{"type": "FeatureCollection", "features": [{"id": "community-antimicrobial-resistance-genes-and-concentrations-of-polycyclic-aromatic-hydroca-2016", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:28:35Z", "type": "Dataset", "title": "Community antimicrobial resistance genes and concentrations of polycyclic aromatic hydrocarbons and metals in NE England soils (2016)", "description": "The dataset collates the relative concentration of nearly 300 antimicrobial resistance (AMR) genes, and concentrations of polycyclic aromatic hydrocarbons (PAH) and potentially toxic elements (PTE; e.g., \u201cmetals\u201d) found in soils across northeastern England during a sampling expedition in June 2016 by researchers at Newcastle University. Top soils (15 cm depths; \u201cA\u201d horizon) were obtained from 24 rural and urban locations around Newcastle upon Tyne, representing a spectrum of landscape conditions relative to anticipated PTE contamination. There are three files related to different types of data collected: antimicrobial resistance genes, metal concentrations and PAH concentrations. The high-throughput analysis of nearly 300 AMR genes include many resistance traits representing major antibiotic classes: aminoglycosides, beta lactams, FCA (fluoroquinolone, quinolone, chloramphenicol, florfenicol and amphenicol resistance genes), MLSB (macrolide, lincosamide, streptogramin B), tetracycline, vancomycin, sulphonamide, and efflux pumps. PAH data represent the US Environmental Protection Agency priority polycyclic aromatic hydrocarbons as one of the measures of pollution impact. The other measure of impact is based on levels of twelve PTE represented by \u201ctotal\u201d and \u201ctwo bio-available\u201d concentrations, based on three extraction methods. Elements included aluminium, arsenic, beryllium, cadmium, chromium, copper, iron, lead, mercury, nickel, phosphorus, and zinc. Full details about this dataset can be found at https://doi.org/10.5285/35b49db6-8522-4c6b-a779-820268292603", "formats": [{"name": "ZIP"}], "keywords": ["gb", "soil"]}, "links": [{"href": "https://data-package.ceh.ac.uk/data/35b49db6-8522-4c6b-a779-820268292603"}, {"href": "https://data-package.ceh.ac.uk/sd/35b49db6-8522-4c6b-a779-820268292603.zip"}, {"href": "http://data.europa.eu/88u/dataset/community-antimicrobial-resistance-genes-and-concentrations-of-polycyclic-aromatic-hydroca-2016"}, {"rel": "self", "type": "application/geo+json", "title": "community-antimicrobial-resistance-genes-and-concentrations-of-polycyclic-aromatic-hydroca-2016", "name": "item", "description": "community-antimicrobial-resistance-genes-and-concentrations-of-polycyclic-aromatic-hydroca-2016", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/community-antimicrobial-resistance-genes-and-concentrations-of-polycyclic-aromatic-hydroca-2016"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "/", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:13:50Z", "type": "Dataset", "title": "DrSch\u00e4r mais field monitoring timeseries", "description": "Timeseries of the DrSch\u00e4r field monitoring in Este (PD) during summer 2022. Dataset of the soil temperature and soil humidity collected from different type of sensors distributed among the mais field. In the field were installed different types of sensors as many TDR sensors and one capacitive sensor; they collect temperature and humidity of the soil. The data from the sensor were collected by two networks: a Zigbee-based and one LoraWAN-based network.", "keywords": ["capacitive", "environmental-monitoring-facilities", "eu", "humidity", "irrigation", "lorawan", "mais", "sensor", "soil", "soil-moisture", "tdr", "temperature", "water", "zigbee"]}, "links": [{"href": "http://data.europa.eu/88u/dataset/17af841d-1329-4c5a-a8b8-c4326f0614f9"}, {"rel": "self", "type": "application/geo+json", "title": "/", "name": "item", "description": "/", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items//"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "08125912-4c3c-464f-0998-0998ecf8427e", "type": "Feature", "geometry": null, "properties": {"updated": "1970-01-01", "type": "Dataset", "title": "INSPIRE Download Service (predefined ATOM) f\u00fcr Datensatz INSPIRE-BFD5W: Nutzbare Feldkapazit\u00e4t 100 cm", "description": "Beschreibung des INSPIRE Download Service (predefined Atom): INSPIRE-Version der BFD5w. Die nutzbare Feldkapazit\u00e4t eines Bodens ist der Teil der Feldkapazit\u00e4t, der f\u00fcr die Vegetation verf\u00fcgbar ist. Sie beinhaltet die Wassermenge, die ein grundwasserferner Standort in nat\u00fcrlicher Lagerung nach ausreichender S\u00e4ttigung gegen die Schwerkraft zur\u00fcckhalten kann und entspricht gem\u00e4\u00df Konvention einer Saugspannung von pF 1,8 bis 4,2. $Absatz$ <a href='https://www.lgb-rlp.de/fileadmin/service/lgb_downloads/inspire/boden/bfd5w/bfd5w_nfk1m.gml' target='_blank'>GML-Download</a> - Der/die Link(s) f\u00fcr das Herunterladen der Datens\u00e4tze wird/werden dynamisch aus Download Link aus einem Metadatensatz generiert", "formats": [{"name": "ATOM"}], "keywords": ["1", "ag_geoinformation", "bodenfunktionen", "de", "geodaten", "infofeatureaccessservice", "inspireidentifiziert", "lagen", "lgb", "rheinland-pfalz", "soil", "stein-und-wein", "wbk", "weinbergsbodenkarte"]}, "links": [{"href": "https://www.geoportal.rlp.de/mapbender//php/mod_inspireDownloadFeed.php?id=08125912-4c3c-464f-a5ca-6d284bcc7346&type=SERVICE&generateFrom=metadata"}, {"href": "http://data.europa.eu/88u/dataset/08125912-4c3c-464f-0998-0998ecf8427e"}, {"rel": "self", "type": "application/geo+json", "title": "08125912-4c3c-464f-0998-0998ecf8427e", "name": "item", "description": "08125912-4c3c-464f-0998-0998ecf8427e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/08125912-4c3c-464f-0998-0998ecf8427e"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "1-250000-land-capability-for-agriculture-wms", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:13:59Z", "type": "Dataset", "title": "1:250,000 Land Capability for Agriculture WMS", "description": "This service is the digital (vector) version of the Land Capability for Agriculture of Scotland 1:250,000 maps. Refer to the datasets for more information.", "formats": [{"name": "WMS_SRVC"}], "keywords": ["gb", "infomapaccessservice", "land-use", "soil"]}, "links": [{"href": "http://DRUID.HUTTON.AC.UK/arcgis/services/Hutton_LCA/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "http://data.europa.eu/88u/dataset/1-250000-land-capability-for-agriculture-wms"}, {"rel": "self", "type": "application/geo+json", "title": "1-250000-land-capability-for-agriculture-wms", "name": "item", "description": "1-250000-land-capability-for-agriculture-wms", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1-250000-land-capability-for-agriculture-wms"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "1-50000-land-capability-for-agriculture", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:13:59Z", "type": "Dataset", "title": "1:50,000 Land Capability for Agriculture", "description": "The Land Capability Classification for Agriculture has as its objective the presentation of detailed information on soil, climate and relief in a form which will be of value to land use planners, agricultural advisers, farmers and others involved in optimising the use of land resources. The classification ranks land on the basis of its potential productivity and cropping flexibility determined by the extent to which its physical characteristics (soil, climate and relief) impose long term restrictions on its agricultural use. THE CLASSES Class 1. Land capable of producing a very wide range of crops with high yields Class 2. Land capable of producing a wide range of crops with yields less high than Class 1. Class 3. Land capable of producing good yields from a moderate range of crops. Class 4. Land capable of producing a narrow range of crops. Class 5. Land suited only to improved grassland and rough grazing. Class 6. Land capable only of use as rough grazing. Class 7. Land of very limited agricultural value. THE DIVISIONS A division is a ranking within a class. As the requirements of the crops suited to Classes 1 and 2 are fairly stringent, land in these classes has inherently low degrees of internal variability and no divisions are present.  The requirements of crops grown in the remaining classes are less rigorous, consequently land included is more variable in character.", "formats": [{"name": "ZIP"}], "keywords": ["agriculture", "gb", "land-use", "soil"]}, "links": [{"href": "https://DRUID.HUTTON.AC.UK/arcgis/services/Hutton_LCA_50K_OSGB/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "https://www.hutton.ac.uk/sites/default/files/files/soils/downloads/lca_50k.zip"}, {"href": "http://data.europa.eu/88u/dataset/1-50000-land-capability-for-agriculture"}, {"rel": "self", "type": "application/geo+json", "title": "1-50000-land-capability-for-agriculture", "name": "item", "description": "1-50000-land-capability-for-agriculture", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1-50000-land-capability-for-agriculture"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "1-50000-land-capability-for-agriculture-wms-land-capability-for-agriculture-partial-cover", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:13:59Z", "type": "Dataset", "title": "1:50,000 Land Capability for Agriculture WMS. (Land capability for agriculture, partial cover)", "description": "This service is the digital (vector) version of the Land Capability for Agriculture of Scotland 1:50,000 maps. Also known as \"Land capability for agriculture (partial cover)\". Refer to the datasets for more information.", "formats": [{"name": "WMS_SRVC"}], "keywords": ["gb", "infomapaccessservice", "land-use", "soil"]}, "links": [{"href": "https://DRUID.HUTTON.AC.UK/arcgis/services/Hutton_LCA_50K_OSGB/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"href": "http://data.europa.eu/88u/dataset/1-50000-land-capability-for-agriculture-wms-land-capability-for-agriculture-partial-cover"}, {"rel": "self", "type": "application/geo+json", "title": "1-50000-land-capability-for-agriculture-wms-land-capability-for-agriculture-partial-cover", "name": "item", "description": "1-50000-land-capability-for-agriculture-wms-land-capability-for-agriculture-partial-cover", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1-50000-land-capability-for-agriculture-wms-land-capability-for-agriculture-partial-cover"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1016/j.jag.2024.103718", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:27Z", "type": "Journal Article", "created": "2024-02-20", "title": "Interseasonal transfer learning for crop mapping using Sentinel-1 data", "description": "Crop maps are highly desired information in modern agriculture as they enable possessors to manage their business in the most optimal way. Usually in remote sensing, crop mapping is performed using satellite images and within-season ground truth samples that are collected in extensive survey campaigns every year, neglecting information and knowledge that past seasons\u2019 classification models provided. This paper assessed different temporal transferring approaches, including transfer learning, together with traditional crop mapping approach to provide an exhaustive comparison. Transferring approaches differed in portion of knowledge utilized from a historical model and that coming from a target season dataset. Three distinct algorithms, Random Forest, Convolutional Neural Network and Transformer, were employed and evaluated using highly dense time series of Sentinel-1 data. Source and target domain were respectively represented by two sets, 2017\u20132020 and 2021 season data, and 9 different crop types were classified. Results showcased that transferring a model has a great potential in crop mapping when little to no ground truth data is available for the target season. However, traditional approach catches up rather quickly and even surpasses transfer learning approach in terms of performance after a certain portion of target domain data is collected. Without target season ground truth data, model transferring can yield modest crop mapping performance of 78% for F1 score, between 84% and 86% F1 score with transfer learning employed in conjunction with limited target season ground truth (i.e. between 120 and 720 parcels), and 88% F1 score at best with traditional approach (ca. 720 parcels). Even though a good discriminatory is found between different crop types, there is still a room for improvement regarding the least represented classes in the dataset. The study significantly contributes to the area of agricultural monitoring and management by demonstrating the effectiveness of transfer learning while lessening the necessity for extensive and labor-intensive data collection, thereby fostering cost and time efficiency. Utilizing Sentinel-1 data, it provides a practical and efficient solution for agricultural analysis worldwide regardless of cloudiness.", "keywords": ["2. Zero hunger", "Physical geography", "Crop mapping", "0211 other engineering and technologies", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "Transfer learning", "GB3-5030", "Environmental sciences", "Sentinel-1", "Pre-trained model", "0401 agriculture", " forestry", " and fisheries", "GE1-350", "Domain"]}, "links": [{"href": "https://doi.org/10.1016/j.jag.2024.103718"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Applied%20Earth%20Observation%20and%20Geoinformation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jag.2024.103718", "name": "item", "description": "10.1016/j.jag.2024.103718", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jag.2024.103718"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-01T00:00:00Z"}}, {"id": "10.1016/j.jag.2022.103101", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:27Z", "type": "Journal Article", "created": "2022-11-10", "title": "Forest foliage fuel load estimation from multi-sensor spatiotemporal features", "description": "Foliage fuel is the most flammable component in crown fires. Spatiotemporal dynamics of foliage fuel load (FFL) are important for fire managers to assess fire risk. Here, we integrated optical data from the Landsat 8 Operational Land Imager (OLI) with synthetic aperture radar (SAR) data from Sentinel-1 to estimate FFL. We first reconstructed seamless time series from the Landsat 8 and Sentinel-1 imagery by accounting for unequal time intervals between image observations and outliers. We then extracted temporal features that are proxies of the intra- and inter-annual dynamics from these time series. In addition, we derived spatial features from the imagery that quantify spatial context and therefore used varying window sizes. The random forest regression was implemented to assess the importance of the spatiotemporal features, reduce errors, and derive robust FFL estimates. The satellite estimates were validated against 96 field measurements from Pinus yunnanensis forests in the Liangshan Yi Autonomous Prefecture, Sichuan Province, China. Both the spatiotemporal features of SAR and optical data importantly contributed to FFL estimation. When only optical data was used, the model achieved a R2 of 0.75 (relative Root Mean Squared Error (rRMSE)\u00a0=\u00a025.3\u00a0%), while when only SAR data was used the R2 was 0.76 (rRMSE\u00a0=\u00a025.6\u00a0%). However, when optical and SAR data were combined, the R2 increased to 0.81 (rRMSE\u00a0=\u00a023.2\u00a0%). We also found that temporal features were more important predictors of FFL than features that captured spatial context. We demonstrated our FFL mapping method by a case study in the Chinese Sichuan Province, in relation to the occurrence of a fire. Our method needs additional validation over different tree species and forest types, yet has potential for mapping forest fuel loads and fire risk.", "keywords": ["Landsat 8", "Physical geography", "04 agricultural and veterinary sciences", "15. Life on land", "Fire risk", "01 natural sciences", "GB3-5030", "Spatiotemporal features", "Environmental sciences", "Forest foliage fuel load", "Sentinel-1", "0401 agriculture", " forestry", " and fisheries", "GE1-350", "SDG 14 - Life Below Water", "Random forest", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.jag.2022.103101"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Applied%20Earth%20Observation%20and%20Geoinformation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jag.2022.103101", "name": "item", "description": "10.1016/j.jag.2022.103101", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jag.2022.103101"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-12-01T00:00:00Z"}}, {"id": "10.1016/j.jag.2024.103659", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:27Z", "type": "Journal Article", "created": "2024-01-21", "title": "Automatized Sentinel-2 mosaicking for large area forest mapping", "description": "Creating maps of forest inventory variables is commonly taking advantage of satellite images, which are mosaicked together for gaining larger coverage. Recently, mosaicking has increasingly shifted towards user friendly cloud-based online environments such as Google Earth Engine (GEE), which are equipped with huge image repositories and extensive processing capabilities. This enables the easy transferability of workflows into new image sets and diversifies the range of methodological options for mosaicking. The quality control of the output mosaic, ensuring that the reflectance values are representative to the targeted land cover, is however primarily based on certain assumptions or pre-set rules which may not always produce an optimal result. Our study focuses on assessing and comparing the performance of three different mosaicking algorithms for predicting forest inventory variables, based on an extensive set of field data on the main site type, fertility class, and volume and biomass of growing stock. One of the compared mosaics derives from manual image selection, thus enabling rigorous visual quality control, and two others are resting on GEE-assisted automatized methods which include applying a percentile-based statistic over all the input reflectance values and selecting the best pixels using predefined quality indicators. The results indicate that the manual and the percentile-based mosaics are generally providing the best and relatively equal performance levels. Compared to them, the quality-based mosaic has slightly lower accuracy particularly when predicting continuous variables (i.e., the volume and biomass of growing stock) and it suffers from minor image defects. For the total volume of growing stock, for example, the RMS errors are 56.22 % for the manual, 56.33 % for the percentile-based, and 59.47 % for the quality-based mosaics, respectively. These results indicate that from the perspective of large area forest mapping, automatically generated mosaics may provide approximately similar accuracy as compared to manually controlled workflow at a fraction of the workload.", "keywords": ["Image mosaicking", "Physical geography", "791", "forest research", "04 agricultural and veterinary sciences", "15. Life on land", "Feature prediction", "01 natural sciences", "GB3-5030", "Environmental sciences", "0401 agriculture", " forestry", " and fisheries", "GE1-350", "Sentinel-2", "Google Earth Engine", "satellite images", "Forest inventory", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Balazs Andras, Tuominen Sakari, Pitk\u00e4nen Timo P.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.jag.2024.103659"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Applied%20Earth%20Observation%20and%20Geoinformation", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jag.2024.103659", "name": "item", "description": "10.1016/j.jag.2024.103659", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jag.2024.103659"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-01T00:00:00Z"}}, {"id": "10.1007/s13595-016-0540-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:15:14Z", "type": "Journal Article", "created": "2016-02-08", "title": "The Effects Of Forest Type On Soil Microbial Activity In Changbai Mountain, Northeast China", "description": "AbstractKey messageForty years after clear-cutting mixed old-growth forest (broadleaf/Korean pine) in the Changbai Mountain area (Northeast China), a mixed forest with natural broadleaf regeneration and larch plantation displayed larger microbial biomass and activity in the soil than either a naturally regenerated birch forest or a monospecific spruce plantation.ContextClear-cutting with limited restoration effort was until the end of the twentieth century the norm for managing primary forests in Northeast China. Forest restoration plays an important role in the recovery of soil quality after clear-cutting, but the effects of different regeneration procedures on forest soil quality remain poorly known in Northeast China.AimsWe assessed the effects of three regeneration procedures, i.e., (i) naturally regenerated birch forest, (ii) spruce plantation, and (iii) naturally regenerated broadleaf species interspersed with planted larch on soil quality and microbial activity in the Changbai Mountain area. An old-growth mixed broadleaf/Korean pine forest was used as a reference.MethodsPhysical and chemical properties and microbial biomass were recorded in the soil. Basal respiration and carbon mineralization were measured with a closed-jar alkali-absorption method.ResultsMicrobial biomass was smaller in the birch forest and spruce plantation than in the old-growth and the mixed broadleaf/larch forests. Moreover, microbial biomass, microbial quotient, and potentially mineralizable carbon were larger in the mixed broadleaf/larch than in the birch forest, while no difference was found between spruce plantation and birch forest for microbial biomass and microbial quotient. Basal respiration and metabolic quotient were larger in the birch forest as compared to the three other forest types, indicating a larger energy need for maintenance of the microbial community and lower microbial activity in the naturally regenerated birch forest.ConclusionMixed broadleaf/larch forest displayed a larger microbial biomass and higher substrate use efficiency of the soil microbial community than either naturally regenerated birch forest or spruce plantation. The combined natural and artificial regeneration procedure (mixed broadleaf-larch forest) seems better suited to restore soil quality after clear-cutting in the Changbai Mountain.", "keywords": ["[SDV] Life Sciences [q-bio]", "Changbai Mountain", "Forest restoration", "Carbon mineralization", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Microbial biomass carbon", "15. Life on land", "Soil quality"], "contacts": [{"organization": "Li Zhou, Dapao Yu, Xiang-Min Fang, Xiang-Min Fang, Wangming Zhou, Limin Dai,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s13595-016-0540-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Annals%20of%20Forest%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s13595-016-0540-y", "name": "item", "description": "10.1007/s13595-016-0540-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s13595-016-0540-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-02-08T00:00:00Z"}}, {"id": "10.1016/j.ejrh.2021.100882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:00Z", "type": "Journal Article", "created": "2021-07-30", "title": "Surface water and groundwater interaction at long-term exploited riverbank filtration site based on groundwater flow modelling (Mosina-Krajkowo, Poland)", "description": "Study region: Poland, Warta River catchment. Study focus: The study aimed to explain the reasons for spatial variability in chloride concentrations at the Mosina-Krajkowo riverbank filtration (RBF) site located along the river. This variability is attributed to RBF\u2019s different intensity along the river sections, related, among others, to clogging development. The RBF effectiveness was studied using groundwater flow modelling by: examining the water balance in zones established on hydrogeological setting and chloride concentrations; travel time of the bankfiltrate investigation; RBF parametrisation (i.e. infiltration per unit area and specific infiltration per unit of riverbank). New Hydrological Insights for the Region: The study identifies zones of the most favourable RBF conditions and establishes the variability causes. The overall share bankfiltrate was found at 75.8 %. Its spatial variation ranged widely from 41.1\u201389.3%, confirming the usefulness of the RBF performance sectional analysis in managing this type of site. The highest proportion of surface water (>80 %) occurred along the straight river section, where the riverbed was built by fine and medium sands (preventing penetration of organic suspension into the aquifer). In contrast, the lowest values (<42 %) occurred in the meander zone (with the most favourable RBF conditions at the beginning of site operation), where deep erosion reached coarse-grained sediments in the river bottom, followed by the development of clogging processes and a decrease in the RBF efficiency with time.", "keywords": ["Physical geography", "QE1-996.5", "Riverbed clogging", "Numerical modelling", "0208 environmental biotechnology", "0207 environmental engineering", "Geology", "Modflow", "02 engineering and technology", "Riverbank filtration", "6. Clean water", "Modpath", "GB3-5030"]}, "links": [{"href": "https://doi.org/10.1016/j.ejrh.2021.100882"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hydrology%3A%20Regional%20Studies", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ejrh.2021.100882", "name": "item", "description": "10.1016/j.ejrh.2021.100882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ejrh.2021.100882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-01T00:00:00Z"}}, {"id": "10.1016/j.ejrh.2021.100903", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:01Z", "type": "Journal Article", "created": "2021-09-03", "title": "Evaluation of pedotransfer functions for predicting soil hydraulic properties: A voyage from regional to field scales across Europe", "description": "Study region: Europe. A total of 660, 522, and 4940 soil samples belonging to GRIZZLY, HYPRES, and EU-HYDI databases, respectively, were used for parametric evaluation. Study focus: The soil water retention and hydraulic conductivity functions are crucial input information for land surface models. Determining these functions by using direct methods is hampered by excessive time and unaffordable costs required for field activities and laboratory analyses. Pedotransfer functions (PTFs) are widely-used indirect techniques enabling soil hydraulic properties to be predicted by using easily-retrievable soil information. In a parametric evaluation, the predictive capability of PTFs is examined by comparing measured and estimated soil water retention parameters and saturated hydraulic conductivity. Yet information about the performance of PTFs for specific modeling applications is mandatory to evaluate PTF effectiveness in greater depth. This approach is commonly defined as functional evaluation. New hydrological insights for the region: The best performing four PTFs selected in the parametric evaluations are tested under two functional evaluations. The first encompasses a spatial interpolation with a geostatistical technique, whereas the second employs Hydrus-1D to simulate the water balance components along an experimental transect. Our results reinforce and integrate the insights of previous studies about the use of a PTF, and highlight the ability, or inability, of this technique to adequately reproduce the observed spatial variability of soil hydraulic properties and simulated water fluxes.", "keywords": ["S1 Agriculture (General) / mez\u0151gazdas\u00e1g \u00e1ltal\u00e1ban", "Physical geography", "QE1-996.5", "Water retention function", "Hydrus-1D", "saturated hydraulic conductivity", "0208 environmental biotechnology", "0207 environmental engineering", "Geology", "02 engineering and technology", "15. Life on land", "Semi-variogram", "S590 Soill / Talajtan", "Saturated hydraulic conductivity", "6. Clean water", "GB3-5030", "Kriging", "semi-variogram", "functional evaluation", "water retention function", "Functional evaluation", "kriging", "water retention function", " saturated hydraulic conductivity", " semi-variogram", " kriging", " functional evaluation", " Hydrus-1D"]}, "links": [{"href": "https://doi.org/10.1016/j.ejrh.2021.100903"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hydrology%3A%20Regional%20Studies", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ejrh.2021.100903", "name": "item", "description": "10.1016/j.ejrh.2021.100903", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ejrh.2021.100903"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2016.11.018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:23Z", "type": "Journal Article", "created": "2016-11-24", "title": "Impacts Of Conversion Of Tropical Peat Swamp Forest To Oil Palm Plantation On Peat Organic Chemistry, Physical Properties And Carbon Stocks", "description": "Ecosystem services provided by tropical peat swamp forests, such as carbon (C) storage and water regulation, are under threat due to encroachment and replacement of these natural forests by drainage-based agriculture, commonly oil palm plantation. This study aims to quantify how the chemical and physical properties of peat change during land conversion to oil palm. This will be addressed by comparing four separate stages of conversion; namely, secondary peat swamp forests, recently deeply drained secondary forests, cleared and recently planted oil palm, and mature oil palm plantation in North Selangor, Malaysia. Results indicate accelerated peat decomposition in surface peats of mature oil palm plantations due to the lowered water table and altered litter inputs associated with this land-use change. Surface organic matter content and peat C stocks at secondary forest sites were higher than at mature oil palm sites (e.g. C stocks were 975 \u00b1 151 and 497 \u00b1 157 Mg ha\u2212 1 at secondary forest and mature oil palm sites, respectively). Land conversion altered peat physical properties such as shear strength, bulk density and porosity, with mirrored changes above and below the water table. Our findings suggest close links between the organic matter and C content and peat physical properties through the entire depth of the peat profile. We have demonstrated that conversion from secondary peat swamp forest to mature oil palm plantation may seriously compromise C storage and, through its impact on peat physical properties, the water holding capacity in these peatlands.", "keywords": ["GE", "QH301 Biology", "G Geography (General)", "Q Science (General)", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "333", "6. Clean water", "13. Climate action", "GB Physical geography", "0401 agriculture", " forestry", " and fisheries", "GE Environmental Sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://researchonline.ljmu.ac.uk/id/eprint/12410/3/Impacts%20of%20conversion%20of%20tropical%20peat%20swamp%20forest%20to%20oil%20palm%20plantation%20on%20peat%20organic%20chemistry%2C%20physical%20properties%20and%20carbon%20stocks.pdf"}, {"href": "https://doi.org/10.1016/j.geoderma.2016.11.018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2016.11.018", "name": "item", "description": "10.1016/j.geoderma.2016.11.018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2016.11.018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-03-01T00:00:00Z"}}, {"id": "10.1016/j.srs.2024.100118", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:16:57Z", "type": "Journal Article", "created": "2024-01-28", "title": "Satellite-based soil organic carbon mapping on European soils using available datasets and support sampling", "description": "Soil organic carbon (SOC) plays a major role in the global carbon cycle and is an important factor for soil health and fertility. Accurate mapping of SOC and other influencing parameters are crucial to guide the optimization of agricultural land management to maintain and restore soil health, to increase soil fertility, and thus to quantify its potential for sequestering CO2. Remote sensing and machine learning techniques offer promising approaches for predicting SOC distribution. In this study, we used remote sensing data and machine learning algorithms to map SOC at regional to large scale, which we then combined with temporospatial and spectral signature-based soil sampling to integrate local ground measurements. A rigorous validation approach was performed where several independent unseen datasets with a high number of samples were used, which additionally involved densely sampled fields. We found that our approach could predict SOC with an average percentage error of less than 10\u00a0% with an R2 of 0.91 using support sampling on croplands located on mineral soils, demonstrating the potential of remote sensing, machine learning, and specific ground measurements for mapping SOC. Our results suggest that this approach could make small carbon differences measurable and inform carbon sequestration efforts and improve our understanding of the impacts of land use and field management practices on soil carbon cycling.", "keywords": ["2. Zero hunger", "Physical geography", "Precision agriculture", "Science", "Q", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "GB3-5030", "13. Climate action", "Soil health", "Machine learning", "Soil carbon mapping", "0401 agriculture", " forestry", " and fisheries", "Soil carbon sequestration", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.srs.2024.100118"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.srs.2024.100118", "name": "item", "description": "10.1016/j.srs.2024.100118", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.srs.2024.100118"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-01T00:00:00Z"}}, {"id": "10.1029/2021ms002730", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:17:27Z", "type": "Journal Article", "created": "2022-02-17", "title": "Characterising the response of vegetation cover to water limitation in Africa using geostationary satellites", "description": "Abstract<p>Hydrological interactions between vegetation, soil, and topography are complex, and heterogeneous in semi\uffe2\uff80\uff90arid landscapes. This along with data scarcity poses challenges for large\uffe2\uff80\uff90scale modeling of vegetation\uffe2\uff80\uff90water interactions. Here, we exploit metrics derived from daily Meteosat data over Africa at ca. 5\uffc2\uffa0km spatial resolution for ecohydrological analysis. Their spatial patterns are based on Fractional Vegetation Cover (FVC) time series and emphasize limiting conditions of the seasonal wet to dry transition: the minimum and maximum FVC of temporal record, the FVC decay rate and the FVC integral over the decay period. We investigate the relevance of these metrics for large scale ecohydrological studies by assessing their co\uffe2\uff80\uff90variation with soil moisture, and with topographic, soil, and vegetation factors. Consistent with our initial hypothesis, FVC minimum and maximum increase with soil moisture, while the FVC integral and decay rate peak at intermediate soil moisture. We find evidence for the relevance of topographic moisture variations in arid regions, which, counter\uffe2\uff80\uff90intuitively, is detectable in the maximum but not in the minimum FVC. We find no clear evidence for wide\uffe2\uff80\uff90spread occurrence of the \uffe2\uff80\uff9cinverse texture effect\uffe2\uff80\uff9d on FVC. The FVC integral over the decay period correlates with independent data sets of plant water storage capacity or rooting depth while correlations increase with aridity. In arid regions, the FVC decay rate decreases with canopy height and tree cover fraction as expected for ecosystems with a more conservative water\uffe2\uff80\uff90use strategy. Thus, our observation\uffe2\uff80\uff90based products have large potential for better understanding complex vegetation\uffe2\uff80\uff90water interactions from regional to continental scales.</p>", "keywords": ["Physical geography", "GROUNDWATER-DEPENDENT ECOSYSTEMS", "water limitation", "GC1-1581", "geostationary", "SOIL-MOISTURE", "Oceanography", "01 natural sciences", "ecohydrology", "ROOTING DEPTH", "ACTIVE-ROLE", "WOODY COVER", "0105 earth and related environmental sciences", "fractional vegetation cover", "HYDROLOGIC PROCESSES", "15. Life on land", "6. Clean water", "GB3-5030", "MODEL", "CLIMATE", "13. Climate action", "Earth and Environmental Sciences", "PRECIPITATION", "Africa", "PATTERNS", "Research Article"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2021MS002730"}, {"href": "https://doi.org/10.1029/2021ms002730"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Advances%20in%20Modeling%20Earth%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2021ms002730", "name": "item", "description": "10.1029/2021ms002730", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2021ms002730"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-25T00:00:00Z"}}, {"id": "10.1080/10106049.2025.2493741", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:18:01Z", "type": "Journal Article", "created": "2025-04-28", "title": "The model for grain wheat yield prediction at high spatial resolution based on physical-geographical properties and satellite vegetation indices", "description": "Precision agriculture is promising approach for improving agricultural production, especially nowadays when the population is rapidly increasing. For that, crop yield estimation provides valuable information. The main research focus was to predict within-field grain yield and detect its drivers. The Random Forest regression model on data from diverse sources at the 10-meter spatial resolution was developed. The study was conducted in the Vojvodina region (Serbia) for eight wheat-planted fields, having precise grain yield data. Open-source data including 15 vegetation indices (VIs) was calculated from Sentinel-2 satellite bands, physical-geographical features obtained from the digital elevation model and soil properties. The model succeeded in predicting the wheat grain yield with the RMSE of 0.66 t/ha (average yield of 0.09 t/ha) and the best predictors were VIs considering chlorophyll and moisture content in plants, while physical-geographical properties managed to explain within-field variability. This methodology can be applied to other crops (maize, soybean).", "keywords": ["Topography", "remote sensing", "Physical geography", "machine learning", "remotesensing", "wheat yield", "GB3-5030"], "contacts": [{"organization": "Blagojevi\u0107, Dragana, Pajevi\u0107, Nina, Mimi\u0107, Gordan, \u0106ukovi\u0107, Stefanija, Markovi\u0107, Slobodan B., Maestrini, Bernardo, Brdar, Sanja,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1080/10106049.2025.2493741"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geocarto%20International", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1080/10106049.2025.2493741", "name": "item", "description": "10.1080/10106049.2025.2493741", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1080/10106049.2025.2493741"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-28T00:00:00Z"}}, {"id": "10.15468/dl.cda3ch", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2025-03-14", "title": "Occurrence Download", "description": "A dataset containing 2606222 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is one of (Rhizedra lutosa (H\u00fcbner, 1803), Hydraecia micacea Esper, 1789, Eublemma recta Guen\u00e9e, 1852, Aglaonice hirtipalpis Walker, 1858, Hypena laceratalis Walker, 1859, Hypena obsitalis (H\u00fcbner), Orthosia cerasi Fabricius, 1775, Pandesma anysa Guen\u00e9e, 1852, Erschoviella musculana Erschoff, 1874, Uraba lugens Walker, 1863, Pardasena virgulana Mabille, 1880, Earias vernana (Fabricius, 1787), Earias cupreoviridis (Walker, 1862), Earias biplaga Walker, 1866, Earias ansorgei Tams, 1930, Earias insulana (Boisduval, 1833), Earias vittella (Fabricius, 1794), Earias roseifera Butler, 1881, Utetheisa ornatrix Linnaeus, 1758, Antichloris viridis Druce, 1884, Antichloris eriphia Fabricius, 1776, Pyrrharctia isabella J.E.Smith, 1797, Syntomeida epilais Walker, 1854, Spilosoma virginica Fabricius, 1798, Lycomorphodes sordida (Butler, 1877), Hyphantria cunea (Drury, 1773), Empyreuma affinis Rothschild, 1912, Calliteara pudibunda Linnaeus, 1758, Orgyia antiqua (Linnaeus, 1758), Leucoma salicis Linnaeus, 1758, Lymantria monacha Linnaeus, 1758, Lymantria umbrosa, Lymantria albescens, Lymantria dispar Linnaeus, 1758, Lymantria postalba, Lymantria mathura Moore, 1865, Teia anartoides Walker, 1855, Euproctis chrysorrhoea Linnaeus, 1758, Euproctis fraterna Moore, 1883, Clostera anachoreta (Denis &amp; Schifferm\u00fcller), 1775, Thaumetopoea processionea Linnaeus, 1758, Thaumetopoea pityocampa (Denis &amp; Schifferm\u00fcller), 1776, Datana major Grote &amp; Robinson, 1866, Spatalia argentina (Denis &amp; Schifferm\u00fcller), 1776, Endoclita excrescens (Butler, 1877), Perileucoptera coffeella (Gu\u00e9rin-M\u00e9neville &amp; Perrotet, 1842), Stegommata sulfuratella Meyrick, 1880, Acrolepia assectella (Zeller, 1839), Argyresthia curvella (Linnaeus, 1761), Argyresthia pruniella (Clerck, 1759), Argyresthia laevigatella Herrich-Sch\u00e4ffer, 1855, Argyresthia cupressella Walsingham, 1890, Argyresthia conjugella Zeller, 1839, Argyresthia fundella Fischer von R\u00f6slerstamm, 1835, Argyresthia trifasciata Staudinger, 1871, Argyresthia thuiella Packard, 1871, Swammerdamia caesiella Stainton, 1870, Swammerdamia pyrella de Villiers, 1789, Yponomeuta padella Linnaeus, 1758, Ocnerostoma piniariella Zeller, 1847, Ocnerostoma friesei Svensson, 1966, Prays nephelomima Meyrick, 1907, Prays oleae Bernard, 1788, Prays citri Milli\u00e8re, 1873, Ypsolophus ustella (Clerck, 1759), Plutella xylostella (Linnaeus, 1767), Plutella porrectella Linnaeus, 1758, Stathmopoda auriferella Walker, 1864, Stathmopoda skelloni Butler, 1880, Stathmopoda cephalaea Meyrick, 1897, Stathmopoda plumbiflua Meyrick, 1911, Bedellia somnulentella (Zeller, 1847), Ochsenheimeria vacculella Fischer von R\u00f6slerstamm, 1842, Pterolonche inspersa Staudinger, 1859, Martyringa xeraula Meyrick, 1910, Leptocroca sanguinolenta Meyrick, 1886, Sphyrelata amotella (Walker, 1864), Schiffermuelleria amasiella (Herrich-Sch\u00e4ffer, 1855), Stenoma catenifer Walsingham, 1912, Hofmannophila pseudospretella Stainton, 1849, Endrosis sarcitrella Linnaeus, 1758, Depressaria daucella Denis &amp; Schiffermuller, Depressaria apiella H\u00fcbner, 1801, Depressaria pastinacella Duponchel, 1838, Opisina arenosella Walker, 1864, Barea consignatella Walker, 1864, Barea confusella (Walker, 1864), Barea exarcha (Meyrick, 1883), Barea codrella Felder &amp; Rogenhofer, 1875, Borkhausenia nefrax Hodges, 1974, Eutorna phaulocosma Meyrick, 1906, Agonopterix alstroemeriana (Clerck, 1759), Agonopterix nervosa Haworth, 1812, Agonopterix umbellana Fabricius, 1794, Batia lunaris Haworth, 1829, Trachypepla indolescens Meyrick, 1927, Scythris inspersella (H\u00fcbner, 1817), Pyroderces argyrogrammos Zeller, 1847, Bifascioides leucomelanella (Rebel, 1917), Neomariania rebeli (Walsingham, 1894), Gisilia stereodoxa (Meyrick, 1925), Ascalenia acaciella Chr\u00e9tien, 1915, Ethmia bipunctella Fabricius, 1775, Ethmia nigroapicella Saalm\u00fcller, 1880, Ethmia terminella Fletcher, 1938, Ethmia submissa Busck, 1914, Oegoconia quadripuncta Haworth, 1829, Oegoconia novimundi Busck, 1915, Oegoconia caradjai Popescu-Gorj &amp; Capuse, 1965, Mompha trithalama Meyrick, 1922, Metopleura potosi Busck, 1912, Ornativalva erubescens (Walsingham, 1904), Pexicopia malvella (H\u00fcbner, 1805), Monochroa moyses Uffen, 1991, Monochroa fragariae (Busck, 1919), Monochroa niphognatha (Gozm\u00e1ny, 1953), Dichomeris vacciniella Busck, 1915, Dichomeris ligulella H\u00fcbner, 1818, Dichomeris picrocarpa (Meyrick, 1913), Dichomeris marginella (Fabricius, 1781), Anarsia lineatella Zeller, 1839, Ephysteris promptella (Staudinger, 1859), Bilobata subsecivella (Zeller, 1852), Aproaerema anthyllidella (H\u00fcbner, 1813), Anacampsis populella (Clerck, 1759), Anacampsis humilis Hodges, 1970, Recurvaria leucatella (Clerck, 1759), Recurvaria nanella (Denis &amp; Schifferm\u00fcller), 1775, Exoteleia dodecella (Linnaeus, 1758), Metzneria paucipunctella (Zeller, 1839), Anisoplaca cosmia Bradley, 1956, Sitotroga cerealella (Olivier, 1789), Scrobipalpa aptatella (Walker, 1864), Scrobipalpa obsoletella (Fischer von R\u00f6slerstamm, 1841), Scrobipalpa ocellatella (Boyd, 1858), Symmetrischema tangolias (Gyen, 1913), Symmetrischema capsica (Bradley &amp; Povoln\u00fd, 1965), Gelechia senticetella (Staudinger, 1859), Gelechia sabinellus (Zeller, 1839), Tecia solanivora (Povoln\u00fd, 1973), Platyedra subcinerea (Haworth, 1828), Aroga trialbamaculella (Chambers, 1875), Chrysoesthia sexguttella (Thunberg, 1794), Chrysoesthia drurella (Fabricius, 1775), Coleotechnites piceaella (Kearfott, 1903), Phthorimaea operculella (Zeller, 1873), Keiferia lycopersicella (Walsingham, 1897), Stenolechia bathrodyas Meyrick, 1935, Blastobasis phycidella Zeller, 1839, Blastobasis lacticolella Rebel, 1939, Blastobasis adustella Walsingham, 1894, Blastobasis tarda Meyrick, 1902, Blastobasis decolorella (Wollaston, 1858), Blastobasis maroccanella Amsel, 1952, Blastobasis vittata (Wollaston, 1858), Batrachedra amydraula Meyrick, 1916, Batrachedra knabi (Walsingham, 1909), Lepidoscia lainodes Meyrick, 1921, Kotochalia junodi (Heylaerts, 1890), Psyche casta (Pallas, 1767), Cebysa leucotelus Walker, 1854, Xylesthia pruniramiella Clemens, 1859, Psychoides filicivora (Meyrick, 1937), Praeacedes atomosella (Walker, 1863), Niditinea fuscella (Linnaeus, 1758), Haplotinea insectella (Fabricius, 1794), Haplotinea ditella (Pierce et al., 1938), Setomorpha rutella Zeller, 1852, Neurothaumasia ankerella (Mann, 1867), Nemapogon variatella (Clemens, 1859), Nemapogon granella (Linnaeus, 1758), Dryadaula terpsichorella (Busck, 1910), Dryadaula pactolia Meyrick, 1901, Opogona sacchari (Bojer, 1856), Opogona omoscopa (Meyrick, 1893), Opogona comptella (Walker, 1864), Opogona purpuriella Swezey, 1913, Erechthias minuscula (Walsingham, 1897), Trichophaga tapetzella (Linnaeus, 1758), Tineola bisselliella (Hummel, 1823), Monopis crocicapitella (Clemens, 1859), Monopis obviella (Denis &amp; Schiff., 1775), Monopis argillacea (Meyrick, 1893), Monopis ethelella (Newman, 1856), Tinea translucens Meyrick, 1917, Tinea dubiella Stainton, 1859, Tinea pallescentella Stainton, 1851, Tinea pellionella Linnaeus, 1758, Tinea murariella Staudinger, 1859, Tinea flavescentella Haworth, 1828, Lantanophaga pusillidactylus (Walker, 1864), Megalorhipida leucodactylus (Fabricius, 1794), Emmelina monodactyla (Linnaeus, 1758), Platyptilia carduidactylus (Riley, 1869), Amblyptilia pica (Walsingham, 1880), Nippoptilia vitis (Sasaki, 1913), Stenoptilodes brevipennis (Zeller, 1874), Incurvaria flavimitrella (H\u00fcbner), Heliozela catoptrias Meyrick, 1897, Coptodisca juglandella (Chambers, 1874), Agrius convolvuli Linnaeus, 1758, Hippotion celerio Linnaeus, 1758, Daphnis nerii Linnaeus, 1758, Theretra oldenlandiae Fabricius, 1775, Theretra latreillii MacLeay, Hyles euphorbiae Linnaeus, 1758, Cephonodes hylas Linnaeus, 1771, Manduca quinquemaculatus Haworth, 1803, Erinnyis ello Linnaeus, 1758, Deilephila elpenor Linnaeus, 1758, Samia cynthia Drury, 1773, Antheraea pernyi Gu\u00e9rin-M\u00e9neville, 1855, Antheraea yamamai Gu\u00e9rin-M\u00e9neville, 1861, Antheraea polyphemus Cramer, 1775, Antheraea paphia Linnaeus, 1758, Hylesia nigricans Berg, 1875, Copaxa lavendera Westwood, 1853, Saturnia pyri (Denis &amp; Schifferm\u00fcller), 1775, Bombyx mori Linnaeus, 1758, Epermenia aequidentellus (Hofmann, 1867), Apomyelois ceratoniae (Zeller, 1839), Doloessa viridis Zeller, 1848, Epimorius testaceellus Ragonot, 1887, Etiella zinckenella (Treitschke, 1832), Cactoblastis cactorum (Berg, 1885), Anypsipyla univitella Dyar, 1914, Achroia grisella (Fabricius, 1794), Hypsopygia costalis Fabricius, 1775, Moodna bisinuella Hampson, 1901, Eccopisa effractella Zeller, 1848, Arenipses sabella Hampson, 1901, Citripestis sagittiferella Moore, 1891, Maliarpha separatella Ragonot, 1888, Pyralis farinalis Linnaeus, 1758, Cryptoblabes gnidiella Milli\u00e8re, 1867, Amyelois transitella Walker, 1863, Plodia interpunctella (H\u00fcbner, 1813), Eldana saccharina Walker, 1865, Bema neuricella Zeller, 1848, Lipographis subosseella Hulst, 1892, Hypsipyla grandella Zeller, 1848, Sciota adelphella Fischer von R\u00f6slerstamm, 1836, Cadra cautella (Walker, 1863), Cadra figulilella (Gregson, 1871), Cadra calidella Guen\u00e9e, 1845, Gauna aegusalis Walker, 1859, Acrobasis nuxvorella Neunzig, 1970, Acrobasis vaccinii Riley, 1884, Phycita diaphana Staudinger, 1870, Euzophera batangensis Caradja, 1939)'  ] }   The dataset includes 2606222 records from 2271 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008965-250310093411724/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.cda3ch"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.cda3ch", "name": "item", "description": "10.15468/dl.cda3ch", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.cda3ch"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.15468/dl.f97tke", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2024-03-25", "title": "Occurrence Download", "description": "A dataset containing 19 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Impatiens luteoviridis H.Perrier'  ] }   The dataset includes 19 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0026642-240321170329656/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.f97tke"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.f97tke", "name": "item", "description": "10.15468/dl.f97tke", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.f97tke"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.15468/dl.cc4i6e", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2019-12-25", "title": "Occurrence Download", "description": "A dataset containing 933 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Achnatherum sibiricum (L.) Keng ex Tzvelev'  ] }   The dataset includes 933 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0029397-191105090559680/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.cc4i6e"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.cc4i6e", "name": "item", "description": "10.15468/dl.cc4i6e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.cc4i6e"}, {"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": "10.15468/dl.ce7vd9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2022-08-23", "title": "Occurrence Download", "description": "A dataset containing 476 species occurrences available in GBIF matching the query: {  'and' : [  'HasCoordinate is true',  'HasGeospatialIssue is false',  'TaxonKey is Arctocephalus galapagoensis Heller, 1904'  ] }   The dataset includes 476 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0430032-210914110416597/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.ce7vd9"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.ce7vd9", "name": "item", "description": "10.15468/dl.ce7vd9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.ce7vd9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.15468/dl.cvm3yw", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2022-07-14", "title": "Occurrence Download", "description": "A dataset containing 3321 species occurrences available in GBIF matching the query: {  'and' : [  'BasisOfRecord is Specimen',  'Geometry POLYGON((-162.71521 -1.38196,-0.01100 -1.38196,-0.01100 63.67187,-162.71521 63.67187,-162.71521 -1.38196))',  'HasCoordinate is true',  'HasGeospatialIssue is false',  'OccurrenceStatus is Present',  'TaxonKey is Schizachyrium scoparium (Michx.) Nash'  ] }   The dataset includes 3321 records from 121 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0389598-210914110416597/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.cvm3yw"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.cvm3yw", "name": "item", "description": "10.15468/dl.cvm3yw", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.cvm3yw"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.15468/dl.dd25sm", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2020-12-12", "title": "Occurrence Download", "description": "A dataset containing 0 species occurrences available in GBIF matching the query: {  'and' : [  'HasCoordinate is true',  'BasisOfRecord is Human Observation',  'InstitutionCode is one of (CLO, iNaturalist)',  'Year is greater than or equal to 2010',  'Geometry MULTIPOLYGON (((-123.2789 44.9665, -123.2789 44.96745, -123.2759 44.96744, -123.2759 44.96999, -123.2687 44.96995, -123.2686 44.97719, -123.2685 44.98357, -123.2644 44.98355, -123.2643 44.98405, -123.2645 44.98405, -123.2645 44.98396, -123.2648 44.98396, -123.2645 44.98631, -123.2645 44.98632, -123.2645 44.98651, -123.2645 44.98671, -123.2644 44.9869, -123.2644 44.98709, -123.2643 44.98728, -123.2642 44.98746, -123.2641 44.98763, -123.2633 44.98903, -123.257 44.98896, -123.257 44.99064, -123.2535 44.99063, -123.2536 44.98351, -123.2467 44.98348, -123.2467 44.98294, -123.2441 44.98294, -123.2441 44.98348, -123.235 44.98346, -123.235 44.981, -123.235 44.97958, -123.235 44.9783, -123.2452 44.97834, -123.2452 44.97014, -123.2452 44.96987, -123.2452 44.95548, -123.2455 44.95548, -123.2455 44.95199, -123.2455 44.94347, -123.2502 44.9437, -123.2503 44.9437, -123.2503 44.94072, -123.2555 44.94366, -123.2663 44.9499, -123.2664 44.94987, -123.271 44.95252, -123.271 44.95263, -123.2763 44.9557, -123.2767 44.95595, -123.2783 44.95681, -123.2788 44.9572, -123.2795 44.95746, -123.2807 44.95814, -123.281 44.95831, -123.281 44.95929, -123.279 44.9593, -123.279 44.96245, -123.2792 44.96245, -123.2792 44.96404, -123.2789 44.96404, -123.2789 44.9665), (-123.2789 44.9665, -123.2698 44.9665, -123.2634 44.96649, -123.2698 44.9665, -123.2789 44.9665), (-123.2543 44.96989, -123.2542 44.96168, -123.2573 44.96169, -123.2542 44.96168, -123.2543 44.96989, -123.2469 44.96988, -123.2543 44.96989)))'  ] }   The dataset includes 0 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0134955-200613084148143/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.dd25sm"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.dd25sm", "name": "item", "description": "10.15468/dl.dd25sm", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.dd25sm"}, {"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": "10.15468/dl.exmdqz", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2024-10-04", "title": "Occurrence Download", "description": "A dataset containing 12557 species occurrences available in GBIF matching the query: {  'DatasetKey' : [  'is Herbarium of Karaganda Buketov University (QAR)'  ] }   The dataset includes 12557 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0040459-240906103802322/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.exmdqz"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.exmdqz", "name": "item", "description": "10.15468/dl.exmdqz", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.exmdqz"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.15468/dl.f62hpf", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2016-04-16", "title": "Occurrence Download", "description": "A dataset containing 2 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Spintherobolus ankoseion Weitzman &amp; Malabarba, 1999'  ] }   The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010584-160311141623029/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.f62hpf"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.f62hpf", "name": "item", "description": "10.15468/dl.f62hpf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.f62hpf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.15468/dl.fju8qd", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2024-09-09", "title": "Occurrence Download", "description": "A dataset containing 1374932 species occurrences available in GBIF matching the query: {  'and' : [  'OccurrenceStatus is Present',  'TaxonKey is Rutilus rutilus (Linnaeus, 1758)'  ] }   The dataset includes 1374932 records from 671 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006972-240906103802322/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.fju8qd"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.fju8qd", "name": "item", "description": "10.15468/dl.fju8qd", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.fju8qd"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.15468/dl.fvxk7e", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2021-05-03", "title": "Occurrence Download", "description": "A dataset containing 19720 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Cyperus rotundus L.'  ] }   The dataset includes 19720 records from 526 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0266278-200613084148143/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "13. Climate action", "species occurrences", "15. Life on land", "6. Clean water", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.fvxk7e"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.fvxk7e", "name": "item", "description": "10.15468/dl.fvxk7e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.fvxk7e"}, {"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": "10.15468/dl.g77puz", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2021-07-19", "title": "Occurrence Download", "description": "A dataset containing 367 species occurrences available in GBIF matching the query: {  'and' : [  'HasCoordinate is true',  'HasGeospatialIssue is false',  'OccurrenceStatus is Present',  'TaxonKey is Lomatia hirsuta (Lam.) Diels'  ] }   The dataset includes 367 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0326563-200613084148143/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.g77puz"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.g77puz", "name": "item", "description": "10.15468/dl.g77puz", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.g77puz"}, {"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": "10.15468/dl.h5umcx", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2023-07-24", "title": "Occurrence Download", "description": "A dataset containing 36 species occurrences available in GBIF matching the query: {  'and' : [  'Continent is North America',  'Country is Mexico',  'OccurrenceStatus is Present',  'TaxonKey is Bison bison (Linnaeus, 1758)',  'Year 2017-2023'  ] }   The dataset includes 36 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111010-230530130749713/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.h5umcx"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.h5umcx", "name": "item", "description": "10.15468/dl.h5umcx", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.h5umcx"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.15468/dl.hbhzep", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2022-05-18", "title": "Occurrence Download", "description": "A dataset containing 2 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Atractus insipidus Roze, 1961'  ] }   The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0289279-210914110416597/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.hbhzep"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.hbhzep", "name": "item", "description": "10.15468/dl.hbhzep", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.hbhzep"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.15468/dl.hm0mn5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2018-09-18", "title": "Occurrence Download", "description": "A dataset containing 54 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Zygaspis violacea (Peters, 1854)'  ] }   The dataset includes 54 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0013275-180824113759888/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.hm0mn5"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.hm0mn5", "name": "item", "description": "10.15468/dl.hm0mn5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.hm0mn5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.15468/dl.ie9pa5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2016-04-12", "title": "Occurrence Download", "description": "A dataset containing 19 species occurrences available in GBIF matching the query: {  'and' : [  'TaxonKey is Lepidaploa arborescens (L.) H.Rob.',  'HasGeospatialIssue is false',  'HasCoordinate is true'  ] }   The dataset includes 19 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009342-160311141623029/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.ie9pa5"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.ie9pa5", "name": "item", "description": "10.15468/dl.ie9pa5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.ie9pa5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.15468/dl.jfmyhu", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2018-07-28", "title": "Occurrence Download", "description": "A dataset containing 9895 species occurrences available in GBIF matching the query: {  'and' : [  'TaxonKey is Cenchrus clandestinus (Hochst. ex Chiov.) Morrone',  'HasCoordinate is TRUE'  ] }   The dataset includes 9895 records from 103 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0049801-180508205500799/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.jfmyhu"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.jfmyhu", "name": "item", "description": "10.15468/dl.jfmyhu", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.jfmyhu"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.15468/dl.jhc6ev", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2025-08-07", "title": "Occurrence Download", "description": "A dataset containing 0 species occurrences available in GBIF matching the query: {  'and' : [  'TaxonKey is one of (Pyrrhula waterstradti)',  'HasCoordinate is true',  'OccurrenceStatus is Present',  'License is one of (CC-BY 4.0, CC0 1.0)'  ] }   The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025490-250802193616735/datasets/export for details.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.jhc6ev"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.jhc6ev", "name": "item", "description": "10.15468/dl.jhc6ev", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.jhc6ev"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.15468/dl.k697p8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2020-11-11", "title": "Occurrence Download", "description": "A dataset containing 110 species occurrences available in GBIF matching the query: {  'CatalogNumber' : [  'is 217880'  ] }   The dataset includes 110 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0108887-200613084148143/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.k697p8"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.k697p8", "name": "item", "description": "10.15468/dl.k697p8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.k697p8"}, {"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": "10.15468/dl.kknsxm", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2022-10-06", "title": "Occurrence Download", "description": "A dataset containing 0 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Spryginia winkleri subsp. araneosa Botsch.'  ] }   The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054736-220831081235567/datasets/export for details.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.kknsxm"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.kknsxm", "name": "item", "description": "10.15468/dl.kknsxm", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.kknsxm"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.15468/dl.kqzqm5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2024-10-08", "title": "Occurrence Download", "description": "A dataset containing 2656 species occurrences available in GBIF matching the query: {  'and' : [  'HasGeospatialIssue is false',  'OccurrenceStatus is Present',  {  'not' : {  'DatasetKey' : [  'is Global database of alien macrofungi'  ]  }  },  'TaxonKey is Polyporus varius Pers.'  ] }   The dataset includes 2656 records from 71 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0001784-241007104925546/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.kqzqm5"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.kqzqm5", "name": "item", "description": "10.15468/dl.kqzqm5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.kqzqm5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.15468/dl.ku58jm", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2021-06-10", "title": "Occurrence Download", "description": "A dataset containing 1062 species occurrences available in GBIF matching the query: {  'and' : [  'BasisOfRecord is Human Observation',  'Continent is South America',  'OccurrenceStatus is Present',  {  'or' : [  'TaxonKey is Vireo olivaceus (Linnaeus, 1766)',  'TaxonKey is Dacnis cayana (Linnaeus, 1766)'  ]  }  ] }   The dataset includes 1062 records from 73 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0299091-200613084148143/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.ku58jm"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.ku58jm", "name": "item", "description": "10.15468/dl.ku58jm", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.ku58jm"}, {"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": "10.15468/dl.lxp6t4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2020-02-03", "title": "Occurrence Download", "description": "A dataset containing 4124 species occurrences available in GBIF matching the query: {  'and' : [  'DatasetKey is iNaturalist Research-grade Observations',  'TaxonKey is Urocyon cinereoargenteus (Schreber, 1775)'  ] }   The dataset includes 4124 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003813-200127171203522/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.lxp6t4"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.lxp6t4", "name": "item", "description": "10.15468/dl.lxp6t4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.lxp6t4"}, {"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": "10.15468/dl.m7yc6w", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2025-08-25", "title": "Occurrence Download", "description": "A dataset listing the 1 species recorded in GBIF matching the query: {  'and' : [  'Country is Brazil',  'Geometry POLYGON((-62.75178 -0.54698,-60.91887 -0.54698,-60.91887 1.10712,-62.75178 1.10712,-62.75178 -0.54698))',  'HasCoordinate is true',  'HasGeospatialIssue is false',  'OccurrenceStatus is Present',  'TaxonKey is Platyrrhinus lineatus'  ] }   The dataset's 1 records were derived from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042653-250811113504898/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.m7yc6w"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.m7yc6w", "name": "item", "description": "10.15468/dl.m7yc6w", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.m7yc6w"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.15468/dl.mbyfsz", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2022-02-03", "title": "Occurrence Download", "description": "A dataset containing 4743 species occurrences available in GBIF matching the query: {  'and' : [  {  'or' : [  'Country is United Kingdom of Great Britain and Northern Ireland',  'Country is Ireland'  ]  },  'TaxonKey is Cetorhinus maximus (Gunnerus, 1765)',  'Year 2000-2022'  ] }   The dataset includes 4743 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0121344-210914110416597/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "14. Life underwater", "15. Life on land", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.mbyfsz"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.mbyfsz", "name": "item", "description": "10.15468/dl.mbyfsz", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.mbyfsz"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.15468/dl.mqnbhe", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2015-10-31", "title": "Occurrence Download", "description": "A dataset containing 1 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Xyleborus procer Eichhoff, 1878'  ] }   The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005457-151016162008034/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.mqnbhe"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.mqnbhe", "name": "item", "description": "10.15468/dl.mqnbhe", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.mqnbhe"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-01T00:00:00Z"}}, {"id": "10.15468/dl.mueawq", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2023-07-10", "title": "Occurrence Download", "description": "A dataset containing 507 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Meriania nobilis Triana'  ] }   The dataset includes 507 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0078887-230530130749713/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.mueawq"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.mueawq", "name": "item", "description": "10.15468/dl.mueawq", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.mueawq"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.15468/dl.myve0z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:18Z", "type": "Dataset", "created": "2018-11-30", "title": "Occurrence Download", "description": "A dataset containing 434456 species occurrences available in GBIF matching the query: {  'and' : [  'HasCoordinate is true',  'TaxonKey is Sphingidae',  'HasGeospatialIssue is false'  ] }   The dataset includes 434456 records from 577 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011467-181108115102211/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "15. Life on land", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.myve0z"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.myve0z", "name": "item", "description": "10.15468/dl.myve0z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.myve0z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.15468/dl.n2d9v9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2023-02-07", "title": "Occurrence Download", "description": "A dataset containing 17 species occurrences available in GBIF matching the query: {  'and' : [  'Geometry POLYGON((63.84022 17.44976,109.66194 17.44976,109.66194 35.78884,63.84022 35.78884,63.84022 17.44976))',  'HasCoordinate is true',  'HasGeospatialIssue is false',  'OccurrenceStatus is Present',  'TaxonKey is Torreya grandis Fortune ex Lindl.'  ] }   The dataset includes 17 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0274874-220831081235567/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.n2d9v9"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.n2d9v9", "name": "item", "description": "10.15468/dl.n2d9v9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.n2d9v9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.15468/dl.nqpc3m", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2024-03-06", "title": "Occurrence Download", "description": "A dataset containing 1361 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Pterocarpus macrocarpus Kurz'  ] }   The dataset includes 1361 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0025939-240229165702484/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.nqpc3m"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.nqpc3m", "name": "item", "description": "10.15468/dl.nqpc3m", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.nqpc3m"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.15468/dl.nuuzj7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2023-03-09", "title": "Occurrence Download", "description": "A dataset containing 15 species occurrences available in GBIF matching the query: {  'and' : [  'TaxonKey is one of (Archboldomys maximus Balete, Rickart, Heaney, Alviola, M.V.Duya, M.R.M.Duya, Sosa &amp; Jansa, 2012)',  'BasisOfRecord is one of (Specimen, Human Observation, Observation, Machine Observation)',  'HasCoordinate is true',  'HasGeospatialIssue is false'  ] }   The dataset includes 15 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0065997-230224095556074/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.nuuzj7"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.nuuzj7", "name": "item", "description": "10.15468/dl.nuuzj7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.nuuzj7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.15468/dl.o7zo50", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2020-04-07", "title": "Occurrence Download", "description": "A dataset containing 89 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Lophostoma evotis (Davis &amp; Carter, 1978)'  ] }   The dataset includes 89 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036944-200221144449610/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.o7zo50"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.o7zo50", "name": "item", "description": "10.15468/dl.o7zo50", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.o7zo50"}, {"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": "10.15468/dl.odlm44", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2016-09-23", "title": "Occurrence Download", "description": "A dataset containing 24 species occurrences available in GBIF matching the query: {  'DatasetKey' : [  'is (Table 6) Distribution of Pleistocene to late Pliocene nannofossils in ODP Hole 108-660A'  ] }   The dataset includes 24 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010362-160910150852091/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.odlm44"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.odlm44", "name": "item", "description": "10.15468/dl.odlm44", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.odlm44"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.15468/dl.p1elvj", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2018-11-28", "title": "Occurrence Download", "description": "A dataset containing 1168 species occurrences available in GBIF matching the query: {  'and' : [  'Country is Japan',  'TaxonKey is Rotala L.'  ] }   The dataset includes 1168 records from 42 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010409-181108115102211/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.p1elvj"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.p1elvj", "name": "item", "description": "10.15468/dl.p1elvj", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.p1elvj"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.15468/dl.q9pmwe", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-24T16:19:19Z", "type": "Dataset", "created": "2022-10-06", "title": "Occurrence Download", "description": "A dataset containing 98 species occurrences available in GBIF matching the query: {  'TaxonKey' : [  'is Scartichthys viridis (Valenciennes, 1836)'  ] }   The dataset includes 98 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0056608-220831081235567/datasets/export for details.   Data from some individual datasets included in this download may be licensed under less restrictive terms.", "keywords": ["GBIF", "species occurrences", "biodiversity"], "contacts": [{"organization": "GBIF.Org User", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15468/dl.q9pmwe"}, {"rel": "self", "type": "application/geo+json", "title": "10.15468/dl.q9pmwe", "name": "item", "description": "10.15468/dl.q9pmwe", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15468/dl.q9pmwe"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=gb&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=gb&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=gb&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=gb&offset=50", "hreflang": "en-US"}], "numberMatched": 1220, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-05-25T02:11:13.488402Z"}