirement Satisfaction Index", "runoff", "correlation", "PET", "AET", "LGP", "SWCN", "WUE", "WRSI", "AI", "WP4", "ClimAfrica", "Tag_climafrica", "Africa"], "contacts": [{"name": "Christelle Vancutsem", "organization": "FAO-UN", "position": null, "roles": ["originator"], "phones": [{"value": null}], "emails": [{"value": "Christelle.Vancutsem@fao.org"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}, {"organization": "FAO-UN", "roles": ["creator"]}], "distancevalue": "10", "distanceuom": "Km", "edition": "First"}, "links": [{"href": "https://www.fao.org/3/i7040e/i7040e.pdf", "name": "Scenarios of major production systems in Africa", "protocol": "WWW:LINK-1.0-http--link", "rel": null}, {"href": "https://www.cmcc.it/projects/climafrica-climate-change-predictions-in-sub-saharian-africa-impacts-and-adaptations", "name": "CLIMAFRICA \u2013 Climate change predictions in Sub-Saharan Africa: impacts and adaptations", "protocol": "WWW:LINK-1.0-http--link", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/uuid/6caa2183-090d-487a-8636-124f065a7818/resources/Cor_Yieldsea_lpjm_B1_teco_rf_new.zip", "description": "Correlation coefficient between yield and other factors for maize - historical period (1981-2050)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/uuid/6caa2183-090d-487a-8636-124f065a7818/thumbnail/lpjm_b1_Teco_rf_yield_vs_tmax_s.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/uuid/6caa2183-090d-487a-8636-124f065a7818/large_thumbnail/lpjm_b1_Teco_rf_yield_vs_tmax.png", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "6caa2183-090d-487a-8636-124f065a7818", "name": "item", "description": "6caa2183-090d-487a-8636-124f065a7818", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/6caa2183-090d-487a-8636-124f065a7818"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1981-01-01T00:00:00Z", "2050-12-31T00:00:00Z"]}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Growing+season&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Growing+season&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Growing+season&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Growing+season&offset=10", "hreflang": "en-US"}], "numberMatched": 10, "numberReturned": 10, "distributedFeatures": [], "timeStamp": "2026-05-30T19:07:28.676595Z"}