{"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": "10.1029/2019gb006393", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-30T16:18:11Z", "type": "Journal Article", "created": "2020-02-07", "title": "Sources of Uncertainty in Regional and Global Terrestrial CO 2 Exchange Estimates", "description": "<p>The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO  growth rate, fossil fuel emissions, and modeled (bottom\uffe2\uff80\uff90up) land and ocean fluxes cannot be fully closed, leading to a \uffe2\uff80\uff9cbudget imbalance,\uffe2\uff80\uff9d highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom\uffe2\uff80\uff90up and top\uffe2\uff80\uff90down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO  growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El\uffc2\uffa0Ni\uffc3\uffb1o\uffe2\uff80\uff93Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high\uffe2\uff80\uff90resolution remote\uffe2\uff80\uff90sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.</p>", "keywords": ["[SDE] Environmental Sciences", "FLUXES", "550", "BURNED AREA PRODUCT", "atmospheric inversions", "01 natural sciences", "Environnement et pollution", "DATA ASSIMILATION", "Ph\u00e9nom\u00e8nes atmosph\u00e9riques", "PLANT FUNCTIONAL TYPES", "global carbon budget", "carbon cycle", "ATMOSPHERIC CO2", "0105 earth and related environmental sciences", "LAND-COVER CHANGE", "FOSSIL-FUEL", "VEGETATION MODEL ORCHIDEE", "15. Life on land", "ddc:910", "CARBON-DIOXIDE EMISSIONS", "13. Climate action", "[SDE]Environmental Sciences", "dynamic global vegetation models", "contr\u00f4le de la pollution", "Technologie de l'environnement", "INCORPORATING SPITFIRE"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019GB006393"}, {"href": "https://doi.org/10.1029/2019gb006393"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2019gb006393", "name": "item", "description": "10.1029/2019gb006393", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2019gb006393"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-01T00:00:00Z"}}, {"id": "10.1088/1748-9326/aaeae7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:18:57Z", "type": "Journal Article", "created": "2018-10-24", "title": "Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling", "description": "Open AccessA wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.", "keywords": ["Global vegetation models", "550", "manipulation experiments", "Terrestrial-Aquatic Linkages", "Kolefni", "01 natural sciences", "Nutrient cycle", "Agricultural and Biological Sciences", "Terrestrial ecosystem", "SDG 13 - Climate Action", "Climate change", "Jar\u00f0vegur", "Environmental resource management", "Global change", "General Environmental Science", "SDG 15 - Life on Land", "Carbon-nutrient cycle interactions", "2. Zero hunger", "Data syntheses", "Global and Planetary Change", "Ecology", "Geography", "Physics", "Life Sciences", "Application of Stable Isotopes in Trophic Ecology", "Cycling", "Carbon cycle", "04 agricultural and veterinary sciences", "Chemistry", "ORGANIC-MATTER", "Archaeology", "Physical Sciences", "Nutrient availability", "NET PRIMARY PRODUCTIVITY", "Ecosystem Functioning", "570", "LAND", "TROPICAL RAIN-FOREST", "carbon-nutrient cycle interactions", "data syntheses", "Soil Science", "Environmental science", "[SDU] Sciences of the Universe [physics]", "SOIL-PHOSPHORUS AVAILABILITY", "global vegetation models", "SDG 3 - Good Health and Well-being", "nutrients", "USE EFFICIENCY", "SDG 7 - Affordable and Clean Energy", "GLOBAL CHANGE", "Key (lock)", "Biology", "Ecosystem", "Manipulation experiments", "0105 earth and related environmental sciences", "Renewable Energy", " Sustainability and the Environment", "Ecosystem Structure", "Public Health", " Environmental and Occupational Health", "Nutrients", "15. Life on land", "Computer science", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "ECOSYSTEM RESPONSES", "FOS: Biological sciences", "Global Methane Emissions and Impacts", "Environmental Science", "0401 agriculture", " forestry", " and fisheries", "NITROGEN-FIXATION", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient Limitation", "ELEVATED CO2", "Nutrient"]}, "links": [{"href": "https://doi.org/10.1088/1748-9326/aaeae7"}, {"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/aaeae7", "name": "item", "description": "10.1088/1748-9326/aaeae7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1088/1748-9326/aaeae7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-12-07T00:00:00Z"}}, {"id": "10.5194/hess-24-3789-2020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:22:51Z", "type": "Journal Article", "created": "2020-07-27", "title": "Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. The main objective of this work is to question the representation of the energy budget in soil\u2013vegetation\u2013atmosphere transfer\u00a0(SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere\u00a0(ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one\u00a0patch), is compared to the new multiple energy balance\u00a0(MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two\u00a0patches) is also considered for the olive orchard. Continuous observations of evapotranspiration\u00a0(ET), with an eddy covariance system and plant transpiration\u00a0(Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA\u2013MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil\u2013vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA\u2013MEB did not exceed 10\u2009W\u2009m\u22122 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P\u00a0(ISBA\u2013MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled\u00a0(ISBA-2P) and the coupled\u00a0(ISBA\u2013MEB) representations, outperformed the single-source version\u00a0(ISBA-1P), with slightly better results for ISBA\u2013MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA\u2013MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of\u00a01.60, 0.90, and 0.70\u2009mm\u2009d\u22121 and R2\u00a0of\u00a00.43, 0.69, and\u00a00.70\u00a0for ISBA-1P, ISBA-2P and ISBA\u2013MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalis\u00e9e (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA\u2013MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA\u2013MEB model.                     </p></article>", "keywords": ["Technology", "Atmospheric Science", "Atmospheric sciences", "550", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "02 engineering and technology", "Energy balance", "Eddy covariance", "Environmental technology. Sanitary engineering", "01 natural sciences", "Environmental science", "G", "Meteorology", "Geography. Anthropology. Recreation", "GE1-350", "Biology", "TD1-1066", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Evapotranspiration", "Ecology", "Global Forest Drought Response and Climate Change", "T", "Causes and Impacts of Climate Change Over Millennia", "Physics", "Hydrology (agriculture)", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "[SDV] Life Sciences [q-bio]", "Environmental sciences", "Earth and Planetary Sciences", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Global Drought Monitoring and Assessment", "Leaf area index", "Thermodynamics", "Global Vegetation Models"]}, "links": [{"href": "https://doi.org/10.5194/hess-24-3789-2020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-24-3789-2020", "name": "item", "description": "10.5194/hess-24-3789-2020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-24-3789-2020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-15T00:00:00Z"}}, {"id": "10.60692/khb9k-9s285", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:25:23Z", "type": "Journal Article", "created": "2020-07-27", "title": "Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. The main objective of this work is to question the representation of the energy budget in soil\u2013vegetation\u2013atmosphere transfer\u00a0(SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere\u00a0(ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one\u00a0patch), is compared to the new multiple energy balance\u00a0(MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two\u00a0patches) is also considered for the olive orchard. Continuous observations of evapotranspiration\u00a0(ET), with an eddy covariance system and plant transpiration\u00a0(Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA\u2013MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil\u2013vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA\u2013MEB did not exceed 10\u2009W\u2009m\u22122 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P\u00a0(ISBA\u2013MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled\u00a0(ISBA-2P) and the coupled\u00a0(ISBA\u2013MEB) representations, outperformed the single-source version\u00a0(ISBA-1P), with slightly better results for ISBA\u2013MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA\u2013MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of\u00a01.60, 0.90, and 0.70\u2009mm\u2009d\u22121 and R2\u00a0of\u00a00.43, 0.69, and\u00a00.70\u00a0for ISBA-1P, ISBA-2P and ISBA\u2013MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalis\u00e9e (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA\u2013MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA\u2013MEB model.</p></article>", "keywords": ["Technology", "Atmospheric Science", "Atmospheric sciences", "550", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "02 engineering and technology", "Energy balance", "Eddy covariance", "Environmental technology. Sanitary engineering", "01 natural sciences", "Environmental science", "G", "Meteorology", "Geography. Anthropology. Recreation", "GE1-350", "Biology", "TD1-1066", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Evapotranspiration", "Ecology", "Global Forest Drought Response and Climate Change", "T", "Causes and Impacts of Climate Change Over Millennia", "Physics", "Hydrology (agriculture)", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "[SDV] Life Sciences [q-bio]", "Environmental sciences", "Earth and Planetary Sciences", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Global Drought Monitoring and Assessment", "Leaf area index", "Thermodynamics", "Global Vegetation Models"]}, "links": [{"href": "https://doi.org/10.60692/khb9k-9s285"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/khb9k-9s285", "name": "item", "description": "10.60692/khb9k-9s285", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/khb9k-9s285"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-15T00:00:00Z"}}, {"id": "20.500.11815/1261", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:26:37Z", "type": "Journal Article", "created": "2018-10-24", "title": "Using research networks to create the comprehensive datasets needed to assess nutrient availability as a key determinant of terrestrial carbon cycling", "description": "Open AccessA wide range of research shows that nutrient availability strongly influences terrestrial carbon (C) cycling and shapes ecosystem responses to environmental changes and hence terrestrial feedbacks to climate. Nonetheless, our understanding of nutrient controls remains far from complete and poorly quantified, at least partly due to a lack of informative, comparable, and accessible datasets at regional-to-global scales. A growing research infrastructure of multi-site networks are providing valuable data on C fluxes and stocks and are monitoring their responses to global environmental change and measuring responses to experimental treatments. These networks thus provide an opportunity for improving our understanding of C-nutrient cycle interactions and our ability to model them. However, coherent information on how nutrient cycling interacts with observed C cycle patterns is still generally lacking. Here, we argue that complementing available C-cycle measurements from monitoring and experimental sites with data characterizing nutrient availability will greatly enhance their power and will improve our capacity to forecast future trajectories of terrestrial C cycling and climate. Therefore, we propose a set of complementary measurements that are relatively easy to conduct routinely at any site or experiment and that, in combination with C cycle observations, can provide a robust characterization of the effects of nutrient availability across sites. In addition, we discuss the power of different observable variables for informing the formulation of models and constraining their predictions. Most widely available measurements of nutrient availability often do not align well with current modelling needs. This highlights the importance to foster the interaction between the empirical and modelling communities for setting future research priorities.", "keywords": ["Global vegetation models", "550", "manipulation experiments", "Terrestrial-Aquatic Linkages", "Kolefni", "01 natural sciences", "Nutrient cycle", "Agricultural and Biological Sciences", "Terrestrial ecosystem", "SDG 13 - Climate Action", "Climate change", "Jar\u00f0vegur", "Environmental resource management", "Global change", "General Environmental Science", "SDG 15 - Life on Land", "Carbon-nutrient cycle interactions", "2. Zero hunger", "Data syntheses", "Global and Planetary Change", "Ecology", "Geography", "Physics", "Life Sciences", "Application of Stable Isotopes in Trophic Ecology", "Cycling", "Carbon cycle", "04 agricultural and veterinary sciences", "Chemistry", "ORGANIC-MATTER", "Archaeology", "Physical Sciences", "Nutrient availability", "NET PRIMARY PRODUCTIVITY", "Ecosystem Functioning", "570", "LAND", "TROPICAL RAIN-FOREST", "carbon-nutrient cycle interactions", "data syntheses", "Soil Science", "Environmental science", "[SDU] Sciences of the Universe [physics]", "SOIL-PHOSPHORUS AVAILABILITY", "global vegetation models", "SDG 3 - Good Health and Well-being", "nutrients", "USE EFFICIENCY", "SDG 7 - Affordable and Clean Energy", "GLOBAL CHANGE", "Key (lock)", "Biology", "Ecosystem", "Manipulation experiments", "0105 earth and related environmental sciences", "Renewable Energy", " Sustainability and the Environment", "Ecosystem Structure", "Public Health", " Environmental and Occupational Health", "Nutrients", "15. Life on land", "Computer science", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "ECOSYSTEM RESPONSES", "FOS: Biological sciences", "Global Methane Emissions and Impacts", "Environmental Science", "0401 agriculture", " forestry", " and fisheries", "NITROGEN-FIXATION", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient Limitation", "ELEVATED CO2", "Nutrient"]}, "links": [{"href": "https://doi.org/20.500.11815/1261"}, {"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": "20.500.11815/1261", "name": "item", "description": "20.500.11815/1261", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.11815/1261"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-12-07T00:00:00Z"}}, {"id": "2980519968", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-30T16:27:13Z", "type": "Journal Article", "created": "2020-07-27", "title": "Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. The main objective of this work is to question the representation of the energy budget in soil\u2013vegetation\u2013atmosphere transfer\u00a0(SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere\u00a0(ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one\u00a0patch), is compared to the new multiple energy balance\u00a0(MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two\u00a0patches) is also considered for the olive orchard. Continuous observations of evapotranspiration\u00a0(ET), with an eddy covariance system and plant transpiration\u00a0(Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA\u2013MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil\u2013vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA\u2013MEB did not exceed 10\u2009W\u2009m\u22122 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P\u00a0(ISBA\u2013MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled\u00a0(ISBA-2P) and the coupled\u00a0(ISBA\u2013MEB) representations, outperformed the single-source version\u00a0(ISBA-1P), with slightly better results for ISBA\u2013MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA\u2013MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of\u00a01.60, 0.90, and 0.70\u2009mm\u2009d\u22121 and R2\u00a0of\u00a00.43, 0.69, and\u00a00.70\u00a0for ISBA-1P, ISBA-2P and ISBA\u2013MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalis\u00e9e (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA\u2013MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA\u2013MEB model.                     </p></article>", "keywords": ["Technology", "Atmospheric Science", "Atmospheric sciences", "550", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "02 engineering and technology", "Energy balance", "Eddy covariance", "Environmental technology. Sanitary engineering", "01 natural sciences", "Environmental science", "G", "Meteorology", "Geography. Anthropology. Recreation", "GE1-350", "Biology", "TD1-1066", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Evapotranspiration", "Ecology", "Global Forest Drought Response and Climate Change", "T", "Causes and Impacts of Climate Change Over Millennia", "Physics", "Hydrology (agriculture)", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "[SDV] Life Sciences [q-bio]", "Environmental sciences", "Earth and Planetary Sciences", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Global Drought Monitoring and Assessment", "Leaf area index", "Thermodynamics", "Global Vegetation Models"]}, "links": [{"href": "https://doi.org/2980519968"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2980519968", "name": "item", "description": "2980519968", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2980519968"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-15T00:00:00Z"}}, {"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"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Global+Vegetation+Models&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=Global+Vegetation+Models&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=Global+Vegetation+Models&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Global+Vegetation+Models&offset=8", "hreflang": "en-US"}], "numberMatched": 8, "numberReturned": 8, "distributedFeatures": [], "timeStamp": "2026-05-30T19:05:26.463814Z"}