{"type": "FeatureCollection", "features": [{"id": "10.5281/zenodo.3964082", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:48Z", "type": "Dataset", "title": "Lysimeters data from Windmoser and Michel 2020", "description": "Open AccessThe authors thanks the von Humboldt Stiftung for financial support of the MaNiP project through the Max Planck research prize 2013 to Markus Reichstein", "keywords": ["2. Zero hunger", "13. Climate action", "15. Life on land"], "contacts": [{"organization": "Windmoser, Peter, Perez-Priego, Oscar, El-Madany, Tarek S., Carrara, Arnaud, Kolle, Olaf, Hertel, Martin, L\u00f3pez-Jimenez, Ramon, Reichstein, Markus, Migliavacca, Mirco,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3964082"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3964082", "name": "item", "description": "10.5281/zenodo.3964082", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3964082"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-28T00:00:00Z"}}, {"id": "10.5281/zenodo.4293454", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Soil organic carbon distribution for 0-3 m soils at 1 km2 scale of the frozen ground in the Third Pole Regions", "description": "Soil organic carbon (SOC) is very important in the vulnerable ecological environment of the Third Pole; however, data regarding the spatial distribution of SOC are still scarce and uncertain. Based on multiple environmental variables and soil profile data from 458 pits (depth of 0\u20131 m) and 114 cores (depth of 0\u20133 m), this study uses a machine-learning approach to evaluate the SOC storage and spatial distribution at different soil depths (0\u201330 cm, 0\u201350 cm, 0\u2013100 cm, 0\u2013200 cm, and 0\u2013300 cm) in the frozen ground area of the Third Pole region. Our results provide information on the storage, patterns, and environmental controls of SOCSs at a 1 km2 scale for areas of frozen ground in the Third Pole region, thus providing a scientific basis for future studies pertaining to Earth system models. Soil organic carbon data is stored in grids format, and the file name is 'TP-SOC-d.tif', where d represents soil depth, for example, 'TP-SOC-30.tif' represents the spatial distribution of soil organic carbon stocks in the Third Pole regions of the upper 30 cm depth interval.", "keywords": ["13. Climate action", "15. Life on land"], "contacts": [{"organization": "Wang, Dong, Tonghua Wu, Xiaodong Wu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4293454"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4293454", "name": "item", "description": "10.5281/zenodo.4293454", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4293454"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-27T00:00:00Z"}}, {"id": "10.5281/zenodo.3832031", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:48Z", "type": "Dataset", "title": "Radiocarbon content of carbon dioxide, methane, dissolved organic carbon and particulate organic carbon from the northern permafrost region and other studies", "description": "The dataset includes 14C measurements of CO2, CH4, DOC and POC mostly from the northern permafrost region. Some other studies are included from sites not underlained by permafrost. The dataset focuses on 14C measurements of gaseous soil emissions and waterborne ecosystem C fluxes but the database also included C forms belowground, such as soil gases and pore water DOC.", "keywords": ["13. Climate action", "15. Life on land", "radiocarbon", " permafrost", " carbon dioxide", " methane", " dissolved organic carbon", " particulate organic carbon", " DOC", " POC", " thermokarst", " thaw"], "contacts": [{"organization": "Estop-Aragon\u00e9s, Cristian", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3832031"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3832031", "name": "item", "description": "10.5281/zenodo.3832031", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3832031"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-18T00:00:00Z"}}, {"id": "10.5281/zenodo.3971022", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:48Z", "type": "Dataset", "title": "VDMBC_vertical_distribution_soil_microbial_biomass_carbon", "description": "Soil microbial biomass carbon (SMBC) is important in regulating soil organic carbon (SOC) dynamics along soil profiles by mediating the decomposition and formation of SOC. The dataset (VDMBC) is about the vertical distributions of SOC, SMBC, and soil microbial quotient (SMQ = SMBC/SOC) and their relations to environmental factors across five continents. Data were collected from literature, with a total of 289 soil profiles and 1040 observations in different soil layers compiled. The associated environment data collectd include climate, ecosystem types, and edaphic factors. We developed this dataset by searching the the Web of Sciene and the China National Knowledge Infrastructure from the year of 1970 to 2019. All the data in this dataset met two creteria: 1) there were at least three mineral soil layers along a soil profile, and 2) SMBC was measured using the fumigation extraction method. The data in tables and texts were obtained from literature directly, and the data in figures were extracted by using the GetData Graph digitizer software version 2.25. When climate and soil properties were not available from publications, we obtainted the data from the World Weather Information Service (https://worldweather.wmo.int/en/home.html) and SoilGrids at a spatial resolution of 250 meters (version 0.5.3, https://soilgrids.org). The units of all the variables were converted to the standard international units or commonly used ones and the values were converted correspondingly. For example, the value of soil organic matter (SOM) was converted to SOC using the equation (SOC = SOM \u00d7 0.58). Soil depth was calculated as the arithmetic mean value of the upper and lower boundaries for a given soil layer. This dataset can be used in predicting global SOC change along soil profiles using the multi-layer soil carbon models. It can also be used to analyse how soil microbial biomass changes with plant roots as well as the composition, structure, and functions of soil microbial communities along soil profiles at large spatial scales. This dataset offers opportunities to improve our prediction of SOC dynamics under global changes and to advance our understanding of the environmental controls.", "keywords": ["2. Zero hunger", "soil organic carbon", "13. Climate action", "deep soils", "soil clay content", "soil C/N ratio", "soil profile", "15. Life on land", "micorbial quotient"], "contacts": [{"organization": "Sun, Tingting, Wang, Yugang, Hui, Dafeng, Jing, Xin, Feng, Wenting,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3971022"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3971022", "name": "item", "description": "10.5281/zenodo.3971022", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3971022"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-03T00:00:00Z"}}, {"id": "10.5281/zenodo.3997845", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:48Z", "type": "Journal Article", "title": "Predicting crop yield using data fusion by matrix factorization algorithm", "description": "How to choose the best hybrid of particular crop for the given location when there are thousands of choices of different varieties on the market? Yield is one of the best indicators for making the decision which seed varieties would be suitable. In order to choose the best hybrid for the given location we need to be able to predict crop yield of all existing hybrids for that location. Not all varieties will be suitable for all fields. This task may be seen as recommendation system where we want to recommend the best hybrid, the one that will give the highest yield, on the chosen farm. Predicting yield is a hard task. There are many parameters like weather, soil and genetics that influence on yield. The biggest challenge in improving the accuracy of prediction is to jointly analyze the complex interaction of all those parameters. In this task we used Data Fusion by Matrix Factorization (DFMF) algorithm that allows us to inference that complex interactions. DFMF uses a penalized matrix tri-factorization model that collectively tri-factorizes many data matrices such that each data matrix is decomposed into a product of tree latent matrices. Data that was analyzed in the paper comes from Syngenta Crop Challenge. It contains information about soil, weather and performance of various hybrids. We created matrix where the rows were hybrids and the columns were fields present in the chosen year and the entries of the matrix represent yield. Only ~10% of the matrix was known and the task was to complete the rest of the matrix, to find out the yield of all hybrid on all locations. In order to do that other data sources should help us. We wanted to enrich historical dataset as it is impossible to plant every seed variety on all fields. Getting new, enriched dataset would help us in making predictions for the next season, identifying the behavior of hybrids in different settings, deciding weather hybrid is tolerant or not to stresses...", "keywords": ["2. Zero hunger", "crop yield prediction", " data fusion", " matrix factorization", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3997845"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/EFITA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3997845", "name": "item", "description": "10.5281/zenodo.3997845", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3997845"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4005650", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:48Z", "type": "Dataset", "title": "Dataset_2020_Biogeosciences_Protists and collembolans alter microbial community composition, C dynamics and soil aggregation in simplified consumer - prey systems", "description": "Dataset associated to the publication: Erktan, A., Rillig, M.C., Carminati, A., Jousset, A., Scheu, S. (2020) Protists and collembolans alter microbial community composition, C dynamics and soil aggregation in simplified consumer - prey systems, Biogeosciences, accepted the 27/08/2020.", "keywords": ["15. Life on land"], "contacts": [{"organization": "Erktan, Amandine, Rillig, Matthias C., Carminati, Andrea, Jousset, Alexandre, Scheu, Stefan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4005650"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4005650", "name": "item", "description": "10.5281/zenodo.4005650", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4005650"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-28T00:00:00Z"}}, {"id": "10.5281/zenodo.4069473", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Supplemental information for McClelland et al. (2020). Management of cover crops in temperate climates influences soil organic carbon stocks \u2013 A meta-analysis", "description": "All supplemental information for McClelland et al. (2020). Management of cover crops in temperate climates influences soil organic carbon stocks \u2013 A meta-analysis.", "keywords": ["2. Zero hunger", "13. Climate action", "Soil organic carbon", "Cover crop", "15. Life on land"], "contacts": [{"organization": "McClelland, Shelby C, Paustian, Keith, Schipanski, Meagan E,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4069473"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4069473", "name": "item", "description": "10.5281/zenodo.4069473", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4069473"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-06T00:00:00Z"}}, {"id": "10.5281/zenodo.4090927", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "iSDAsoil: soil organic carbon for Africa predicted at 30 m resolution at 0-20 and 20-50 cm depths", "description": "Open AccessiSDA is a social enterprise with the mission to improve smallholder farmer profitability across Africa. iSDA builds on the legacy of the African Soils information service (AfSIS) project. We are grateful for the outputs generated by all former AfSIS project partners: Columbia University, Rothamsted Research, World Agroforestry (ICRAF), Quantitative Engineering Design (QED), ISRIC \u2014 World Soil Information, International Institute of Tropical Agriculture (IITA), Ethiopia Soil Information Service (EthioSIS), Ghana Soil Information Service (GhaSIS), Nigeria Soil Information Service (NiSIS) and Tanzania Soil Information Service (TanSIS). More details on AfSIS partners and data contributors can be found at https://isda-africa.com/isdasoil", "keywords": ["2. Zero hunger", "iSDA", "13. Climate action", "organic carbon", "Africa", "15. Life on land", "soil"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4090927"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4090927", "name": "item", "description": "10.5281/zenodo.4090927", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4090927"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-15T00:00:00Z"}}, {"id": "10.5281/zenodo.4384530", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Dataset", "title": "Soil profile, climatic, physiographic, overstory and understory data in mixed and monospecific plots of Pinus sylvestris and Pinus pinaster in Spain", "description": "Open AccessThis dataset provides valuable environmental information about a triplets\u2019 essay of Scots pine and Maritime pine in Spain. The data characterizes the soil profile (physicochemical parameters of organic and mineral horizons), climate, physiography, understory and overstory. The essay, located in North-Central Spain, consists of eighteen forest plots divided in six triplets. Each triplet includes three circular plots of 15 m-radius located less than 1 km from each other: two monospecific plots dominated by P. sylvestris or P. pinaster, and one mixed plot of both species. In each plot, one pit up to 50 cm depth, one 15 m-radius overstory features inventory and ten understory 1x1 m inventories were carried out. Additionally, physiographic and climatic variables were collected per plot. The file contains information about the 215 environmental variables studied in the eighteen forest plots. Triplet: Triplet to which the plot belongs(1: Triplet 1; 2: Triplet 2; 3: Triplet 3; 4: Triplet 4; 5: Triplet 5; 6: Triplet 6). Stand_type: Type of stand (PS: monospecific stand of Pinus sylvestris L.; PP: monospecific stand of Pinus pinaster Ait.; MM: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait.). Plot: Plot identification (PS01: monospecific stand of Pinus sylvestris L. of triplet 1; PS02: monospecific stand of Pinus sylvestris L. of triplet 2; PS03: monospecific stand of Pinus sylvestris L. of triplet 3; PS04: monospecific stand of Pinus sylvestris L. of triplet 4; PS05: monospecific stand of Pinus sylvestris L. of triplet 5; PS06: monospecific stand of Pinus sylvestris L. of triplet 6; MM01: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 1; MM02: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 2; MM03: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 3; MM04: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 4; MM05: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 5; MM06: mixed stand of Pinus sylvestris L.and Pinus pinaster Ait. of triplet 6; PP01: monospecific stand of Pinus pinaster Ait. of triplet 1; PP02: monospecific stand of Pinus pinaster Ait. of triplet 2; PP03: monospecific stand of Pinus pinaster Ait. of triplet 3; PP04: monospecific stand of Pinus pinaster Ait. of triplet 4; PP05: monospecific stand of Pinus pinaster Ait. of triplet 5; PP06: monospecific stand of Pinus pinaster Ait. of triplet 6). Lat: Plot latitude in degrees. Long: Plot longitude in degrees. Province: Province to which the plot belongs (B:Province of Burgos; Sp: Province of Soria). Municipality: Municipality to which the plot belongs (M: Town of Mamolar; HP: Town of Hontoria del Pinar; N: Town of Navaleno; St: Town of Soria; CP: Town of Cabrejas del Pinar). Forest: Name of the forest where is located the plot (MB: Mata Blanca; MR: Mata Robledo; FP: Fuente del Pardo; PM: Pajar de la molinera; MP: Mojon Pardo; CM: Cueva de Matarubias). Alti: Plot elevation above sea level in m a.s.l. Slope: Slope (gradient) of the plot in percentage. Ori: Plot orientation in degrees. Clim: Climate clasification acording to K\u00f6ppen classification (1936) (Cfb: Temperate without dry season and temperate summer climate; Csb: Temperate with dry summer climate). XR: Accumulated rainfall in one year according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. JR: January rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 mm FR: February rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. MR: March rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. AR: April rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. MyR: May rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. JnR: June rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. JlR: July rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. AgR: August rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. SR: September rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. OR: October rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. NR: November rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. DR: December rainfall according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in mm. XT: Anual mean temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. JT: January temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. FT: February temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. MT: March temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. AT: April temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. MyT: May temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. JnT: June temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. JlT: July temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. AgT: August temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. ST: September temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. OT: October temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. NT: November temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. DT: December temperature according to \u2018Atlas Agroclim\u00e1tico de Castilla y Le\u00f3n-ITACYL-AEMET\u2019 in \u00baC. Par_mat: Soil parental material according to Spanish Geological Map on a 1M scale. (IGME , 2015) (SM: Sandstones and Marls). Geo_age: Geological age of plot according to Spanish Geological Map on a 1M scale. (IGME, 2015) (Mz: Mesozoic age). Soil: Soil type according to Soil-Survey-Staff (2014) (TpDx: Typic Dystroxerept; TpHx:: Typic Humixerept; AqHx:: Aquic humixerept) Litter_B: Total Leaf Litter Biomass in Mg/ha. FF_Th: Forest floor Thickness in cm. Fsh: Percentage of Fresh to Total Leaf Litter in %. Frg: Percentage of Fragmented to Total Leaf Litter in %. Hmf: Percentage of Humified to Total Leaf Litter in %. GH1: Fist genetic soil horizon according to Soil-Survey-Staff (2014) (Ah:: Mineral horizon with accumulation of organic matter. This horizon is formed at the soil surface or below an O horizon). GH2: Second genetic soil horizon according to Soil-Survey-Staff (2014) (AB: Transition horizon between A and B. A is a mineral horizon formed at the surface or below an O horizon, B is a subsurface horizon in which the structure of the rock is obliterated; AC: Transition horizon between A and C. A is a mineral horizon formed at the surface or below an O horizon; C is a mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Bw: Mineral B horizon where the development of colour or structure are its more important diagnostic characteristics). GH3: Third genetic soil horizon according to Soil-Survey-Staff (2014) (Bw: : Mineral B horizon where the development of colour or structure are its more important diagnostic characteristics; C: Mineral horizon, excluding hard bedrock, that is little affected by pedogenetic processes; Cg: Mineral horizon in which a distinct pattern of mottling occurs that reflects alternating conditions of oxidation and reduction of sesquioxides, caused by seasonal surface waterlogging). Th_H1: Thickness of the first soil horizon in cm. Th_H2: Thickness of the second soil horizon in cm. Th_H3: Thickness of the third soil horizon in cm. wetCol_H1: Wet matrix colour (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR2/1: black; 10YR2/2: very dark brown; 10YR3/1: very dark grey; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR6/3: pale brown). wetCol_H2: Wet matrix colour (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (5YR5/8: yellowish red; 7.5YR4/6: strong brown; 10YR3/2: very dark greyish brown; 10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/3: brown; 10YR5/4: yellowish brown with chroma 4; 10YR5/6: yellowish brown with chroma 6; 10YR5/8: yellowish brown with chroma 8; 10YR6/4: light yellowish brown; 10YR6/6: brownish yellow). wetCol_H3: Wet matrix colour (Hue Value/Chroma) of the third soil horizon according to Munsell soil color chards (5YR4/6: yellowish red; 10YR4/4: dark yellowish brown with chroma 4; 10YR4/6: dark yellowish brown with chroma 6; 10YR5/8: yellowish brown; 10YR6/1: grey). dryCol_H1:Dry matrix colour (Hue Value/Chroma) of the first soil horizon according to Munsell soil color chards (10YR4/1: dark grey; 10YR4/2: dark greyish brown; 10YR5/1: grey with value 5; 10YR5/2: greyish brown; 10YR5/3: brown; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown; 10YR7/2: light grey). dryCol_H2: Dry matrix colour (Hue Value/Chroma) of the second soil horizon according to Munsell soil color chards (7.5YR6/6: redish brown; 10YR4/1: dark grey; 10YR6/1: grey with value 6; 10YR6/2: light yellowish brown with chroma 2; 10YR6/3: pale brown; 10YR6/4: light yellowish brown with chroma 4; 10YR6/6: brownish yellow; 10YR7/3: very pale brown with value 7 and choma 3; 10YR7/4: very pale brown withvalue 7 and choma 4; 10YR8/4: very pale brown with value 8 and choma 4). dryCol_H3: Dry matrix colour (Hue Value/Chroma) of the third soil horizon according to Munsell soil color chards (5YR5/6: yellowish red; 7.5YR5/6: strong brown; 10YR6/4: light yellowish brown; 10YR6/6: brownish yellow; 10YR7/4: very pale brown; 10YR8/1: white). Sand_H1: Percentage of sand of the first soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Sand_H2: Percentage of sand of the second soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Sand_H3: Percentage of sand of the third soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Silt_H1: Percentage of silt of the first soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Silt_H2: Percentage of silt of the second soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Silt_H3: Percentage of silt of the third soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Clay_H1: Percentage of clay of the first soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Clay_H2: Percentage of clay of the second soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Clay_H3: Percentage of clay of the third soil horizon determined by the pipette method (MAPA 1994) according to Soil-Survey-Staff (2014) in % weight/weight. Tex_H1: Textural class of the first soil horizon according to Soil-Survey-Staff (2014) (SL: Sandy Loam; LfS: Loamy Fine Sand; L: Loam). Tex_H2: Textural class of the second soil horizon according to Soil-Survey-Staff (2014) (SL: Sandy Loam; LfS: Loamy Fine Sand; L: Loam, CL: Clay loam). Tex_H3: Textural class of the third soil horizon according to Soil-Survey-Staff (2014) (SL: Sandy Loam; L: Loam; C: Clay). Stones_H1: Coarse soil material (> 2 mm) of the first soil horizon in % weight/weight. Stones_H2: Coarse soil material (> 2 mm) of the second soil horizon in % weight/weight. Stones_H3: Coarse soil material (> 2 mm) of the third soil horizon in % weight/weight. %FR_H1: Fine roots (< 5 mm) of the first soil horizon in %. %FR_H2: Fine roots (< 5 mm) of the second soil horizon in %. %FR_H3: Fine roots (< 5 mm) of the third soil horizon in %. %CR_H1: Coarse roots (> 5 mm) of the first soil horizon in %. %CR_H2: Coarse roots (> 5 mm) of the second soil horizon in %. %CR_H3: Coarse roots (> 5 mm) of the third soil horizon in %. bD_H1: Bulk density of the first soil horizon according to MAPA (1994) in g/cm3. bD_H2: Bulk density of the second soil horizon according to MAPA (1994) in g/cm3. bD_H3: Bulk density of the third soil horizon according to MAPA (1994) in g/cm3. pD_H1: Particle density of the first soil horizon according to MAPA (1994) in g/cm3. pD_H2: Particle density of the second soil horizon according to MAPA (1994) in g/cm3. pD_H3: Particle density of the third soil horizon according to MAPA (1994) in g/cm3. Poro_H1: Porosity of the first soil horizon according to MAPA (1994) in % vol/vol. Poro_H2: Porosity of the second soil horizon according to MAPA (1994) in % vol/vol. Poro_H3: Porosity of the third soil horizon according to MAPA (1994) in % vol/vol. pH_H1: pH (1:2.5 H2O) of the first soil horizon according to MAPA (1994) pH_H2: pH (1:2.5 H2O) of the second soil horizon according to MAPA (1994) pH_H3: pH (1:2.5 H2O) of the third soil horizon according to MAPA (1994) EC_H1: Electrical conductivity of the first soil horizon according to MAPA (1994) in dS/m. EC_H2: Electrical conductivity of the second soil horizon according to MAPA (1994) in dS/m. EC_H3: Electrical conductivity of the third soil horizon according to MAPA (1994) in dS/m. avP_H1: Available phosphorus of the first soil horizon according to Olsen and Sommers (1982) in mg/kg. avP_H2: Available phosphorus of the second soil horizon according to Olsen and Sommers (1982) in mg/kg. avP_H3: Available phosphorus of the third soil horizon according to Olsen and Sommers (1982) in mg/kg. avPstock_H1: Available phosphorus stock of the first soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. avPstock_H2: Available phosphorus stock of the second soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. avPstock_H3: Available phosphorus stock of the third soil horizon up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. avPstock_50: Available phosphorus stock of whole soil profile up to 50 cm depth accorging to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TN_H1. Total nitrogen of the first soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TN_H2: Total nitrogen of the second soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TN_H3: Total nitrogen of the third soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TNstock_H1: Total nitrogen stock of the first soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TNstock_H2: Total nitrogen stock of the second soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TNstock_H3: Total nitrogen stock of the third soil horizon up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TNstock_50: Total nitrogen stock of whole soil profile up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TOC_H1: Total organic carbon of the first soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TOC_H2: Total organic carbon of the second soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TOC_H3: Total organic carbon of the third soil horizon analyzed with a LECO-CHN 2000 elemental analyser in mg/kg. TOCstock_H1:Total organic carbon stock of the first soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TOCstock_H2: Total organic carbon stock of the second soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TOCstock_H3: Total organic carbon stock of the third soil horizon up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. TOCstock_50: Total organic carbon stock of whole soil profile up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. C/N_H1: Ratio of total organic carbon to total nitrogen of the first soil horizon C/N_H2 : Ratio of total organic carbon to total nitrogen of the second soil horizon C/N_H3: Ratio of total organic carbon to total nitrogen of the third soil horizon OxC_H1: Easily oxidizable carbon of the first soil horizon according to Walkley (1947) in mg/kg. OxC_H2: Easily oxidizable carbon of the second soil horizon according to Walkley (1947) in mg/kg. OxC_H3: Easily oxidizable carbon of the third soil horizon according to Walkley (1947) in mg/kg. OxCstock_H1: Easily oxidizable carbon stock of the first soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. OxCstock_H2: Easily oxidizable carbon stock of the second soil horizon according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. OxCstock_H3: Easily oxidizable carbon stock of the third soil horizon up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. OxCstock_50: Easily oxidizable carbon stock of whole soil profile up to 50 cm depth according to L\u00f3pez-Marcos et al. (2019) in Mg/ha. CEC_H1: Cation exchange capacity of the first soil horizon according to Mehlich (1953) in cmol+/kg. CEC_H2: Cation exchange capacity of the second soil horizon according to Mehlich (1953) in cmol+/kg. CEC_H3: Cation exchange capacity of the third soil horizon according to Mehlich (1953) in cmol+/kg. Na+_H1: Exchangeable sodium of the first soil horizon by means of extracting with 1N ammonium acetate (pH=7) (Schollenberger and Simon 1945) in cmol+/kg. Na+_H2: Exchangeable sodium", "keywords": ["Physicochemical soil profile parameters", "Mixed stand", "Understory characterization", "Overstory features", "Pinus sylvestris", "Pinus pinaster", "15. Life on land", "Climatic parameters"], "contacts": [{"organization": "Marcos, Daphne L\u00f3pez, Turri\u00f3n, Mar\u00eda-Bel\u00e9n, Bravo, Felipe, Mart\u00ednez-Ruiz, Carolina,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4384530"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4384530", "name": "item", "description": "10.5281/zenodo.4384530", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4384530"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-03T00:00:00Z"}}, {"id": "10.5281/zenodo.3997846", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:48Z", "type": "Journal Article", "title": "Predicting crop yield using data fusion by matrix factorization algorithm", "description": "How to choose the best hybrid of particular crop for the given location when there are thousands of choices of different varieties on the market? Yield is one of the best indicators for making the decision which seed varieties would be suitable. In order to choose the best hybrid for the given location we need to be able to predict crop yield of all existing hybrids for that location. Not all varieties will be suitable for all fields. This task may be seen as recommendation system where we want to recommend the best hybrid, the one that will give the highest yield, on the chosen farm. Predicting yield is a hard task. There are many parameters like weather, soil and genetics that influence on yield. The biggest challenge in improving the accuracy of prediction is to jointly analyze the complex interaction of all those parameters. In this task we used Data Fusion by Matrix Factorization (DFMF) algorithm that allows us to inference that complex interactions. DFMF uses a penalized matrix tri-factorization model that collectively tri-factorizes many data matrices such that each data matrix is decomposed into a product of tree latent matrices. Data that was analyzed in the paper comes from Syngenta Crop Challenge. It contains information about soil, weather and performance of various hybrids. We created matrix where the rows were hybrids and the columns were fields present in the chosen year and the entries of the matrix represent yield. Only ~10% of the matrix was known and the task was to complete the rest of the matrix, to find out the yield of all hybrid on all locations. In order to do that other data sources should help us. We wanted to enrich historical dataset as it is impossible to plant every seed variety on all fields. Getting new, enriched dataset would help us in making predictions for the next season, identifying the behavior of hybrids in different settings, deciding weather hybrid is tolerant or not to stresses...", "keywords": ["2. Zero hunger", "crop yield prediction", " data fusion", " matrix factorization", "15. Life on land"], "contacts": [{"organization": "Brki\u0107, Milica, Brdar, Sanja, Crnojevi\u0107, Vladimir,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3997846"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/EFITA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3997846", "name": "item", "description": "10.5281/zenodo.3997846", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3997846"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4005651", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:48Z", "type": "Dataset", "title": "Dataset_2020_Biogeosciences_Protists and collembolans alter microbial community composition, C dynamics and soil aggregation in simplified consumer - prey systems", "description": "Dataset associated to the publication: Erktan, A., Rillig, M.C., Carminati, A., Jousset, A., Scheu, S. (2020) Protists and collembolans alter microbial community composition, C dynamics and soil aggregation in simplified consumer - prey systems, Biogeosciences, accepted the 27/08/2020.", "keywords": ["15. Life on land"], "contacts": [{"organization": "Erktan, Amandine, Rillig, Matthias C., Carminati, Andrea, Jousset, Alexandre, Scheu, Stefan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4005651"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4005651", "name": "item", "description": "10.5281/zenodo.4005651", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4005651"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-28T00:00:00Z"}}, {"id": "10.5281/zenodo.4087876", "type": "Feature", "geometry": null, "properties": {"license": "Restricted", "updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Phosphorus addition decreases microbial residual contribution to soil organic carbon pool in a tropical coastal forest", "description": "This is the data supporting the study of 'Phosphorus addition decreases microbial residual contribution to soil organic carbon pool in a tropical coastal forest'. Data in the excel sheet were used for the figures and tables in the article.", "keywords": ["15. Life on land", "6. Clean water"], "contacts": [{"organization": "Zhanfeng, Liu", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4087876"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4087876", "name": "item", "description": "10.5281/zenodo.4087876", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4087876"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-14T00:00:00Z"}}, {"id": "10.5281/zenodo.4091029", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Mapping the irrecoverable carbon in Earth's ecosystems", "description": "These datasets provide global maps of carbon density (aboveground, belowground biomass carbon and soil organic carbon stocks) for the year 2010 and 2018 at ~300-m spatial resolution in Mg ha-1 (Coordinate System: WGS 1984, float format). Input maps were collected from published literature, and where necessary, updated to cover the focal time period. These updates were applied to the manageable carbon, vulnerable carbon and irrecoverable carbon maps. Manageable carbon is carbon in terrestrial and coastal ecosystems that could experience an anthropogenic land-use conversion event . Vulnerable carbon is the carbon that would be that would be released in a typical land-use conversion. Irrecoverable carbon is the carbon that, if lost, would not recover by mid-century. Datasets are disaggregated for carbon density in biomass or soils. To view these datasets, go to: https://irrecoverable.resilienceatlas.org/map.", "keywords": ["13. Climate action", "14. Life underwater", "15. Life on land", "carbon density", " manageable carbon", " vulnerable carbon", " irrecoverable carbon"], "contacts": [{"organization": "Noon, Monica, Goldstein, Allie, Ledezma, Juan Carlos, Roehrdanz, Patrick, Cook-Patton, Susan C., Spawn-Lee, Seth A., Wright, Timothy Maxwell, Gonzalez-Roglich, Mariano, Hole, David G., Rockstr\u00f6m, Johan, Turner, Will R.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4091029"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4091029", "name": "item", "description": "10.5281/zenodo.4091029", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4091029"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-13T00:00:00Z"}}, {"id": "10.5281/zenodo.4104138", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Journal Article", "created": "2020-10-17", "title": "Initial quartz OSL and dust mass accumulation rate investigation of the Kisiljevo loess sequence in north-eastern Serbia", "description": "The thick and apparently continuous loess-palaeosol sequences in the Vojvodina region of northern Serbia are recognized and well understood as some of the oldest and most complete terrestrial European palaeoclimatic archives. By contrast, there are few published records for loess profiles from other regions in Serbia. Here we address this knowledge gap by investigating an 8 m thick loess sequence exposed near the village of Kisiljevo in north eastern Serbia, describing the pedostratigraphy and environmental magnetic signatures in detail and placing these within a chronologic framework using quartz optically stimulated luminescence (OSL) on the 4-11 and 63-90 \u03bcm size fractions. Our results show dust accumulation over the last c. 32 ka, with substantial primary loess accumulation during the Early Holocene prior to the formation of the modern soil. We applied two age-depth modelling approaches to estimate dust mass accumulation rates: the Bacon.35 r software and ADmin model. Both yield high accumulation rates, especially during MIS 2, averaging 550- 600 g m\u22122 a\u22121 which exceed estimates for other investigated loess sequences in the region.", "keywords": ["15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4104138"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Quaternary%20International", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4104138", "name": "item", "description": "10.5281/zenodo.4104138", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4104138"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4133892", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Data on ground ice, organic carbon and soluble cations in tundra permafrost and active-layer soils near Lac de Gras in the Slave Geological Province, N.W.T., Canada", "description": "Open Access{'references': ['Gruber, S., Brown, N., Stewart-Jones, E., Karunaratne, K., Riddick, J., Peart, C., Subedi, R., Kokelj, S. 2018. Drill logs, visible ice content and core photos from 2015 surficial drilling in the Canadian Shield tundra near Lac de Gras, Northwest Territories, Canada, v. 1.0 (2015-2015). Nordicana D38, doi: 10.5885/45558XD-EBDE74B80CE146C6.']}", "keywords": ["permafrost ground ice", " soil carbon", "", "15. Life on land", "permafrost", " ground ice", " soil carbon", " Laurentide ice sheet"], "contacts": [{"organization": "Rupesh, Subedi, Kokelj, Steven V., Gruber, Stephan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4133892"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4133892", "name": "item", "description": "10.5281/zenodo.4133892", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4133892"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-27T00:00:00Z"}}, {"id": "10.5281/zenodo.4161694", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Dataset for \"Changes in Global Terrestrial Live Biomass over the 21st Century\"", "description": "Live woody vegetation is the largest reservoir of biomass carbon with its restoration considered one of the most effective natural climate solutions. However, carbon fluxes associated with terrestrial ecosystems still remain the largest source of uncertainty of the global carbon balance. Here, we develop spatially explicit estimates of global carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show live biomass has removed 4.9-5.5 PgC yr-1 from the atmosphere in this century, offsetting 4.6\u00b10.1 PgC yr-1 of gross emissions from land-use and environmental disturbances and adding substantially (0.23-0.88 PgC yr-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.", "keywords": ["inventory", "remote sensing", "biomass", "13. Climate action", "vegetation", "carbon", "15. Life on land"], "contacts": [{"organization": "Xu, Liang, Saatchi, Sassan S., Yang, Yan, Yu, Yifan, Pongratz, Julia, Bloom, A. Anthony, Bowman, Kevin, Worden, John, Liu, Junjie, Yin, Yi, Domke, Grant, McRoberts, Ronald E., Woodall, Christopher, Nabuurs, Gert-Jan, de-Miguel, Sergio, Keller, Michael, Nancy, Harris, Maxwell, Sean, Schimel, David,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4161694"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4161694", "name": "item", "description": "10.5281/zenodo.4161694", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4161694"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4173186", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Detailed global modelling of soil organic carbon in cropland, grassland and forest soils", "description": "Supporting information of the paper: Morais, T.G., Teixeira, R.F.M., Domingos, T. 2019. Detailed global modelling of soil organic carbon in cropland, grassland and forest soils. PloS One. Version 2 includes raster files (.tif) for each land use class (including: Attainable SOC stock, mineralization rate, and fator K).", "keywords": ["Attainable SOC", "Soil Organic Carbon", "Land use", "SOC mineralization", "15. Life on land", "RothC", "Ecological modelling"], "contacts": [{"organization": "Morais, T.G., Teixeira, R.F.M., Domingos, Tigao,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4173186"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4173186", "name": "item", "description": "10.5281/zenodo.4173186", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4173186"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-05T00:00:00Z"}}, {"id": "10.5281/zenodo.4247969", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Soil Moisture Active/Passive (SMAP) Level 4 Carbon (L4C) Nature Run version 7.2", "description": "Open AccessThe Soil Moisture Active/ Passive (SMAP) Level 4 Carbon (L4C) product is a daily, global, terrestrial carbon budget driven, in part, by soil moisture estimates from the Level 4 Soil Moisture (L4SM) product and, in turn, on brightness temperature observations from the SMAP satellite [1,2]. The SMAP L4C operational product's record begins on March 31, 2015, shortly after the launch of SMAP, and continues to the present, with an average latency of 9 days [3]. SMAP L4C data are posted to a global, 9-km equal-area EASE-Grid 2.0 [4]. In order to improve the longitudinal coverage of the SMAP L4C record, a model-only 'Nature Run' was devised, with daily carbon budget estimates beginning January 1, 2000. The Nature Run differs from the SMAP L4C operational product in the following ways: - The SMAP L4C Nature Run uses the MERRA-2 re-analysis dataset for meteorological driver data, instead of the GEOS-5 FP driver data used in the operational product.
- The SMAP L4C Nature Run uses soil moisture and soil temperature estimates from the L4SM Nature Run, which is a model-only version of the operational L4SM product that does not assimilate SMAP brightness temperature data. This repository contains the full README for the data. The data can be downloaded from: http://files.ntsg.umt.edu/data/SMAP_L4C_NatureRun/NRv7.2/", "keywords": ["carbon flux", "soil organic carbon", "primary productivity", "13. Climate action", "net ecosystem exchange", "15. Life on land", "earth system", "respiration"], "contacts": [{"organization": "Endsley, K. Arthur, Jones, Lucas, Kimball, John,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4247969"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4247969", "name": "item", "description": "10.5281/zenodo.4247969", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4247969"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-05T00:00:00Z"}}, {"id": "10.5281/zenodo.4125709", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Dataset for: Short-term temperature history affects mineralization of fresh litter and extant soil organic matter, irrespective of agricultural management", "description": "Open AccessDataset for the article: Mason-Jones, K., Vrehen, P, Koper, K., Wang, J., van der Putten, W.H., Veen, G.F. 2020. Short-term temperature history affects mineralization of fresh litter and extant soil organic matter, irrespective of agricultural management. Soil Biology and Biochemistry, 150, 107985. Article DOI: 10.1016/j.soilbio.2020.107985", "keywords": ["2. Zero hunger", "13. Climate action", "Analysed data", "Life Science", "Mineralization dynamics", " Temperature sensitivity", " Soil carbon", " Priming effect", "15. Life on land", "Geanalyseerde data"], "contacts": [{"organization": "Mason-Jones, Kyle, Vrehen, Pim, Koper, Kevin, Wang, Jin, van der Putten, Wim H., Veen, G.F. (Ciska),", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4125709"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4125709", "name": "item", "description": "10.5281/zenodo.4125709", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4125709"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4262469", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:49Z", "type": "Report", "title": "The use of advanced technologies for integrated management of root-knot nematodes (Meloidogyne spp., Nematoda: Meloidogynidae) : doctoral dissertation", "description": "Tropical root-knot nematodes (RKN) are extremely polyphagous pests causing large yield losses in agriculture. Some species, such as Meloidogyne ethiopica, M. inornata and M. luci (MEG) are highly related and difficult to distinguish. We sequenced 7 RKN isolates from the MEG group and following the genome assembly, determined their phylogenetic position within the genus. The genome assembly of M. luci SI-Smartno V13 is currently the most complete publicly available RKN genome, having 327 contigs, N50 contig size of 1.7 Mb, and final assembly size of 209.2 Mb. Phylogenetic analysis showed the positioning of all MEG-group isolates within a single monophyletic clade, and the species M. luci differed significantly from the species M. ethiopica and M. inornata. We tested the applicability of hyperspectral imaging for the early differentiation of biotic stress (RKN infestation) from abiotic stress (drought) in tomato plants. Using hyperspectral image analysis in the 400-2500 nm spectral range, it was possible to distinguish well-watered from water deficient plants with 100 % accuracy; and nematode-infested from healthy plants with 90-100 % accuracy. We also evaluated nematicidal activity and analysed the genomes of Bacillus firmus I-1582 and Bacillus sp. ZZV12-4809 and found multiple putative virulence factors. In the pot experiments as well as in the microplots, the strain I-1582 reduced M. luci infestation rates by 51-53 % compared to untreated control. I-1582 showed nematicidal and plant-growth promoting effects, as indicated by plant morphology measurements, relative chlorophyll content, leaf nutrient composition, and hyperspectral image analysis. Utilising supervised classification for hyperspectral image analysis, we successfully discriminated between B. firmus-treated and untreated plants \u2013 in the pot experiment we achieved 97.4 % and in the microplot experiment 96.3 % classification success.", "keywords": ["2. Zero hunger", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Susi\u010d, Nik", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4262469"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4262469", "name": "item", "description": "10.5281/zenodo.4262469", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4262469"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4262804", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:49Z", "type": "Report", "title": "EXCALIBUR: EIP", "description": "The poster present main objectives and expected outcomes of the project and their transfer to farmers.", "keywords": ["2. Zero hunger", "15. Life on land"], "contacts": [{"organization": "Nika Cvelbar Weber, Jaka Razinger,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4262804"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4262804", "name": "item", "description": "10.5281/zenodo.4262804", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4262804"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-10T00:00:00Z"}}, {"id": "10.5281/zenodo.4277166", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Data from: Dwarf shrubs impact tundra soils: drier, colder, and less organic carbon", "description": "In the tundra, woody plants are dispersing towards higher latitudes and altitudes due to increasingly favourable climatic conditions. The coverage and height of woody plants are increasing, which may influence the soils of the tundra ecosystem. Here, we use structural equation modelling to analyse 171 study plots and to examine if the coverage and height of woody plants affect the growing-season topsoil moisture and temperature (< 10 cm) as well as soil organic carbon stocks (< 80 cm). In our study setting, we consider the hierarchy of the ecosystem by controlling for other factors, such as topography, wintertime snow depth and the overall plant coverage that potentially influence woody plants and soil properties in this dwarf-shrub dominated landscape in northern Fennoscandia. We found strong links from topography to both vegetation and soil. Further, we found that woody plants influence multiple soil properties: the dominance of woody plants inversely correlated with soil moisture, soil temperature, and soil organic carbon stocks (standardised regression coefficients = -0.39; -0.22; -0.34, respectively), even when controlling for other landscape features. Our results indicate that the dominance of dwarf shrubs may lead to soils that are drier, colder, and contain less organic carbon. Thus, there are multiple mechanisms through which woody plants may influence tundra soils. Kemppinen, Niittynen, Virkkala, Happonen, Riihim\u00e4ki, Aalto & Luoto (2021). Dwarf shrubs impact tundra soils: drier, colder, and less organic carbon. Ecosystems. These are the data from Kemppinen et al. (2021).", "keywords": ["tundra", "Arctic", "13. Climate action", "carbon cycle", "structural equation model", "15. Life on land", "snow", "shrubification", "microclimate", "dwarf shrubs"], "contacts": [{"organization": "Kemppinen, Julia, Niittynen, Pekka, Virkkala, Anna-Maria, Happonen, Konsta, Riihim\u00e4ki, Henri, Aalto, Juha, Luoto, Miska,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4277166"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4277166", "name": "item", "description": "10.5281/zenodo.4277166", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4277166"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-17T00:00:00Z"}}, {"id": "10.5281/zenodo.4281013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Roots Carbon Dynamics in Temperate forest roots, Thuringia, Germany", "description": "Open AccessThese files contain radiocarbon, d13C, NSC concentrations, and CO2 efflux rates measured for aspen (Populus tremula hybrids) roots collected during 2018 growing season in the Gro\u00dfer Hermannsberg Mountain, Germany (50\u00b042\u201950\u2019\u2019 N, 10\u00b036\u201913\u2019\u2019 E, 616 m a.s.l). Coarse (> 2 mm) and fine (2 \u2264 mm) roots collected from three 'treatments': before stem girdling (Pre-girdling), ~3 months after girdling (Girdling) and ~3 months after girdling but in un-girdled trees (Control). The files with the relevant results: '13C', '14C', 'CO2_efflux', 'NSC'. Few roots from the 'Pre-girdling' treatment were incubated for respiration measurements 7 d after harvest. The files with the relevant results: 'Repeated_incubations_isotopes', 'Repeated_incubations_fluxes'. Results of incubations used for Q10 calculations presented in the file 'CO2_efflux_Q10'. Temperature and rainfall in the site during 2018 growing season are presented in the file 'Field_temperature_rainfall'. Results used to reconstruct local atmospheric D14C-CO2 record are presented in the file 'Local_atmospheric_CO2_D14C'. The file 'Metadata' contains information about the headers in the other files.", "keywords": ["tree roots", "d13C", "15. Life on land", "storage dynamics", "nonstructural carbohydrates", "radiocarbon (14C)", "respiration"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4281013"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4281013", "name": "item", "description": "10.5281/zenodo.4281013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4281013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-24T00:00:00Z"}}, {"id": "10.5281/zenodo.4262805", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:49Z", "type": "Report", "title": "EXCALIBUR: EIP", "description": "The poster present main objectives and expected outcomes of the project and their transfer to farmers.", "keywords": ["2. Zero hunger", "15. Life on land"], "contacts": [{"organization": "Weber, Nika Cvelbar, Razinger, Jaka,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4262805"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4262805", "name": "item", "description": "10.5281/zenodo.4262805", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4262805"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-10T00:00:00Z"}}, {"id": "10.5281/zenodo.4268864", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "LandModels", "description": "This repository is for the manuscript: 'Leveraging observed soil heterotrophic respiration fluxes as a novel constraint on global-scale models'", "keywords": ["15. Life on land", "Soil organic carbon models", " heterotrophic respiration", " MIMICS", " CASACNP", " CORPSE", " benchmarking"], "contacts": [{"organization": "Jian, Jinshi", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4268864"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4268864", "name": "item", "description": "10.5281/zenodo.4268864", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4268864"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-12T00:00:00Z"}}, {"id": "10.5281/zenodo.4281012", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:49Z", "type": "Dataset", "title": "Roots Carbon Dynamics in Temperate forest roots, Thuringia, Germany", "description": "Open AccessThese files contain radiocarbon, d13C, NSC concentrations, and CO2 efflux rates measured for aspen (Populus tremula hybrids) roots collected during 2018 growing season in the Gro\u00dfer Hermannsberg Mountain, Germany (50\u00b042\u201950\u2019\u2019 N, 10\u00b036\u201913\u2019\u2019 E, 616 m a.s.l). Coarse (> 2 mm) and fine (2 \u2264 mm) roots collected from three 'treatments': before stem girdling (Pre-girdling), ~3 months after girdling (Girdling) and ~3 months after girdling but in un-girdled trees (Control). The files with the relevant results: '13C', '14C', 'CO2_efflux', 'NSC'. Few roots from the 'Pre-girdling' treatment were incubated for respiration measurements 7 d after harvest. The files with the relevant results: 'Repeated_incubations_isotopes', 'Repeated_incubations_fluxes'. Results of incubations used for Q10 calculations presented in the file 'CO2_efflux_Q10'. Temperature and rainfall in the site during 2018 growing season are presented in the file 'Field_temperature_rainfall'. Results used to reconstruct local atmospheric D14C-CO2 record are presented in the file 'Local_atmospheric_CO2_D14C'. The file 'Metadata' contains information about the headers in the other files.", "keywords": ["tree roots", "d13C", "15. Life on land", "storage dynamics", "nonstructural carbohydrates", "radiocarbon (14C)", "respiration"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4281012"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4281012", "name": "item", "description": "10.5281/zenodo.4281012", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4281012"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-24T00:00:00Z"}}, {"id": "10.5281/zenodo.4384105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Software", "title": "A Colab-Python script code to identify palaeo-landscape features", "description": "Open Access{'references': ['1. Python Software Foundation. Python Language Reference. 2020. Available: http://www.python.org', '2. Wu Q. geemap: A Python package for interactive mapping with Google Earth Engine. Journal of Open Source Software. 2020;5: 2305', '3. Bisong E. Google Colaboratory. In: Bisong E, editor. Building Machine Learning and Deep Learning Models on Google Cloud Platform: u00a0 u00a0 u00a0A Comprehensive Guide for Beginners. Berkeley, CA: Apress; 2019. pp. 59 u201364', '4. Project Jupyter. Jupyter Notebook. 2020. Available: https://jupyter.org/', '5. QGIS Development Team. QGIS Geographic Information System. Open Source Geospatial Foundation Project. 2019. u00a0 u00a0 u00a0Available: https://www.qgis.org/en/site/index.html', '6. Gillies S et al. Rasterio: geospatial raster I/O for Python programmers. Mapbox; 2013. Available: https://github.com/mapbox/rasterio', '7. Hunter JD. Matplotlib: A 2D Graphics Environment. Comput Sci Eng. 2007;9: 90 u201395.']}", "keywords": ["Remote Sensing", "Multispectral analysis", "Landscape Archaeology", "Spectral decomposition", "15. Life on land", "Sentinel-2", "Riverscape", "Fluvial and Alluvial Archaeology", "12. Responsible consumption", "Python"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4384105"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4384105", "name": "item", "description": "10.5281/zenodo.4384105", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4384105"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-22T00:00:00Z"}}, {"id": "10.5281/zenodo.4312071", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:49Z", "type": "Report", "title": "DNA barcoding of hoverflies (Diptera Syrphidae) \u2013 new species discovery in the Merodon aureus species group", "description": "Open AccessMerodon is the richest genus of hoverflies in Europe with 120 recognized species. The adult species of this genus are important pollinators of diverse plants, while larvae are phytophagous and they develop in geophytes. Species discovery within genus is facilitated by the application of DNA barcoding approach in almost all recent studies. DNA barcoding is based on the analysis of sequence divergence of the short fragment on 5\u2019 end of mitochondrial cytochrome c oxidase subunit I gene (COI), although, in hoverflies, both 5\u2019 and 3\u2019 COI sequences are equally used and often combined. The aim of this study was to identify hoverfly specimens collected in Morocco, Italy, Turkey and Georgia to a species level within the M. aureus species group. In order to achieve this, we analysed 5\u2019 COI sequences of aforementioned specimens. The sequences were blasted against the NCBI nucleotide database and used for Maximum parsimony and Maximum likelihood trees construction. Three new candidate species are discovered: M. sp. nova 1, M. sp. nova 2 and M. aff. bessarabicus. The three species are resolved as reciprocally monophyletic clades with strong branch support on both trees. In order to verify and describe the three species, additional examination of morphological character states is needed.", "keywords": ["15. Life on land"], "contacts": [{"organization": "Ljiljana, \u0160a\u0161i\u0107 Zori\u0107, Kurtek Lea, Djan Mihajla, Vuji\u0107 Ante,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4312071"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4312071", "name": "item", "description": "10.5281/zenodo.4312071", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4312071"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4326766", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Report", "title": "Report on demonstration activities in the study sites (D5.2)", "description": "Demonstration activities in the study sites. The SoilCare project aims at developing soil improving cropping systems. At 16 study sites dispersed
over Europe experiments have been implemented. These were selected in collaboration with the
stakeholders (WP3) and based on a literature review (WP2). The methodology for monitoring the
experiments was compiled by WP4. The results are being compiled by WP5. In addition, all study sites
had to organize demonstration activities and field days of the selected cropping systems. The
combined findings by the study sites are an important input for the upscaling by WP6, the policy
analysis by WP7 and the dissemination by WP8.
The demonstrations/field days for the stakeholders are an important tool for sharing experiences
between the stakeholders and the researchers while inspecting and reflecting over the experiments in
the field. A total of 31 demonstration events/field days took place in the 16 study sites over two years.
Four out of the sixteen study sites organised three or more. Six out of the sixteen study sites organised
two demonstration/field days and six organised one. In total, about 937 stakeholders attended the
demonstration events. The average number of participants in the events was 30. The
demonstration/field days are experienced by the stakeholders and researchers of the study sites as a
very useful activity in combination with a more systematic consultation with the stakeholders.
The specific feedback by each study site is given in a table and can be found in more detail in the
reports by the study sites in appendix I. Several points were discussed in different degrees: the need
for machinery, the incentives by subsidies, the selection of crops, rotations and cover crops, the
erodibility and the soil structure/quality. Also many participants stressed the need for communication
and information on soil improving cropping systems. A major general concern for all stakeholders was
the economic performance of the cropping systems. Also, weed infestation and weed control
management was also a recurring theme.", "keywords": ["2. Zero hunger", "SoilCare", " Soil improving", " cropping systems", "", "15. Life on land"], "contacts": [{"organization": "Panagea, Ioanna, Wyseure, Guido,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4326766"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4326766", "name": "item", "description": "10.5281/zenodo.4326766", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4326766"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-16T00:00:00Z"}}, {"id": "10.5281/zenodo.4333554", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Dataset", "title": "Best4Soil_databases_datamining_V1", "description": "This document contains data on the host plant status of field crops, vegetable crops and green manure crops for soilborne plant parasitic nematodes and soilborne fungal pathogens. The data was used for the construction of two databases in context of the Best4Soil Thematic Network, a Horizon 2020 project (Grant Agreement n\u00b0817696). The databases are accessible through the website https://ww.best4soil.eu/database ; they are hosted on https://nematodes.soilhealthtool.eu/", "keywords": ["2. Zero hunger", "field crop", "Best4Soil", " database", " hostplant", " soilborne pathogen", " nematode", " field crop", " vegetable", " green manure", " cover crop", "green manure", "hostplant", "nematode", "Best4Soil", "vegetable", "cover crop", "15. 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The adult species of this genus are important pollinators of diverse plants, while larvae are phytophagous and they develop in geophytes. Species discovery within genus is facilitated by the application of DNA barcoding approach in almost all recent studies. DNA barcoding is based on the analysis of sequence divergence of the short fragment on 5\u2019 end of mitochondrial cytochrome c oxidase subunit I gene (COI), although, in hoverflies, both 5\u2019 and 3\u2019 COI sequences are equally used and often combined. The aim of this study was to identify hoverfly specimens collected in Morocco, Italy, Turkey and Georgia to a species level within the M. aureus species group. In order to achieve this, we analysed 5\u2019 COI sequences of aforementioned specimens. The sequences were blasted against the NCBI nucleotide database and used for Maximum parsimony and Maximum likelihood trees construction. Three new candidate species are discovered: M. sp. nova 1, M. sp. nova 2 and M. aff. bessarabicus. The three species are resolved as reciprocally monophyletic clades with strong branch support on both trees. In order to verify and describe the three species, additional examination of morphological character states is needed.", "keywords": ["15. Life on land"], "contacts": [{"organization": "Ljiljana, \u0160a\u0161i\u0107 Zori\u0107, Kurtek Lea, Djan Mihajla, Vuji\u0107 Ante,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4312072"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4312072", "name": "item", "description": "10.5281/zenodo.4312072", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4312072"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4333555", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Dataset", "title": "Best4Soil_databases_datamining_V1", "description": "This document contains data on the host plant status of field crops, vegetable crops and green manure crops for soilborne plant parasitic nematodes and soilborne fungal pathogens. The data was used for the construction of two databases in context of the Best4Soil Thematic Network, a Horizon 2020 project (Grant Agreement n\u00b0817696). The databases are accessible through the website https://ww.best4soil.eu/database ; they are hosted on https://nematodes.soilhealthtool.eu/", "keywords": ["2. Zero hunger", "field crop", "Best4Soil", " database", " hostplant", " soilborne pathogen", " nematode", " field crop", " vegetable", " green manure", " cover crop", "green manure", "hostplant", "nematode", "Best4Soil", "vegetable", "cover crop", "15. Life on land", "soilborne pathogen", "database"], "contacts": [{"organization": "Molendijk, Leendert, van Asperen, Paulien, Michel, Vincent, H\u00e4ller, Bruno, Gaffney, Michael, de Cara, Miguel, Damsgaard Thorsted, Marian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4333555"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4333555", "name": "item", "description": "10.5281/zenodo.4333555", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4333555"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4462142", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Dataset", "title": "ECOBREED WP3 entomopathogenic fungi-wireworm data related to Razinger et al. (2020)", "description": "Raw data related to Figures 1 to 5 and Table 1 plus suplementary raw data of the publication Razinger et al. (2020) Frontiers in Plant Science 11:535005; doi: 10.3389/fpls.2020.535005.", "keywords": ["2. Zero hunger", "Plant-microbe-insect interaction", "Wireworm", "Biological control", "Plant-microbe interaction", "Rhizosphere", "Sustainable agriculture", "Entomopathogenic fungus", "Biocontrol", "15. Life on land", "Biopesticide", "Plant-microbe-pest interaction", "Agriotes lineatus"], "contacts": [{"organization": "Razinger, Jaka, Praprotnik, Eva, Schroers, Hans-Josef,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4462142"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4462142", "name": "item", "description": "10.5281/zenodo.4462142", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4462142"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-25T00:00:00Z"}}, {"id": "10.5281/zenodo.4472669", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Report", "title": "EU Citizen Observatories Landscape Report II: Addressing the Challenges of Awareness, Acceptability, and Sustainability", "description": "Citizen Observatories (COs) are community-based environmental monitoring initiatives that invite the public to contribute observations, data and information in complement to authoritative, traditional insitu and remote sensing Earth Observation data. COs can play an important role in crucial areas such as climate change, sustainable development, air monitoring, flood and drought monitoring, land cover or land-use change. They can also provide new data sources for policy-making, and can result in increased citizen participation in environmental management and governance at a large scale. With the increasing prevalence of COs globally, there have been calls for a more integrated approach to handling their complexities, and to sharing knowledge for the design and management of stable, reliable and scalable CO programmes. Answering this challenge in the European context, the Horizon 2020-funded project WeObserve aims to improve coordination between existing COs and related European activities, while tackling three key challenges that inhibit the mainstreaming of citizen science, namely: Awareness, Acceptability, and Sustainability. 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The protocols considered in this handbook are:
- Soil sampling (oriented to determine dry bulk density, biodiversity or physicochemical characteristics).
- Earthworm sampling.
- Physical characterization of the soil including determination of dry bulk density, coarse fragments, humidity, particle size distribution and aggregates.
- Soil chemical characterization including determination of pH, content of organic matter, organic and inorganic carbon, total and inorganic nitrogen, available phosphorus, potassium, calcium, magnesium, effective exchange capacity, available micronutrients (iron, manganese, copper and zinc), and pesticides.
- Soil biological analyses that include biodiversity measurements for earthworms, nematodes and microorganisms (fungi and prokaryotes). This work was funded by the European Commission Horizon 2020 project SoildiverAgro [grant agreement 817819].", "keywords": ["2. Zero hunger", "13. Climate action", "analysis", "15. Life on land", "handbook", "soil"], "contacts": [{"organization": "Fern\ufffd\ufffdndez Calvi\ufffd\ufffdo, David, Soto G\ufffd\ufffdmez, Diego, Koefoed Brandt, Kristian, Waeyenberge, Lieven,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4476816"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4476816", "name": "item", "description": "10.5281/zenodo.4476816", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4476816"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-03T00:00:00Z"}}, {"id": "10.5281/zenodo.4476976", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Journal Article", "created": "2020-10-09", "title": "Temporal and Cultivar-Specific Effects on Potato Root and Soil Fungal Diversity", "description": "

The soil fungal community plays an important role in determining plant growth and health. In this study, we investigated the fungal diversity and community composition in the roots and soil of 21 potato (Solanum tuberosum L.) cultivars using high-throughput sequencing at three different time points across the growing season. In soil and roots, the fungal richness and relative abundance of pathogens and saprotrophs were mainly affected by sampling time. While sampling time affected fungal composition in soil, root fungal communities were also significantly affected by cultivar. The cultivar had the strongest effect on diversity of pathogens and abundance of particular pathogen species. Our results demonstrate changes in soil and root fungal communities of potato over the growing season, as well as highlighting the importance of potato cultivar on root fungal communities and abundance of pathogens.

", "keywords": ["2. Zero hunger", "0301 basic medicine", "0303 health sciences", "agroecosystems", "S", "high-throughput sequencing", "fungal guild", "Solanum tuberosum", "Agriculture", "15. 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(2020)", "description": "Raw data related to Figures 1 to 5 and Table 1 plus suplementary raw data of the publication Razinger et al. (2020) Frontiers in Plant Science 11:535005; doi: 10.3389/fpls.2020.535005.", "keywords": ["2. Zero hunger", "Plant-microbe-insect interaction", "Wireworm", "Biological control", "Plant-microbe interaction", "Rhizosphere", "Sustainable agriculture", "Entomopathogenic fungus", "Biocontrol", "15. Life on land", "Biopesticide", "Plant-microbe-pest interaction", "Agriotes lineatus"], "contacts": [{"organization": "Razinger, Jaka, Praprotnik, Eva, Schroers, Hans-Josef,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4462143"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4462143", "name": "item", "description": "10.5281/zenodo.4462143", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4462143"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-25T00:00:00Z"}}, {"id": "10.5281/zenodo.4472670", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Report", "title": "EU Citizen Observatories Landscape Report II: Addressing the Challenges of Awareness, Acceptability, and Sustainability", "description": "Citizen Observatories (COs) are community-based environmental monitoring initiatives that invite the public to contribute observations, data and information in complement to authoritative, traditional insitu and remote sensing Earth Observation data. COs can play an important role in crucial areas such as climate change, sustainable development, air monitoring, flood and drought monitoring, land cover or land-use change. They can also provide new data sources for policy-making, and can result in increased citizen participation in environmental management and governance at a large scale. With the increasing prevalence of COs globally, there have been calls for a more integrated approach to handling their complexities, and to sharing knowledge for the design and management of stable, reliable and scalable CO programmes. Answering this challenge in the European context, the Horizon 2020-funded project WeObserve aims to improve coordination between existing COs and related European activities, while tackling three key challenges that inhibit the mainstreaming of citizen science, namely: Awareness, Acceptability, and Sustainability. This D2.4 Landscape Report frames the second part of a dynamic exercise to examine the three core challenges faced by these COs, and to consolidate the experience of a range of stakeholders into a set of recommendations for strengthening the ecosystem around COs in Europe.", "keywords": ["0301 basic medicine", "citizen science", " citizen observatories", "0303 health sciences", "03 medical and health sciences", "13. Climate action", "11. Sustainability", "15. Life on land", "12. Responsible consumption"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4472670"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4472670", "name": "item", "description": "10.5281/zenodo.4472670", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4472670"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4487144", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:50Z", "type": "Dataset", "title": "Eddy Covariance data from ICOS-associated station IT-NIV \u2013 August-November 2019", "description": "RestrictedData stored here refer to Eddy Covariance (EC) data measured in 2019 between August and November at the Alpine CZO (Critical Zone Observatory, hereafter CZO@Nivolet) which was established at the Nivolet Plain (Piani del Nivolet) in the Gran Paradiso National Park (GPNP), located in the western Italian Alps. The EC site (IT-NIV) is an ICOS-associated station. CZO@Nivolet is aimed at investigating the cross-scale interactions between climatic shifts and ecosystem functions multiple scales, involving multidisciplinary studies. The main research questions that we aim to answer are concerning: (a) the effect of bedrock lithology, soil physics and chemisty, topographic hetereogenity, biotic components and meteo-climatic parameters in modulating CO2 flux in alpine grassland; and (b) what are the controlling factors of organic C and weathering under geologic substrates and different topographic positions. The investigations started in 2017. In 2019, the EC tower was added to deeply study CO2, H20, latent and sensible heat exchanges between soil, vegetation, and atmosphere. Carbon dioxide fluxes and environmental variables are recorded during the snow-free season to estimate carbon storage and explore CO2 fluxes drivers in high-altitude grasslands. Further developments will regard the integration of different techniques (Eddy Covariance, Remote Sensing, Flux chambers) to improve both spatial and temporal extent of carbon fluxes estimates to finally assess grasslands' productivity.", "keywords": ["13. Climate action", "alpine grassland", "15. Life on land", "Gran Paradiso National Park", "Mountain", "EO_Data", "Eddy Covariance", "Net Ecosystem Exchange", "ecosystem-atmosphere carbon exchange"], "contacts": [{"organization": "Vivaldo, Gianna, Raco, Brunella, Baneschi, Ilaria, Giamberini, Maria Silvia,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4487144"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4487144", "name": "item", "description": "10.5281/zenodo.4487144", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4487144"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-20T00:00:00Z"}}, {"id": "10.5281/zenodo.4519215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Report", "title": "Interactions between agricultural management and soil biodiversity: an overview of current knowledge", "description": "This book presents a literature review of the soil biodiversity problems of the European Farmers and the strategies developed to solve them.
The aspects considered in this revision book are:
- The importance of the soil biodiversity in the design of cropping systems.
- Crop rotation and its effect over the edaphic fauna.
- The effect of tillage on the communities that inhabit in the cultivated soils.
- The ability of soil fauna to regulate the proliferation of pathogenic fungi related to certain crop diseases.
- Different types of bacteria that promote plant growth.
- The relationship between soil contamination and biodiversity.
- The effect of organic and synthetic fertilizers on the biodiversity of the edaphic fauna.
- The development of alarm systems that allow the early detection of pathogens.
- The increase in soil quality associated with the use of cover crops.
- The use of trap crops to reduce the use of pesticides while maintaining production and quality. This work was funded by the European Commission Horizon 2020 project SoildiverAgro [grant agreement 817819].", "keywords": ["2. Zero hunger", "book", "organic farming", "15. Life on land", "soil", "biodiversity"], "contacts": [{"organization": "Soto G\u00f3mez, Diego, Fern\u00e1ndez Calvi\u00f1o, David, Shanskiy, Merrit,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4519215"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4519215", "name": "item", "description": "10.5281/zenodo.4519215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4519215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-30T00:00:00Z"}}, {"id": "10.5281/zenodo.4519230", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Report", "title": "Protocols for sampling general, general soil characterization and soil biodiversity analysis", "description": "This handbook presents the methods to carry out all the analyses that will allow establishing the characteristics of the different pedoclimatic regions. The protocols considered in this handbook are:
- Soil sampling (oriented to determine dry bulk density, biodiversity or physicochemical characteristics).
- Earthworm sampling.
- Physical characterization of the soil including determination of dry bulk density, coarse fragments, humidity, particle size distribution and aggregates.
- Soil chemical characterization including determination of pH, content of organic matter, organic and inorganic carbon, total and inorganic nitrogen, available phosphorus, potassium, calcium, magnesium, effective exchange capacity, available micronutrients (iron, manganese, copper and zinc), and pesticides.
- Soil biological analyses that include biodiversity measurements for earthworms, nematodes and microorganisms (fungi and prokaryotes). This work was funded by the European Commission Horizon 2020 project SoildiverAgro [grant agreement 817819].", "keywords": ["2. Zero hunger", "13. Climate action", "analysis", "15. Life on land", "handbook", "soil"], "contacts": [{"organization": "Fern\ufffd\ufffdndez Calvi\ufffd\ufffdo, David, Soto G\ufffd\ufffdmez, Diego, Koefoed Brandt, Kristian, Waeyenberge, Lieven,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4519230"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4519230", "name": "item", "description": "10.5281/zenodo.4519230", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4519230"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-03T00:00:00Z"}}, {"id": "10.5281/zenodo.4541586", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "SoilKsatDB: global compilation of soil saturated hydraulic conductivity measurements for geoscience applications", "description": "Open AccessA total of 13,258 Ksat measurements from 1,908 sites were assembled from the published literature and other sources, standardized, and quality-checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most global regions, with the highest data density from North America, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,584 measurements), bulk density (11,262 measurements), soil organic carbon (9,787 measurements), field capacity (7,382) and wilting point (7,411) are also included in the data set. To cite this dataset please use: Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., and Or, D.: SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-149, in review, 2021. Examples of using the SoilKsatDB to generate global maps of Ksat can be found in: Gupta, S., Hengl, T., Lehmann, P., Bonetti, S., Papritz, A. and Or, D. (2021): Global prediction of soil saturated hydraulic conductivity using random forest in a Covariate-based Geo Transfer Functions (CoGTF) framework. accepted for publication in Journal of Advances in Modeling Earth Systems (JAMES). Importing and binding steps are described in detail here. To report an issue or bug please use this link. Ksat data tutorial explaining how to access and use data is available here. In the following, we introduce two different file packages, one for the soil saturated hydraulic conductivity (\u201csol_ksat\u201d) and another one collecting additional soil hydraulic properties (\u201csol_hydro\u201d) as well that will be extended in the near future. Note that the package \u201csol_hydro\u201d is not related to the publication listed above (Gupta et al., 2021a). Description of the files: The datasets in this repository include: sol_ksat.pnts_horizons.***: provides a global compilation of Ksat values and the information described in Table 2 in Gupta et al., (2020). This data is provided in three different data formats. sol_ksat.pnts_horizons.arff, sol_ksat.pnts_horizons.csv.gz, sol_ksat.pnts_horizons.rds, sol_ksat.pnts_metadata_cl_pedo.csv: provides meta-information with Ksat methods and information of estimated soil pedologic unit and climatic region for each Ksat sample. sol_ksat.points_horizons_rm.rds: All ksat values overlaid on climatic, topographic, and vegetation based remote sensing data and extracted the corresponding values. These datasets can be used for spatial modeling for the future. In addition to Ksat points, add these files here as well for the reader that is interested in this topic. sol_hydro.pnts_horizons.***: provides water retention curve values and other soil hydraulic properties. This data is provided in three different data formats. sol_hydro.pnts_horizons.arff, sol_hydro.pnts_horizons.csv.gz, sol_hydro.pnts_horizons.rds, sol_hydro.pnts_horizons_rm.rds: All soil hydraulic values overlaid on climatic, topographic, and vegetation based remote sensing data and extracted the corresponding values. These datasets can be used for spatial modeling for the future. SoilKsatDB is available in CSV, ARFF and RDS formats. ARFF was prepared using the farff package for R. ARFF' (Attribute-Relation File Format) files are like 'CSV' files, with a little bit of added meta information in a header and standardized NA values. Column codes are based on the National Cooperative Soil Survey (NCSS) Soil Characterization Database naming convention (see 'README.pdf' for explanation of codes). The SoilKsatDB is a compilation of numerous existing datasets from which the most significant: SWIG data set (Rahmati et al., 2018), UNSODA (Leij et al., 1996), and HYBRAS (Ottoni et al., 2018). Full list of data sources for Ksat data is available in Gupta et al (2021) and in the Readme.pdf.", "keywords": ["Ecology", "Science Policy", "Information Systems not elsewhere classified", "Plant Biology", "hydrology", "clay", "15. Life on land", "Microbiology", "6. Clean water", "soil", "Sociology", "LandGIS", "OpenLandMap", "Genetics", "hydraulic conductivity", "Biological Sciences not elsewhere classified"], "contacts": [{"organization": "Surya, Gupta, Hengl, Tomislav, Lehmann, Peter, Bonetti, Sara, Or, Dani,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4541586"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4541586", "name": "item", "description": "10.5281/zenodo.4541586", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4541586"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4581699", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:51Z", "type": "Journal Article", "title": "Accretional soil formation in northern hemisphere loess regions - evidence from OSL- dating of the Pleistocene-Holocene climatic transition from China, Europe and North America", "description": "Loess deposits intercalated by paleosols are detailed terrestrial archives of Quaternary climate variability providing information on the global dust cycle and landscape dynamics. Their paleoclimate significance is most often explored by quantifying the
mineral magnetic properties due to their sensitivity to local/regional hydroclimate variability. Detailed chronological assessment of such regional proxy records around the climatic transitions allow a better understanding of how regional records react to
major global climatic transitions such as the Pleistocene-Holocene climatic transition.
First, logs of high-resolution magnetic susceptibility and its frequency dependence were used as paleoclimatic proxies to define the environmental transition from the last glacial loess to the current interglacial soil as reflected in nine loess-paleosol
sequences across the northern hemisphere, from the Chinese Loess Plateau, the southeastern European loess belt and the central Great Plains, Nebraska, USA. Second, the onset of increase in their values above typical loess values was used to assess the onset of, and developments during, the Pleistocene-Holocene climatic transition. High-resolution luminescence dating is applied on multiple grain-sizes (4-11 \u03bcm, 63-90\u03bcm, 90-125 \u03bcm) of quartz extracts from the same sample in order to investigate the
timing of Pleistocene-Holocene climatic transition in the investigated sites. The magnetic susceptibility signal shows a smooth and gradual increase for the majority of the sites from the typical low loess values to the interglacial ones. The initiation of this increase, interpreted as recording the initiation of the Pleistocene-Holocene climatic transition at each site, was dated to 14-17.5 ka or even earlier. Our results highlight the need of combining paleoclimatic proxies (magnetic susceptibility) with absolute dating when investigating the Pleistocene-Holocene climatic transition as reflected by the evolution of this proxy in order to avoid chronostratigraphic misinterpretations in loess-paleosol records caused by simple pattern correlation. The detailed luminescence chronologies evidence the continuity of eolian mineral dust accumulation regardless of glacial or interglacial global climatic regimes. Coupled with magnetic susceptibility records it indicates that dust sedimentation and pedogenesis act simultaneously and result in the formation of accretional Holocene soils in loess regions across the Northern Hemisphere. The luminescence ages allowed the
modelling of accumulation rates for the Holocene soil which are similar for European, Chinese and U.S. loess sites investigated and vary from 2 cm ka-1 to 9 cm ka-1. While accretional pedogenesis has often been implicitly or explicitly assumed in paleoclimatic
interpretation of loess-paleosol sequences, especially in the Chinese Loess Plateau, our luminescence data add direct evidence for ongoing sedimentation as soils formed.", "keywords": ["13. Climate action", "15. Life on land"], "contacts": [{"organization": "Daniela, Constantin, Joseph, Mason, Veres Daniel, Hambach Ulrich, Panaiotu Cristian, Zeeden Christian, Liping, Zhou, Markovi\u0107 Slobodan, Gerasimenko Natalia, Anca, Avram, Tecsa Viorica, Sacaciu-Groza Madalina, Laura, Del Valle Villalonga, Begy Robert, Timar-Gabor Alida,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4581699"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20Science%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4581699", "name": "item", "description": "10.5281/zenodo.4581699", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4581699"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4574684", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Data for \"Effects of fire on soil respiration and its components in a Dahurian larch (Larix gmelinii) forest in northeast China: implications for forest ecosystem carbon cycling\"", "description": "One csv file named \u201cData for Effects of fire on soil respiration and its components in a Dahurian larch (Larix gmelinii) forest in northeast China: implications for forest ecosystem carbon cycling\u201d contains data of soil total respiration (Rs), soil heterotrophic respiration (Rh), soil autotrophic respiration (Ra), soil temperature for total soil respiration at 5cm (T_for_ Rs), soil temperature for heterotrophic respiration in trenched point at 5cm (T_for_TE), soil moisture for total soil respiration at 5 cm (W_for_ Rs), soil water content for heterotrophic respiration in trenched point at 5cm (W_for_TE), soil microbial biomass carbon (MBC), soil pH value (pH), fine roots biomass (FR), soil ammonium-nitrogen (NH4), soil organic carbon (SOC), soil nitrate-nitrogen (NO3) in control and burned plots were collected from 2017/05/15 to 2018/4/15. Another csv file named of \u201cData Dictionary\u201d contains the description of information the exact row header name of csv file named \u201cData for Effects of fire on soil respiration and its components in a Dahurian larch (Larix gmelinii) forest in northeast China: implications for forest ecosystem carbon cycling\u201d.", "keywords": ["2. Zero hunger", "13. Climate action", "Fire ecology", "Forestry", "15. Life on land"], "contacts": [{"organization": "Tongxin, Hu, Long, Sun,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4574684"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4574684", "name": "item", "description": "10.5281/zenodo.4574684", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4574684"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-03T00:00:00Z"}}, {"id": "10.5281/zenodo.4730278", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Data and software for Endsley et al. \"Satellite monitoring of global surface soil organic carbon dynamics using the SMAP Level 4 Carbon product\"", "description": "Data and software for reproducing key results from: Endsley, K.A., J.S. Kimball, R.H. Reichle, J.D. Watts. 'Satellite monitoring of global surface soil organic carbon dynamics using the SMAP Level 4 Carbon product.' *Submitted to Journal of Geophysical Research: Biogeosciences.*

Corresponding author: K. Arthur Endsley, arthur.endsley@ntsg.umt.edu", "keywords": ["soil organic carbon", "carbon flux", "15. Life on land", "soil carbon", "respiration"], "contacts": [{"organization": "Endsley, K. Arthur, Kimball, John S., Reichle, Rolf H., Watts, Jennifer D.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4730278"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4730278", "name": "item", "description": "10.5281/zenodo.4730278", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4730278"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-10T00:00:00Z"}}, {"id": "10.5281/zenodo.4724779", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Data underlying publication https://doi.org/10.1007/s13280-017-0983-x", "description": "Open AccessThe data files attached are underlying publication doi: https://doi.org/10.1007/s13280-017-0983-x Title: Functional Land Management: Bridging the Think-Do-Gap using a multi-stakeholder science policy interface. Authors: Lilian O'Sullivan (https://orcid.org/0000-0002-5333-5758), David Wall (https://orcid.org/0000-0002-2365-0335), Rachel Creamer (https://orcid.org/0000-0003-3617-1357), Francesca Bampa (https://orcid.org/0000-0002-4488-0420) & Rogier P.O. Schulte (https://orcid.org/0000-0002-9014-4344) Abstract: Functional Land Management (FLM) is proposed as an integrator for sustainability policies and assesses the functional capacity of the soil and land to deliver primary productivity, water purification and regulation, carbon cycling and storage, habitat for biodiversity and recycling of nutrients. This paper presents the catchment challenge as a method to bridge the gap between science, stakeholders and policy for the effective management of soils to deliver these functions. Two challenges were completed by a wide range of stakeholders focused around a physical catchment model\u2014(1) to design an optimised catchment based on soil function targets, (2) identify gaps to implementation of the proposed design. In challenge 1, a high level of consensus between different stakeholders emerged on soil and management measures to be implemented to achieve soil function targets. Key gaps including knowledge, a mix of market and voluntary incentives and mandatory measures were identified in challenge 2.", "keywords": ["2. Zero hunger", "Functional Land Management", " Policy Framework", " Soil Functions", " Stakeholder Workshops", " Sustainability", "15. Life on land", "12. Responsible consumption"], "contacts": [{"organization": "O'Sullivan", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4724779"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4724779", "name": "item", "description": "10.5281/zenodo.4724779", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4724779"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4647078", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Carbon dioxide fluxes and carbon balance of an agricultural grassland in southern Finland", "description": "The data set contains CO2 and H2O eddy covariance flux data and meteorological measurements from agricultural grassland site at Qvidja in southern Finland (60.29550\u00b0N, 22.39281\u00b0E, elevation 5 m) measured in 2018 - 2020. Additionally, the data set contains leaf area index data and measurements of soil organic carbon content. Fluxes_Heimsch_et_al_2020.csv contains the CO2 and H2O flux data. Meteorology_Heimsch_et_al_2020.csv and Precipitation_Heimsch_et_al_2020.csv contain the meteorological measurements. LAI_Heimsch_et_al_2020.csv contains the leaf area index data obtained from the Sentinel-2 satellite. SOC_Heimsch_et_al_2020.xlsx contains the measurements of soil organic carbon from five soil core samples.", "keywords": ["2. Zero hunger", "13. Climate action", "15. Life on land"], "contacts": [{"organization": "Heimsch, Laura, Lohila, Annalea, Tuovinen, Juha-Pekka, Vekuri, Henriikka, Heinonsalo, Jussi, Nevalainen, Olli, Korkiakoski, Mika, Liski, Jari, Laurila, Tuomas, Kulmala, Liisa,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4647078"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4647078", "name": "item", "description": "10.5281/zenodo.4647078", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4647078"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-30T00:00:00Z"}}, {"id": "10.5281/zenodo.4724780", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Data underlying publication https://doi.org/10.1007/s13280-017-0983-x", "description": "Open AccessThe data files attached are underlying publication doi: https://doi.org/10.1007/s13280-017-0983-x Title: Functional Land Management: Bridging the Think-Do-Gap using a multi-stakeholder science policy interface. Authors: Lilian O'Sullivan (https://orcid.org/0000-0002-5333-5758), David Wall (https://orcid.org/0000-0002-2365-0335), Rachel Creamer (https://orcid.org/0000-0003-3617-1357), Francesca Bampa (https://orcid.org/0000-0002-4488-0420) & Rogier P.O. Schulte (https://orcid.org/0000-0002-9014-4344) Abstract: Functional Land Management (FLM) is proposed as an integrator for sustainability policies and assesses the functional capacity of the soil and land to deliver primary productivity, water purification and regulation, carbon cycling and storage, habitat for biodiversity and recycling of nutrients. This paper presents the catchment challenge as a method to bridge the gap between science, stakeholders and policy for the effective management of soils to deliver these functions. Two challenges were completed by a wide range of stakeholders focused around a physical catchment model\u2014(1) to design an optimised catchment based on soil function targets, (2) identify gaps to implementation of the proposed design. In challenge 1, a high level of consensus between different stakeholders emerged on soil and management measures to be implemented to achieve soil function targets. Key gaps including knowledge, a mix of market and voluntary incentives and mandatory measures were identified in challenge 2.", "keywords": ["2. Zero hunger", "Functional Land Management", " Policy Framework", " Soil Functions", " Stakeholder Workshops", " Sustainability", "15. Life on land", "12. Responsible consumption"], "contacts": [{"organization": ", O'Sullivan", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4724780"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4724780", "name": "item", "description": "10.5281/zenodo.4724780", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4724780"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.4738633", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Effects of Management and Hillside Position on Soil Organic Carbon Stratification in Mediterranean Centenary Olive Grove", "description": "The short- and medium\u2014long-term effects of management and hillside position on soil
organic carbon (SOC) changes were studied in a centenary Mediterranean rainfed olive grove. One
way to measure these changes is to analyze the soil quality, as it assesses soil degradation degree
and attempts to identify management practices for sustainable soil use. In this context, the SOC
stratification index (SR-COS) is one of the best indicators of soil quality to assess the degradation
degree from SOC content without analyzing other soil properties. The SR-SOC was calculated in soil
profiles (horizon-by-horizon) to identify the best soil management practices for sustainable use. The
following time periods and soil management combinations were tested: (i) in the medium-long-term
(17 years) from conventional tillage (CT) to no-tillage (NT), (ii) in the short-term (2 years) from CT
to no-tillage with cover crops (NT-CC), and (iii) the effect in the short-term (from CT to NT-CC) of
different topographic positions along a hillside. The results indicate that the SR-SOC increased with
depth for all management practices. The SR-SOC ranged from 1.21 to 1.73 in CT0, from 1.48 to 3.01 in
CT1, from 1.15 to 2.48 in CT2, from 1.22 to 2.39 in NT-CC and from 0.98 to 4.16 in NT; therefore, the
soil quality from the SR-SOC index was not directly linked to the increase or loss of SOC along the
soil profile. This demonstrates the time-variability of SR-SOC and that NT improves soil quality in
the long-term.", "keywords": ["2. Zero hunger", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Aguilera-Huertas, Jes\u00fas, Lozano-Garc\u00eda, Beatriz, Gonz\u00e1lez-Rosado, Manuel, Parras-Alc\u00e1ntara, Luis,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4738633"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4738633", "name": "item", "description": "10.5281/zenodo.4738633", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4738633"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-05T00:00:00Z"}}, {"id": "10.5281/zenodo.4745479", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-04-04T16:23:51Z", "type": "Dataset", "title": "Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil", "description": "This file includes the variable description of the data files published on Zenodo for the manuscript submitted to Biogeosciences titled 'Soil carbon loss in warmed subarctic grasslands is rapid and restricted to topsoil' 'stocks_data.csv'; includes the C stock data
grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland
sampling_year: year in which the soil samples were taken (2013 or 2018)
SOC_stock_corr: Mass-corrected soil organic carbon stock
SOC_stock: Uncorrected soil organic carbon stock
C_perc: soil C % of the soil sample
warming: degrees of soil warming (\u00b0C)
ID: plot soil ID
soil_layer: layer of soil sampled (0-10cm or 10-30cm)
BD: bulk density (g cm-3)
YOW: Years of warming; years the soil was warmed before sampling
'C_input_data.csv'; includes the C input data
ID: plot soil ID
grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland
AMF_Cnew: C sequestered by AMF (ton C ha-1); data from Zhang et al., 2020
fine_root_C: fine root C in soil (ton C ha-1)
AGB_C: aboveground biomass C on top of soil (ton C ha-1)
warming: degrees of soil warming (\u00b0C) 'agg_data.csv'; includes the aggregate fractionation data
ID: plot soil ID
grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland
warming: degrees of soil warming (\u00b0C)
rel_mass: Relative aggregate fraction (%)
C_perc: C amount in the aggregate fraction (%)
abs_C_mass: absolute amount of C per fraction (g C 100 g-1 dw soil) 'DOC_data.csv'; includes the dissolved organic carbon leachate data (data from Edlinger, 2016)
year: sampling year of the leachates
grassland: medium-term warmed (MTW) or long-term warmed (LTW) grassland
ID: plot soil ID
warming: degrees of soil warming (\u00b0C)
DOC: dissolved organic carbon (ppm) 'T_profile_LTW.csv'; includes temperature profile data from the long-term warmed grassland
grassland: long-term warmed (LTW) grassland
ID: plot soil ID
depth: depth (cm) at which the the temperature was measured
T_diff_from_10cm: temperature difference compared to 10cm depth (\u00b0C) 'fine_root_LTW.csv'; includes fine root density data from the long-term warmed grassland
warming: degrees of soil warming (\u00b0C)
fine_root_density: fine root density (mg roots cm-3)
soil_layer: layer of soil sampled (0-10cm or 10-30cm)
grassland: long-term warmed (LTW) grassland
ID: plot soil ID", "keywords": ["2. Zero hunger", "13. Climate action", "15. Life on land"], "contacts": [{"organization": "Verbrigghe, Niel, Leblans, Niki I. W., Sigurdsson, Bjarni D., Vicca, Sara, Fang, Chao, Fuchslueger, Lucia, Soong, Jennifer L., Weedon, James T., Poeplau, Christopher, Ariza-Carricondo, Cristina, Bahn, Michael, Guenet, Bertrand, Gundersen, Per, Gunnarsd\ufffd\ufffdttir, Gunnhildur E., K\ufffd\ufffdtterer, Thomas, Liu, Zhanfeng, Maljanen, Marja, Mara\ufffd\ufffd\ufffd\ufffdn-Jim\ufffd\ufffdnez, Sara, Meeran, Kathiravan, Oddsd\ufffd\ufffdttir, Edda S., Ostonen, Ivika, Pe\ufffd\ufffdelas, Josep, Richter, Andreas, Sardans, Jordi, Sigur\ufffd\ufffdsson, P\ufffd\ufffdll, Van Bodegom, Peter M., Verbruggen, Erik, Walker, Tom W. N., Wallander, H\ufffd\ufffdkan, Janssens, Ivan A.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4745479"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4745479", "name": "item", "description": "10.5281/zenodo.4745479", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4745479"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-10T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=15.+Life+on+land&offset=10300&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=15.+Life+on+land&offset=10300&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": "prev", "title": "items (prev)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=15.+Life+on+land&offset=10250", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=15.+Life+on+land&offset=10350", "hreflang": "en-US"}], "numberMatched": 12443, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-04-05T07:22:46.728745Z"}