{"type": "FeatureCollection", "features": [{"id": "10.1016/b978-0-444-64177-9.00006-0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:15:34Z", "type": "Report", "created": "2020-04-16", "title": "SfM photogrammetry for GeoArchaeology", "description": "Geoarchaeological studies have benefits from new technological developments in remote-sensing technologies that have become an integral and important part of the archeological researches. In particular, structure-from-motion (SfM) photogrammetry is one of the most successful emerging techniques in high-resolution topography (HRT) and provides exceptionally fast, low-cost, and easy three-dimensional (3D) survey for geoscience applications. In this chapter, we present an example of SfM application for geoarchaeology. The purpose is to realize HRT digital terrain models (DTMs) of an area of prehistoric agricultural terracing together with a geoarchaeological excavation trench in the Ingram Valley, Northumberland National Park, NE England. The study area is one of the six pilot case studies of TerrACE archeological research project (ERC-2017-ADG: 787790, 2018\u20132023; https://www.terrace.no/), a 5-year European Research Council grant funded by the European Union. An integrated approach utilizing ground-based and UAV (nadir and oblique) images was used to preserve fine-grained topographic detail and permit the accurate survey of highly vegetated areas and steep or subvertical surfaces (e.g., vertical walls of terraces), while also allowing for the capture of large spatial datasets. The SfM-DTM provided an accurate and high level of detail of the terrace landscape, the archeological features, and the soil and sediment stratigraphy along the excavation trench. An additional terrace was identified that had not been recognized before due to the HRT study bringing out a level of detail that had not been previously observable in this area. The SfM 3D outputs allowed the extraction of profiles, sections, scaled plans, and orthomosaics of the terrace complex and the excavation trench, simplifying and speeding the archeologist's field and laboratory work. SfM has shown it to be a rapid, cost effective, and highly accurate technique for surveying archeological sites at both a landscape and localized scale and adding new and more accurate information in nationally important landscapes and beyond.", "keywords": ["Archeological sites; Digital terrain models; Prehistoric agricultural terraces; Structure from motion; TerrACE project; Unmanned aerial vehicles", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.1016/b978-0-444-64177-9.00006-0"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/b978-0-444-64177-9.00006-0", "name": "item", "description": "10.1016/b978-0-444-64177-9.00006-0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/b978-0-444-64177-9.00006-0"}, {"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": "10.1071/sr13043", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:19:07Z", "type": "Journal Article", "created": "2013-12-20", "title": "Impact Of Carbon Farming Practices On Soil Carbon In Northern New South Wales", "description": "<p>This study sought to quantify the influence of \uffe2\uff80\uff98carbon farming\uffe2\uff80\uff99 practices on soil carbon stocks, in comparison with conventional grazing and cropping, in northern New South Wales. The study had two components: assessment of impacts of organic amendments on soil carbon and biological indicators in croplands on Vertosols of the Liverpool Plains; and assessment of the impact of grazing management on soil carbon in Chromosols of the Northern Tablelands. The organic amendment sites identified for the survey had been treated with manures, composts, or microbial treatments, while the conventional management sites had received only chemical fertilisers. The rotational grazing sites had been managed so that grazing was restricted to short periods of several days, followed by long rest periods (generally several months) governed by pasture growth. These were compared with sites that were grazed continuously. No differences in total soil carbon stock, or soil carbon fractions, were observed between sites treated with organic amendments and those treated with chemical fertiliser. There was some evidence of increased soil carbon stock under rotational compared with continuous grazing, but the difference was not statistically significant. Similarly, double-stranded DNA (dsDNA) stocks were not significantly different in either of the management contrasts, but tended to show higher values in organic treatments and rotational grazing. The enzymatic activities of \uffce\uffb2-glucosidase and leucine-aminopeptidase were significantly higher in rotational than continuous grazing but statistically similar for the cropping site treatments. Relative abundance and community structure, measured on a subset of the cropping sites, showed a higher bacteria\uffe2\uff80\uff89:\uffe2\uff80\uff89fungi ratio and provided evidence that microbial process rates were significantly higher in chemically fertilised sites than organic amendment sites, suggesting enhanced mineralisation of organic matter under conventional management. The higher enzyme activity and indication of greater efficiency of microbial populations on carbon farming sites suggests a greater potential to build soil carbon under these practices. Further research is required to investigate whether the indicative trends observed reflect real effects of management.</p>", "keywords": ["2. Zero hunger", "Land Capability and Soil Degradation", "550", "XXXXXX - Unknown", "0401 agriculture", " forestry", " and fisheries", "Carbon Sequestration Science", "04 agricultural and veterinary sciences", "15. Life on land", "Land capability and soil productivity"]}, "links": [{"href": "https://doi.org/10.1071/sr13043"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1071/sr13043", "name": "item", "description": "10.1071/sr13043", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1071/sr13043"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-01-01T00:00:00Z"}}, {"id": "10.1111/gcb.12819", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:19:55Z", "type": "Journal Article", "created": "2014-12-05", "title": "Soil Warming And Co2 Enrichment Induce Biomass Shifts In Alpine Tree Line Vegetation", "description": "Abstract<p>Responses of alpine tree line ecosystems to increasing atmospheric CO2 concentrations and global warming are poorly understood. We used an experiment at the Swiss tree line to investigate changes in vegetation biomass after 9\uffc2\uffa0years of free air CO2 enrichment (+200\uffc2\uffa0ppm; 2001\uffe2\uff80\uff932009) and 6\uffc2\uffa0years of soil warming (+4\uffc2\uffa0\uffc2\uffb0C; 2007\uffe2\uff80\uff932012). The study contained two key tree line species, Larix decidua and Pinus uncinata, both approximately 40\uffc2\uffa0years old, growing in heath vegetation dominated by dwarf shrubs. In 2012, we harvested and measured biomass of all trees (including root systems), above\uffe2\uff80\uff90ground understorey vegetation and fine roots. Overall, soil warming had clearer effects on plant biomass than CO2 enrichment, and there were no interactive effects between treatments. Total plant biomass increased in warmed plots containing Pinus but not in those with Larix. This response was driven by changes in tree mass (+50%), which contributed an average of 84% (5.7\uffc2\uffa0kg\uffc2\uffa0m\uffe2\uff88\uff922) of total plant mass. Pinus coarse root mass was especially enhanced by warming (+100%), yielding an increased root mass fraction. Elevated CO2 led to an increased relative growth rate of Larix stem basal area but no change in the final biomass of either tree species. Total understorey above\uffe2\uff80\uff90ground mass was not altered by soil warming or elevated CO2. However, Vaccinium myrtillus mass increased with both treatments, graminoid mass declined with warming, and forb and nonvascular plant (moss and lichen) mass decreased with both treatments. Fine roots showed a substantial reduction under soil warming (\uffe2\uff88\uff9240% for all roots &lt;2\uffc2\uffa0mm in diameter at 0\uffe2\uff80\uff9320\uffc2\uffa0cm soil depth) but no change with CO2 enrichment. Our findings suggest that enhanced overall productivity and shifts in biomass allocation will occur at the tree line, particularly with global warming. However, individual species and functional groups will respond differently to these environmental changes, with consequences for ecosystem structure and functioning.</p>", "keywords": ["0106 biological sciences", "2. Zero hunger", "Models", " Statistical", "Temperature", "Larix", "Carbon Dioxide", "15. Life on land", "Pinus", "Global Warming", "01 natural sciences", "Soil", "Species Specificity", "13. Climate action", "Biomass", "Tundra", "Switzerland"]}, "links": [{"href": "https://doi.org/10.1111/gcb.12819"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.12819", "name": "item", "description": "10.1111/gcb.12819", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.12819"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-30T00:00:00Z"}}, {"id": "10.1111/gcbb.12255", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:20:00Z", "type": "Journal Article", "created": "2015-02-19", "title": "Bioenergy Harvest, Climate Change, And Forest Carbon In The Oregon Coast Range", "description": "Abstract<p>Forests provide important ecological, economic, and social services, and recent interest has emerged in the potential for using residue from timber harvest as a source of renewable woody bioenergy. The long\uffe2\uff80\uff90term consequences of such intensive harvest are unclear, particularly as forests face novel climatic conditions over the next century. We used a simulation model to project the long\uffe2\uff80\uff90term effects of management and climate change on above\uffe2\uff80\uff90 and belowground forest carbon storage in a watershed in northwestern Oregon. The multi\uffe2\uff80\uff90ownership watershed has a diverse range of current management practices, including little\uffe2\uff80\uff90to\uffe2\uff80\uff90no harvesting on federal lands, short\uffe2\uff80\uff90rotation clear\uffe2\uff80\uff90cutting on industrial land, and a mix of practices on private nonindustrial land. We simulated multiple management scenarios, varying the rate and intensity of harvest, combined with projections of climate change. Our simulations project a wide range of total ecosystem carbon storage with varying harvest rate, ranging from a 45% increase to a 16% decrease in carbon compared to current levels. Increasing the intensity of harvest for bioenergy caused a 2\uffe2\uff80\uff933% decrease in ecosystem carbon relative to conventional harvest practices. Soil carbon was relatively insensitive to harvest rotation and intensity, and accumulated slowly regardless of harvest regime. Climate change reduced carbon accumulation in soil and detrital pools due to increasing heterotrophic respiration, and had small but variable effects on aboveground live carbon and total ecosystem carbon. Overall, we conclude that current levels of ecosystem carbon storage are maintained in part due to substantial portions of the landscape (federal and some private lands) remaining unharvested or lightly managed.\uffc2\uffa0Increasing the intensity of harvest for bioenergy on currently harvested land, however,\uffc2\uffa0led to a relatively small reduction in the ability of forests to store carbon. Climate change is unlikely to substantially alter carbon storage in these forests, absent shifts in disturbance regimes.</p>", "keywords": ["0106 biological sciences", "Carbon dioxide mitigation", "Forest ecology -- Oregon -- Oregon Coast Range", "Forest biomass", "13. Climate action", "Carbon cycle (Biogeochemistry)", "Biomass energy", "Forest Biology", "15. Life on land", "01 natural sciences", "7. Clean energy", "Climatic change", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1111/gcbb.12255"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/GCB%20Bioenergy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcbb.12255", "name": "item", "description": "10.1111/gcbb.12255", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcbb.12255"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-05-25T00:00:00Z"}}, {"id": "10.1128/aem.02264-23", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:20:30Z", "type": "Journal Article", "created": "2024-02-19", "title": "Novel endolithic bacteria of phylum             Chloroflexota             reveal a myriad of potential survival strategies in the Antarctic desert", "description": "ABSTRACT                                     <p>               The ice-free McMurdo Dry Valleys of Antarctica are dominated by nutrient-poor mineral soil and rocky outcrops. The principal habitat for microorganisms is within rocks (endolithic). In this environment, microorganisms are provided with protection against sub-zero temperatures, rapid thermal fluctuations, extreme dryness, and ultraviolet and solar radiation. Endolithic communities include lichen, algae, fungi, and a diverse array of bacteria.               Chloroflexota               is among the most abundant bacterial phyla present in these communities. Among the               Chloroflexota               are four novel classes of bacteria, here named               Candidatus               Spiritibacteria class. nov. (=UBA5177),               Candidatus               Martimicrobia class. nov. (=UBA4733),               Candidatus               Tarhunnaeia class. nov. (=UBA6077), and               Candidatus               Uliximicrobia class. nov. (=UBA2235). We retrieved 17 high-quality metagenome-assembled genomes (MAGs) that represent these four classes. Based on genome predictions, all these bacteria are inferred to be aerobic heterotrophs that encode enzymes for the catabolism of diverse sugars. These and other organic substrates are likely derived from lichen, algae, and fungi, as metabolites (including photosynthate), cell wall components, and extracellular matrix components. The majority of MAGs encode the capacity for trace gas oxidation using high-affinity uptake hydrogenases, which could provide energy and metabolic water required for survival and persistence. Furthermore, some MAGs encode the capacity to couple the energy generated from H               2               and CO oxidation to support carbon fixation (atmospheric chemosynthesis). All encode mechanisms for the detoxification and efflux of heavy metals. Certain MAGs encode features that indicate possible interactions with other organisms, such as Tc-type toxin complexes, hemolysins, and macroglobulins.             </p>                            IMPORTANCE               <p>                 The ice-free McMurdo Dry Valleys of Antarctica are the coldest and most hyperarid desert on Earth. It is, therefore, the closest analog to the surface of the planet Mars. Bacteria and other microorganisms survive by inhabiting airspaces within rocks (endolithic). We identify four novel classes of phylum                 Chloroflexota                 , and, based on interrogation of 17 metagenome-assembled genomes, we predict specific metabolic and physiological adaptations that facilitate the survival of these bacteria in this harsh environment\uffe2\uff80\uff94including oxidation of trace gases and the utilization of nutrients (including sugars) derived from lichen, algae, and fungi. We propose that such adaptations allow these endolithic bacteria to eke out an existence in this cold and extremely dry habitat.               </p>", "keywords": ["570", "Bacteria", "Fungi", "Antarctic Regions", "Chloroflexi", "15. Life on land", "Survival strategies", "Cold Temperature", "Extremophiles", "13. Climate action", "Antarctica", "Endolithic communities", "Metagenomics", "14. Life underwater", "Sugars", "Settore BIO/19 - MICROBIOLOGIA GENERALE"]}, "links": [{"href": "https://doi.org/10.1128/aem.02264-23"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.02264-23", "name": "item", "description": "10.1128/aem.02264-23", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.02264-23"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-19T00:00:00Z"}}, {"id": "10.1186/s12302-025-01141-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:20:42Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract                        Background             <p>Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.</p>                                   Results             <p>The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.</p>                                   Conclusions             <p>The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.</p>", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1186/s12302-025-01141-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s12302-025-01141-6", "name": "item", "description": "10.1186/s12302-025-01141-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s12302-025-01141-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10138/578894", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:26:43Z", "type": "Journal Article", "created": "2024-05-31", "title": "Comparison between lower-cost and conventional eddy covariance setups for CO2 and evapotranspiration measurements above monocropping and agroforestry systems", "description": "Open AccessPeer reviewed", "keywords": ["Physical sciences", "Evapotranspiration", "Lower-cost eddy covariance", "Carbon dioxide flux", "Agroforestry", "Gas analyzer"]}, "links": [{"href": "https://doi.org/10138/578894"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10138/578894", "name": "item", "description": "10138/578894", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10138/578894"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-01T00:00:00Z"}}, {"id": "10.2139/ssrn.4556085", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:21:56Z", "type": "Journal Article", "created": "2023-08-29", "title": "A Laser Diffractometry Technique for Determining the Soil Water Stable Aggregates Index", "description": "Open AccessPeer reviewed", "keywords": ["Water stable aggregates index", "Laser diffractometry", "Wet sieving", "Soil aggregates"]}, "links": [{"href": "https://doi.org/10.2139/ssrn.4556085"}, {"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": "10.2139/ssrn.4556085", "name": "item", "description": "10.2139/ssrn.4556085", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.4556085"}, {"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": "10.3390/toxins11100550", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:22:48Z", "type": "Journal Article", "created": "2019-09-20", "title": "Graphene-Based Sensing Platform for On-Chip Ochratoxin A Detection", "description": "<p>In this work, we report an on-chip aptasensor for ochratoxin A (OTA) toxin detection that is based on a graphene field-effect transistor (GFET). Graphene-based devices are fabricated via large-scale technology, allowing for upscaling the sensor fabrication and lowering the device cost. The sensor assembly was performed through covalent bonding of graphene\uffe2\uff80\uff99s surface with an aptamer specifically sensitive towards OTA. The results demonstrate fast (within 5 min) response to OTA exposure with a linear range of detection between 4 ng/mL and 10 pg/mL, with a detection limit of 4 pg/mL. The regeneration time constant of the sensor was found to be rather small, only 5.6 s, meaning fast sensor regeneration for multiple usages. The high reproducibility of the sensing response was demonstrated via using several recycling procedures as well as various GFETs. The applicability of the aptasensor to real samples was demonstrated for spiked red wine samples with recovery of about 105% for a 100 pM OTA concentration; the selectivity of the sensor was also confirmed via addition of another toxin, zearalenone. The developed platform opens the way for multiplex sensing of different toxins using an on-chip array of graphene sensors.</p>", "keywords": ["Communication", "graphene", "R", "aptamer", "Biosensing Techniques", "02 engineering and technology", "Aptamers", " Nucleotide", "Ochratoxins", "01 natural sciences", "7. Clean energy", "0104 chemical sciences", "12. Responsible consumption", "on-chip", "sensor", "Limit of Detection", "transistor", "Medicine", "Graphite", "0210 nano-technology", "ochratoxin A"]}, "links": [{"href": "https://www.mdpi.com/2072-6651/11/10/550/pdf"}, {"href": "https://doi.org/10.3390/toxins11100550"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Toxins", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/toxins11100550", "name": "item", "description": "10.3390/toxins11100550", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/toxins11100550"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-20T00:00:00Z"}}, {"id": "10.5061/dryad.pb271", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:23:17Z", "type": "Dataset", "title": "Data from: Interactions among roots, mycorrhizae and free-living microbial communities differentially impact soil carbon processes", "description": "unspecifiedPlant roots, their associated microbial community and free-living soil  microbes interact to regulate the movement of carbon from the soil to the  atmosphere, one of the most important and least understood fluxes of  terrestrial carbon. Our inadequate understanding of how plant\u2013microbial  interactions alter soil carbon decomposition may lead to poor model  predictions of terrestrial carbon feedbacks to the atmosphere. Roots,  mycorrhizal fungi and free-living soil microbes can alter soil carbon  decomposition through exudation of carbon into soil. Exudates of simple  carbon compounds can increase microbial activity because microbes are  typically carbon limited. When both roots and mycorrhizal fungi are  present in the soil, they may additively increase carbon decomposition.  However, when mycorrhizas are isolated from roots, they may limit soil  carbon decomposition by competing with free-living decomposers for  resources. We manipulated the access of roots and mycorrhizal fungi to  soil in situ in a temperate mixed deciduous forest. We added 13C-labelled  substrate to trace metabolized carbon in respiration and measured  carbon-degrading microbial extracellular enzyme activity and soil carbon  pools. We used our data in a mechanistic soil carbon decomposition model  to simulate and compare the effects of root and mycorrhizal fungal  presence on soil carbon dynamics over longer time periods. Contrary to  what we predicted, root and mycorrhizal biomass did not interact to  additively increase microbial activity and soil carbon degradation. The  metabolism of 13C-labelled starch was highest when root biomass was high  and mycorrhizal biomass was low. These results suggest that mycorrhizas  may negatively interact with the free-living microbial community to  influence soil carbon dynamics, a hypothesis supported by our enzyme  results. Our steady-state model simulations suggested that root presence  increased mineral-associated and particulate organic carbon pools, while  mycorrhizal fungal presence had a greater influence on particulate than  mineral-associated organic carbon pools. Synthesis. Our results suggest  that the activity of enzymes involved in organic matter decomposition was  contingent upon root\u2013mycorrhizal\u2013microbial interactions. Using our  experimental data in a decomposition simulation model, we show that  root\u2013mycorrhizal\u2013microbial interactions may have longer-term legacy  effects on soil carbon sequestration. Overall, our study suggests that  roots stimulate microbial activity in the short term, but contribute to  soil carbon storage over longer periods of time.", "keywords": ["2. Zero hunger", "roots", "13. Climate action", "simulation model", "carbon dynamics", "Rhizosphere", "stable isotope", "plant-soil (belowground) interactions", "15. Life on land", "extra-cellular enzyme activity", "mycorrhizae"], "contacts": [{"organization": "Moore, Jessica A. M., Jiang, Jiang, Patterson, Courtney M., Wang, Gangsheng, Mayes, Melanie A., Classen, Aim\u00e9e T.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.pb271"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.pb271", "name": "item", "description": "10.5061/dryad.pb271", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.pb271"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-09-14T00:00:00Z"}}, {"id": "10.5194/acp-10-7017-2010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:23:21Z", "type": "Journal Article", "created": "2010-04-29", "description": "<p>Abstract. We present and discuss a new dataset of gridded emissions covering the historical period (1850\uffe2\uff80\uff932000) in decadal increments at a horizontal resolution of 0.5\uffc2\uffb0 in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models is used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.                         </p>", "keywords": ["info:eu-repo/classification/ddc/550", "550", "IPCC", "[SDE.MCG]Environmental Sciences/Global Changes", "Physics", "QC1-999", "emissions", "551", "01 natural sciences", "7. Clean energy", "J", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "13. Climate action", "[SDE.ES] Environmental Sciences/Environment and Society", "CMIP5", "[SDE.ES]Environmental Sciences/Environment and Society", "QD1-999", "AR5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "https://doi.org/10.5194/acp-10-7017-2010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-10-7017-2010", "name": "item", "description": "10.5194/acp-10-7017-2010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-10-7017-2010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-02-19T00:00:00Z"}}, {"id": "10.5194/egusphere-egu2020-21951", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:23:31Z", "type": "Journal Article", "created": "2019-05-21", "title": "Assimilation of Sentinel-2 Leaf Area Index Data into a Physically-Based Crop Growth Model for Yield Estimation", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Remote sensing data, crop growth models, and optimization routines constitute a toolset that can be used together to map crop yield over large areas when access to field data is limited. In this study, Leaf Area Index (LAI) data from the Copernicus Sentinel-2 satellite were combined with the Environmental Policy Integrated Climate (EPIC) model to estimate crop yield using a re-calibration data assimilation approach. The experiment was implemented for a winter wheat crop during two growing seasons (2016 and 2017) under four different fertilization management strategies. A number of field measurements were conducted spanning from LAI to biomass and crop yields. LAI showed a good correlation between the Sentinel-2 estimates and the ground measurements using non-destructive method. A correlating fit between satellite LAI curves and EPIC modelled LAI curves was also observed. The assimilation of LAI in EPIC provided an improvement in yield estimation in both years even though in 2017 strong underestimations were observed. The diverging results obtained in the two years indicated that the assimilation framework has to be tested under different environmental conditions before being applied on a larger scale with limited field data.</p></article>", "keywords": ["2. Zero hunger", "yield estimation", "S", "Leaf Area Index", "EPIC model", "Agriculture", "Crop growth model", "04 agricultural and veterinary sciences", "15. Life on land", "crop growth model", "Yield estimation", "13. Climate action", "Data assimilation", "0401 agriculture", " forestry", " and fisheries", "Sentinel-2", "data assimilation"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/9/5/255/pdf"}, {"href": "https://www.mdpi.com/2073-4395/9/5/255/pdf"}, {"href": "https://doi.org/10.5194/egusphere-egu2020-21951"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/egusphere-egu2020-21951", "name": "item", "description": "10.5194/egusphere-egu2020-21951", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/egusphere-egu2020-21951"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-21T00:00:00Z"}}, {"id": "10.5281/zenodo.10060810", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:23:42Z", "type": "Dataset", "title": "SoilCompDB: Global soil compressive properties database. Version 1.0", "description": "Data collection and processing Our data collection comprised published journal articles sourced from Web of Science and Scopus databases, using search terms such as 'soil precompression stress,' 'soil compression index,' 'soil compaction index,' 'soil recompression index,' 'soil swelling index,' 'soil precompaction stress,' and 'preconsolidation pressure' for articles published up to February 2022. \u00a0A total of 1235 publications were found. Duplicate records were eliminated using the Endnote Web citation management application. The remaining references were exported to Rayyan software for title and abstract screening based on predefined criteria for full-text selection. \u00a0After a careful review, we identified 128 papers where the data on soil compressive properties (precompression stress, compression index, and swelling index) were reported in numerical format or legible graphical format and considered suitable for inclusion in the database. \u00a0We employed the WebPlotDigitizer software to extract data from figures within the original publications. For each chosen study, we systematically recorded data concerning soil compressive properties and collected information on soil properties, soil conditions, site characteristics, and experimental settings. We compiled 4,743 individual data entries. Time and place The database includes data from 128 independent studies published between 1992 and 2021. Each study reported between 1 and 360 measurements, with a study median of 14 measurements and a mean of 38 measurements, totalling 4743 database entries. Our database includes data from 20 countries, with a significant concentration of the data originating from Brazil, followed by Germany, Switzerland, Sweden, and Denmark. The majority of the data came from arable soils, representing approximately 72% of data entries.\u00a0\u00a0 Instruments The soil compressive properties included in the database were based on soil compressive tests performed in the laboratory by uniaxial method. The procedure used for stress application on soil samples was mainly the stepwise stress application method, while the constant strain rate method was applied in few studies (less than 2% of the data). The component of the compressive curve related to the soil packing state was represented by soil bulk density, void ratio, and strain. The stress component of the curve was represented in a logarithmic form in the entirety of the database. The database also comprised eight different methods for calculating precompresion stress: Casagrande (1936), Dias Junior and Pierce (1995), Lamand\u00e9 et al. (2017), Sullivan and Robertson (1996), Casini (2012), Culley and Larson (1987), Pacheco Silva (1990), Gregory et al. (2006). Resources Web of Science, Scopus \u2013 literature search Endnote Web \u2013 removal of duplicates Rayyan software \u2013 initial paper selection based on title and abstract WebPlotDigitizer \u2013 data extraction from figures Microsoft Access \u2013 database platform Description of the collected data (column, unit, and description) Sample ID-\u00a0\u00a0\u00a0 A unique identification number assigned to each individual sample within the database\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Study ID- Identification number assigned to each research study in the database Reference - Research paper reference Year - Year of research paper publication \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Language - Language of the research paper \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Soil classification (SiBCS) - Soil Classification according to the Brazilian System (SiBCS), as described in portuguese-language papers Soil classification (original in paper) - Soil classification described in research paper\u00a0 Soil classification (convertion to Soil Taxonomy orders) -\u00a0 Soil classification aligned with the Soil Taxonomy system developed by the United States Department of Agriculture (USDA)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Location - Study location country\u00a0\u00a0\u00a0 Texture classification (USDA) -\u00a0Soil textural classification according USDA Texture\u00a0 classification USDA (letter code) - Letter code for soil textural classification according USDA: S=sand; LS=loamy sand; SL=sandy loam; SiL=silt loam; Si=silt; L=loam; SCL= Sandy clay loam; SiCL=Silty clay loam; CL=clay loam; SC=Sandy clay; SiC=Silty clay; C=clay Clay (USDA) - % - Soil clay content (weight based) - (<0.002 mm) \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Silt (USDA) - % - Soil silt content (weight based) - (0.002 < x < 0.05 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006)\u00a0 Sand (USDA) - % - Soil sand content (weight based)\u00a0 - (0.05 < x < 2 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006) USDA PSD interpolated - =0 if the data was NOT interpolated; =1 if the data was interpolated Published texture class - Texture classification provided in the source publication when the values for clay, silt and sand were not available Clay - g kg-1 - Soil clay content - original in the paper Clay class upper boundary - \u00b5m - The clay class upper boundary informed in source publication Silt - g kg-1 - Silt clay content - original in the paper Silt class upper boundary - \u00b5m - The silt class upper boundary informed in source publication Sand - Soil sand content - original in the paper Sand class upper boundary - \u00b5m - The sand class upper boundary informed in source publication Particle size data flag - =0 if no issues; =1 if there are issues (summing) Sum particle size- g kg-1 - Sum of clay, silt, and sand content Soil depth FROM \u2013 cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the minimum depth at which soil samples were collected\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Soil depth TO \u2013 cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the maximum depth at which soil samples were collected\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Depth \u2013 cm -Specific depth value as presented in paper, or when soil depth is showed as a range (e.g., 0-10cm), it indicates the average depth at which soil samples were collected (e.g 5cm) \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 SOC - g kg-1 - Soil organic carbon content informed in research paper or soil organic carbon content calculate from soil organic matter content by multiplying by 0,58\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 SOC converted from SOM - 1= yes for soil organic carbon derived from soil organic matter content calculations Particle density - Mg m-3 - Soil particle density\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial matric potential \u2013 hPa - Soil water matric potential before loading log Initial matric potential - Soil water matric potential expressed by log\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wetness (based on initial matric potential) - \u00a01=if initial matric potential (MP)<100 hPa; 2= if 100<=initial MP<1000 hPa; 3= initial MP>=1000 hPa Initial gravimetric water content - g g-1 - Gravimetric soil water content before loading provided by source publication, or calculated by volumetric water content divided by soil bulk density Initial volumetric water content - m3 m-3 - Volumetric soil water content before loading, when the soil bulk density was not reported Initial water content data source -\u00a0Graph or table from where the data was collected, or explanation on calculation used Matric potential type - Compressive tests performed on soil samples under different conditions: 1= equilibrated at matric potential; 2= field matric potential; 3= air-dried samples\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial bulk density - Mg m-3 - Soil bulk density before loading\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial BD data source - Graph or table from where the data was collected, or explanation on calculation used\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial volumetric water content calculated - m3 m-3 - Soil volumetric water content calculated by multiplying soil gravimetric water content by soil bulk density Precompression stress \u2013 kPa - Precompression stress \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Precompression stress (SD) \u2013 kPa - Standard deviation for precompression stress values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Precompression stress data source - Graph or table from where the data was collected, or explanation on calculation used Compression index - Compression index \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Compression index (SD) - Standard deviation of compression index values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Compression index data source - Graph or table from where the data was collected, or explanation on calculation used Swelling index - Swelling index\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Swelling index (SD) - Standard deviation of swelling index values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Swelling index data source - Graph or table from where the data was collected, or explanation on calculation used N -\u00a0Number of replicates used for calculating precompression stress, compression index, and swelling index when mean values are reported Land use (paper) -\u00a0Land use described in the research paper Land use (categories) -\u00a0Land use categorized Land use standardized -\u00a0Land use classified as: arable, forest, grassland, and native vegetation. The latter includes forest, grassland, and savanna Land use (number code) -\u00a0Number code for land use: 1=Arable, 2= forest, 3= grassland, and 4= native vegetation Tillage system -\u00a0Tillage system Tillage system (arable soils) - Tillage system for arable soils classified as 'conventional' and 'conservation' Coordinates -\u00a0\u00a0Geographical coordinates\u00a0 of study location Climate -\u00a0Climatic region classification: temperate, tropical, subtropical Climatecod -\u00a0\u00a0\u00a0 Code number assigned to each climatic region: 1=temperate, 2=tropical, 3=subtropical Sampling position (paper) -\u00a0Field position where soil samples were collected with details described in the paper Sampling position -\u00a0Field position where soil samples were collected standardized Treatment -\u00a0Experimental treatment type where the soil samples were collected Stress rate - \u00a0kPa - Stress applied in compressive tests\u00a0 Minimum stress \u2013\u00a0kPa - Minimum stress applied in compressive tests Maximum stress \u2013\u00a0kPa - Maximum stress applied in compressive tests Number of stress rate steps -\u00a0Number of steps in stepwise stress application procedure Stess application type -\u00a01=Stepwise stress 2=one sample per stress 3=Strain controlled Stess application type \u2013\u00a0min - Time for stress application in each step in stepwise stress application procedure Degree of deformation at the end of loading -\u00a0% - Degree of deformation at the end of compressive test Sample diameter \u2013\u00a0cm - Diameter of the soil samples Sample height \u2013\u00a0cm - Height of the soil samples Ratio sample diameter and height\u00a0-\u00a0Ratio between diameter and height of the soil samples Sample volume -\u00a0cm3 -Sample volume when the sample diameter and height are nor presented Precompression stress calculation method -\u00a0Calculation method of precompression stress Precompression stress calculation method (number code) -\u00a0Number code for calculation method PC:1=Casagrande (1936); 2=Dias Junior and Pierce (1995); 3= Lamand\u00e9 et al. (2017); 4=O`Sullivan and Robertson (1996); 5=Casini (2012); 6=Culley and Larson (1987);7=ABNT (1990); 8=Gregory et al. (2006) Description of precompression stress calculation -\u00a0Brief explanation of precompression stress calculation Soil compressive curve components -\u00a0Component of the soil compression curve related to the soil packing state: soil bulk density, void ratio, and strain.\u00a0 Soil compressive curve components (number code) -\u00a0Number code for component of the soil compressive curve related to the soil packing state: 1= soil bulk density; 2= strain; 3= void ratio Curve components source -\u00a0Source of the component of the soil compressive curve related to the soil packing state: 1= showed in the paper, 2= according to original method for precompression stress calculation, 3= described in method, but not clear in the paper Compressive curve available -\u00a0Original soil compressive curve available in the paper: 1= No 2=Yes Comments -\u00a0Brief comments on the paper Issues and remarks We sought out important information not included in the paper by directly communicating with the authors whenever possible. In cases where multiple papers covered the same experiment, we prioritized the one offering more comprehensive details. If two papers complemented each other, we included both. When analyzing studies comparing various methods for calculating soil precompression stress, we exclusively gathered data calculated using the widely accepted Casagrande (1936) method. To ensure comparability across studies, we standardized the collected data by converting it to the same unit. The standardization process involved: i) assuming that 58% of soil organic matter (SOM) was soil organic carbon (SOC) when only SOM was reported, ii) calculating soil bulk density using a soil particle density of 2.65 Mg m-3 when only total porosity data were provided, and iii) harmonizing all texture data to the USDA classification system, which defines the silt/sand boundary as 50 \u03bcm, utilizing the k-nearest neighbor approach (referred to as 'similarity method' by Nemes et al. (1999). \u00a0 Reference Associa\u00e7\u00e3o Brasileira de Normas T\u00e9cnicas - ABNT. NBR 12007: Ensaio de adensamento unidimensional. Rio de Janeiro: 1990. Casagrande, A., 1936. Determination of the preconsolidation load and its practical significance. In: Proceedings of the International Conference on Soil Mechanics and Foundation Engineering, vol. III, Harvard University, Cambridge, MA, pp. 60\u201364.Casini, F. 2012. Deformation induced by wetting: A simple model. Can. Geotech. J. 49:954\u2013960 10.1139/T2012-054. doi:10.1139/t2012-054 Culley, J.L.B., Larson, W.E., 1987. Susceptibility to compression of a clay loam Haplaquoll. Soil Sci. Soc. Am. J. 51, 562\u2013567. Dias Junior, M.S., Pierce, F.J., 1995. A simple procedure for estimating preconsolidation pressure from soil compression curves. Soil Technology 8, 139\u2013151. doi:10.1016/0933-3630(95)00015-8 Gregory, A.S., Whalley, W.R., Watts, C.W., Bird, N.R.A., Hallett, P.D., Whitmore, A.P., 2006. Calculation of the compression index and pre-compression stress from soil compression test data. Soil Till Res. 89:45-57. doi:10.1016/j.still.2005.06.012 Lamand\u00e9, M., Schj\u00f8nning, P., Labouriau, R., 2017. A novel method for estimating soil precompression stress from uniaxial confined compression tests. Soil Sci. Soc. Am. J. 81 https://doi.org/10.2136/sssaj2016.09.0274. Nemes, A., \u00a0W\u00f6sten, J.H.M., Lilly, A., \u00a0Oude Voshaar, J.H., 1999. Evaluation of different procedures to interpolate the cumulative particle-size distribution to achieve compatibility within a soil database.\u00a0Geoderma 90: 187-202. 129\u00a0 O'Sullivan, M.F., Robertson, E.A.G., 1996. Critical state parameters from intact samples of two agricultural topsoils. Soil Tillage Res 39(3 \u2013 4):161 \u2013 173.", "keywords": ["2. Zero hunger", "soil compression curve", "precompression stress", "15. Life on land", "soil mechanical properties", "compression index", "soil moisture", "uniaxial compression test", "swelling index"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.10060810"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.10060810", "name": "item", "description": "10.5281/zenodo.10060810", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.10060810"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-06T00:00:00Z"}}, {"id": "10.5281/zenodo.14008412", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:24:17Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders soil sealing cookbook", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national and European scales.The data was prepared according to the Level 2 methodology of the SERENA soil sealing cookbook. For Belgium, the application was carried out at the regional scale for the Flanders region. \u00a0The automatically generated yearly soil sealing maps (1 m resolution GeoTIFF rasters)\u00a0combine \u201cknown\u201d sealing from administrative databases (buildings and transport infrastructure) with modelled sealing based on artificial intelligence. Administrative databases do not (adequately) cover parking lots, private driveways and garden terraces, which are a substantial part of the sealed area in Flanders. Hence, a machine learning model was built for deriving this remaining sealing from aerial imagery. For this purpose, an assessor manually labeled the sealed parts on a subset of the images. Based on this training set, a convolutional neural network model was used to produce a sealing probability map, which was converted to a binary modelled sealing map. Finally, a continuity correction was applied to ensure a temporally consistent result across the yearly maps. \u00a0The objective of the SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The selected indicator was the degree of soil sealing. By evaluating this degree at two moments in time, the change in soil sealing can be determined. \u00a0\u00a0The following data were used:\u00a0         Large-scale Reference Database (Grootschalig Referentiebestand or Basiskaart), the digital topographic reference map for Flanders (vector)\u00a0           Medium-scale annual winter aerial images of Flanders (15 or 25 cm raster resolution)    This dataset is originally hosted at Geopunt (www.geopunt.be). For the most up-to-date version of the dataset, please access the data from the Geopunt repository.", "keywords": ["soil sealing", "remote sensing", "BELGIUM (FLANDERS)", "aerial images", "SERENA", "EJP-Soil", "photointerpretation"], "contacts": [{"organization": "Cockx, Kasper, Oorts, Katrien,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14008412"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14008412", "name": "item", "description": "10.5281/zenodo.14008412", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14008412"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.15277024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:24:48Z", "type": "Dataset", "title": "Management of rice straw in rice-soybean succession in tropical lowland", "description": "This study aims to investigate alternative management practices for rice straw in tropical lowland rice-soybean systems. The goal is to twofold:\u00a0 first, to identify methods that maximize the yield of the subsequent soybean crop, and second, to quantify the effects of these practices on soil properties. 'Ten treatments (below) consisting of a combination of rice straw management (burning, removal and incorporation with disc harrow, leveling disc harrow, and knife-roller) with soybean sowing (no-tillage and conventional) were evaluated in a completely randomized design, with six replications. The disc harrow operated at 0.20-0.25 m, the leveling disc harrow at 0.10 m, and the knife-roller at 0.13 m depth. The total plot area was 600 m2 (10 m wide and 60 m long).  \u00a0  Tillage treatments were:  Burning (M1)  Straw removal (M2)  Incorporation with one pass of a disc harrow (GA) and two (M3) or three (M4) passes of a leveling harrow (GN)  Incorporation with one pass of a roller knife (RF) and no-till soybean planting (M5)  Incorporation with one pass of RF and two (M6) or three (M7) passes of GN  Incorporation with two passes of RF and no-till soybean planting (M8)  Two (M9) or three (M10) passes of GN.' 'Grain yield was determined in an area of 2.55 m\u00b2, corresponding to six 2.5 m rows spaced 0.17 m apart, which was expressed in kg ha-1, after moisture was adjusted to 13%.  \u00a0  The yield components were determined: the number of panicles in one meter of the planting row; plant height, measured from the soil level to the tip of the panicle in five tillers. The HI was obtained by the ratio between grain yield and total dry matter in 1 m2. The number of grains and empty spikelets in ten panicles and the mass of 100 grains. The determination of the industrial quality of grains in 100 g samples of processed seeds. Rice and soybean grain yields were determined annually and the cumulative yields of these crops were calculated.' The experimental design is completely randomized, with six replicates. '2015 and 2017: 0-10, 10-20cm  2023: 0-10, 10-20, 20-30, 30-40cm' 'This study investigated the following chemical properties of the soil: pH, and the levels of calcium (Ca2+), magnesium (Mg2+), hydrogen (H+), aluminum (Al3+), phosphorus (P), potassium (K+), copper (Cu2+), zinc (Zn2+), iron (Fe3+), manganese (Mn2+), and organic matter.  \u00a0  -Soil pH was measured in water.  -Calcium and magnesium were extracted using a 1 molar potassium chloride (KCl) solution and then analyzed by atomic absorption spectroscopy.  -Potential acidity (the combined amount of hydrogen and aluminum) was determined through titration with a 0.5 molar calcium acetate solution at a pH of 7.  -Phosphorus, potassium, and micronutrients were extracted with Mehlich 1 solution (a mixture of 0.5 N hydrochloric acid (HCl) and 0.025 N sulfuric acid (H2SO4)) and analyzed by inductively coupled plasma atomic emission spectroscopy.  -Soil organic matter (SOM) was estimated by multiplying the total organic carbon content of the soil by 1.724. This calculation was based on the chromic acid titration method.  \u00a0  The specific methods used for these analyses were referenced from Teixeira et al. (2017) and Soltanpour et al. (1996).' '2015 and 2017: 0-10, 10-20cm  2023: 0-10, 10-20, 20-30, 30-40cm  \u00a0  - In 2015 and 2017, soil organic carbon content was estimated indirectly by measuring soil organic matter (SOM) using the chromic acid titration method (Teixeira et al., 2017). The total soil organic carbon content was obtained by multiplying the SOM by a factor of 1.724.  - In 2023, soil organic carbon content was measured directly using dry combustion with Total Organic Carbon (TOC) analysis.  - Soil carbon stocks were calculated using soil bulk density. A volumetric ring was used to determine the bulk density at different depths (0-10 cm, 10-20 cm, 20-30 cm, and 30-40 cm). Since bulk density varied between treatments, estimates of soil organic carbon stocks (in Mg ha-1) were based on equivalent soil masses (Sisti et al., 2004).' The following soil physical properties were measured: bulk density, total porosity, microporosity, and macroporosity. Additionally, plant available water capacity was determined following the method of Teixeira et al. (2017). The S index, an indicator of soil physical quality, was calculated based on Dexter (2004). Finally, air capacity (AC) was assessed using the method outlined by Reynolds et al. (2002). Clay loam texture '-Sample collection: Soil samples for biological properties were collected at a depth of 0-10 cm.  \u00a0  -Enzyme analysis: Betaglucosidase, aryl-sulfatase, and acid phosphatase activities were determined following the methods described by Tabatabai (1994) as modified by Lopes (2013). The analysis was performed using dried air-sampled soil.'", "keywords": ["Field crops", "plintossolo", "Plinthosol", "culturas de campo"], "contacts": [{"organization": "Ananias Soler da Silva, Mellissa, Ba\u00eata dos Santos, Alberto,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15277024"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15277024", "name": "item", "description": "10.5281/zenodo.15277024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15277024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-16T00:00:00Z"}}, {"id": "10.5281/zenodo.15328215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:24:49Z", "type": "Dataset", "title": "1000 Soils Pilot Dataset, version 8, May 2025", "description": "This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data.  A beta visualization tool is available for some data types at\u00a0https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback.  Data completed include:    Geochemistry, texture, respiration, and enzyme activities  FTICR-MS organic matter chemistry  Microbial biomass C and N  TOC/TDN of water-extractable OM  X-ray computed tomography (derived metrics available here, raw data available upon request)  Metagenomes; a variety of data formats are available upon request  Soil hydraulic properties   Data in progress:    LC-MS/MS in development, timeline TBD, inquire for status   1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and\u00a0  1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography.  icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates.  1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information.  Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information.  Readme File_v4.xlsx is the readme file.  Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions.  The following file and all raw data are\u00a0available upon request:  icr_by_mass_for_single_sample_analysis_only.csv\u00a0contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs.  For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet  Acknowledgment:\u00a0  Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.\u00a0  The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at\u00a0https://sc-data.emsl.pnnl.gov/.", "keywords": ["2. Zero hunger", "decomposition", "13. Climate action", "FTICR-MS", "biogeochemistry", "carbon", "molecular", "15. Life on land", "6. Clean water", "soil"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15328215"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15328215", "name": "item", "description": "10.5281/zenodo.15328215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15328215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-02T00:00:00Z"}}, {"id": "10.5281/zenodo.15395350", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:24:51Z", "type": "Dataset", "title": "NSW 25-ha Drone Survey Grid", "description": "NSW 25-ha Drone Survey Grid   This repository provides a 25-hectare (500m x 500m) resolution spatial grid for New South Wales.  This grid layer was used to align systematic drone surveys and spatially structure binomial N-mixture models for estimating the abundance of koalas at the landscape-scale. It supports presence/absence and abundance frameworks and is suitable for use in large-scale ecological monitoring programs.  The grid was used in the following study:    Ryan, S.A., Southwell, D.M., Beranek, C.T., Clulow, J., Jordan, N.R., Witt, R.R., 2025.\u00a0Estimating the landscape-scale abundance of an arboreal folivore using thermal imaging drones and binomial N-mixture modellingBiological Conservation. Manuscript ID: 111207. https://doi.org/10.1016/j.biocon.2025.111207   \ud83d\udcd8 Abstract  Estimating the abundance of wildlife populations at a landscape-scale is vital for conservation, but is often hampered by survey costs, data processing and imperfect detection. In this study, we developed a framework that combines a protocol for validating nocturnal thermal drone detections in real-time with N-mixture modelling to estimate the landscape-scale abundance of arboreal folivores. As a case study, we estimated the abundance of koalas (Phascolarctos cinereus) across seven reserves (673 km\u00b2) in New South Wales, Australia. We conducted thermal drone surveys of 208, 25-ha sites stratified across vegetation type and fire history, on average, three times over consecutive nights (range 1\u201312 repeats), between 18:00\u201304:00 h (May to September). All koala detections were validated by field personnel or in real-time with drones equipped with a thermal camera and searchlight. Koalas were detected on 245 occasions. We fitted N-mixture models to validated repeat count data to quantify the effect of site and observation variables on abundance and detectability. Using our top set of competing models, we estimated that 4357 koalas (95 % CI = 2319\u20138307) occupy the seven reserves, with a mean detection probability of 0.22 (95 % CI = 0.15\u20130.31) over all survey occasions. We found detection probability decreased with increases in relative humidity and temperature. Koala abundance was negatively associated with fire severity, elevation, tree height and soil clay content, and positively associated with available water content, forest cover and soil organic carbon. Our framework, which combines real-time field validated drone data while accounting for imperfect detection, improves the accuracy of abundance estimates for arboreal folivores across large-scales.    \ud83d\udcc2 Contents     Grid_Albers_00500m_NSW_Polys.shp and associated filesA shapefile representing 25-ha (500 m \u00d7 500 m) grid cells across New South Wales.     \ud83d\uddfa\ufe0f Spatial Details     CRS: GDA94 / Australian Albers (EPSG:3577)  Geometry Type: Polygon  Cell Size: 500 m \u00d7 500 m (25 hectares)  Total Features: 3,222,693  Attribute Fields: Id (unique cell identifier)  Bounding Box (minx, miny, maxx, maxy):(826250.0, \u20134212250.0, 2082750.0, \u20133181250.0)     \u2705 Intended Applications     Thermal drone survey planning  Spatial alignment of repeatable wildlife monitoring  Koala and arboreal mammal detection  Binomial or Poisson N-mixture model design  Landscape-scale ecological stratification     \u26a0\ufe0f Data Use and Licensing   This grid layer was provided by Allen Mcilwee (NSW Government) and is published with permission as open-access supplementary material to support the following paper:    Ryan, S.A., Southwell, D.M., Beranek, C.T., Clulow, J., Jordan, N.R., Witt, R.R. (2025)Estimating the landscape-scale abundance of an arboreal folivore using thermal imaging drones and binomial N-mixture modellingBiological Conservation. Manuscript ID: 111207. https://doi.org/10.1016/j.biocon.2025.111207   The dataset is made available to support open ecological research and systematic drone survey planning in New South Wales.\u00a0  Users applying this grid for survey or monitoring purposes in NSW are encouraged to submit resulting species detection records to NSW BioNet to contribute to state-wide biodiversity data and conservation efforts.", "keywords": ["spatial grid", "wildlife monitoring", "25-ha grid", "New South Wales", "koala", "spatial layer", "thermal drone survey", "abundance modelling"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15395350"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15395350", "name": "item", "description": "10.5281/zenodo.15395350", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15395350"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-04T00:00:00Z"}}, {"id": "10.5281/zenodo.15680931", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:24:59Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract                        Background             <p>Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.</p>                                   Results             <p>The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.</p>                                   Conclusions             <p>The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.</p>", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1186/s12302-025-01141-6.pdf"}, {"href": "https://doi.org/10.5281/zenodo.15680931"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15680931", "name": "item", "description": "10.5281/zenodo.15680931", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15680931"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.5281/zenodo.15781488", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:01Z", "type": "Report", "title": "Results of stakeholder surveys on preferred NSWRM implementation plans. Deliverable D5.3 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D5.3 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756)    The objective of this deliverable is to convey OPTAIN\u2019s optimisation approach, methodologies and results to stakeholders of each case study\u2019s Multi-Actor Reference Groups. More importantly, it will create a common understanding of the potential of the NSWRMs for improving water and nutrient retention in the CS, as well as of the associated trade-offs such as costs and potential reductions in crop production. Finally, this task will determine those NSWRM implementation plans preferred by individual actors using the tool, ParetoPick-R, developed in the previous task 5.3. This sets the stage for the subsequent in-depth, cross-sectoral discussion about a spatially targeted implementation of NSWRM.    Summary\u00a0  This deliverable from the EU Horizon 2020 OPTAIN project presents the results from stakeholder interviews across eleven European case studies, focusing on the identification of preferred implementation plans for Natural/Small Water Retention Measures (NSWRMs).\u00a0It builds on the modelling and multi-objective optimisation workflows employed in OPTAIN, which explored numerous options for potential measure implementation optimised for environmental and economic objectives.  Stakeholders of each case study\u2019s Multi-Actor Reference Groups (MARG) participated in structured interviews. Using the interactive ParetoPick-R app, they developed a common understanding of the potential of NSWRMs and explored trade-offs among four optimisation objectives, such as water/nutrient retention, crop production, and cost. They then selected their preferred implementation plans based on weights assigned to each objective and filter options applied to the solution space.  Key Findings:    Trade-offs & preferences: Stakeholders' preferences varied significantly across sectors and case studies. Agricultural actors typically prioritised crop production and cost-efficiency, while those in the water and nature conservation sectors leaned towards environmental benefits.  Common measures: Frequently preferred NSWRMs included soil and/or crop management measures, followed by greening measures and engineered solutions.  Feasibility issues: Technical feasibility, land ownership, and institutional hurdles (e.g., need for permits) influenced stakeholder choices.  Tool feedback: The ParetoPick-R tool was generally well-received for visualising trade-offs and supporting decision-making. However, some users found it too complex and suggested improvements in usability, guidance, and map functionality.   This deliverable D5.3 sets the foundation for the final MARG workshops in the case studies, which will seek to negotiate compromise solutions that are acceptable to all actors. The report underscores the importance of participatory modelling tools and multi-sector engagement in water and land management planning.", "keywords": ["multiobjective optimisation", "trade-offs", "NSWRM", "agricultural production", "H2020", "OPTAIN", "SWAT", "NWRM", "stakeholder", "water retention"], "contacts": [{"organization": "Strauch, Michael, Wittekind, Cordula,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15781488"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15781488", "name": "item", "description": "10.5281/zenodo.15781488", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15781488"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15797289", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:01Z", "type": "Dataset", "title": "Database of soil characteristics under specific pesticide management", "description": "Database of soil characteristics under specific pesticide management  Contributors: Mark\u00e9ta Mayerov\u00e1 and Veronika \u0158ez\u00e1\u010dov\u00e1  Affiliation: Czech Agrifood Research Center, Drnovsk\u00e1 507/73, CZ-160 00 Prague 6, Czech Republic  Database of soil characteristics will contribute to the realization of the project\u00b4s goal to identify appropriate and inappropriate pesticides from the point of the view of their impact on the non-target organisms and soil characteristics.  Field I.  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The experiment took place at the site of the experiment that had been running there since 2013 and included 5 different herbicide treatments in 4 replications (Mayerov\u00e1 et al. 2018)  The new trial area was split into 20 randomised plots with 2 different herbicide treatments in 8 replications and control without herbicides in 4 replications. Herbicide treatments differed in the mode of action (Table 1)  Table 1. Summary of the herbicides and active ingredients used in the trial. Classification Group by Herbicide Resistance Action Committee (HRAC).       herbicide     dose    formulation    active ingredient    content of a.i.    HRAC group    target weeds      Agritox 50 SL    1.5 l/ha    EC    MCPA    500 g/l    O    dicot      Glean 75 PX    15 g/ha    WG    chlorsulfuron    750 g/l    B    dicot + annual grasses       \u00a0  The area of each plot was 100 m2 and the 10 by 10 m plots were separated from field boundaries and from each other by 2 m on all sides to eliminate interaction between plots. Herbicides were applied post emergency in spring (April 26, 2024) from the tillering crop stage to the beginning of stem elongation (BBCH 21\u201331) by the Agrio-Napa 12 sprayer. Winter wheat was grown in the experimental field in 2024. At the beginning of March, it was mineral fertilized with LAD (ammonium nitrate with dolomite - NH4NO3\u00a0+\u00a0CaMg (CO3)2; 27 % N) at a dose 100 kg/ha.   Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer in each replication before herbicide application (April 24, 2024), 14 days after herbicide application (May 9, 2024) and 7 weeks after herbicide application (June 14, 2024). \u00a0A total of 20 soil samples were collected at each sampling. The soil samples were subsequently dried and sieved through a 2 mm sieve, thus simultaneously homogenised. The following soil properties were determined: pH (H2O), electric conductivity, available P and K, concentration NH4 and NO3, soil organic carbon, and total organic nitrogen content. Available P and K were assessed according to the Mehlich III method (Mehlich, 1984) on an Agilant ICP-OES 5110 VDV instrument. NO3 and NH4 were determined using calcium chloride solution as extractant according to ISO 14255:1998 on automated chemistry analyser SKALAR. Soil organic carbon and soil organic matter content were determined by sulfochromic oxidation according to ISO 14235:1998.   Field II  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The total area of the experiment is about 11 ha including the protective area around the entire experiment. The experimental area is divided into two halves, 120m wide and 300m long.\u00a0 One half was treated on June 17, 2024, with insecticide Decis forte (active ingredient deltamethrin) at a dose 62.5ml/ha, the other half was without insecticide treatment. Both areas are further divided into other halves. One half was treated on May 15, 2024, with herbicide Agritox (active ingredient MCPA) at a dose 1.5l/ha, the other was treated with hoeing only. We thus obtained 4 strips 60m wide with following treatment combinations: (A) herbicide + insecticide; (B) hoeing + insecticide; (C) hoeing; (D) herbicide. Spring wheat was grown in the experimental field in 2024. It was fertilized with mineral nitrogen at a dose of 150 kg N/ha before sowing and with 39 kg N/ha (DAM 390 - ammonium nitrate with urea) in the tillering phenophase.  In the middle of each strip (i.e. treatment), 8 sampling sites were marked in a row, 20 m apart from each other. Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer at each sampling site 14 days after herbicide application and 14 days after insecticide application. A total of 32 soil samples were collected at each sampling. Further sample processing was the same as for Field I.  The database will be gradually supplemented in the following years.   Funding: Development for this work is funded primarily by the Technology Agency of the Czech Republic, project SS07020100: \u201cThe impact of plant protection products on non-target biodiversity: soil microorganisms, invertebrates and wild plants\u201d, and the Ministry of Agriculture of the Czech Republic, institutional support MZE-RO0425.  The database was approved on September 2, 2025, by the Ministry of Agriculture of the Czech Republic.  References:  Mayerov\u00e1 M., Mikulka J., Soukup J. (2018): Effects of selective herbicide treatment on weed community in cereal crop rotation. Plant Soil Environ., 64: 413\u2013420. https://doi.org/10.17221/289/2018-PSE  \u00a0Mehlich A. (1984): Mehlich 3 Soil Test Extractant. A Modification of the Mehlich 2 Extractant. Commun. Soil Sci. Plant Anal. 15, 1409-1416. http://dx.doi.org/10.1080/00103628409367568.", "keywords": ["field trial", " herbicides", " insecticides", " soil properties"], "contacts": [{"organization": "Mayerov\u00e1, Mark\u00e9ta, \u0158ez\u00e1\u010dov\u00e1, Veronika,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15797289"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15797289", "name": "item", "description": "10.5281/zenodo.15797289", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15797289"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-03T00:00:00Z"}}, {"id": "10.5281/zenodo.4506403", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:19Z", "type": "Journal Article", "title": "Quantifying biogenic carbon dioxide fluxes in an urban area", "description": "Urban areas constitute complex and highly heterogeneous mosaics of CO\u2082 sources and sinks. Anthropogenic emissions - mainly from fuel combustion due to vehicle traffic, building heating, energy production and other industrial activities - are producing high amounts of CO\u2082, dominating the urban CO\u2082 flux. The biogenic fluxes (i.e. photosynthesis, autotrophic-heterotrophic respiration) are usually smaller than the anthropogenic fluxes in urban areas, however they potentially affect the seasonal and spatial variability of urban emissions according to green area cover fraction and seasonal climate variability. Quantifying the urban biogenic fluxes would help in discriminating human emissions from natural fluxes, recognizing the seasonal and interannual CO\u2082 emission variability and trends, enhance our current understanding on urban metabolism and function, and eventually improve the current urban emission inventories. Urban biogenic flux dynamics are expected to differ significantly from the rural ecosystems due to the extreme variability of urban climate in micro and local scales, urban-related stressors and diverse management practices. The Urban Heat Island (UHI) phenomenon is one of the factors that would potentially alter the urban biogenic CO\u2082 balance, since it affects both soil and air temperature which are important environmental drivers of the biogenic CO\u2082 flux processes. A relevant scientific question is if urban green tends to behave as carbon sink or source in the long term, which is still a matter of controversy in today\u2019s literature. In the framework of diFUME project (https://mcr.unibas.ch/difume/), the spatial and temporal variability of CO\u2082 flux by the anthropogenic and biogenic sources and sinks in Basel city centre is modelled and monitored. The approach involves the development of mechanistic models of photosynthetic uptake, plant respiration and soil respiration, dedicated to urban environment, according to meteorological observations, spatial representation of urban structure and EO monitoring of vegetation dynamics. An extended urban sensor network in the study area is used to monitor air temperature, soil temperature and soil moisture variability. The spatial variability of solar radiation is modelled according to the 3-dimensional architecture of the urban canopy. A high-resolution aerial Lidar dataset of the study area is used to extract building and tree morphology, as well as tree Leaf Area Index (LAI). The multiple radiation interactions between buildings and urban vegetation are considered in a multilayer modelling approach of radiation intercepted by plant canopies, taking into account horizontal and vertical distribution of LAI and building structures. The biogenic flux models are calibrated during an extended field campaign of microscale in-situ CO\u2082 flux measurements on urban trees and soils of Basel city centre during the summer of 2020. This study presents the developed modelling approaches for the three biogenic fluxes, the first results from the field measurement campaign and initial estimations of the spatial and temporal variability the urban biogenic CO\u2082 fluxes.", "keywords": ["diFUME", "urban biogenic carbon dioxide flux", "13. Climate action", "11. Sustainability", "15. Life on land", "7. Clean energy", "12. Responsible consumption"], "contacts": [{"organization": "Stavros, Stagakis, Christian, Feigenwinter, Vogt Roland, Mutti Miriam, Zurbriggen Etienne, Pitacco Andrea,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4506403"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ICOS%20Science%20Conference%202020", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4506403", "name": "item", "description": "10.5281/zenodo.4506403", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4506403"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.5574882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:22Z", "type": "Report", "created": "2020-03-09", "title": "Hyperspectral imaging for high resolution mapping of soil profile organic carbon distribution in an Austrian Alpine landscape", "description": "<p>         &amp;lt;p&amp;gt;Studies on soil organic carbon (SOC) stocks mostly focus on topsoils (&amp;lt; 30 cm). However, 30 to 63% of the SOC are stored in the subsoils (30 to 100 cm), and the factors controlling SOC storage in subsoils may be substantially different than in topsoils. The low mean SOC content in subsoils makes its quantification and characterization challenging. Thus, new approaches are required to depict the SOC stocks distribution in full soil profile. Hyperspectral imaging of soil core samples can provide high spatial resolution of the vertical distribution of SOC in a soil profile. The main objective of the ongoing study, within the Horizon 2020 European Project Circular Agronomics, is to apply laboratory hyperspectral imaging with a variety of machine learning approaches for the mapping of OC distribution in undisturbed soil cores. Soil cores were collected down to a depth of one meter in grasslands of 15 organic farms located in the Lungau Valley, in Austria. Some samples were divided into five depths in the field for classical bulk soil measurements (total carbon and nitrogen, texture, pH, EC and bulk density) on disturbed samples. Undisturbed soil cores were sliced vertically for laboratory hyperspectral imaging in the range of Vis-NIR (400-1000 nm). We were able to reveal the hotspots of OC and map the OC distribution in soil profile by applying a variety of machine learning approaches (i.e. partial least square and random forest regression) as a function of spectral responses. A digital elevation model was further exploited to investigate the effects of topographical factors such as elevation, aspect and slope on SOC profile distribution. Landsat 8 data were also used to depict the spatial variability of land insensitive cover/vegetation in study area.&amp;lt;/p&amp;gt;         </p>", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Vis-NIR imaging spectroscopy", " Alpine grassland", " Digital elevation model", " Subsoils"], "contacts": [{"organization": "YASER OSTOVARI, K\u00f6ppend\u00f6rfer, Baptist, Guigue, Julien, Van Groenigen, Jan Willem, Creamer, Rachel, Guggenberger, Thomas, Grassauer, Florian, Hobley, Eleanor, Ferron, Laura, Martens, Henk, K\u00f6gel-Knabner, Ingrid, Vidal, Alix,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5574882"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5574882", "name": "item", "description": "10.5281/zenodo.5574882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5574882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-23T00:00:00Z"}}, {"id": "10.5281/zenodo.6202061", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:24Z", "type": "Dataset", "title": "Bias-corrected EURO-CORDEX RCM simulations for the OPTAIN case studies", "description": "Open AccessBias-corrected EURO-CORDEX RCM simulations are available on a daily timescale for: -period 1981-2099/2100, -6 RCM, -3 scenarios (RCPs 2.6, 4.5 and 8.5), -7 variables (mean, minimum and maximum temperature, precipitation, solar radiation, wind speed at 2 m and relative humidity) and -18 domains and 23 locations within these domains. Bias correction and further downscaling to 0.1\ufffd\ufffd was done using ERA5-Land reanalysis data with non-parametric empirical quantile mapping. Moreover, the interpolation of gridded bias-corrected climate model simulations to the locations was made using universal kriging. <strong>Organization of the data</strong> The name of the files are <em>domain</em>-<em>type</em>.zip, where <em>type</em> is gridded (NetCDF) or point (csv). Each zip file contains multiple files, organized in subfolders: <em>experiment</em>/<em>modelNumber</em>/<em>variable</em>.nc for gridded and <em>experiment</em>/<em>modelNumber</em>/<em>variable-pilotFieldNumber</em>.txt for point data, where <em>experiment </em>is rcp26, rcp45 or rcp85. <em>domain and pilotFieldNumber</em> <strong>domain</strong> <strong>domain </strong><strong>location (min and max. Longitude, min and max latitude</strong><strong>)</strong> <strong>pilotFieldNumber</strong> <strong>pilot field </strong><strong>location (longitude, latitude)</strong> <strong>case study</strong><strong> number</strong> <strong>country</strong> <strong>Name (OPTAIN case study)</strong> 01 50.95 51.45 14.55 15.05 1 DEU Schoeps 02 46.35 47.05 6.55 7.15 2 46.816667 6.95 2 CHE Petite Glane 02_1 46.75 47.25 7.25 7.75 1 46.983333 7.466667 02_34 47.35 47.85 8.35 3 4 47.433333 8.516667 47.683333 8.616667 02_5 46.15 46.65 5.95 6.45 5 46.4 6.233333 03a 46.65 47.15 17.45 17.95 1 2 3 4 46.92649 17.68246 46.9166 17.68976 46.91283 17.69754 46.91283 17.69723 3a HUN Csorsza 03b 46.45 46.95 16.65 17.15 3b HUN Felso Valicka 04 52.35 52.85 18.45 18.95 1 52.597469 18.728617 4 POL Upper Zglowiaczka 05 46.35 46.85 15.35 15.85 5 SVN Pesnica 06 46.45 46.95 16.15 16.65 6 HUN/SVN Kebele/Kobiljski 07 49.85 50.35 4.75 5.25 7 BEL La Wimbe 08 55.15 55.75 23.55 24.05 1 2 55.522057 23.799235 55.42233194 23.82580339 8 LTU Dotnuvele 09 45.45 45.95 9.65 10.15 9 ITA Cherio 10 59.45 59.95 10.75 11.25 1 2 3 4 5 6 7 8 59.71949 10.83576 59.6833306 10.8833298 59.6833306 10.8833298 59.665 10.9475 59.665 10.9475 59.841012 10.903597 59.757631 11.072031 59.539623 10.856447 10 NOR Krogstad 11 46.45 46.95 17.55 18.05 1 2 46.658333 17.75583 46.656944 17.75833 11 HUN Tetves 12 49.35 49.85 14.75 15.25 1 49.616837 15.078266 12 CZE Cechticky 13 55.85 56.35 25.85 26.45 13 LVA Dviete 14 59.75 60.25 17.55 18.05 14 SWE Ingvastaan Lehstaan <em>modelNumber</em> <strong>modelNumber</strong> <strong>Driving Model (GCM)</strong> <strong>Ensemble</strong> <strong>RCM </strong> <strong>End date</strong> 1 EC-EARTH r12i1p1 CCLM4-8-17 31.12.2100 2 EC-EARTH r3i1p1 HIRHAM5 31.12.2100 3 HadGEM2-ES r1i1p1 HIRHAM5 30.12.2099 4 HadGEM2-ES r1i1p1 RACMO22E 30.12.2099 5 HadGEM2-ES r1i1p1 RCA4 30.12.2099 6 MPI-ESM-LR r2i1p1 REMO2009 31.12.2100 <em>variable</em> <strong>variable</strong> <strong>description</strong> <strong>Unit</strong> Tmean Mean temperature \ufffd\ufffdC Tmin Min temperature \ufffd\ufffdC Tmax Max temperature \ufffd\ufffdC prec Precipitation mm solarRad Solar radiation MJ/m2 windSpeed Wind speed at 2m m/s relHum Relative humidity % <strong>Methodolody</strong> Bias correction was done using non-parametric empirical quantile mapping with modified method from R package qmap. Parameters selected were: corrections for each day of the year using a moving windows for a 31 days; 100 quantiles; wet days corrections for precipitation. The reference period is 1981-2010. The interpolation of gridded bias-corrected climate model simulations to the location was made using universal kriging with R packages automap and gstat with (external) variables x, y, x2, y2, x*y, z, where x is latitude, y is longitude, and z is elevation. For Digital Elevation Model Shuttle Radar Topography Mission was used. If there was an error using above mentioned variables, the number of variables was reduced to x, y, x*y, z and if there was still an error to x, y, z. <strong>Funding</strong> This project has received funding from the European Union\ufffd\ufffd\ufffds Horizon 2020 research and innovation programme under grant agreement No 862756.", "keywords": ["CORDEX", "13. Climate action", "RCM", "ERA5-Land", "OPTAIN", "EURO-CORDEX", "bias correction"], "contacts": [{"organization": "Honzak, Luka", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.6202061"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.6202061", "name": "item", "description": "10.5281/zenodo.6202061", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.6202061"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-21T00:00:00Z"}}, {"id": "10.7910/DVN/W9LSAD", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:26:36Z", "type": "Dataset", "created": "2015-01-01", "title": "Replication data: Zn efficient rice genotypes alter soil Zn availability, composition and Zn uptake in Zn-deficient and Zn-sufficient field soils under continuous flooding", "description": "Open Accessapplication/vnd.ms-excel, null", "keywords": ["biofortification", "Agricultural Sciences", "zinc deficiency", "Oryza sativa"], "contacts": [{"organization": "Goloran, Johnvie", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/W9LSAD"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/W9LSAD", "name": "item", "description": "10.7910/DVN/W9LSAD", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/W9LSAD"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-24T00:00:00Z"}}, {"id": "11086/5103", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:06Z", "type": "Report", "title": "Consejer\u00eda sobre salud bucal y cuidados de pr\u00f3tesis dental removible en adultos portadores", "description": "Open AccesspublishedVersion", "keywords": ["Salud bucal", "Cuidado dental para ancianos", "Pr\u00f3tesis dental"], "contacts": [{"organization": "Isla, C.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/11086/5103"}, {"rel": "self", "type": "application/geo+json", "title": "11086/5103", "name": "item", "description": "11086/5103", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11086/5103"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "11449/236856", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:12Z", "type": "Report", "title": "Tradutores de romances-folhetins nos jornais cariocas do s\u00e9culo XIX", "description": "Open Access88887.186062/2018-00", "keywords": ["Romance-folhetim", "Serial novel", "Sources primaires", "Literatura - Hist\u00f3ria e cr\u00edtica", "Histoire de la traduction", "Primary sources", "Roman-feuilleton", "Translation - History and criticism", "Fontes de informa\u00e7\u00e3o prim\u00e1rias", "Traducteur litt\u00e9raire", "Tradutor liter\u00e1rio", "Tradu\u00e7\u00e3o - Hist\u00f3ria e cr\u00edtica", "Tradutores", "Histoire litt\u00e9raire", "Folhetins", "Literature - History and criticism", "Literary translator"], "contacts": [{"organization": "Marques, Lucas de Castro", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/11449/236856"}, {"rel": "self", "type": "application/geo+json", "title": "11449/236856", "name": "item", "description": "11449/236856", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11449/236856"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-06T00:00:00Z"}}, {"id": "13946230", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:20Z", "type": "Journal Article", "created": "2013-06-11", "title": "Observations on Mechanism of Action of the Antifungal Peptide, Ro2-7758.", "description": "SummaryInhibitory action of the antifungal sulfur-containing peptide, Ro2-7758 (formerly X-5079C), against the growth of Mucor corymbifera was annulled by sulfite and cysteine, but not by sulfate or 96 other substances tested. Experiments with S35O4 showed that the drug had no effect on permeability of yeast cells to sulfate. However, production of S35O3 from S35O4 by a cell-free sulfate reductase system from yeast was first stimulated at low drug concentrations and then inhibited at higher concentrations. It was concluded that this action of the drug on sulfate reductase may be involved in its antibiotic activity.", "keywords": ["Antifungal Agents", "Mucor", "Sulfites", "Cysteine", "Peptides", "Fungicides", " Industrial", "3. Good health"], "contacts": [{"organization": "G R, GALE, S M, KENDALL, A M, WELCH,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/13946230"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Experimental%20Biology%20and%20Medicine", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "13946230", "name": "item", "description": "13946230", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/13946230"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1963-05-01T00:00:00Z"}}, {"id": "1854/LU-8743335", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:27Z", "type": "Report", "title": "Global maps of soil temperature", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km(2) resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km(2) pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10 degrees C (mean = 3.0 +/- 2.1 degrees C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 +/- 2.3 degrees C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 +/- 2.3 degrees C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["Technology and Engineering", "soil temperature", "Biology and Life Sciences", "soil-dwelling organisms", "SNOW-COVER", "MITIGATION", "MOISTURE", "FOREST", "weather stations", "LITTER DECOMPOSITION", "PERMAFROST", "near-surface temperatures", "PLANT-RESPONSES", "bioclimatic variables", "CLIMATIC CONTROLS", "Earth and Environmental Sciences", "temperature offset", "SUITABILITY", "global maps", "MICROCLIMATE", "CBCE", "microclimate"]}, "links": [{"href": "https://doi.org/1854/LU-8743335"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8743335", "name": "item", "description": "1854/LU-8743335", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8743335"}, {"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": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:27:27Z", "type": "Journal Article", "created": "2024-03-21", "title": "Environmental drivers and remote sensing proxies of post-fire thaw depth in Eastern Siberian larch forests", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Boreal fire regimes are intensifying because of climate change and the northern parts of boreal forests are underlain by permafrost. Boreal fires combust vegetation and organic soils, which insulate permafrost, and as such deepen the seasonally thawed active layer and can lead to further carbon emissions to the atmosphere. Current understanding of the environmental drivers of post-fire thaw depth is limited but of critical importance. In addition, mapping thaw depth over fire scars may enable a better understanding of the spatial variability in post-fire responses of permafrost soils. We assessed the environmental drivers of post-fire thaw depth using field data from a fire scar in a larch-dominated forest in the continuous permafrost zone in Eastern Siberia. Particularly, summer thaw depth was deeper in burned (mean = 127.3 cm, standard deviation (sd) = 27.7 cm) than in unburned (98.1 cm, sd = 26.9 cm) landscapes one year after the fire, yet the effect of fire was modulated by landscape and vegetation characteristics. We found deeper thaw in well-drained landscape positions, in open larch forest often intermixed with Scots pine, and in high severity burns. The environmental drivers, site moisture, forest type and density, and fire severity explained 73.4 % of the measured thaw depth variability at the study sites. In addition, we evaluated the relationships between field-measured thaw depth and several remote sensing proxies. Albedo, the differenced Normalized Burn Ratio (dNBR), land surface temperature (LST), and pre-fire Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 imagery together explained 66.3 % of the variability in field-measured thaw depth. Based on these remote sensing proxies and multiple linear regression analysis, we estimated thaw depth over the entire fire scar, and found that LST displayed particularly strong correlations with post-fire thaw depth (r = 0.65, p &lt; 0.01). Our study reveals some of the governing processes of post-fire thaw depth development and shows the capability of Landsat imagery to estimate thaw depth at a landscape scale.                         </p></article>", "keywords": ["Dynamic and structural geology", "QE1-996.5", "13. Climate action", "Science", "Q", "Geology", "QE500-639.5", "Deforestation", "15. Life on land", "Landsat", "Multiple linear regression", "Atmospheric temperature"]}, "links": [{"href": "https://esd.copernicus.org/articles/15/1459/2024/esd-15-1459-2024.pdf"}, {"href": "https://doi.org/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Dynamics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "name": "item", "description": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-21T00:00:00Z"}}, {"id": "1cd3d55f-db85-433b-a626-848ca4b4c6a3", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-13T11:22:13.577757", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-06-13 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-06-13 ore 00 UTC - Valido dalle ore 00 UTC del 2025-06-13 alle ore 00 UTC del 2025-06-16. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-06-13", "20250613t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-06-13-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250613T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/1cd3d55f-db85-433b-a626-848ca4b4c6a3"}, {"rel": "self", "type": "application/geo+json", "title": "1cd3d55f-db85-433b-a626-848ca4b4c6a3", "name": "item", "description": "1cd3d55f-db85-433b-a626-848ca4b4c6a3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1cd3d55f-db85-433b-a626-848ca4b4c6a3"}, {"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": "10.5281/zenodo.17826824", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:25:10Z", "type": "Dataset", "title": "Carbon Sequestration Potential in Arable Soils of the Czech Republic \u2013 Values Aggregated at the District Level", "description": "unspecifiedThe dataset presents the results of simulations assessing the carbon sequestration potential of arable soils in the Czech Republic, utilising the EPIC-IIASA CZ simulation platform. It consists of outputs derived from the modelling of various agronomic scenarios at the district level (LAU1), incorporating three climate scenarios: RCP 2.6, 4.5, and 8.5. The data reflect the effects of four model cropping systems, differing levels of nitrogen and manure fertilisation intensity, residue management, and irrigation on the principal parameter\u2014namely, the change in average carbon content within soil organic matter in the top 30 cm of soil during the periods 2040\u20132060 (or 2080\u20132100), compared to the reference average for 2000\u20132020. This parameter is expressed as tonnes of carbon per hectare (t C ha\u207b\u00b9). For a given cropping system and its variants, the values indicate the potential for carbon sequestration over 40- and 80-year timescales.  Structure of the database:       Column name    Meaning and description of values (categories)    Values Example      scenario    Climate scenario identifier     rcp26 / rcp45 / rcp85      timescale    Length of the period for which the value is calculated (years)    40 / 80      system    Code of the model cropping system (see detailed description)    CpCm1 / ApCm1 / CpRg1 / ApRg1      irrigation    Irrigation regime (rainfed, irrigated)    rf / irr      nfert    Nitrogen fertilisation level (Nn = none / Nl = low / Nm = moderate / Nh = high). Level Nh means that for each crop, the annual dose is set to the maximum N application limit according to the Nitrate Directive. Nm = 60% Nh, Nl = 30% Nh, Nn = 0% Nh.    Nn / Nl / Nm / Nh      fmfert    Share of total N dose applied in the form of manure (fm0 = 0 % / fm60 = 60 % / fm100 = 100 %).    fm0 / fm60 / fm100      baler    Post-harvest residue management (R0 = straw removed / R30 = 30 % remains in field / R60 = 60 % / R100 = 100 %)    R0 / R30 / R60 / R100      poly_id    Unique geographical code of the region (LAU 1 code).    CZ0100       value    Numeric value of the metric. Average increase (+) or decrease (-) of organic C content in the top 30 cm of soil (t ha-1)    4.989584358158098      The dataset contains 59,136 records.", "keywords": ["Carbon sequestration", "soil organic carbon", "carbon farming", "Climate change", "Modelling"], "contacts": [{"organization": "MADARAS, Mikul\u00e1\u0161, Skalsky, Rastislav, Balkovic, Juraj,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17826824"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17826824", "name": "item", "description": "10.5281/zenodo.17826824", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17826824"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-12-05T00:00:00Z"}}, {"id": "3129983189", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:28:36Z", "type": "Journal Article", "created": "2021-02-23", "title": "Using NDVI for the assessment of canopy cover in agricultural crops within modelling research", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "0106 biological sciences", "Meta-analysis", "Canopy cover", "NDVI", "Crop modelling", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences"]}, "links": [{"href": "https://doi.org/3129983189"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Computers%20and%20Electronics%20in%20Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3129983189", "name": "item", "description": "3129983189", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3129983189"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-01T00:00:00Z"}}, {"id": "10.1016/j.epsl.2015.12.030", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:16:43Z", "type": "Journal Article", "created": "2016-01-05", "title": "Estimation of the extraterrestrial 3He and 20Ne fluxes on Earth from He and Ne systematics in marine sediments", "description": "Abstract   Sediments contain interplanetary dust particles (IDPs) carrying extraterrestrial noble gases, such as  3 He, which have previously been used to estimate the IDP accretion flux over time and the duration of past environmental events. However, due to its high diffusivity, He can be lost by diffusion either due to frictional heating during entry in the atmosphere, or once it has been incorporated in the sediments. Therefore the absolute values of  3 He IDP fluxes cannot be known. Due to its lower diffusivity, Ne is less likely to be lost by diffusion than He and can potentially provide an absolute IDP flux value. Here, we studied the Ne and He isotopic composition of 21 sediments of different ages (3 to 38 Myr, 56 Myr and 183 Myr) in order to better constrain the retention of  3 He in such deposits. The samples are carbonates from 2 sites of the Integrated Ocean Drilling Program (IODP), which previously showed evidence of detectable extraterrestrial  3 He, and from the Sancerre core in the Paris basin. The  3 He/ 4 He,  20 Ne/ 22 Ne and  21 Ne/ 22 Ne ratios of decarbonated residues vary respectively from    0.09  \u00d7    10    \u2212  6      to    76.5  \u00d7    10    \u2212  6     ,    9.54  \u00b1  0.08    to    11.30  \u00b1  0.60    and from    0.0295  \u00b1  0.0001    to    0.0344  \u00b1  0.0003   . These isotopic compositions can be explained by a mixing between two terrestrial components (atmosphere and radiogenic He and nucleogenic Ne present in the terrigenous fractions) and an extraterrestrial component. The linear relationship between  20 Ne/ 22 Ne and  3 He/ 22 Ne ratios shows that the extraterrestrial component has a unique composition and is similar to the He and Ne composition of implanted solar wind. This composition is different from the individual stratospheric IDPs for which the Ne and He isotopic compositions have been measured. We suggest that this difference is due to a bias in the sampling of the individual IDPs previously analyzed toward the largest ones that are more likely to lose He during entry in the atmosphere. Our data further constrains the size of the majority of the IDPs to be less than    10    \u03bc  m    in diameter. In addition, the constant  3 He/ 22 Ne ratio of the extraterrestrial component present in the samples, which is similar to the implanted solar wind composition, suggests that no diffusive loss of  3 He occurred in the atmosphere or on the seafloor. Thus, neglecting any non-fractionating He and Ne loss by weathering and/or alteration of the host phases on the seafloor, the extraterrestrial  3 He and  20 Ne fluxes between 3 to 38 Myr ago are respectively    0.2  \u00b1  0.1  \u00d7    10    \u2212  12        cm    3        cm    \u2212  2        kyr    \u2212  1      and    0.2  \u00b1  0.1  \u00d7    10    \u2212  11        cm    3        cm    \u2212  2        kyr    \u2212  1     . During the sharp increases of the late Eocene and late Miocene, the IDP  3 He and  20 Ne fluxes reach values up to five times higher.", "keywords": ["[SDU] Sciences of the Universe [physics]", "13. Climate action", "sediments", "IDP", "helium", "neon", "14. Life underwater", "extraterrestrial flux", "implanted solar wind", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.epsl.2015.12.030"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20and%20Planetary%20Science%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.epsl.2015.12.030", "name": "item", "description": "10.1016/j.epsl.2015.12.030", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.epsl.2015.12.030"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-02-01T00:00:00Z"}}, {"id": "383c70fe-7169-43da-89da-e45b126f3a70~~1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:35:20Z", "type": "Dataset", "language": "de", "title": "GcB\u00dcK400 \u2014 Zinc in the upper floor", "description": "Zinc is an essential trace element for plants, animals and humans, which, however, can have a toxic effect on plants and microorganisms at extremely high levels. The concentration of Zn in the upper continental crust (Clark value) is 52\u00a0mg/kg, but it can vary greatly depending on the type of rock. The mean Zn (median) grades of the Saxon main rock types range from 11 to 140\u00a0mg/kg, while the regional Clarke of the Ore Mountains is approximately 79\u00a0mg/kg. Sphalerite (zinc aperture) leading polymetallic lathers can locally lead to additional geogenic Zn enrichments in the soils. Anthropogenic Zn entries are mainly carried out by iron and non-ferrous metallurgy or by the Zn-processing industries (colours, alloys, electroplating) and by large combustion plants. In the area of agglomerations, Zn enrichments are relatively common. Anthropogenic Zn entries are possible in agriculture through the use of organic and mineral fertilisers. For uncontaminated soils, Zn levels of 10 to 80\u00a0mg/kg are considered normal. The regional distribution of the Zn content in the Saxon soils is mainly determined by the geogenic embossing of the substrates; low to medium grades can be expected over the periglacial sands and clays in the north and the loess soils in middle axes (10 to 50\u00a0mg/kg) and weathering soils above the solid rocks of the Ore Mountains/Vogtland (50 to 150\u00a0mg/kg). Within the basement units, significant positive Zn anomalies occur via the polymetallic deposits of the Ore Mountains, depending on the intensity of the mineralisation (Freiberg, Annaberg-Buchholz \u2014 Marienberg, Aue \u2014 Schwarzenberg). Soils over substrates with extremely low Zn content (Granite of Eibenstock, Orthogneise of the Ore Mountains Central Zone, Easter Mountain Eruptive Complex, Cretan sandstones) appear as negative Zn anomalies in the map image. Reinforced Zn accumulators are to be detected in the floodplain floors of the trough system. Due to the higher geogenic basic contents in the water catchment area, the occurrence of Zn-conducting polymetallic minerals and in particular the mining and metallurgical activity in the Freiberg region, high concentrations of Zn (median content 370 and 240\u00a0mg/kg respectively) occur mainly in the meadows of the Freiberger and United Mulde. No test and measure values have been established for the soil-human and soil-plant effects pathways for total levels in the Federal Soil Protection and Contaminant Ordinance (BBodSchV), as Zn is of little importance in the risk assessment.", "keywords": ["anorganischer-schadstoff", "boden", "chemie", "chemisches-element", "de", "geologie", "opendata", "zink", "zn"]}, "links": [{"href": "https://luis.sachsen.de/boden/geodatendownload.html"}, {"href": "http://data.europa.eu/88u/dataset/383c70fe-7169-43da-89da-e45b126f3a70~~1"}, {"href": "https://geoportal.sachsen.de/md/383c70fe-7169-43da-89da-e45b126f3a70"}, {"rel": "self", "type": "application/geo+json", "title": "383c70fe-7169-43da-89da-e45b126f3a70~~1", "name": "item", "description": "383c70fe-7169-43da-89da-e45b126f3a70~~1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/383c70fe-7169-43da-89da-e45b126f3a70~~1"}, {"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": "10.1002/jsfa.4533", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:08Z", "type": "Journal Article", "created": "2011-07-27", "title": "Influence Of Fertilisation Regimes On A Nosz-Containing Denitrifying Community In A Rice Paddy Soil", "description": "Abstract<p>BACKGROUND: Denitrification is a microbial process that has received considerable attention during the past decade since it can result in losses of added nitrogen fertilisers from agricultural soils. Paddy soil has been known to have strong denitrifying activity, but the denitrifying microorganisms responsible for fertilisers in paddy soil are not well known. The objective of this study was to explore the impacts of 17\uffe2\uff80\uff90year application of inorganic and organic fertiliser (rice straw) on the abundance and composition of a nosZ\uffe2\uff80\uff90denitrifier community in paddy soil. Soil samples were collected from CK plots (no fertiliser), N (nitrogen fertiliser), NPK (nitrogen, phosphorus and potassium fertilisers) and NPK + OM (NPK plus organic matter). The nitrous oxide reductase gene (nosZ) community composition was analysed using terminal restriction fragment length polymorphism, and the abundance was determined by quantitative PCR.</p><p>RESULTS: Both the largest abundance of nosZ\uffe2\uff80\uff90denitrifier and the highest potential denitrifying activity (PDA) occurred in the NPK + OM treatment with about four times higher than that in the CK and two times higher than that in the N and NPK treatments (no significant difference). Denitrifying community composition differed significantly among fertilisation treatments except for the comparison between CK and N treatments. Of the measured abiotic factors, total organic carbon was significantly correlated with the observed differences in community composition and abundance (P &lt; 0.01 by Monte Carlo permutation).</p><p>CONCLUSION: This study shows that the addition of different fertilisers affects the size and composition of the nosZ\uffe2\uff80\uff90denitrifier community in paddy soil. Copyright \uffc2\uffa9 2011 Society of Chemical Industry</p>", "keywords": ["2. Zero hunger", "0301 basic medicine", "0303 health sciences", "Bacteria", "Nitrogen", "0402 animal and dairy science", "Agriculture", "Oryza", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "Carbon", "Soil", "03 medical and health sciences", "Genes", " Bacterial", "Denitrification", "0405 other agricultural sciences", "Fertilizers", "Oxidoreductases", "Monte Carlo Method", "Polymorphism", " Restriction Fragment Length", "Soil Microbiology"]}, "links": [{"href": "https://doi.org/10.1002/jsfa.4533"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20the%20Science%20of%20Food%20and%20Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/jsfa.4533", "name": "item", "description": "10.1002/jsfa.4533", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/jsfa.4533"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-07-27T00:00:00Z"}}, {"id": "10.1002/ldr.3136", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:09Z", "type": "Journal Article", "created": "2018-08-18", "title": "Agroforestry systems: Meta-analysis of soil carbon stocks, sequestration processes, and future potentials", "description": "Abstract<p>Agroforestry (AF) has the potential to restore degraded lands, provide a broader range of ecosystem goods and services such as carbon (C) sequestration and high biodiversity, and increase soil fertility and ecosystem stability through additional C input from trees, erosion prevention, and microclimate improvement. Advantages and processes for global C sequestration in AF are unknown. We used a meta\uffe2\uff80\uff90analysis of 427 soil C stock data pairs grouped into four main AF systems\uffe2\uff80\uff94alley cropping, windbreaks, silvopastures, and homegardens\uffe2\uff80\uff94and evaluated changes in AF and adjacent control cropland or pasture. Mean soil C stocks in AF (1\uffe2\uff80\uff90m depth) were 126\uffc2\uffa0Mg\uffc2\uffa0C\uffc2\uffb7ha\uffe2\uff88\uff921, which is 19% more than that in cropland or pasture. The highest C stocks in soil were in subtropical homegardens, AF with younger trees, and topsoil (0\uffe2\uff80\uff9320\uffc2\uffa0cm). Increased soil C stocks in AF were lower than aboveground C stocks in most AF systems, except alley cropping. Homegardens stored the highest C in both aboveground and belowground, especially in the subsoil (20\uffe2\uff80\uff93100\uffc2\uffa0cm). Advantages of AF ecosystem services focusing on mechanisms of belowground C sequestration were analyzed. AF could store 5.3\uffc2\uffa0\uffc3\uff97\uffc2\uffa0109\uffc2\uffa0Mg additional C in soil on 944\uffc2\uffa0Mha globally, with most in the tropics and subtropics. AF systems could greatly contribute to global soil C sequestration if used in larger areas. Future investigations of AF should include (a) mechanistic\uffe2\uff80\uff90 and process\uffe2\uff80\uff90based studies (instead of common monitoring and inventories), (b) models linking forest and crop growth with soil water and C and nutrient cycling, and (c) accurate assessments of the AF area worldwide based on the remote sensing approaches.</p>", "keywords": ["meta-analysis", "2. Zero hunger", "570", "550", "13. Climate action", "sustainable land use", "homegardens", "0401 agriculture", " forestry", " and fisheries", "agroforestry management", "04 agricultural and veterinary sciences", "15. Life on land", "ecosystem services", "carbon sequestration"]}, "links": [{"href": "https://doi.org/10.1002/ldr.3136"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Degradation%20%26amp%3B%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ldr.3136", "name": "item", "description": "10.1002/ldr.3136", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ldr.3136"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-04T00:00:00Z"}}, {"id": "10.1016/j.agwat.2016.01.023", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:15:58Z", "type": "Journal Article", "created": "2016-02-24", "title": "Grain Yield And Water Use Efficiency Of Maize As Influenced By Different Irrigation Regimes Through Sprinkler Irrigation Under Temperate Climate", "description": "In Vojvodina region, water deficit during the growing season is a major factor limiting maize production. Therefore, to achieve the ideal soil water content in this region, it is of crucial importance to optimize irrigation. The effects of different irrigation levels with sprinkler irrigation system on crop yield, yield components, water use, water (WUE) and irrigation water use (IWUE) efficiency of maize (Zea mays L.) were investigated in Vojvodina (northern Serbia), on a Calcaric Chernozem soil in temperate environment for 3 consecutive years (2006\u20132008). Maize was subjected to four irrigation regimes, as follows: non-limited irrigation (I100), 75% of non-limited irrigation (I75), 50% of non-limited irrigation (I50), and rainfed (non-irrigated) as the control (I0). The irrigation treatments were arranged in a complete randomized block design with 4 replicates. Results showed that maize grown in rainfed conditions had high annual variability, mainly due to amount of rainfall and its distribution during the crop-growing seasons. A significant irrigation effect was found for yield, yield components and others investigated parameters under study. Water stress had significant impact on yield response: as an average of the three years, a grain yield increase of 47.8, 32.8, and 22.9% was observed in I100, I75 and I50 treatments compared to rainfed (I0) treatment, respectively. Yield increased linearly with seasonal crop evapotranspiration and irrigation amount. Furthermore, WUE is maximized with a moderate water deficit (I50), while IWUE is the highest in I100 treatment. The deficit irrigation stress index, DISI, decreased with increasing irrigation rate. The results revealed that irrigation is necessary for maize cultivation because rainfall is insufficient to meet the crop water needs in Vojvodina. In addition, the study indicated that the irrigation regime of 25% water saving (I75) could ensure satisfactory grain yield of maize and increment of WUE.", "keywords": ["0106 biological sciences", "2. Zero hunger", "Yield response factor", "Yield components", "IWUE", "13. Climate action", "15. Life on land", "Deficit irrigation", "Zea mays", "01 natural sciences", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2016.01.023"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2016.01.023", "name": "item", "description": "10.1016/j.agwat.2016.01.023", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2016.01.023"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-05-01T00:00:00Z"}}, {"id": "10.1007/s00244-013-9903-7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:25Z", "type": "Journal Article", "created": "2013-04-22", "title": "Nitrous Oxide Emissions From Yellow Brown Soil As Affected By Incorporation Of Crop Residues With Different Carbon-To-Nitrogen Ratios: A Case Study In Central China", "description": "To investigate the influence of crop residues decomposition on nitrous oxide (N2O) emission, a field study was performed with application of crop residues with different C:N ratios in a bare yellow brown soil at the experimental station of Zhangjiachong at Zigui, China. We set up six experimental treatments: no crop residue (CK), rapeseed cake (RC), potato stalk (PS), rice straw (RS), wheat straw (WS), and corn straw (CS). The carbon (C) to nitrogen (N) ratios of these crop residues were 7.5, 32.9, 40.4, 65.7, and 90.9, respectively. Nitrous oxide fluxes were measured using a static closed chamber method. N2O emissions were significantly enhanced by incorporation of crop residues. Cumulative N2O emissions negatively correlated with C:N ratio (R (2) = 0.9821) of the crop residue, but they were positively correlated with average concentrations of dissolved organic carbon and microbial biomass carbon. Nitrogen emission fraction, calculated as N2O-N emissions originated from the crop residues N, positively correlated with C:N ratio of the residues (P < 0.05). Soil temperature did, whereas soil moisture did not, control the residue's induced N2O emissions because a significant correlation (P < 0.01) existed between soil temperature and N2O emissions in all treatments except the control. In contrast, a significant relationship between soil moisture and N2O emissions was found in the control only. Furthermore, N2O emission significantly correlated (P < 0.05) with NO3 (-)-N, and NH4 (+)-N contents from all residue treatments. These results indicate that (1) crop residues with distinct carbon and nitrogen contents can significantly alter soil N2O flux rates; and (2) soil biotic as well as abiotic variables are critical in determining soil-atmospheric N2O emissions after crop residue incorporation into soil.", "keywords": ["Crops", " Agricultural", "2. Zero hunger", "China", "Time Factors", "Nitrogen", "Nitrous Oxide", "04 agricultural and veterinary sciences", "15. Life on land", "Carbon", "Soil", "13. Climate action", "Animals", "0401 agriculture", " forestry", " and fisheries", "Seasons", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1007/s00244-013-9903-7"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Archives%20of%20Environmental%20Contamination%20and%20Toxicology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00244-013-9903-7", "name": "item", "description": "10.1007/s00244-013-9903-7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00244-013-9903-7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-04-23T00:00:00Z"}}, {"id": "10.1007/s00374-009-0370-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:30Z", "type": "Journal Article", "created": "2009-03-25", "title": "Soil Biological Quality Of Grassland Fertilized With Adjusted Cattle Manure Slurries In Comparison With Organic And Inorganic Fertilizers", "description": "We studied the effect of five fertilizers (including two adjusted manure slurries) and an untreated control on soil biota and explored the effect on the ecosystem services they provided. Our results suggest that the available N (NO                   3                   \u2212                  and NH                   4                   +                 ) in the soil plays a central role in the effect of fertilizers on nematodes and microorganisms. Microorganisms are affected directly through nutrient availability and indirectly through grass root mass. Nematodes are affected indirectly through microbial biomass and grass root mass. A lower amount of available N in the treatment with inorganic fertilizer was linked to a higher root mass and a higher abundance and proportion of herbivorous nematodes. A higher amount of available N in the organic fertilizer treatments resulted in a twofold higher bacterial activity (measured as bacterial growth rate, viz. thymidine incorporation), a higher proportion of bacterivorous nematodes, a 30% higher potential N mineralization (aerobic incubation), and 25\u201350% more potentially mineralizable N (anaerobic incubation). Compared to inorganic fertilizer, organic fertilization increased the C total, the N total, the activity of decomposers, and the supply of nutrients via the soil food web. Within the group of organic fertilizers, there was no significant difference in C total, abundances of soil biota, and the potential N mineralization rate. There were no indications that farmyard manure or the adjusted manure slurries provided the ecosystem service \u201csupply of nutrients\u201d better than normal manure slurry. Normal manure slurry provided the highest bacterial activity and the highest amount of mineralizable N and it was the only fertilizer resulting in a positive trend in grass yield over the years\u00a02000\u20132005. The number of earthworm burrows was higher in the treatments with organic fertilizers compared to the one with the inorganic fertilizer, which suggests that organic fertilizers stimulate the ecosystem service of water regulation more than inorganic fertilizer. The trend towards higher epigeic earthworm numbers with application of farmyard manure and one of the adjusted manure slurries, combined with the negative relation between epigeic earthworms and bulk density and a significantly lower penetration resistance in the same fertilizer types, is preliminary evidence that these two organic fertilizer types contribute more to the service of soil structure maintenance than inorganic fertilizer.", "keywords": ["2. Zero hunger", "nitrogenous fertilizers", "dynamics", "04 agricultural and veterinary sciences", "15. Life on land", "pig slurry", "6. Clean water", "earthworms oligochaeta", "13. Climate action", "nematodes", "0401 agriculture", " forestry", " and fisheries", "mineralization", "microorganisms", "term", "management", "biodiversity"]}, "links": [{"href": "https://doi.org/10.1007/s00374-009-0370-2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biology%20and%20Fertility%20of%20Soils", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00374-009-0370-2", "name": "item", "description": "10.1007/s00374-009-0370-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00374-009-0370-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-03-26T00:00:00Z"}}, {"id": "10.1007/s10021-013-9650-7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:42Z", "type": "Journal Article", "created": "2013-02-21", "title": "Stimulation Of Different Functional Groups Of Bacteria By Various Plant Residues As A Driver Of Soil Priming Effect", "description": "The turnover of organic matter in soil depends on the activity of microbial decomposers. However, little is known about how modifications of the diversity of soil microbial communities induced by fresh organic matter (FOM) inputs can regulate carbon cycling. Here, we investigated the decomposition of two 13C labeled crop residues (wheat and alfalfa) and the dynamics of the genetic structure and taxonomic composition of the soil bacterial communities decomposing 13C labeled FOM and native unlabeled soil organic matter (SOM), respectively. It was achieved by combining the stable isotope probing method with molecular tools (DNA genotyping and pyrosequencing of 16S rDNA). Although a priming effect (PE) was always induced by residue addition, its intensity increased with the degradability of the plant residue. The input of both wheat and alfalfa residues induced a rapid dynamics of FOM-degrading communities, corresponding to the stimulation of bacterial phyla which have been previously described as copiotrophic organisms. However, the dynamics and the identity of the bacterial groups stimulated depended on the residue added, with Firmicutes dominating in the wheat treatment and Proteobacteria dominating in the alfalfa treatment after 3\u00a0days of incubation. In both treatments, SOM-degrading communities were dominated by Acidobacteria, Verrucomicrobia, and Gemmatimonadetes phyla which have been previously described as oligotrophic organisms. An early stimulation of SOM-degrading populations mainly belonging to Firmicutes and Bacteroidetes groups was observed in the alfalfa treatment whereas no change occurred in the wheat treatment. Our findings support the hypothesis that the succession of bacterial taxonomic groups occurring in SOM- and FOM-degrading communities during the degradation process may be an important driver of the PE, and consequently of carbon dynamics in soil.", "keywords": ["0301 basic medicine", "2. Zero hunger", "570", "0303 health sciences", "[SDE.MCG]Environmental Sciences/Global Changes", "bacterial diversity", "[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study", "15. Life on land", "[SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology", "630", "soil", "[SDE.MCG] Environmental Sciences/Global Changes", "03 medical and health sciences", "pyrosequencing", "[SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "soil organic matter", "carbon cycle", "[SDU.STU.GC] Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "[SDV.MP.BAC] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "stable isotope probing"]}, "links": [{"href": "https://doi.org/10.1007/s10021-013-9650-7"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecosystems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10021-013-9650-7", "name": "item", "description": "10.1007/s10021-013-9650-7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10021-013-9650-7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-02-22T00:00:00Z"}}, {"id": "07c70060-8df8-4f3f-befc-941f8b9e1891", "type": "Feature", "geometry": null, "properties": {"updated": "2018-10-31", "type": "Dataset", "title": "Forest Functions in Saxony", "description": "A Web Map Service (WMS) of the state enterprise Sachsenforst. The map service visualises the forest functions recorded and identified in the framework of Saxon forest function mapping (WFK) on forest surfaces (wood floor and non-wood floor). The forest functions are divided into the areas of soil, water, air, nature, landscape, culture and recreation. The individual forest functions are divided into legal and special forest functions. The presentation of the forest functions is based on the own data of the state enterprise Sachsenforst as well as on external data from the forestry and specialist authorities.", "formats": [{"name": "WMS_SRVC"}], "keywords": ["anlagenschutzfunktion", "anlagenschutzwald", "bestattungswald", "biospha\u0308renreservat", "biospha\u0308renreservat-zone-i", "biospha\u0308renreservat-zone-ii", "biospha\u0308renreservat-zone-iii", "biospha\u0308renreservat-zone-iv", "boden", "bodenbedeckung", "bodennutzung", "bodenschutz", "bodenschutzfunktion", "bodenschutzwald", "de", "denkmalschutzfunktion", "erhaltung-der-natu\u0308rlichen-pflanzen-und-tierwelt", "erholungsfunktion-stufe-i", "erholungsfunktion-stufe-ii", "erholungswald", "erntebestand", "ffh-arthabitat", "ffh-gebiet", "ffh-lebensraumtyp", "forst", "forstnutzung", "forstwirtschaft", "forstwirtschaftliche-produktion", "freistaat-sachsen", "generhaltungsfunktion", "geschu\u0308tztes-biotop", "gewa\u0308sser", "gewa\u0308sserschutz", "grundwasserschutz", "heilquelle-zone-a", "heilquelle-zone-b", "heilquelle-zone-i", "heilquelle-zone-ii", "heilquelle-zone-iii", "heilquellenschutzgebiete", "historische-waldbauform", "hochwasserentstehungsgebiet", "hochwasserschutzfunktion", "immissionsschutzfunktion", "klimaschutz", "landschaft", "landschaftsbild-pra\u0308gender-wald", "landschaftsschutz", "landschaftsschutzgebiet", "la\u0308rmschutzfunktion", "lebensra\u0308ume-und-biotope", "lichtschutzfunktion", "lokale-klimaschutzfunktion", "luft", "nationalpark", "nationalpark-kernzone", "nationalpark-naturzone-a", "nationalpark-naturzone-b", "nationalpark-pflegezone", "naturdenkmal", "naturgebiet", "naturpark", "naturpark-entwicklungszone", "naturpark-zone-i", "naturpark-zone-ii", "naturschutz", "naturschutzgebiet", "naturwaldzelle", "oberfla\u0308chengewasser", "privatwald", "regionale-klimaschutzfunktion", "reservat", "restwald-in-waldarmer-region", "samenplantage", "schutz-des-wassereinzugsbereichs", "schutzgebiet", "schutzgebiete", "spa-gebiet", "staatsforst", "trinkwasserschutzgebiet", "trinkwasserschutzgebiete", "trinkwasserschutzgebiete-fl", "trinkwasserschutzgebiete-gw", "trinkwasserschutzgebiete-ts", "twsg-flie\u00dfgewa\u0308sser-zone-i", "twsg-flie\u00dfgewa\u0308sser-zone-ii", "twsg-flie\u00dfgewa\u0308sser-zone-iii", "twsg-grundwasser-zone-i", "twsg-grundwasser-zone-ii", "twsg-grundwasser-zone-iii", "twsg-grundwasser-zone-iii-a", "twsg-grundwasser-zone-iii-b", "twsg-talsperre-zone-i", "twsg-talsperre-zone-ii", "twsg-talsperre-zone-ii-a", "twsg-talsperre-zone-ii-b", "twsg-talsperre-zone-iii", "umweltschutz", "u\u0308berschwemmungsgebiet", "wald", "wald-auf-renaturierungsfla\u0308che", "wald-fu\u0308r-forschung-und-lehre", "waldbestand", "waldbrandschutzfunktion", "waldfunktionen", "waldfunktionenkartierung-(wfk)", "waldschutz", "waldschutzgebiet", "waldwirtschaft", "wasser", "wasserschutz", "wasserschutzfunktion", "wasserschutzgebiet", "wasserschutzgebiete", "wertvolles-biotop"], "contacts": [{"organization": "Graichen, Beate", "roles": ["creator"]}]}, "links": [{"href": "https://www.forsten.sachsen.de/kartendienste/waldfunktionen/MapServer/WMSServer"}, {"href": "http://data.europa.eu/88u/dataset/07c70060-8df8-4f3f-befc-941f8b9e1891"}, {"rel": "self", "type": "application/geo+json", "title": "07c70060-8df8-4f3f-befc-941f8b9e1891", "name": "item", "description": "07c70060-8df8-4f3f-befc-941f8b9e1891", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/07c70060-8df8-4f3f-befc-941f8b9e1891"}, {"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.envpol.2021.116827", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:16:41Z", "type": "Journal Article", "created": "2021-03-09", "title": "Cocktails of pesticide residues in conventional and organic farming systems in Europe \u2013 Legacy of the past and turning point for the future", "description": "<p>&amp;lt;p&amp;gt;Considering that pesticides have been used in Europe for over 70 years, a system for monitoring pesticide residues in EU soils and their effects on soil health is long overdue. In an attempt to address this problem, we tested 340 EU agricultural topsoil samples for multiple pesticide residues. These samples originated from 4 representative EU case study sites (CSS), which covered 3 countries and four of the main EU crops: vegetable and orange production in Spain (S-V and S-O, respectively), grape production in Portugal (P-G), and potato production in the Netherlands (N-P). Soil samples were collected between 2015 and 2018 after harvest or before the start of the growing season, depending on the CSS. Conventional and organic farming results were compared in S-V, S-O and N-P. Soils from conventional farms presented mostly mixtures of pesticide residues, with a maximum of 16 residues/sample. Soils from organic farms had significantly fewer residues, with a maximum of 5 residues/sample. The residues with the highest frequency of detection and the highest content in soil were herbicides: glyphosate and its main metabolite AMPA (P-G, N-P, S-O), and pendimethalin (S-V). Total residue content in soil reached values of 0.8 mg kg-1 for S-V, 2 mg kg-1 for S-O and N-P, and 12 mg kg-1 for P-G. Organic soils presented 70-90% lower residue concentrations than the corresponding conventional soils. There is a severe knowledge gap concerning the effects of the accumulated and complex mixtures of pesticide residues found in soil on soil biota and soil health. Safety benchmarks should be defined and introduced into (soil) legislation as soon as possible. Soil remediation techniques should be developed to keep the levels of pesticide residues below such benchmarks. Furthermore, the process of transitioning to organic farming should take into consideration the residue mixtures and their residence time in soil. &amp;amp;#160;&amp;lt;/p&amp;gt;</p>", "keywords": ["2. Zero hunger", "Organic Agriculture", "Portugal", "Pesticide Residues", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "EU agricultural soils", "Europe", "Soil", "Mixtures of pesticide residues", "Spain", "13. Climate action", "Mixtures of pesticide residues; EU agricultural soils Organic", " conventional farming", "Soil Pollutants", "0401 agriculture", " forestry", " and fisheries", "Organic and conventional farming", "Netherlands"]}, "links": [{"href": "https://doi.org/10.1016/j.envpol.2021.116827"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Pollution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.envpol.2021.116827", "name": "item", "description": "10.1016/j.envpol.2021.116827", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.envpol.2021.116827"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-03T00:00:00Z"}}, {"id": "10.1007/s00122-021-03815-0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:24Z", "type": "Journal Article", "created": "2021-03-25", "title": "Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum\u00a0sp.) with information on resistances to soilborne barley mosaic viruses", "description": "Abstract                 Key message                 <p>Genomic prediction with special weight of major genes is a valuable tool to populate bio-digital resource centers.</p>                                Abstract                 <p>Phenotypic information of crop genetic resources is a prerequisite for an informed selection that aims to broaden the genetic base of the elite breeding pools. We investigated the potential of genomic prediction based on historical screening data of plant responses against the Barley yellow mosaic viruses for populating the bio-digital resource center of barley. Our study includes dense marker data for 3838 accessions of winter barley, and historical screening data of 1751 accessions for Barley yellow mosaic virus (BaYMV) and of 1771 accessions for Barley mild mosaic virus (BaMMV). Linear mixed models were fitted by considering combinations for the effects of genotypes, years, and locations. The best linear unbiased estimations displayed a broad spectrum of plant responses against BaYMV and BaMMV. Prediction abilities, computed as correlations between predictions and observed phenotypes of accessions, were low for the marker-assisted selection approach amounting to 0.42. In contrast, prediction abilities of genomic best linear unbiased predictions were high, with values of 0.62 for BaYMV and 0.64 for BaMMV. Prediction abilities of genomic prediction were improved by up to\uffe2\uff80\uff89~\uffe2\uff80\uff895% using W-BLUP, in which more weight is given to markers with significant major effects found by association mapping. Our results outline the utility of historical screening data and W-BLUP model to predict the performance of the non-phenotyped individuals in genebank collections. The presented strategy can be considered as part of the different approaches used in genebank genomics to valorize genetic resources for their usage in disease resistance breeding and research.</p>", "keywords": ["Genetic Markers", "0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Genotype", "Chromosome Mapping", "Genetic Variation", "Hordeum", "Genomics", "Potyviridae", "Linkage Disequilibrium", "Plant Breeding", "03 medical and health sciences", "Phenotype", "Databases", " Genetic", "Original Article", "Genetic Association Studies", "Disease Resistance", "Plant Diseases"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1007/s00122-021-03815-0.pdf"}, {"href": "https://doi.org/10.1007/s00122-021-03815-0"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Theoretical%20and%20Applied%20Genetics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00122-021-03815-0", "name": "item", "description": "10.1007/s00122-021-03815-0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00122-021-03815-0"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-25T00:00:00Z"}}, {"id": "10.1007/s00248-003-9001-x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:25Z", "type": "Journal Article", "created": "2004-06-15", "title": "Microbial Community Structure And Oxidative Enzyme Activity In Nitrogen-Amended North Temperate Forest Soils", "description": "Large regions of temperate forest are subject to elevated atmospheric nitrogen (N) deposition which can affect soil organic matter dynamics by altering mass loss rates, soil respiration, and dissolved organic matter production. At present there is no general model that links these responses to changes in the organization and operation of microbial decomposer communities. Toward that end, we studied the response of litter and soil microbial communities to high levels of N amendment (30 and 80 kg ha(-1) yr(-1)) in three types of northern temperate forest: sugar maple/basswood (SMBW), sugar maple/red oak (SMRO), and white oak/black oak (WOBO). We measured the activity of extracellular enzymes (EEA) involved directly in the oxidation of lignin and humus (phenol oxidase, peroxidase), and indirectly, through the production of hydrogen peroxide (glucose oxidase, glyoxal oxidase). Community composition was analyzed by extracting and quantifying phospholipid fatty acids (PLFA) from soils. Litter EEA responses at SMBW sites diverged from those at oak-bearing sites (SMRO, BOWO), but the changes were not statistically significant. For soil, EEA responses were consistent across forests types: phenol oxidase and peroxidase activities declined as a function of N dose (33-73% and 5-41%, respectively, depending on forest type); glucose oxidase and glyoxal oxidase activities increased (200-400% and 150-300%, respectively, depending on forest type). Principal component analysis (PCA) ordinated forest types and treatment responses along two axes; factor 1 (44% of variance) was associated with phenol oxidase and peroxidase activities, factor 2 (31%) with glucose oxidase. Microbial biomass did not respond to N treatment, but nine of the 23 PLFA that formed >1 mol% of total biomass showed statistically significant treatment responses. PCA ordinated forest types and treatment responses along three axes (36%, 26%, 12% of variance). EEA factors 1 and 2 correlated negatively with PLFA factor 1 ( r = -0.20 and -0.35, respectively, n = 108) and positively with PLFA factor 3 ( r = +0.36 and +0.20, respectively, n = 108). In general, EEA responses were more strongly tied to changes in bacterial PLFA than to changes in fungal PLFA. Collectively, our data suggests that N inhibition of oxidative activity involves more than the repression of ligninase expression by white-rot basidiomycetes.", "keywords": ["Michigan", "Nitrogen", "Science", "Ecology and Evolutionary Biology", "Nature Conservation", "Microbiology", "Trees", "Soil", "Geoecology/Natural Processes", "Health Sciences", "Cellular and Developmental Biology", "Ecosystem", "Phospholipids", "Soil Microbiology", "2. Zero hunger", "Analysis of Variance", "Principal Component Analysis", "Ecology", "Life Sciences", "Natural Resources and Environment", "Molecular", "04 agricultural and veterinary sciences", "15. Life on land", "Enzymes", "13. Climate action", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://doi.org/10.1007/s00248-003-9001-x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microbial%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00248-003-9001-x", "name": "item", "description": "10.1007/s00248-003-9001-x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00248-003-9001-x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2004-04-19T00:00:00Z"}}, {"id": "10.1007/s11104-022-05594-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:15:13Z", "type": "Journal Article", "created": "2022-07-29", "title": "Evaluating soil evaporation and transpiration responses to alternate partial rootzone drying to minimise water losses", "description": "Abstract                 Purpose                 <p>Partial rootzone drying (PRD) typically alternates the dry and irrigated parts of the rootzone, but how plant physiology and soil evaporation respond to this alternation are poorly understood.</p>                                Methods                 <p>Dwarf tomatoes were grown in small split pots comprising two 250\uffc2\uffa0cm3 compartments and fully irrigated (WW: 100% ETc) or subjected to three deficit irrigation treatments (75% ETc): homogeneous rootzone drying (HRD; irrigation evenly distributed); fixed PRD (PRD-F, irrigation applied to one fixed compartment); alternated PRD (PRD-A: as PRD-F but alternating the irrigated compartment every three days). Stem diameter and evapotranspiration were monitored during alternation cycles. The day after alternating the irrigated side of the root system, whole-plant gas exchange and leaf water potential were measured following step increments of vapour pressure deficit.</p>                                Results                 <p>Alternation did not affect stem diameter contractions or evapotranspiration, which were lower in HRD than in the two PRD treatments. However, soil evaporation was higher in HRD and PRD-A after alternation than in PRD-F. Following alternation, higher soil evaporation was counteracted by decreased transpiration compared with fixed PRD, despite similar overall soil water content. VPD increments did not change this pattern.</p>                                Conclusion                 <p>Irrigation placement determined soil moisture distribution, which in turn affected soil evaporation and whole plant gas exchange. Optimising the frequency of PRD alternation to maximise water savings while ensuring productive water use needs to consider how soil moisture distribution affects both soil evaporation and plant water use.</p>", "keywords": ["580", "Irrigation efficiency", "0106 biological sciences", "2. Zero hunger", "Evapotranspiration", "Stem diameter variations", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "630", "6. Clean water", "0401 agriculture", " forestry", " and fisheries", "Plant water status", "Deficit irrigation"]}, "links": [{"href": "https://eprints.lancs.ac.uk/id/eprint/174395/1/Pu_rtolas_final_manuscript_1_.pdf"}, {"href": "https://link.springer.com/content/pdf/10.1007/s11104-022-05594-z.pdf"}, {"href": "https://doi.org/10.1007/s11104-022-05594-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11104-022-05594-z", "name": "item", "description": "10.1007/s11104-022-05594-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-022-05594-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-27T00:00:00Z"}}, {"id": "10.1007/s10021-015-9855-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:14:42Z", "type": "Journal Article", "created": "2015-03-09", "title": "Defoliation And Soil Compaction Jointly Drive Large-Herbivore Grazing Effects On Plants And Soil Arthropods On Clay Soil", "description": "In addition to the well-studied impacts of defecation and defoliation, large herbivores also affect plant and arthropod communities through trampling, and the associated soil compaction. Soil compaction can be expected to be particularly important on wet, fine-textured soils. Therefore, we established a full factorial experiment of defoliation (monthly mowing) and soil compaction (using a rammer, annually) on a clay-rich salt marsh at the Dutch coast, aiming to disentangle the importance of these two factors. Additionally, we compared the effects on soil physical properties, plants, and arthropods to those at a nearby cattle-grazed marsh under dry and under waterlogged conditions. Soil physical conditions of the compacted plots were similar to the conditions at cattle-grazed plots, showing decreased soil aeration and increased waterlogging. Soil salinity was doubled by defoliation and quadrupled by combined defoliation and compaction. Cover of the dominant tall grass Elytrigia atherica was decreased by 80% in the defoliated plots, but cover of halophytes only increased under combined defoliation and compaction. Effects on soil micro-arthropods were most severe under waterlogging, showing a fourfold decrease in abundance and a smaller mean body size under compaction. Although the combined treatment of defoliation and trampling indeed proved most similar to the grazed marsh, large discrepancies remained for both plant and soil fauna communities, presumably because of colonization time lags. We conclude that soil compaction and defoliation differently affect plant and arthropod communities in grazed ecosystems, and that the magnitude of their effects depends on herbivore density, productivity, and soil physical properties.", "keywords": ["COLLEMBOLA", "0106 biological sciences", "570", "wadden sea", "GRASSLAND", "growth", "cow", "DIVERSITY", "01 natural sciences", "630", "diversity", "Aranaea", "simulated grazing", "SALT-MARSH", "MOUNTAIN PASTURES", "MANAGEMENT", "Environmental Chemistry", "Acari", "NITROGEN MINERALIZATION", "nitrogen mineralization", "Ecology", " Evolution", " Behavior and Systematics", "2. Zero hunger", "macro-detritivores", "mountain pastures", "Ecology", "COW", "national", "collembola", "WADDEN SEA", "15. Life on land", "Coleoptera", "salt-marsh", "Collembola", "GROWTH", "grassland", "management"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/72900/1/Published_Version.PDF"}, {"href": "https://doi.org/10.1007/s10021-015-9855-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecosystems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10021-015-9855-z", "name": "item", "description": "10.1007/s10021-015-9855-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10021-015-9855-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-03-10T00:00:00Z"}}, {"id": "10.1007/s12520-018-00775-3", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:15:27Z", "type": "Journal Article", "created": "2019-01-16", "title": "Decoration composition of Iberian Iron Age ivory artifacts identified by no-destructive chemical analyses", "description": "Open AccessSe analizan mediante an\u00e1lisis no destuctivos 5 mangos de marfil con decoraci\u00f3n incrustada. Se detecta \u00e1mbar y esta\u00f1o.", "keywords": ["an\u00e1lisis no destructivos", "Mundo Ib\u00e9rico", "Edad del Hierro", ":ANTROPOLOG\u00cdA [UNESCO]", "marfil", "UNESCO::ANTROPOLOG\u00cdA", "esta\u00f1o", "\u00e1mbar", "01 natural sciences", "UNESCO::HISTORIA::Ciencias auxiliares de la historia::Arqueolog\u00eda", ":HISTORIA::Ciencias auxiliares de la historia::Arqueolog\u00eda [UNESCO]", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s12520-018-00775-3"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Archaeological%20and%20Anthropological%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s12520-018-00775-3", "name": "item", "description": "10.1007/s12520-018-00775-3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s12520-018-00775-3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-17T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2021.151567", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:17:32Z", "type": "Journal Article", "created": "2021-11-08", "title": "Mineral characterization and composition of Fe-rich flocs from wetlands of Iceland: Implications for Fe, C and trace element export", "description": "Open AccessIn freshwater wetlands, redox interfaces characterized by circumneutral pH, steep gradients in O2, and a continual supply of Fe(II) form ecological niches favorable to microaerophilic iron(II) oxidizing bacteria (FeOB) and the formation of flocs; associations of (a)biotic mineral phases, microorganisms, and (microbially-derived) organic matter. On the volcanic island of Iceland, wetlands are replenished with Fe-rich surface-, ground- and springwater. Combined with extensive drainage of lowland wetlands, which forms artificial redox gradients, accumulations of bright orange (a)biotically-derived Fe-rich flocs are common features of Icelandic wetlands. These loosely consolidated flocs are easily mobilized, and, considering the proximity of Iceland's lowland wetlands to the coast, are likely to contribute to the suspended sediment load transported to coastal waters. To date, however, little is known regarding (Fe) mineral and elemental composition of the flocs. In this study, flocs from wetlands (n = 16) across Iceland were analyzed using X-ray diffraction and spectroscopic techniques (X-ray absorption and 57Fe M\u00f6ssbauer) combined with chemical extractions and (electron) microscopy to comprehensively characterize floc mineral, elemental, and structural composition. All flocs were rich in Fe (229\u2013414 mg/g), and floc Fe minerals comprised primarily ferrihydrite and nano-crystalline lepidocrocite, with a single floc sample containing nano-crystalline goethite. Floc mineralogy also included Fe in clay minerals and appreciable poorly-crystalline aluminosilicates, most likely allophane and/or imogolite. Microscopy images revealed that floc (bio)organics largely comprised mineral encrusted microbially-derived components (i.e. sheaths, stalks, and EPS) indicative of common FeOB Leptothrix spp. and Gallionella spp. Trace element contents in the flocs were in the low \u03bcg/g range, however nearly all trace elements were extracted with hydroxylamine hydrochloride. This finding suggests that the (a)biotic reductive dissolution of floc Fe minerals, plausibly driven by exposure to the varied geochemical conditions of coastal waters following floc mobilization, could lead to the release of associated trace elements. Thus, the flocs should be considered vectors for transport of Fe, organic carbon, and trace elements from Icelandic wetlands to coastal waters.", "keywords": ["Minerals", "Iron", "Iceland", "Freshwater flocs", "04 agricultural and veterinary sciences", "15. Life on land", "Ferric Compounds", "01 natural sciences", "6. Clean water", "Trace Elements", "EXAFS", "13. Climate action", "Freshwater flocs; Fe(II)-oxidizing bacteria; Biominerals; Wetlands; EXAFS; 57Fe M\u00f6ssbauer", "Wetlands", "57Fe M\u00f6ssbauer", "Biominerals", "Fe(II)-oxidizing bacteria", "0401 agriculture", " forestry", " and fisheries", "14. Life underwater", "Oxidation-Reduction", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2021.151567"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2021.151567", "name": "item", "description": "10.1016/j.scitotenv.2021.151567", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2021.151567"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-01T00:00:00Z"}}, {"id": "10.1016/j.dib.2025.111585", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:16:27Z", "type": "Journal Article", "created": "2025-05-01", "title": "Dataset on physico-chemical characteristics of Exogenous Organic Matters (EOMs) gathered from various European countries", "description": "Many activities generate organic wastes, including urban activities (e.g., biowaste, sewage sludge), industry (e.g. vinasse) and agriculture (e.g., livestock manure, crop residues). Exogenous Organic Matters (EOMs) are secondary raw materials, i.e., wastes and residues from agriculture, municipalities or industry, which are either used as such or further processed with different technologies. The large variability in the raw materials and production technologies increases the diversity of EOM characteristics, which in turn affect their efficacy when applied to soils. The datapaper presents the database \u201cPhysico-chemical characteristics of Exogenous Organic Matters (EOMs)\u201d which is available in the Zenodo repository (https://doi.org/10.5281/zenodo.13969793). The database is a non-relational database in column format established in the framework of the EJP SOIL EOM4SOIL project, which aimed at establishing a database on EOM\u2019s characteristics. The database gathered EOM characteristics collected in national databases and surveys from 6 European countries, and completed by data published in scientific articles. It describes physico-chemical characteristics of 126 types of EOMs encompassing urban, industrial and agricultural origins (e.g. urine, biowastes, sewage sludge, farmyard manures) and 91 characteristics (e.g. major elements, trace metals, emerging organic contaminants, pathogens, potentially mineralised C and N). There is an average of about 20 variables collected per type of EOM. Preliminary description of the EOM characteristics database is proposed in the present datapaper using descriptive statistics. The characteristics of the 126 types of EOMs provide valuable insights that can help farmers, policymakers, and agricultural consultants to optimize the use of these materials in fertilization and soil amendment practices. This knowledge is essential for better management of EOM application practices by the farmers in order to increase soil carbon stocks and reduce the reliance on mineral fertilizers.", "keywords": ["[SDE] Environmental Sciences", "[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy", "Science (General)", "Computer applications to medicine. Medical informatics", "Digestate", "R858-859.7", "Compost", "Urine", "Sludge Urine", "Sludge", "Biochar", "Livestock manure", "Q1-390", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "Composition", "Data Article"]}, "links": [{"href": "https://doi.org/10.1016/j.dib.2025.111585"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Data%20in%20Brief", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.dib.2025.111585", "name": "item", "description": "10.1016/j.dib.2025.111585", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.dib.2025.111585"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-01T00:00:00Z"}}, {"id": "10.1016/j.earscirev.2018.05.017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-03T16:16:27Z", "type": "Journal Article", "created": "2018-06-02", "title": "Advances in the determination of humification degree in peat since  : Applications in geochemical and paleoenvironmental studies", "description": "Peer reviewed", "keywords": ["2. Zero hunger", "Decomposition", "Organic matter decay", "13. Climate action", "Bog", "Bogs; C cycle; Decomposition; H/C; Organic matter decay; Earth and Planetary Sciences (all)", "H/C", "C cycle; Decomposition; Organic matter decay; Bogs", " H/C", "C cycle", "15. Life on land", "Earth and Planetary Sciences (all)", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://cris.unibo.it/bitstream/11585/690169/5/POSTPRINT%20690169.pdf"}, {"href": "https://doi.org/10.1016/j.earscirev.2018.05.017"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth-Science%20Reviews", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.earscirev.2018.05.017", "name": "item", "description": "10.1016/j.earscirev.2018.05.017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.earscirev.2018.05.017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-01T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=de&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=de&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=de&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=de&offset=50", "hreflang": "en-US"}], "numberMatched": 11076, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-04-04T07:55:38.999825Z"}