We used a nonintrusive field experiment carried out at six sites \uffe2\uff80\uff93 Wales (UK), Denmark (DK), the Netherlands (NL), Hungary (HU), Sardinia (Italy \uffe2\uff80\uff93 IT), and Catalonia (Spain \uffe2\uff80\uff93 SP) \uffe2\uff80\uff93 along a climatic and latitudinal gradient to examine the response of plant species richness and primary productivity to warming and drought in shrubland ecosystems. The warming treatment raised the plot daily temperature by ca. 1 \uffc2\uffb0C, while the drought treatment led to a reduction in soil moisture at the peak of the growing season that ranged from 26% at the SP site to 82% in the NL site. During the 7 years the experiment lasted (1999\uffe2\uff80\uff932005), we used the pin\uffe2\uff80\uff90point method to measure the species composition of plant communities and plant biomass, litterfall, and shoot growth of the dominant plant species at each site. A significantly lower increase in the number of species pin\uffe2\uff80\uff90pointed per transect was found in the drought plots at the SP site, where the plant community was still in a process of recovering from a forest fire in 1994. No changes in species richness were found at the other sites, which were at a more mature and stable state of succession and, thus less liable to recruitment of new species. The relationship between annual biomass accumulation and temperature of the growing season was positive at the coldest site and negative at the warmest site. The warming treatment tended to increase the aboveground net primary productivity (ANPP) at the northern sites. The relationship between annual biomass accumulation and soil moisture during the growing season was not significant at the wettest sites, but was positive at the driest sites. The drought treatment tended to reduce the ANPP in the NL, HU, IT, and SP sites. The responses to warming were very strongly related to the Gaussen aridity index (stronger responses the lower the aridity), whereas the responses to drought were not. Changes in the annual aboveground biomass accumulation, litterfall, and, thus, the ANPP, mirrored the interannual variation in climate conditions: the most outstanding change was a decrease in biomass accumulation and an increase in litterfall at most sites during the abnormally hot year of 2003. Species richness also tended to decrease in 2003 at all sites except the cold and wet UK site. Species\uffe2\uff80\uff90specific responses to warming were found in shoot growth: at the SP site, Globularia alypum was not affected, while the other dominant species, Erica multiflora, grew 30% more; at the UK site, Calluna vulgaris tended to grow more in the warming plots, while Empetrum nigrum tended to grow less. Drought treatment decreased plant growth in several studied species, although there were some species such as Pinus halepensis at the SP site or C. vulgaris at the UK site that were not affected. The magnitude of responses to warming and drought thus depended greatly on the differences between sites, years, and species and these multiple plant responses may be expected to have consequences at ecosystem and community level. Decreases in biodiversity and the increase in E. multiflora growth at the SP site as a response to warming challenge the assumption that sensitivity to warming may be less well developed at more southerly latitudes; likewise, the fact that one of the studied shrublands presented negative ANPP as a response to the 2003 heat wave also challenges the hypothesis that future climate warming will lead to an enhancement of plant growth and carbon sequestration in temperate ecosystems. Extreme events may thus change the general trend of increased productivity in response to warming in the colder sites.
", "keywords": ["0106 biological sciences", "Onada de calor", "arctic ecosystems", "Matorral", "drought", "Biomasa vegetal", "heathland", "global warming", "01 natural sciences", "Sequ\u00eda", "Productividad primaria neta", "Forest-steppe", "Gradiente Europea", "Climate change", "Canvi clim\u00e0tic", "Cambio clim\u00e1tico", "net primary productivity", "evergreen mediterranean forest", "species richness", "litterfall", "biodiversity", "European gradient", "Plant growth", "2. Zero hunger", "Global warming", "terrestrial ecosystems", "phillyrea-latifolia", "Biodiversity", "Sequera", "Crecimiento de las plantas", "6. Clean water", "Net primary productivity", "climate change", "Brezal", "Biomassa vegetal", "climate-change", "heat wave", "Bosc-estepa", "environmental-change", "Litterfall", "Shrubland", "Biodiversidad", "soil", "Riquesa d'esp\u00e8cies", "forest-steppe", "Heat wave", "Bruguerar", "carbon-cycle", "Riqueza de especies", "quercus-ilex", "14. Life underwater", "plant biomass", "Hojarasca", "Plant biomass", "Drought", "Escalfament global", "plant growth", "15. Life on land", "biodiversity; climate change; global warming; plant community; primary production; shrubland; species richness", " Benelux; Catalonia; Central Europe; Denmark; Eurasia; Europe; Hungary; Italy; Netherlands; Northern Europe; Sardinia; Scandinavia; Southern Europe; Spain; United Kingdom; Wales; Western Europe", " Calluna; Calluna vulgaris; Empetrum nigrum; Erica multiflora; Globularia alypum; Pinus halepensis; Biodiversity; Climate change; Drought; European gradient; Forest-steppe; Global warming; Heat wave; Heathland; Litterfall; Net primary productivity; Plant biomass; Plant growth; Shrubland; Species richness", "Gradient Europea", "Biodiversitat", "Creixement de les plantes", "Productivitat prim\u00e0ria neta", "13. Climate action", "cistus-albidus", "Calentamiento global", "Bosque-estepa", "shrubland", "Fullaraca", "Heathland", "Species richness", "Ola de calor"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2007.01464.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2486.2007.01464.x", "name": "item", "description": "10.1111/j.1365-2486.2007.01464.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2007.01464.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-10-04T00:00:00Z"}}, {"id": "10.1897/04-036r.1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:20:03Z", "type": "Journal Article", "created": "2005-03-19", "title": "Toxicity Of Heavy Metals In Soil Assessed With Various Soil Microbial And Plant Growth Assays: As Comparative Study", "description": "AbstractElevated metal concentrations in soils can disturb the soil ecosystem; thus, researcherss rive to identify the most sensitive assay for detection of the early signs of toxicity. The purpose of the present study was to compare eight different ecotoxicological endpoints on the same set of metal-contaminated soils that were collected from seven series of soils sampled during field trials. The endpoints are based on three microbial assays (potential nitrification rate [PNR], substrate-induced respiration [SIR], and basal respiration [BR]) and two plant growth tests, one of which included symbiotic N fixation. The overall sensitivity of the endpoints to detect statistically significant adverse effects ranked as follows: PNR > SIR (lag time) > plant yield and N fixation > SIR (respiration after 24 and 48 h) > BR. The lowest adverse effect concentrations were found with the PNR at 7 mg kg\uffe2\uff88\uff921 of Cd and 107 mg kg\uffe2\uff88\uff921 of Zn. The variability of these endpoints among different uncontaminated soils was additionally assessed on 14 soil samples. That variability showed a strong correlation with sensitivity scores, illustrating that metal-sensitive endpoints have a large natural variability. We question the ecological relevance of highly sensitive microbial assays, because they tend to have a large natural variability. The identification of toxicity in the field requires endpoints that are highly sensitive and that do not vary greatly among soils (i.e., robust); however, no such endpoint was found in the present study. The endpoints that combined average sensitivity and robustness were SIR (lag time), clover yield, and N fixation in clover.
", "keywords": ["Hungary", "Sewage", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "Zinc", "Nitrogen Fixation", "London", "Lolium", "Soil Pollutants", "0401 agriculture", " forestry", " and fisheries", "Trifolium", "France", "Soil Microbiology", "Cadmium"]}, "links": [{"href": "https://doi.org/10.1897/04-036r.1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Toxicology%20and%20Chemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1897/04-036r.1", "name": "item", "description": "10.1897/04-036r.1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1897/04-036r.1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2005-03-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14002689", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:22:31Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil organic carbon concentration map for the topsoil of Hungary (2016)", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales. The data was prepared according to the methodology of SERENA SOC loss cookbook for the territory of Hungary. To compile the soil organic carbon map, soil organic carbon (0-30 cm, year 2016) data of the Hungarian Soil Information and Monitoring System (SIMS) were used, which are not publicly available. The selection of environmental covariates, which are then used to model and map SOC content, was based on the \u2018scorpan\u2019 model: (s) soil properties, (c) climate, (o) organisms, (r) relief, (p) parent material, (a) age and (n) spatial coordinates. The following covariates were used: soil type map of Hungary (P\u00e1sztor et al., 2018); long-term mean annual evapotranspiration, -evaporation, -precipitation, and -temperature (Szentimrey et al., 2007); CORINE Land Cover 2012; EU-DEM and derivatives; Geological map of Hungary (Gyalog & S\u00edkhegyi, 2005). Random forest kriging (RFK, combination of the random forest machine learning algorithm and the kriging technique) was used for the prediction of the SOC concentration.", "keywords": ["EJP SOIL", "Hungary", "soil organic carbon (SOC)", "SERENA project", "digital soil mapping", "SOC loss"], "contacts": [{"organization": "Ben\u0151, Andr\u00e1s, Szatm\u00e1ri, G\u00e1bor, Bakacsi, Zsofia, P\u00e1sztor, L\u00e1szl\u00f3, Szab\u00f3, Brigitta, Kassai, Piroska, Kocsis, Mih\u00e1ly, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, Laborczi, Annam\u00e1ria,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14002689"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14002689", "name": "item", "description": "10.5281/zenodo.14002689", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14002689"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.14006019", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-25T16:22:32Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil water erosion map of Hungary according to the RUSLE model", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales. Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion (ST). To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor).", "keywords": ["EJP SOIL", "Hungary", "RUSLE", "water erosion", "erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14006019"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14006019", "name": "item", "description": "10.5281/zenodo.14006019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14006019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "1069afa2-e7ee-4c57-8e5f-06cf489b7623", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[12.1, 41.2], [12.1, 60.0], [41.1, 60.0], [41.1, 41.2], [12.1, 41.2]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Europe"}, {"id": "Eastern Europe"}, {"id": "Central Europe"}, {"id": "Bulgaria"}, {"id": "Czech Republic"}, {"id": "Belarus"}, {"id": "Hungary"}, {"id": "Moldova"}, {"id": "Poland"}, {"id": "Romania"}, {"id": "Russia"}, {"id": "Slovakia"}, {"id": "Ukraine"}, {"id": "Estonia"}, {"id": "Latvia"}, {"id": "Lithuania"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:16", "type": "Dataset", "language": "eng", "title": "SOTER-based soil parameter estimates (SOTWIS) for Central and Eastern Europe, version 1.0", "description": "This harmonized set of soil parameter estimates for Central and Eastern Europe has been derived from a revised version of the 1:2.5M Soil and Terrain (SOTER) Database for Central and Eastern Europe (SOVEUR ver. 1.1) and the ISRIC-WISE soil profile database.\n\nThe land surface of Central and Eastern Europe, West of the Ural Mountains, has been characterized using 8361 unique maps or SOTER units. The corresponding GIS files include some 9500 mapped polygons, including miscellaneous units. The major soils have been described using 662 profiles, selected by national soil experts as being representative for these units. The associated soil analytical data have been derived from soil survey reports. These sources seldom hold all the physical and chemical attributes ideally required by SOTER. Gaps in the measured soil profile data have been filled using a procedure that uses taxotransfer rules, based on about 9600 soil profiles held in the WISE database, complemented with expert-rules. \n\nParameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments (less than 2 mm), and available water capacity (-33 to -1500 kPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and analyses of global environmental change. \n\nThe current parameter estimates should be seen as best estimates based on the current selection of soil profiles and data clustering procedure; taxotransfer rules have been flagged to provide an indication of the confidence in the derived data.\n\nResults are presented as summary files and can be linked to the 1:2.5M scale SOVEUR map in a GIS, through the unique SOTER-unit code. The secondary data are considered appropriate for studies at the continental scale (greater than 1:2.5 million); correlation of soil analytical data should be done more rigorously when more detailed scientific work is considered.", "formats": [{"name": "zip"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["calcium", "carbon", "cation exchange capacity", "electrical conductivity", "nitrogen", "organic matter", "bulk density", "soil profiles", "pH", "salinity", "texture", "water holding capacity", "nutrients", "Soil science", "Europe", "Eastern Europe", "Central Europe", "Bulgaria", "Czech Republic", "Belarus", "Hungary", "Moldova", "Poland", "Romania", "Russia", "Slovakia", "Ukraine", "Estonia", "Latvia", "Lithuania"], "contacts": [{"name": "Niels Batjes", "organization": "ISRIC - World Soil Information", "position": "Senior Soil Scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "niels.batjes@isric.org"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "denominator": "2500000"}, "links": [{"href": "https://files.isric.org/public/sotwis/SOTWIS_SOVEUR_v1.zip", "name": "Download", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/projects/harmonized-continental-soter-derived-database-sotwis", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://isric.org/sites/default/files/isric_report_2000_02a.pdf", "name": "Report", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/sotwis/SOTWIS_SOVEUR_v2.jpg", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "1069afa2-e7ee-4c57-8e5f-06cf489b7623", "name": "item", "description": "1069afa2-e7ee-4c57-8e5f-06cf489b7623", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1069afa2-e7ee-4c57-8e5f-06cf489b7623"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1930-07-01T00:00:00Z", "1997-09-01T00:00:00Z"]}}, {"id": "1081ac75-78f7-4db3-b8cc-23b78a3aa769", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-172.5, -38.6], [-172.5, 64.9], [153.1, 64.9], [153.1, -38.6], [-172.5, -38.6]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Australia"}, {"id": "Botswana"}, {"id": "Brazil"}, {"id": "Cameroon"}, {"id": "China"}, {"id": "Colombia"}, {"id": "Costa Rica"}, {"id": "Cote d Ivoire"}, {"id": "Cuba"}, {"id": "Ecuador"}, {"id": "Finland"}, {"id": "France"}, {"id": "Gabon"}, {"id": "Germany"}, {"id": "Ghana"}, {"id": "Greece"}, {"id": "Hungary"}, {"id": "Spain"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:10", "type": "Dataset", "language": "eng", "title": "A Globally Distributed Soil Spectral Library Visible Near Infrared Diffuse Reflectance Spectra", "description": "The ICRAF-ISRIC Soil VNIR Spectral Library contains visible near infrared spectra of 4,438 soils selected from the Soil Information System (ISIS) of the International Soil Reference and Information Centre (ISRIC). The samples consist of all physically archived samples at ISRIC in 2004 for which soil attribute data was available. The spectra were measured at the World Agroforestry Center's (ICRAF) Soil and Plant Spectral Diagnostic Laboratory. The samples are from 58 countries spanning Africa, Asia, Europe, North America, and South America. Associated attribute data, such as geographical coordinates, horizon (depth), and physical and chemical properties, are provided in a single relational database. The purpose of the library is to provide a resource for research and applications for sensing soil quality both in the laboratory and from space.", "formats": [{"name": "zip"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["soil profiles", "colour", "moisture", "texture", "spectroscopy data", "Soil science", "Australia", "Botswana", "Brazil", "Cameroon", "China", "Colombia", "Costa Rica", "Cote d Ivoire", "Cuba", "Ecuador", "Finland", "France", "Gabon", "Germany", "Ghana", "Greece", "Hungary", "Spain"], "contacts": [{"name": "Keith Shepherd", "organization": "World Agroforestry Centre", "position": "Senior scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "afsis.info@africasoils.net"}], "addresses": [{"deliveryPoint": ["PO Box 30677"], "city": "Nairobi", "administrativeArea": null, "postalCode": "00100", "country": "Kenya"}], "links": [{"href": null}]}, {"name": "Stephan Mantel", "organization": "ISRIC - World Soil Information", "position": "Sustainable land management", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "stephan.mantel@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "denominator": "100000"}, "links": [{"href": "https://files.isric.org/public/other/", "name": "Download", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/explore/ISRIC-collections", "name": "Project webpage ISRIC", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://www.worldagroforestry.org/sd/landhealth/soil-plant-spectral-diagnostics-laboratory/soil-spectra-library", "name": "Project webpage ICRAF", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "http://worldagroforestry.org/sites/default/files/Description_ICRAF-ISRIC%20Soil%20VNIR%20Spectral%20Library.pdf", "name": "Report", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/other/ICRAF-ISRICVNIRSoilDatabase.jpg", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "1081ac75-78f7-4db3-b8cc-23b78a3aa769", "name": "item", "description": "1081ac75-78f7-4db3-b8cc-23b78a3aa769", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1081ac75-78f7-4db3-b8cc-23b78a3aa769"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1996-11-01T00:00:00Z", "2006-11-01T00:00:00Z"]}}, {"id": "1b65024a-cd9f-11e9-a8f9-a0481ca9e724", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-172.5, -38.6], [-172.5, 64.9], [153.1, 64.9], [153.1, -38.6], [-172.5, -38.6]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Australia"}, {"id": "Botswana"}, {"id": "Brazil"}, {"id": "Cameroon"}, {"id": "China"}, {"id": "Colombia"}, {"id": "Costa Rica"}, {"id": "Cote d Ivoire"}, {"id": "Cuba"}, {"id": "Ecuador"}, {"id": "Finland"}, {"id": "France"}, {"id": "Gabon"}, {"id": "Germany"}, {"id": "Ghana"}, {"id": "Greece"}, {"id": "Hungary"}, {"id": "Spain"}], "scheme": "Region"}], "updated": "2021-07-14T11:52:27", "type": "Dataset", "language": "eng", "title": "A Globally Distributed Soil Spectral Library Mid Infrared Diffuse Reflectance Spectra", "description": "The ICRAF-ISRIC Soil MIR Spectral Library contains visible near infrared spectra of 4,438 soils selected from the Soil Information System (ISIS) of the International Soil Reference and Information Centre (ISRIC). The samples consist of all physically archived samples at ISRIC in 2004 for which soil attribute data was available. The spectra were measured at the World Agroforestry Center's (ICRAF) Soil and Plant Spectral Diagnostic Laboratory. The samples are from 58 countries spanning Africa, Asia, Europe, North America, and South America. Associated attribute data, such as geographical coordinates, horizon (depth), and physical and chemical properties, are provided in a single relational database. The purpose of the library is to provide a resource for research and applications for sensing soil quality both in the laboratory and from space", "formats": [{"name": "zip"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["soil profiles", "colour", "moisture", "texture", "spectroscopy data", "Soil science", "Australia", "Botswana", "Brazil", "Cameroon", "China", "Colombia", "Costa Rica", "Cote d Ivoire", "Cuba", "Ecuador", "Finland", "France", "Gabon", "Germany", "Ghana", "Greece", "Hungary", "Spain"], "contacts": [{"name": "Keith Shepherd", "organization": "World Agroforestry Centre", "position": "Senior scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "afsis.info@africasoils.net"}], "addresses": [{"deliveryPoint": ["PO Box 30677"], "city": "Nairobi", "administrativeArea": null, "postalCode": "00100", "country": "Kenya"}], "links": [{"href": null}]}, {"name": "Stephan Mantel", "organization": "ISRIC - World Soil Information", "position": "Sustainable land management", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "stephan.mantel@wur.nl"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}], "denominator": "100000"}, "links": [{"href": "https://files.isric.org/public/other/", "name": "Download", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/explore/ISRIC-collections", "name": "Project webpage ISRIC", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://www.worldagroforestry.org/sd/landhealth/soil-plant-spectral-diagnostics-laboratory/soil-spectra-library", "name": "Project webpage ICRAF", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "http://worldagroforestry.org/sites/default/files/Description_ICRAF-ISRIC%20Soil%20VNIR%20Spectral%20Library.pdf", "name": "Report", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/other/ICRAF-ISRICVNIRSoilDatabase.jpg", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "1b65024a-cd9f-11e9-a8f9-a0481ca9e724", "name": "item", "description": "1b65024a-cd9f-11e9-a8f9-a0481ca9e724", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1b65024a-cd9f-11e9-a8f9-a0481ca9e724"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1996-11-01T00:00:00Z", "2006-11-01T00:00:00Z"]}}, {"id": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:26:51Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil water erosion map of Hungary according to the RUSLE model", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales. Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. The objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. Soil loss was used as an indicator for soil erosion (ST). To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor).", "keywords": ["EJP SOIL", "Hungary", "RUSLE", "water erosion", "erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::1b6081f8bd9a44803fc91990862b9ee4"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "name": "item", "description": "50|od______2659::1b6081f8bd9a44803fc91990862b9ee4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::1b6081f8bd9a44803fc91990862b9ee4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "50|od______2659::faea77e44934fa0ba199639d29e95776", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-25T16:26:52Z", "type": "Dataset", "title": "SERENA EJP SOIL: Erosion control map of Hungary", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales. Present data was prepared according to the methodology of SERENA Soil erosion and soil erosion control cookbook for the territory of Hungary. The map of soil loss by water erosion (soil threat) was based on the RUSLE model. To create the soil loss map we used data on yearly precipitation of CARPATCLIM database, and AGRI4CAST MARS (R-factor); sand-, silt-, and clay content of DOSoReMI.hu database, and SOC map compiled in the framework of SERENA (K-factor); ESDAC LS-factor for the EU; ESDAC Cover Management factor for the EU (C-factor); ESDAC Support Practices factor for the EU (P-factor). For the soil erosion control, the difference between the erosion map without vegetation (C-factor = 1) and the erosion map with vegetation was calculated. The erosion maps with-, and without vegetation were categorized according to the cookbook, and the result map shows how many categories the pixel has changed when vegetation is taken into account (0: the pixel is in the same category in both maps, 1: minor role of vegetation, 2: moderate role of vegetation, 3: significant role of vegetation).", "keywords": ["EJP SOIL", "Hungary", "erosion control", "RUSLE", "water erosion", "SERENA"], "contacts": [{"organization": "Laborczi, Annam\u00e1ria, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::faea77e44934fa0ba199639d29e95776"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::faea77e44934fa0ba199639d29e95776", "name": "item", "description": "50|od______2659::faea77e44934fa0ba199639d29e95776", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::faea77e44934fa0ba199639d29e95776"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:26:52Z", "type": "Dataset", "title": "SERENA EJP SOIL: Soil organic carbon concentration map for the topsoil of Hungary (2016)", "description": "The internal EJP SOIL project\u00a0SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant\u00a0stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at\u00a0the regional, national, and European scales. The data was prepared according to the methodology of SERENA SOC loss cookbook for the territory of Hungary. To compile the soil organic carbon map, soil organic carbon (0-30 cm, year 2016) data of the Hungarian Soil Information and Monitoring System (SIMS) were used, which are not publicly available. The selection of environmental covariates, which are then used to model and map SOC content, was based on the \u2018scorpan\u2019 model: (s) soil properties, (c) climate, (o) organisms, (r) relief, (p) parent material, (a) age and (n) spatial coordinates. The following covariates were used: soil type map of Hungary (P\u00e1sztor et al., 2018); long-term mean annual evapotranspiration, -evaporation, -precipitation, and -temperature (Szentimrey et al., 2007); CORINE Land Cover 2012; EU-DEM and derivatives; Geological map of Hungary (Gyalog & S\u00edkhegyi, 2005). Random forest kriging (RFK, combination of the random forest machine learning algorithm and the kriging technique) was used for the prediction of the SOC concentration.", "keywords": ["EJP SOIL", "Hungary", "soil organic carbon (SOC)", "SERENA project", "digital soil mapping", "SOC loss"], "contacts": [{"organization": "Ben\u0151, Andr\u00e1s, Szatm\u00e1ri, G\u00e1bor, Bakacsi, Zsofia, P\u00e1sztor, L\u00e1szl\u00f3, Szab\u00f3, Brigitta, Kassai, Piroska, Kocsis, Mih\u00e1ly, Gedeon, Csongor Istv\u00e1n, Csontos, P\u00e9ter, Laborczi, Annam\u00e1ria,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578"}, {"rel": "self", "type": "application/geo+json", "title": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "name": "item", "description": "50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/50|od______2659::b6395b7e6ea6ce00c3c366e98a8e6578"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "94530236-1a4e-450f-8ae4-87899dc4b141", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[15.8, 43.11], [15.8, 51.0], [27.33, 51.0], [27.33, 43.11], [15.8, 43.11]]]}, "properties": {"themes": [{"concepts": [{"id": "environment"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Species distribution"}], "scheme": "GEMET - INSPIRE themes, version 1.0"}, {"concepts": [{"id": "forest ecosystem"}, {"id": "forest"}, {"id": "ecological parameter"}, {"id": "species"}], "scheme": "GEMET"}, {"concepts": [{"id": "Czechia"}, {"id": "Poland"}, {"id": "Slovakia"}, {"id": "Serbia"}, {"id": "Romania"}, {"id": "Ukraine"}, {"id": "Hungary"}], "scheme": "Continents, countries, sea regions of the world."}, {"concepts": [], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "Land use"}, {"id": "Forests and forestry"}, {"id": "Biodiversity"}], "scheme": "EEA topics"}], "updated": "2025-10-09T11:04:10.042447Z", "type": "Dataset", "created": "2016-10-23", "language": "eng", "title": "Forest naturalness, species assemblages in the Carpathians (KEO), Oct. 2016", "description": "The naturalness dataset is calculated as a species assemblages likeliness over the forest coverage. 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pollution"}], "scheme": "GEMET"}, {"concepts": [{"id": "Hungary"}, {"id": "Bulgaria"}, {"id": "Romania"}, {"id": "Italy"}, {"id": "Czechia"}, {"id": "France"}, {"id": "Denmark"}, {"id": "Austria"}, {"id": "Estonia"}, {"id": "Lithuania"}, {"id": "Slovenia"}, {"id": "Greece"}, {"id": "Ireland"}, {"id": "United Kingdom"}, {"id": "Latvia"}, {"id": "Portugal"}, {"id": "Germany"}, {"id": "Spain"}, {"id": "Finland"}, {"id": "Belgium"}, {"id": "Sweden"}, {"id": "Poland"}, {"id": "Luxembourg"}, {"id": "Netherlands"}, {"id": "Slovakia"}], "scheme": "Continents, countries, sea regions of the world."}, {"concepts": [], "scheme": "Temporal resolution"}, {"concepts": [{"id": "European"}], "scheme": "http://inspire.ec.europa.eu/metadata-codelist/SpatialScope"}, {"concepts": [{"id": "Land use"}], "scheme": "https://www.eea.europa.eu/themes"}], "updated": "2021-09-21T12:29:45.75Z", "type": "Dataset", "created": "2020-10-07T00:00:00", "language": "eng", "title": "Concentrations of heavy metals in European agricultural soils, Oct. 2020", "description": "This data set contains current and critical metal concentrations and its exceedances in topsoils, as well as data related to the current and critical metal inputs to and outputs from soils (uptake, accumulation and leaching) and the resulting exceedances of critical metal inputs. \n\nThis data set has been compiled by the European Topic Centre on Urban, Land and Soil Systems (ETC/ULS) in the context of a study on metal and nutrient dynamics where the fate and dynamics of the most abundant heavy metals and nutrients in agricultural soils were investigated. The purpose of this study was to investigate the impacts of agricultural intensification in Europe, and to understand its environmental impact. Metal concentrations in soils were used from two consecutive Europe-wide geochemical surveys, sampled in 1998 (FOREGS survey) and 2009 (GEMAS survey). For land use, the 2010 Eurostat data were used. \n\nThe metals included in this data set are cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn). The results on the fate of Nitrogen (N) and Phosphorus (P) are included in a separate dataset. Cu and Zn are minor nutrients but at high inputs, they may cause adverse impacts on soil biodiversity, whereas Cd and Pb are toxic metals that may lead to soil degradation, by both affecting soil biodiversity and food quality. Metal budgets based on spatially explicit input and output data were calculated using the INTEGRATOR model; approximately 40,000 so-called NCUs as unique combinations of soil type, administrative region, slope class and altitude class were used. Available critical limits for food, water and soil organisms, from different existing regulations and studies, were converted to soil property-dependent critical metal concentrations (soil-based quality standards), which were then used to calculate critical metal inputs. \n\nThe results allow for the first time to identifying spatial hot spots for critical environmental impact of soil pollution for the four most abundant heavy metals. It thus informs policy processes important for planning and guiding sustainable agriculture and soil management. The work is methodologically novel, as it applies endpoint risk to thresholds in soils, and thus guides future impact studies. Updates with more recent land use and soil data are now possible.\n\nThe description of the included model results and the reference report is provided under \"lineage\". The data set is provided as SHP and also in a GDB, the latter including as well the N and P concentrations. 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