{"type": "FeatureCollection", "features": [{"id": "10261/279416", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:07Z", "type": "Journal Article", "created": "2021-12-08", "title": "Rhizosphere microbiomes can regulate plant drought tolerance", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "0301 basic medicine", "Drought stress", "0303 health sciences", "Root-microbe association", "15. Life on land", "Biota", "6. Clean water", "12. Responsible consumption", "Phytohormones", "03 medical and health sciences", "Phytohormone", "13. Climate action", "Metabolites", "Plant growth"], "contacts": [{"organization": "ASLAM, Mehtab Muhammad, OKAL, Eyalira J., IDRIS, Aisha Lawan, QIAN, Zhang, XU, Weifeng, KARANJA, Joseph K., WANI, Shabir H., YUAN, Wei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10261/279416"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Pedosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/279416", "name": "item", "description": "10261/279416", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/279416"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "20.500.12079/70987", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:57Z", "type": "Journal Article", "created": "2022-04-08", "title": "Effects of Multi-Species Microbial Inoculants on Early Wheat Growth and Litterbag Microbial Activity", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The use of microbial consortia (MC) with complementing features is considered to be a promising method of sustainable crop intensification, potentially trumping the limited performance of single-strain applications. We assessed the effect of two novel MC on early wheat growth and litterbag microbial activity in heated and unheated soil. Pot experiments were carried out in duplicate in a greenhouse over 63 days using a completely randomized design with six replications. A range of parameters of plant growth and nutrient uptake were regularly assessed and statistically analyzed by ANOVA. The litterbag-NIRS method was used to trace the microbial activity. Averaged over both trials, soil heating resulted in a significant increase in shoot biomass (+53%) and subsequent nitrogen uptake (+307 mg N pot\u22121) but strongly reduced root development (\u221246%) compared with unheated soil. The application of MC had no effect on wheat growth in the heated soil. By contrast, in the unheated soil, shoot (+12%) and root (+15%) biomass and shoot nitrogen uptake (+11%) were significantly increased after double inoculation with MC compared with autoclaved MC. The litterbag-NIRS method confirmed clear effects of soil heating on microbial activity. Differences between MC application and the control were noted, indicating a buffering effect of MC.</p></article>", "keywords": ["2. Zero hunger", "Greenhouse", "S", "Litterbag-NIRS method", "microbial consortia inoculants", "plant-microbe interactions", "Agriculture", "04 agricultural and veterinary sciences", "Microbial consortia inoculants", "Plant-growth-promoting microorganisms", "plant-growth-promoting microorganisms; microbial consortia inoculants; microbial fertilizer; plant-microbe interactions; pot experiments; greenhouse; litterbag-NIRS method", "microbial fertilizer", "Pot experiments", "plant-growth-promoting microorganisms", "greenhouse", "0401 agriculture", " forestry", " and fisheries", "pot experiments", "Plant-microbe interactions", "Microbial fertilizer"]}, "links": [{"href": "http://www.mdpi.com/2073-4395/12/4/899/pdf"}, {"href": "https://iris.enea.it/bitstream/20.500.12079/70987/1/Effects%20of%20Multi-Species%20Microbial%20Inoculants%20on%20Early%20Wheat%20Growth%20and%20Litterbag%20Microbial%20Activity.pdf"}, {"href": "https://www.mdpi.com/2073-4395/12/4/899/pdf"}, {"href": "https://doi.org/20.500.12079/70987"}, {"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": "20.500.12079/70987", "name": "item", "description": "20.500.12079/70987", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.12079/70987"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-08T00:00:00Z"}}, {"id": "10.5281/zenodo.15395350", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:25Z", "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.15363435", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:24Z", "type": "Report", "title": "Deliverable D7.1_Guidelines and specifications for soil biodiversity and soil health data capture (SOIL O-LIVE_HORIZON EUROPE ID 101091255)", "description": "D7.1. Guidelines and specifications for soil biodiversity and soil health data capture, metadating, geo-linking, and open publication. T.7.1", "keywords": ["geo-linking", "soil health", "metadata", "guidelines", "15. Life on land", "soil o-live", "olive grove", "D7.1", "biodiversity"], "contacts": [{"organization": "University of Ja\u00e9n", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15363435"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15363435", "name": "item", "description": "10.5281/zenodo.15363435", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15363435"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-20T00:00:00Z"}}, {"id": "10.5281/zenodo.15374527", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:24Z", "type": "Dataset", "title": "On the relationship between environment and growth of sweet chestnut (Castanea sativa) in the Caucasus", "description": "unspecifiedThe dataset Data.csv includes 258 observations and 38 elements, featuring entire data without any missing values. The dataset encompasses metrics pertaining to trees elements (diameter D, average annual increment Ave_Inc, and Age), topographical components (elevation - M_SRTM_DEM, slope, aspect, ruggedness), and edaphic factors (soil organic carbon soc_ave, pH phh2o_ave, nitrogen, clay, sand, and silt content). The dataset includes high-resolution bioclimatic variables obtained from the CHELSA database (M_CHELSA_bio_01 to M_CHELSA_bio_19), which provide essential climate indicators such as annual mean temperature, temperature seasonality, and precipitation throughout various time periods. The climate variables are scaled (temperatures multiplied by 10). Furthermore, variables like Sample_CSV and Series serve as identifiers/ records. The database is ready for ecological modeling, and incorporates biophysical, topographic, soil, and climatic data \u00a0relevant to tree growth study.", "keywords": ["Generalized additive models (GAMs)", "Caucasus region", "Dendrochronology", "Castanea sativa", "Climate change", "Tree growth dynamics"], "contacts": [{"organization": "Metreveli, Vasil, Kreft, Holger, Javakhishvili, Zurab, Mdivani, Sandro, Chikorashvili, Giorgi, Akobia, Ilia, Gavashelishvili, Alexander,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15374527"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15374527", "name": "item", "description": "10.5281/zenodo.15374527", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15374527"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-09T00:00:00Z"}}, {"id": "20.500.12079/80427", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:57Z", "type": "Journal Article", "created": "2024-12-12", "title": "Genome Insights into Beneficial Microbial Strains Composing SIMBA Microbial Consortia Applied as Biofertilizers for Maize, Wheat and Tomato", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>For the safe use of microbiome-based solutions in agriculture, the genome sequencing of strains composing the inoculum is mandatory to avoid the spread of virulence and multidrug resistance genes carried by them through horizontal gene transfer to other bacteria in the environment. Moreover, the annotated genomes can enable the design of specific primers to trace the inoculum into the soil and provide insights into the molecular and genetic mechanisms of plant growth promotion and biocontrol activity. In the present work, the genome sequences of some members of beneficial microbial consortia that have previously been tested in greenhouse and field trials as promising biofertilizers for maize, tomato and wheat crops have been determined. Strains belong to well-known plant-growth-promoting bacterial genera such as Bacillus, Burkholderia, Pseudomonas and Rahnella. The genome size of strains ranged from 4.5 to 7.5 Mbp, carrying many genes spanning from 4402 to 6697, and a GC content of 0.04% to 3.3%. The annotation of the genomes revealed the presence of genes that are implicated in functions related to antagonism, pathogenesis and other secondary metabolites possibly involved in plant growth promotion and gene clusters for protection against oxidative damage, confirming the plant-growth-promoting (PGP) activity of selected strains. All the target genomes were found to possess at least 3000 different PGP traits, belonging to the categories of nitrogen acquisition, colonization for plant-derived substrate usage, quorum sensing response for biofilm formation and, to a lesser extent, bacterial fitness and root colonization. No genes putatively involved in pathogenesis were identified. Overall, our study suggests the safe application of selected strains as \u201cplant probiotics\u201d for sustainable agriculture.</p></article>", "keywords": ["biofertilizers", "0301 basic medicine", "0303 health sciences", "03 medical and health sciences", "traceability", "PGP bacteria", "whole-genome sequencing", "QH301-705.5", "microbial consortia", "risk assessment", "Biology (General)", "Article"]}, "links": [{"href": "https://iris.enea.it/bitstream/20.500.12079/80427/1/Genome%20Insights%20into%20Beneficial%20Microbial%20Strains%20Composing%20SIMBA%20Microbial%20Consortia%20Applied%20as%20Biofertilizers%20for%20Maize%2c%20Wheat%20and%20Tomato.pdf"}, {"href": "https://www.mdpi.com/2076-2607/12/12/2562/pdf"}, {"href": "https://doi.org/20.500.12079/80427"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microorganisms", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.12079/80427", "name": "item", "description": "20.500.12079/80427", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.12079/80427"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-12T00:00:00Z"}}, {"id": "20.500.12079/84487", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:57Z", "type": "Journal Article", "created": "2024-10-24", "title": "Culturomics- and metagenomics-based insights into the soil microbiome preservation and application for sustainable agriculture", "description": "<p>Soil health is crucial for global food production in the context of an ever-growing global population. Microbiomes, a combination of microorganisms and their activities, play a pivotal role by biodegrading contaminants, maintaining soil structure, controlling nutrients\uffe2\uff80\uff99 cycles, and regulating the plant responses to biotic and abiotic stresses. Microbiome-based solutions along the soil-plant continuum, and their scaling up from laboratory experiments to field applications, hold promise for enhancing agricultural sustainability by harnessing the power of microbial consortia. Synthetic microbial communities, i.e., selected microbial consortia, are designed to perform specific functions. In contrast, natural communities leverage indigenous microbial populations that are adapted to local soil conditions, promoting ecosystem resilience, and reducing reliance on external inputs. The identification of microbial indicators requires a holistic approach. It is fundamental for current understanding the soil health status and for providing a comprehensive assessment of sustainable land management practices and conservation efforts. Recent advancements in molecular technologies, such as high-throughput sequencing, revealed the incredible diversity of soil microbiomes. On one hand, metagenomic sequencing allows the characterization of the entire genetic composition of soil microbiomes, and the examination of their functional potential and ecological roles; on the other hand, culturomics-based approaches and metabolic fingerprinting offer complementary information by providing snapshots of microbial diversity and metabolic activities both in and ex-situ. Long-term storage and cryopreservation of mixed culture and whole microbiome are crucial to maintain the originality of the sample in microbiome biobanking and for the development and application of microbiome-based innovation. This review aims to elucidate the available approaches to characterize diversity, function, and resilience of soil microbial communities and to develop microbiome-based solutions that can pave the way for harnessing nature\uffe2\uff80\uff99s untapped resources to cultivate crops in healthy soils, to enhance plant resilience to abiotic and biotic stresses, and to shape thriving ecosystems unlocking the potential of soil microbiomes is key to sustainable agriculture. Improving management practices by incorporating beneficial microbial consortia, and promoting resilience to climate change by facilitating adaptive strategies with respect to environmental conditions are the global challenges of the future to address the issues of climate change, land degradation and food security.</p", "keywords": ["sustainable agriculture", "microbiome-based solutions; soil health; microbiome preservation; SynComs; NatComs; omics approaches; microbiome application; sustainable agriculture", "microbiome-based solutions", "omics approaches", "soil health", "microbiome preservation", "microbiome application", "NatComs", "Microbiology", "SynComs", "QR1-502"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/1116082/2/fmicb-15-1473666.pdf"}, {"href": "https://doi.org/20.500.12079/84487"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.12079/84487", "name": "item", "description": "20.500.12079/84487", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.12079/84487"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-24T00:00:00Z"}}, {"id": "10.5281/zenodo.156142", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:32Z", "type": "Journal Article", "created": "2016-09-08", "title": "Review of the genus Onchopelma Hesse, with descriptions of new species (Diptera: Mythicomyiidae)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The genus Onchopelma Hesse is reviewed and a key to species is given. Four new species are described and illustrated: Onchopelma brevifasciatum, sp.n., O. irwini, sp.n., O. majus, sp.n., and O. nitidum, sp.n. Seven species are currently known in the genus, which occurs only in Namibia and South Africa.</p></article>", "keywords": ["0106 biological sciences", "Insecta", "Arthropoda", "Diptera", "Animalia", "Biodiversity", "Bombyliidae", "01 natural sciences", "Taxonomy"], "contacts": [{"organization": "Evenhuis, Neal L.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.156142"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Zootaxa", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.156142", "name": "item", "description": "10.5281/zenodo.156142", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.156142"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2002-08-22T00:00:00Z"}}, {"id": "10.5281/zenodo.16841981", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Journal Article", "created": "2021-09-10", "title": "Assessment of Capsicum annuum L. Grown in Controlled and Semi-Controlled Environments Irrigated with Greywater Treated by Floating Wetland Systems", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Accumulation of trace elements, including heavy metals, were evaluated in soil and fruits of chilli plants (Capsicum annuum L.) grown under both laboratory-controlled and semi-controlled greenhouse location conditions. Chilli plant biomass growth in different development stages and fruit productivity were evaluated and compared with each other for the impact of growth boundary conditions and water quality effects. Treated synthetic greywaters by different operational design set-ups of floating treatment wetland systems were recycled for watering chillies in both locations. Effluents of each individual group of treatment set-up systems were labelled to feed sets of three replicates of chilli plants in both locations. Results revealed that the treated synthetic greywater (SGW) complied with thresholds for irrigation water, except for high concentrations (HC) of phosphates, total suspended soils, and some trace elements, such as cadmium. Chilli plants grew in both locations with different growth patterns in each development stage. First blooming and high counts of flowers were observed in the laboratory. Higher fruit production was noted for greenhouse plants: 2266 chilli fruits with a total weight of 16.824 kg with an expected market value of GBP 176.22 compared to 858 chilli fruits from the laboratory with a weight of 3.869 kg and an estimated price of GBP 17.61. However, trace element concentrations were detected in chilli fruits with the ranking order of occurrence as: Mg &gt; Ca &gt; Na &gt; Fe &gt; Zn &gt; Al &gt; Mn &gt; Cu &gt; Cd &gt; Cr &gt; Ni &gt; B. The highest concentrations of accumulated Cd (3.82 mg/kg), Cu (0.56 mg/kg), and Na (0.56 mg/kg) were recorded in chilli fruits from the laboratory, while greater accumulations of Ca, Cd, Cu, Mn, and Ni with concentrations of 4.73, 1.30, 0.20, 0.21, and 0.24 mg/kg, respectively, were linked to fruits from the greenhouse. Trace elements in chilli plant soils followed the trend: Mg &gt; Fe &gt; Al &gt; Cr &gt; Mn &gt; Cd &gt; Cu &gt; B. The accumulated concentrations in either chilli fruits or the soil were above the maximum permissible thresholds, indicating the need for water quality improvements.</p></article>", "keywords": ["agricultural water management", "2. Zero hunger", "soil pollution", "S", "greywater recycling", "Agriculture", "<i>Capsicum annuum</i> L.", "15. Life on land", "01 natural sciences", "6. Clean water", "12. Responsible consumption", "11. Sustainability", "14. Life underwater", "constructed floating wetland", "heavy metal accumulation", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://usir.salford.ac.uk/id/eprint/61848/1/agronomy-11-01817-v2.pdf"}, {"href": "https://orca.cardiff.ac.uk/id/eprint/150458/1/agronomy-11-01817-v3.pdf"}, {"href": "http://www.mdpi.com/2073-4395/11/9/1817/pdf"}, {"href": "https://www.mdpi.com/2073-4395/11/9/1817/pdf"}, {"href": "https://doi.org/10.5281/zenodo.16841981"}, {"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": "10.5281/zenodo.16841981", "name": "item", "description": "10.5281/zenodo.16841981", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16841981"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-10T00:00:00Z"}}, {"id": "10.5281/zenodo.15622876", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:32Z", "type": "Dataset", "created": "2025-06-09", "title": "Effects of conventional and biodegradable microplastics on soil invertebrate communities in PAPILLONS field plot experiment in Finland, Germany and Spain", "description": "Data on soil invertebrate communities at PAPILLONS field plot experiment sites in Finland (Natural Resources Institute Finland and Finnish Environment Institute), Germany (University of Bonn) and Spain (IMDEA Water), sampled in autumn 2022 and 2023. At all three study sites, five treatments with five replicate plots were established in spring 2022: control with no microplastic addition, and two nominal concentrations (0.005%, 0.05%) of conventional polyethene (PE) and blend of starch and polybutylene adipate terephthalate (PBAT) microplastics. Microarthropods and earthworms from Spain and Germany were analysed at the Vrije Universiteit Amsterdam and part of the earthworms and enchytraeids at Finnish Environment Institute. eDNA data (Natural Resources Institute Finland) on microfauna has been saved in another data repository.", "keywords": ["microarthropod", "springtail", "field experiment", "mite", "enchytraeid", "earthworm", "microplastic", "soil invertebrate", "soil"], "contacts": [{"organization": "Selonen, Salla, van Gestel, Kees, Saartama, Vili, Velmala, Sannakajsa, Haimi, Jari, Kaseva, Janne, de Jeu, Lotte,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15622876"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15622876", "name": "item", "description": "10.5281/zenodo.15622876", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15622876"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2026-12-31T00:00:00Z"}}, {"id": "20.500.12556/RUL-136343", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:57Z", "type": "Journal Article", "created": "2021-09-22", "title": "Integrated Water Quality Management Model for the Rural Transboundary River Basin\u2014A Case Study of the Sutla/Sotla River", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The intensive use of soil and water resources results in a disbalance between the environmental and economic objectives of the river basin. The water quality management model supports good water status, especially downstream of dams and reservoirs, as in the case of the Sutla/Sotla river basin. This research aims to develop a new, improved integrated water quality management model of rural transboundary basins to achieve environmental objectives and protection of the Natura 2000 sites. The model uses river basin pressure analysis to assess the effects of climate and hydrological extreme impacts, and a programme of basic and supplementary measures. The impact assessment of BASE MODEL, PAST, and FUTURE scenarios was modelled using the soil and water assessment tool (SWAT) based on land use, climate and hydrological data, climate change, presence or lack of a reservoir, and municipal wastewater and agriculture measures. Eight future climate change scenarios were obtained with optimistic (RCP4.5) and pessimistic (RCP8.5) forecasts for two periods (2020\u20132050 and 2070\u20132100), both with and without a reservoir. The model shows that the most significant impacts on the waterbody come from the nutrients and sediment hotspots, also shows the risk of not achieving good water status, and water eutrophication risk. The modelled average annual increase in sediment is from 4 to 25% and in total N from 1 to 8%, while the change in total P is from \u22125 to 6%. The conducted analysis provides a base for the selection of tailor-made measures from the catalogue of the supplementary measures that will be outlined in future research.</p></article>", "keywords": ["environmental objectives WFD", "integrated water quality management model", "environmental objectives WFD ; integrated water quality management model ; good water status ; rural transboundary river basin ; Sutla/Sotla ; climate change ; scenarios ; SWAT ; measures", "rural transboundary river basin", "01 natural sciences", "11. Sustainability", "hidrologija", "SWAT", "14. Life underwater", "kakovost voda", "0105 earth and related environmental sciences", "vodotoki", "2. Zero hunger", "scenarios", "measures", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "Sotla", "climate change", "info:eu-repo/classification/udc/556", "13. Climate action", "vodni mened\u017ement", "Sutla/Sotla", "0401 agriculture", " forestry", " and fisheries", "SWAT model", "good water status"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/18/2569/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/18/2569/pdf"}, {"href": "https://doi.org/20.500.12556/RUL-136343"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.12556/RUL-136343", "name": "item", "description": "20.500.12556/RUL-136343", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.12556/RUL-136343"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-17T00:00:00Z"}}, {"id": "10.5281/zenodo.15690530", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Dataset", "title": "Q sortings of factors influencing farmers' soil management - SoilX WP4", "description": "This dataset contains the Q sortings of the participants in the Q-Methodological study that was conducted as part of work package 4 ('Farmer-related challenges to the use of sustainable soil management practices') of the project SoilX ('Soil management to mitigate climate change-related precipitation eXtremes').  The data are provided in an excel document in the format required for using the Q analysis software KADE. Each sheet contains data for one of the case study regions (identified by country: AT = Austria, SE = Sweden, ES = Spain, DK = Denmark, CH = Switzerland). The first sheet also contains information on the sorting grid, as needed for KADE.", "keywords": ["farmer viewpoints", "agricultural soil management", "Q-Methodology", "farmer typology"], "contacts": [{"organization": "Leonhardt, Heidi, Braito, Michael, B\u00fctikofer, Nicole, Graversgaard, Morten, H\u00f6ckert, Jenny, Lunar Koch, Ernesto Jose, Lundstr\u00f6m, Christina, Schreiber, Mariella, Tiselius, Mette,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15690530"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15690530", "name": "item", "description": "10.5281/zenodo.15690530", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15690530"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-24T00:00:00Z"}}, {"id": "10.5281/zenodo.1566066", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:32Z", "type": "Dataset", "title": "N2O and CH4 fluxes/concentrations reported in Krauss et al. 2017", "description": "Open Access{'references': ['Krauss, M., Ruser, R., M u00fcller, T., Hansen, S., M u00e4der, P., Gattinger, A. (2017) Impact of reduced tillage on greenhouse gas emissions and soil carbon stocks in an organic grass-clover ley - winter wheat cropping sequence. Agriculture, Ecosystems &amp; Environment, 239, p. 324-333']}", "keywords": ["2. Zero hunger", "nitrous oxide", " methane", " greenhouse gas emissions", " conservation tillage", " organic farming", "13. Climate action", "11. Sustainability", "12. Responsible consumption"], "contacts": [{"organization": "Krauss, Maike", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.1566066"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.1566066", "name": "item", "description": "10.5281/zenodo.1566066", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.1566066"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-11-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15690531", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Dataset", "title": "Q sortings on factors influencing farmers' soil management", "description": "This dataset contains the Q sortings of the participants in the Q-Methodological study that was conducted as part of work package 4 ('Farmer-related challenges to the use of sustainable soil management practices') of the project SoilX ('Soil management to mitigate climate change-related precipitation eXtremes').  The data are provided in an excel document in the format required for using the Q analysis software KADE. Each sheet contains data for one of the case study regions (identified by country: AT = Austria, SE = Sweden, ES = Spain, DK = Denmark, CH = Switzerland). The first sheet also contains information on the sorting grid, as needed for KADE.", "keywords": ["farmer viewpoints", "agricultural soil management", "Q-Methodology", "farmer typology"], "contacts": [{"organization": "Leonhardt, Heidi, Braito, Michael, B\u00fctikofer, Nicole, Graversgaard, Morten, H\u00f6ckert, Jenny, Lunar Koch, Ernesto Jose, Lundstr\u00f6m, Christina, Schreiber, Mariella, Tiselius, Mette,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15690531"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15690531", "name": "item", "description": "10.5281/zenodo.15690531", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15690531"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-18T00:00:00Z"}}, {"id": "10.5281/zenodo.15714572", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Dataset", "title": "Effects of conventional and biodegradable microplastics on earthworm Eisenia andrei in two generations", "description": "Data on the two-generation test on earthworm Eisenia andrei, exposed to conventional (LDPE) and biodegradable (starch-PBAT blend) microplastics over two generations. Data includes soil water holding capacity (WHC) and pH; survival, reproduction (number of juveniles), growth (change in biomass over time) and biochemical biomarkers of the earthworms; and number microplastics found in earthworms after exposure. The experiments were conducted and microplastics extracted at the Finnish Environment Institute (Syke), biomarker analyses were conducted at the University of Ljubljana and microplastics were analysed at the Norwegian Institute foe Water Research (NIVA). Plastic additives from soil and earthworm samples were analysed at the University of Chemistry and Technology in Prague and the data are found in: https://zenodo.org/records/10990380", "keywords": ["microplastics", "two-generation exposure", "soil ecotoxicology", "earthworm"], "contacts": [{"organization": "Saartama, Vili, CONSOLARO, CHIARA, Forsell, Venla, Haimi, Jari, Hurley, Rachel, Jemec Kokalj, Anita, Kal\u010dikova, Gabriela, Talvitie, Julia, Selonen, Salla,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15714572"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15714572", "name": "item", "description": "10.5281/zenodo.15714572", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15714572"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-22T00:00:00Z"}}, {"id": "10.5281/zenodo.15699696", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Dataset", "title": "Microplastic uptake by earthworms across European agricultural soils", "description": "Dataset and metadata on the abundance of earthworm species and microplastic contents in earthworms, sampled from agricultural soils across Europe. This data is part of PAPILLONS European spatial survey. Microplastic analyses were conducted at Norwegian Institute for Water Research (NIVA) and earthworm community analyses at Vrije Universiteit Amsterdam (VU), Finnish Environment Institute (Syke) and Univeristy of Jyv\u00e4skyl\u00e4. Several institutes across Europe were involved in the samplings and acknowledged as contributors. The data on microplastics and plastic additives in soil samples are found in: https://zenodo.org/records/15540049", "keywords": ["agricultural soil", "PAPILLONS", "earthworm", "microplastic", "microplastic uptake", "agriculture"], "contacts": [{"organization": "Hurley, Rachel, van Gestel, Kees, Haimi, Jari, de Jeu, Lotte, Nizzetto, Luca, Saartama, Vili, Selonen, Salla,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15699696"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15699696", "name": "item", "description": "10.5281/zenodo.15699696", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15699696"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-19T00:00:00Z"}}, {"id": "10.5281/zenodo.15730426", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Report", "title": "PREPSOIL workshop report - Earth observation for soil health monitoring; obstacles and  proposals in overcoming them", "description": "Description of a workshop on 'Earth observation for soil health monitoring; obstacles and \u00a0proposals in overcoming them' held on 7 November 2024. The report is an addition to PREPSOIL 5.2, which contains a review of scientific knowledge (bibliography, expert opinions, current EU projects), an inventory of the technological resources mobilised (vectors, sensors, current and planned products, services), and the identification of obstacles to greater use of Earth observations for soil monitoring and measurement needs to reduce/minimise these difficulties.", "keywords": ["Earth observation", "Soil", "soil health", "soil sensing", "soil monitoring"], "contacts": [{"organization": "van Egmond, Fenny", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15730426"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15730426", "name": "item", "description": "10.5281/zenodo.15730426", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15730426"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-25T00:00:00Z"}}, {"id": "10.5281/zenodo.15730034", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Dataset", "title": "Q sortings of factors influencing farmers' soil management - SoilX WP4", "description": "This dataset contains the Q sortings of the participants in the Q-Methodological study that was conducted as part of work package 4 ('Farmer-related challenges to the use of sustainable soil management practices') of the project SoilX ('Soil management to mitigate climate change-related precipitation eXtremes').  The data are provided in an excel document in the format required for using the Q analysis software KADE. Each sheet contains data for one of the case study regions (identified by country: AT = Austria, SE = Sweden, ES = Spain, DK = Denmark, CH = Switzerland). The first sheet also contains information on the sorting grid, as needed for KADE.", "keywords": ["farmer viewpoints", "agricultural soil management", "Q-Methodology", "farmer typology"], "contacts": [{"organization": "Leonhardt, Heidi, Braito, Michael, B\u00fctikofer, Nicole, Graversgaard, Morten, H\u00f6ckert, Jenny, Lunar Koch, Ernesto Jose, Lundstr\u00f6m, Christina, Schreiber, Mariella, Tiselius, Mette,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15730034"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15730034", "name": "item", "description": "10.5281/zenodo.15730034", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15730034"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-24T00:00:00Z"}}, {"id": "10.5281/zenodo.15744885", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Report", "title": "Webinar - Soil Mission Mirror Groups: Where Do We Stand?", "description": "To gain a better knowledge of the current situation regarding mirror group establishment in Europe, to identify challenges and levers for setting up a mirror group and to understand how existing operational groups work, the PREPSOIL project partners have worked on building an overview of existing mirror groups or structure with similar purposes.\u00a0\u00a0  PREPSOIL organised a webinar on June, 2025 16th\u00a0to share some of the results of this work and to discuss existing initiatives, with feedback from three countries.  The presentation supports used during the webinar are available here.\u00a0  Authors of the presentations available here are:\u00a0    Teresa Pinto-Correia ('Mirror Groups: what are we talking about?')  Flavien Poin\u00e7ot, Line Friis Lindner, Tove Ortman and Amanda Matson ('PREPSOIL overview of Mirror Group establishment across Europe')  Theresa Van Hoesel ('National implementation of the EU Mission Soil in Austria')  Elina Nikkola ('Feedback from Finland')  Aleksandra Per\u010din ('Feedback from Croatia')   For more information and access to the recording, please visit: https://prepsoil.eu/events/soil-mission-mirror-groups-where-do-we-stand", "keywords": ["Mirror groups", "Healthy soils", "PREPSOIL"], "contacts": [{"organization": "Poincot, Flavien, Lindner, Line Friis, Matson, Amanda, ORTMAN, TOVE, Besse-Lototskaya, Anna, Helgheim, Beatrice,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15744885"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15744885", "name": "item", "description": "10.5281/zenodo.15744885", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15744885"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-26T00:00:00Z"}}, {"id": "10.5281/zenodo.15753898", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Report", "title": "Soil Mission Mirror Groups: Where do we stand? - Report", "description": "This document is a report produced to share the main results of the work done in PREPSOIL to identify existing mirror groups and collect information on how they work. The work is related to PREPSOIL objective to foster the establishment and development of Mission Soil Mirror Groups in Europe.", "keywords": ["Healthy soils", "Mission Soil Mirror Groups", "PREPSOIL"], "contacts": [{"organization": "Poincot, Flavien, ORTMAN, TOVE, Lindner, Line Friis,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15753898"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15753898", "name": "item", "description": "10.5281/zenodo.15753898", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15753898"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15753537", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Other", "created": "2025-06-20", "title": "Possible contribution of remote sensing to soil monitoring", "description": "A slideshow for a lecture given for the online training activity \u201cSupporting Capacity Building in Soil Monitoring in Europe\u201d organised for Task T5.4 of PREPSOIL project (CSA, Horizon EUrope).  It is based on the results of Task 5.2 and shows that:    Although necessary, soil monitoring methods based on in situ observations or soil sampling are costly, give estimates with low spatial & temporal resolutions, and provide no information on uncertainties outside the characterized sites;\u00a0  RS provides access to certain soil information or makes soil property covariates available with a spatial resolution and revisit frequency that can be very high;  By using both soil data and other data including RS data, digital soil mapping makes it possible to obtain precise property maps, as well as uncertainty maps.", "keywords": ["Monitoring", "Healthy Soils", "Traditional methods", "Remote sensing", "Digital Soil Mapping", "PREPSOIL"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15753537"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15753537", "name": "item", "description": "10.5281/zenodo.15753537", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15753537"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15755759", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Software", "title": "Atelier fran\u00e7ais : Observation de la terre pour la surveillance de la sant\u00e9 des sols ; obstacles et propositions pour les surmonter", "description": "Ajout au livrable D5.2 pr\u00e9sentant la m\u00e9thode utilis\u00e9e pour l\u2019atelier en France visant \u00e0 :    Identifier les points de blocage (scientifiques, technologiques, techniques, comp\u00e9tences...) \u00e0 une plus grande utilisation des observations de la Terre par satellite ;  Proposer des mesures pour r\u00e9duire/minimiser ces difficult\u00e9s, en les classant en fonction de leur impact suppos\u00e9 sur les points de blocage, et de leur facilit\u00e9 - voire co\u00fbt - de mise en oeuvre.   La pr\u00e9sentation comprend des instructions (EN), un diaporama (FR), ainsi qu'un formulaire de consentement \u00e9clair\u00e9 pour les participants.", "keywords": ["Obstacles", "Monitoring", "T\u00e9l\u00e9d\u00e9tection", "Healthy Soils", "PREPSOIL"], "contacts": [{"organization": "Renault, Pierre", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15755759"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15755759", "name": "item", "description": "10.5281/zenodo.15755759", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15755759"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15763496", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:34Z", "type": "Report", "title": "Technical feasibility in using CLMS satellite-based EO to estimate soil health indicators", "description": "The slideshow contains a summary of the main results issued from PREPSOIL Task T5.2.", "keywords": ["2. Zero hunger", "Earth observation", "Technology", "Monitoring", "Scientific knowledge", "Communication", "Skills", "Sustainable soil management", "Success factors", "Healthy Soils", "15. Life on land", "PREPSOIL", "Remote Sensing", "Gaps"], "contacts": [{"organization": "Renault, Pierre, Xie, Guanyao, Weiss, Marie,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15763496"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15763496", "name": "item", "description": "10.5281/zenodo.15763496", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15763496"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-28T00:00:00Z"}}, {"id": "10.5281/zenodo.15754958", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:33Z", "type": "Software", "title": "Workshop framework: Earth observation for soil health monitoring; obstacles and proposal in overcoming them.", "description": "Addition to Deliverable D5.2 containing the method proposed to organize national workshops aiming to:    Identify bottlenecks (scientific, technological, technical, skills \u2026) to greater use of satellite Earth Observations (EO) and CLMS and/or Galileo/ EGNOS products;  Propose measures to reduce/minimize these difficulties, ranking them successively according to their supposed impact on the bottlenecks, and their ease - or even cost - of implementation.   The Presentation includes instructions, a slideshow to adapt to local context and language, and an informed consent form for participants", "keywords": ["Remote Sensing", "Obstacles", "Monitoring", "Healthy Soils", "PREPSOIL"], "contacts": [{"organization": "Renault, Pierre", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15754958"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15754958", "name": "item", "description": "10.5281/zenodo.15754958", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15754958"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15769818", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:34Z", "type": "Report", "title": "From an EJP SOIL National Hub to a mirror group:  example of the French National Hub", "description": "This document shares feedback on two meetings organized in France to establish a Mission Soil Mirror Group building on the EJP SOIL National Hub. The objective is to share a concrete example of a country building on its National Hub to develop its Mirror Group and the topics discussed with the stakeholders. This document is produced as part of PREPSOIL actions related to the establishment and development of Mission Soil Mirror Groups. For more information about existing Mirror Groups in Europe and how they work, please read PREPSOIL report \u201cMission Soil Mirror Groups: where do we stand?\u201d (10.5281/zenodo.15753898).", "keywords": ["Healthy soils", "Mission Soil Mirror Groups", "PREPSOIL"], "contacts": [{"organization": "Poincot, Flavien", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15769818"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15769818", "name": "item", "description": "10.5281/zenodo.15769818", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15769818"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-30T00:00:00Z"}}, {"id": "2944731604", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:26:26Z", "type": "Journal Article", "created": "2019-05-09", "title": "Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil erosion is one of the main causes of soil degradation among others (salinization, compaction, reduction of organic matter, and non-point source pollution) and is a serious threat in the Mediterranean region. A number of soil properties, such as soil organic matter (SOM), soil structure, particle size, permeability, and Calcium Carbonate equivalent (CaCO3), can be the key properties for the evaluation of soil erosion. In this work, several innovative methods (satellite remote sensing, field spectroscopy, soil chemical analysis, and GIS) were investigated for their potential in monitoring SOM, CaCO3, and soil erodibility (K-factor) of the Akrotiri cape in Crete, Greece. Laboratory analysis and soil spectral reflectance in the VIS-NIR (using either Landsat 8, Sentinel-2, or field spectroscopy data) range combined with machine learning and geostatistics permitted the spatial mapping of SOM, CaCO3, and K-factor. Synergistic use of geospatial modeling based on the aforementioned soil properties and the Revised Universal Soil Loss Equation (RUSLE) erosion assessment model enabled the estimation of soil loss risk. Finally, ordinary least square regression (OLSR) and geographical weighted regression (GWR) methodologies were employed in order to assess the potential contribution of different approaches in estimating soil erosion rates. The derived maps captured successfully the SOM, the CaCO3, and the K-factor spatial distribution in the GIS environment. The results may contribute to the design of erosion best management measures and wise land use planning in the study region.</p></article>", "keywords": ["Landsat 8", "2. Zero hunger", "soil erosion", "550", "Science", "Q", "04 agricultural and veterinary sciences", "Remote sensing", "15. Life on land", "01 natural sciences", "630", "field spectroscopy", "6. Clean water", "soil erosion; remote sensing; Sentinel-2; Landsat 8; ANN; RUSLE; field spectroscopy; OLSR; GWR", "remote sensing", "Field spectroscopy", "OLSR", "13. Climate action", "Soil erosion", "0401 agriculture", " forestry", " and fisheries", "RUSLE", "Sentinel-2", "ANN", "GWR", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/11/9/1106/pdf"}, {"href": "https://doi.org/2944731604"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2944731604", "name": "item", "description": "2944731604", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2944731604"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-05-09T00:00:00Z"}}, {"id": "20.500.12556/RUNG-8752", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:58Z", "type": "Journal Article", "created": "2023-12-22", "title": "Variability in sediment particle size, mineralogy, and Fe mode of occurrence across dust-source inland drainage basins: the case of the lower Dr\u00e2a Valley, Morocco", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. The effects of desert dust upon climate and ecosystems depend strongly on its particle size and size-resolved mineralogical composition. However, there is very limited quantitative knowledge on the particle size and composition of the parent sediments along with their variability within dust-source regions, particularly in dust emission hotspots. The lower Dr\u00e2a Valley, an inland drainage basin and dust hotspot region located in the Moroccan Sahara, was chosen for a comprehensive analysis of sediment particle size and mineralogy. Different sediment type samples (n=\u200942) were collected, including paleo-sediments, paved surfaces, crusts, and dunes, and analysed for particle-size distribution (minimally and fully dispersed samples) and mineralogy. Furthermore, Fe sequential wet extraction was carried out to characterise the modes of occurrence of Fe, including Fe in Fe (oxyhydr)oxides, mainly from goethite and hematite, which are key to dust radiative effects; the poorly crystalline pool of Fe (readily exchangeable ionic Fe and Fe in nano-Fe oxides), relevant to dust impacts upon ocean biogeochemistry; and structural Fe. Results yield a conceptual model where both particle size and mineralogy are segregated by transport and deposition of sediments during runoff of water across the basin and by the precipitation of salts, which causes a sedimentary fractionation. The proportion of coarser particles enriched in quartz is higher in the highlands, while that of finer particles rich in clay, carbonates, and Fe oxides is higher in the lowland dust emission hotspots. There, when water ponds and evaporates, secondary carbonates and salts precipitate, and the clays are enriched in readily exchangeable ionic Fe, due to sorption of dissolved Fe by illite. The results differ from currently available mineralogical atlases and highlight the need for observationally constrained global high-resolution mineralogical data for mineral-speciated dust modelling. The dataset obtained represents an important resource for future evaluation of surface mineralogy retrievals from spaceborne spectroscopy.</p></article>", "keywords": ["Mineral dusts", "geology", "550", "QC1-999", "Climate", "01 natural sciences", "\u00c0rees tem\u00e0tiques de la UPC::Desenvolupament hum\u00e0 i sostenible::Enginyeria ambiental", "Pols minerals", "QD1-999", "Sahara", "0105 earth and related environmental sciences", "mineral dust", "S\u00e0hara", "info:eu-repo/classification/ddc/550", "ddc:550", "Physics", "Aire--Contaminaci\u00f3", "15. Life on land", "info:eu-repo/classification/udc/502.3/.7", "6. Clean water", "Earth sciences", "Chemistry", "13. Climate action", "Air--Pollution", "Desert dust", "aerosols"]}, "links": [{"href": "https://acp.copernicus.org/articles/23/15815/2023/acp-23-15815-2023.pdf"}, {"href": "https://doi.org/20.500.12556/RUNG-8752"}, {"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": "20.500.12556/RUNG-8752", "name": "item", "description": "20.500.12556/RUNG-8752", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.12556/RUNG-8752"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-22T00:00:00Z"}}, {"id": "10.5281/zenodo.15796964", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:35Z", "type": "Report", "title": "Conclusion Report on Training Needs for Monitoring and Assessment of Soil Health with Curriculum for Pilot Course", "description": "This deliverable, produced under Task 5.4 of the PREPSOIL project, summarises the identification of training needs and the development of a pilot course to support soil health monitoring in line with the Soil Monitoring Law and the EU Mission Soil. The process was based on expert consultation and co-creation with key stakeholders, including public authorities, research institutions, and European projects working on soil health. The deliverable presents the resulting modular curriculum, the implementation of four pilot training sessions held in June 2025, and an evaluation of their relevance and effectiveness. This report provides a foundation for scaling up capacity-building efforts at the EU level.", "keywords": ["Soil Monitoring Law", "Training curriculum", "EU Mission Soil", "Soil health", "Capacity building", "Indicators", "Policy implementation", "PREPSOIL"], "contacts": [{"organization": "Pita-Romero Herrero, Jos\u00e9 Luis, Pablo, G\u00f3mez Grande,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15796964"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15796964", "name": "item", "description": "10.5281/zenodo.15796964", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15796964"}, {"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": "3020629696", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:26:37Z", "type": "Journal Article", "created": "2020-04-25", "title": "Alternation of wet and dry sides during partial rootzone drying irrigation enhances leaf ethylene evolution", "description": "Soil drying increases endogenous ABA and ACC concentrations in planta, but how these compounds interact to regulate stomatal responses to soil drying and re-watering is still unclear. To determine the temporal dynamics and physiological significance of root, xylem and leaf ABA and ACC concentrations in response to deficit irrigation (DI) or partial rootzone drying (PRD-F) and re-watering, these variables were measured in plants exposed to similar whole pot soil water contents. Both DI and PRD-F plants received only a fraction of the irrigation supplied to well-watered (WW) plants, either to all (DI) or part (PRD-F) of the rootzone of plants grown in split-pots. Both DI and PRD-F induced partial stomatal closure, increased root ABA and ACC accumulation consistent with local soil water content, but did not affect xylem or leaf concentrations of these compounds compared to WW plants. Two hours after re-watering all (DI-RW) or part of the rootzone (PRD-A) to the same soil water content, stomatal conductance returned to WW values or further decreased respectively. Re-watering the whole rootzone had no effect on xylem and leaf ABA and ACC concentrations, while re-watering the dry side of the pot in PRD plants had no effect on xylem and leaf ABA concentrations but increased xylem and leaf ACC concentrations and leaf ethylene evolution. Leaf water potential was similar between all irrigation treatments, with stomatal conductance declining as xylem ABA concentrations and leaf ACC concentrations increased. Prior to re-watering PRD plants, accounting for the spatial differences in soil water uptake best explained variation in xylem ACC concentration suggesting root-to-shoot ACC signalling, but this model did not account for variation in xylem ACC concentration after re-watering the dry side of PRD plants. Thus local (foliar) and long-distance (root-to-shoot) variation in ACC status both seem important in regulating the temporal dynamics of foliar ethylene evolution in plants exposed to PRD.", "keywords": ["0106 biological sciences", "Irrigation", "Stomatal conductance", "Root-to-shoot signalling", "Ethylene", "Physiological significance", "Deficit irrigation", "Plant Science", "Leaf water", "F06 Irrigation", "01 natural sciences", "ACC", "Ecology", " Evolution", " Behavior and Systematics", "580", "2. Zero hunger", "Xylem", "15. Life on land", "F60 Plant physiology and biochemistry", "6. Clean water", "Horticulture", "13. Climate action", "Soil water", "Agronomy and Crop Science", "Soil moisture heterogeneity", "Partial rootzone drying"]}, "links": [{"href": "https://eprints.lancs.ac.uk/id/eprint/144510/1/Juan_EEB_Manuscript_final.pdf"}, {"href": "https://doi.org/3020629696"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20and%20Experimental%20Botany", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3020629696", "name": "item", "description": "3020629696", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3020629696"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15847855", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:35Z", "type": "Dataset", "title": "Enhanced rock weathering altered soil organic carbon fluxes in a plant trial", "description": "Enhanced rock weathering altered soil organic carbon fluxes in a plant triel. Raw and processed datasets in support of the findings of Boito et al. (2025).", "keywords": ["Climate change mitigation", "Soil organic carbon", "Earthworm", "Enhanced rock weathering", "Plants", "CO2 emissions"], "contacts": [{"organization": "Boito, Lucilla, Steinwidder, Laura, Rijnders, Jet, Berwouts, Jesse, Janse, Sarah, Niron, Harun, Roussard, Jasper, Vicca, Sara, Vienne, Arthur,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15847855"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15847855", "name": "item", "description": "10.5281/zenodo.15847855", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15847855"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-09T00:00:00Z"}}, {"id": "11572/401550", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:29Z", "type": "Journal Article", "created": "2023-10-06", "title": "Stabilization against gravity and self-tuning of an elastic variable-length rod through an oscillating sliding sleeve", "description": "An elastic rod, straight in its undeformed state, has a mass attached at one end and a variable length, due to a constraint at the other end by a frictionless sliding sleeve. The constraint is arranged with the sliding direction parallel to a gravity field, in a way that the rod can freely slip inside of the sleeve, when the latter is not moving. In this case, the fere fall of the mass continues until the rod is completely injected into the constraint. However, when the sliding sleeve is subject to a harmonic transverse vibration, it is shown that the fall of the mass and the rod injection are hindered by the presence of a configurational force developing at the sliding sleeve and acting oppositely to gravity. During the dynamic motion, such a configurational force is varying in time because it is associated with the variable bending moment at the sleeve entrance. It is (experimentally, analytically, and numerically) demonstrated that, in addition to the states of complete injection or ejection of the elastic rod (for which the mass falls down or is thrown out), a stable sustained oscillation around a finite height can be realized. This \u2018suspended motion\u2019 is the signature of a new attractor, that arises by the constraint oscillation. This behaviour shares similarities with parametric oscillators, as for instance the Kapitza inverted pendulum. However, differently from the classical parametric oscillators, the \u2018suspended\u2019 configuration of the rod violates equilibrium and the stabilization occurs through a transverse mechanical input, instead of a longitudinal one. By varying the sliding sleeve oscillation amplitude and frequency within specific sets of values, the system spontaneously adjusts the sustained motion through a self-tuning of the rod\u2019s external length. This self-tuning property opens the way to the design of vibration-based devices with extended frequency range.", "keywords": ["Elastica; Configurational mechanics; Dynamic bifurcation", "Classical Physics (physics.class-ph)", "FOS: Physical sciences", "Physics - Classical Physics", "02 engineering and technology", "0101 mathematics", "0210 nano-technology", "7. Clean energy", "01 natural sciences"]}, "links": [{"href": "https://iris.unitn.it/bitstream/11572/401550/1/1-s2.0-S0022509623002569-main.pdf"}, {"href": "https://doi.org/11572/401550"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20the%20Mechanics%20and%20Physics%20of%20Solids", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11572/401550", "name": "item", "description": "11572/401550", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11572/401550"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15827291", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:35Z", "type": "Journal Article", "created": "2022-07-01", "title": "Impact of Temperature and Coagulants on Sludge Dewaterability", "description": "Temperature and coagulant types have an important impact on the quantity and quality of the residue (sludge) in water and wastewater treatment processes. Temperature influences water viscosity and the distribution of the coagulant in water. Coagulants can promote the agglomeration of fine particles into larger flocs so that they can be more easily separated from the water. Experiments have been conducted to explore the relationship between temperature (16-26\u00b0C), the type of coagulant, and sludge dewaterability (estimated using the capillary suction time (CST)). Alum, Ferric, and Moringa oleifera Lam were used as coagulants. The influences of different mixer shapes, turbidity values, and flocs sizes on sludge dewaterability have been assessed. The results show that ferric chloride was unaffected by temperature, whereas alum and M. oleifera performances were influenced by temperature. CST results using the coagulant ferric chloride, regardless of mixer shape, turbidity, and floc size, were insensitive to temperature differences.", "keywords": ["Technology", "T", "coagulants", "T1-995", "temperatures.", "sludge dewaterability", "01 natural sciences", "Technology (General)", "6. Clean water", "capillary suction time", "floc sizes", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Fitria, Dewi, Scholz, Miklas, Swift, Gareth M, Al-Faraj, Furat,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15827291"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15827291", "name": "item", "description": "10.5281/zenodo.15827291", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15827291"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15827808", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:35Z", "type": "Journal Article", "created": "2023-02-10", "title": "Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Agriculture has significantly aided in meeting the food needs of growing population. In addition, it has boosted economic development in irrigated regions. In this study, an assessment of the groundwater (GW) quality for agricultural land was carried out in El Kharga Oasis, Western Desert of Egypt. Several irrigation water quality indices (IWQIs) and geographic information systems (GIS) were used for the modeling development. Two machine learning (ML) models (i.e., adaptive neuro-fuzzy inference system (ANFIS) and support vector machine (SVM)) were developed for the prediction of eight IWQIs, including the irrigation water quality index (IWQI), sodium adsorption ratio (SAR), soluble sodium percentage (SSP), potential salinity (PS), residual sodium carbonate index (RSC), and Kelley index (KI). The physicochemical parameters included T\u00b0, pH, EC, TDS, K+, Na+, Mg2+, Ca2+, Cl\u2212, SO42\u2212, HCO3\u2212, CO32\u2212, and NO3\u2212, and they were measured in 140 GW wells. The hydrochemical facies of the GW resources were of Ca-Mg-SO4, mixed Ca-Mg-Cl-SO4, Na-Cl, Ca-Mg-HCO3, and mixed Na-Ca-HCO3 types, which revealed silicate weathering, dissolution of gypsum/calcite/dolomite/ halite, rock\u2013water interactions, and reverse ion exchange processes. The IWQI, SAR, KI, and PS showed that the majority of the GW samples were categorized for irrigation purposes into no restriction (67.85%), excellent (100%), good (57.85%), and excellent to good (65.71%), respectively. Moreover, the majority of the selected samples were categorized as excellent to good and safe for irrigation according to the SSP and RSC. The performance of the simulation models was evaluated based on several prediction skills criteria, which revealed that the ANFIS model and SVM model were capable of simulating the IWQIs with reasonable accuracy for both training \u201cdetermination coefficient (R2)\u201d (R2 = 0.99 and 0.97) and testing (R2 = 0.97 and 0.76). The presented models\u2019 promising accuracy illustrates their potential for use in IWQI prediction. The findings indicate the potential for ML methods of geographically dispersed hydrogeochemical data, such as ANFIS and SVM, to be used for assessing the GW quality for irrigation. The proposed methodological approach offers a useful tool for identifying the crucial hydrogeochemical components for GW evolution assessment and mitigation measures related to GW management in arid and semi-arid environments.</p></article>", "keywords": ["2. Zero hunger", "machine learning", "groundwater quality", "hydrogeochemistry", "water quality indices", "710", "14. Life underwater", "15. Life on land", "01 natural sciences", "irrigation", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/15/4/694/pdf"}, {"href": "https://www.mdpi.com/2073-4441/15/4/694/pdf"}, {"href": "https://research.usq.edu.au/download/1c0f24478d75e81d1b30c7d2ef129cd978901a29587ebd125c32afb1fbbe09b0/16662935/Evaluation%20and%20Prediction%20of%20Groundwater%20Quality.pdf"}, {"href": "https://doi.org/10.5281/zenodo.15827808"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15827808", "name": "item", "description": "10.5281/zenodo.15827808", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15827808"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-10T00:00:00Z"}}, {"id": "10.5281/zenodo.15849753", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:35Z", "type": "Software", "title": "LandRisk: A GUI python based software to assess contaminated land risk using Source - Pathway - Receptor setting", "description": "Python-Based Risk Screening System (RSS) for Environmental Risk Assessment  a Python-based Risk Screening System (RSS) designed to perform qualitative environmental risk assessments by evaluating potential contaminant linkages. The system assesses risk based on three fundamental components:      Hazard (Source)\u00a0\u2013 The origin of potential contamination (e.g., chemical spills, industrial waste).     Exposure Pathway\u00a0\u2013 The route through which the hazard propagates to reach a receptor (e.g., soil leaching, groundwater migration, airborne dispersion).     Receptor\u00a0\u2013 The entity that may be adversely affected (e.g., human populations, aquatic ecosystems, wildlife).    Key Applications  Pre-Survey Screening:, serves as an initial qualitative assessment before a walkover survey, helping prioritise areas of concern.\u00a0It evaluates risk pathways, including:    On-site to on-site\u00a0(internal contamination spread)  On-site to off-site\u00a0(migration beyond property boundaries)  Off-site to on-site\u00a0(external sources impacting the site)   Supports evaluation across different environmental pathways:    Soil (e.g., toxic metals, hydrocarbons)  Groundwater\u00a0(e.g., leaching contaminants)  Surface water (e.g., runoff contamination)  Air\u00a0(e.g., volatile organic compounds)  Sediment (e.g., accumulated contaminants in water bodies)   Risk Scoring Methodology  The RSS calculates risk using a\u00a0Likelihood \u00d7 Impact\u00a0framework, where:      Likelihood\u00a0depends on hazard magnitude and pathway completeness.     Impact\u00a0considers receptor sensitivity and population exposure.    This systematic approach enables\u00a0rapid risk prioritization, guiding further investigation and remediation planning.", "keywords": ["source - pathway - receptor", "risk assessment", "contaminated land"], "contacts": [{"organization": "Tyrologou, Pavlos, Couto, Nazar\u00e9, Koukouzas, Nikolaos, Makris, George, Kaija, Juha,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15849753"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15849753", "name": "item", "description": "10.5281/zenodo.15849753", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15849753"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-09T00:00:00Z"}}, {"id": "10.5281/zenodo.17834473", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:42Z", "type": "Dataset", "title": "Vast, overlooked peat and organic soils in Brazil's Cerrado: carbon storage, dynamics, and stability", "description": "Data accompanying the paper 'Vast, overlooked peat and organic soils in Brazil's Cerrado: carbon storage, dynamics, and stability.'Authors: Larissa S Verona1,2, Amy E Zanne2, Susan Trumbore3, Paulo N. Bernardino\u00b2,4, Guilherme M Alencar4, Thalia Andreuccetti\u00b9, David Herrera3,5,6, Jo\u00e3o C F Cardoso7, Demetrius Lira-Martins4, Guilherme G Mazzochini8, Natashi Pilon4, Rafael S Oliveira4  1. Programa de p\u00f3s-gradua\u00e7\u00e3o em Biologia Vegetal, Departamento de Biologia Vegetal,Instituto de Biologia, Universidade Estadual de Campinas, Campinas, S\u00e3o Paulo, Brazil;  2. Cary Institute of Ecosystems Studies, Millbrook, NY, US;  3. Max Planck Institute for Biogeochemistry, Jena, Germany  4. Universidade Estadual de Campinas, Departamento de Biologia Vegetal, Campinas, S\u00e3o Paulo, Brazil;  5. Yale School of the Environment, Yale University, New Haven, US;  6. Yale Institute for Biospheric Studies, Yale University, New Haven, US;  7. Programa de P\u00f3s-Gradua\u00e7\u00e3o em Ecologia, Conserva\u00e7\u00e3o e Manejo da Fauna Silvestre, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.  8. Programa de P\u00f3s-Gradua\u00e7\u00e3o em Ecologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Rio de Janeiro, Brazil  \u00a0  # SupportingTable1_CarbonStorageData:Data regarding herbaceous biomass, palm biomass, and soil carbon storage.## Tab: Biomass - HerbaceousDry height for herbaceous biomass in each plot, point, and site, for above and below-ground sampling.  ## Tab: \u00a0Tab: Biomass - PalmsPalm height and derived above and below-ground biomass according Goodman et al., 2013, in each point and site.\u00a0## Tab: Soil CarbonCarbon and Nitrogen %, dry bulk density, volume, length, and carbon density for each sample, point, transect and site.\u00a0  # SupportingTable2_ValidationPointsRandomForestLatitude, Longitude (WGS84), and Class for validation points used to train Random Forest models.  # SupportingTable3_CarbonStabilityData## Tab: RadiocarbonF14, error for F14 measures, derived calendar age max, min, mean and errors, max probability for calendar age, and curve used to estimate calendar age for each sample, point, and site.\u00a0## Tab: FTIRHolecellulose and lignin percentages, carbon %, and flooding patterns for each sample, point, and site.\u00a0# SupportingTable4_FluxesAndEnviromentalVariablesData## LocationSampling information description including temporal replication, spatial replication, point, site, month, position, latitude and longitude (WGS84) and flooding pattern. ## GasesGas measurements including flux, rate, coefficient of determination r,\u00b2 and coefficient of variation for CH4 and CO2## Environmental VariableTotal and mean precipitation in lags of 0-6 months.\u00a0  # SupportingTable5_ConfusionMatricesPredicted and truth classes for validation points in 10\u00a0 random forest models.", "keywords": ["Veredas", "climate change", "tropical peatlands", "methane", "carbon cycle", "carbon dioxide", "Cerrado", "wetlands"], "contacts": [{"organization": "da Silveira Verona, Larissa", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17834473"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17834473", "name": "item", "description": "10.5281/zenodo.17834473", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17834473"}, {"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": "10.5281/zenodo.16017208", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:36Z", "type": "Dataset", "title": "Cashew orchard soil properties, Dodamarg, Northern Western Ghats, India", "description": "Soil properties of cashew orchards of the Northern Western Ghats, India  This project contains chemical properties of soil collected from cashew orchards of Dodamarg, Northern Western Ghats, for a study investigating the factors influencing the effects of forest cover, flower abundance, temperature and (potentially) soil composition on cashew pollinators.  Taxonomic Coverage:\u00a0Not applicable  Geographic Coverage: Dodamarg, Sindhudurg District, Maharashtra, India  Temporal Coverage: March 2025  \u00a0  Description of field and lab methods  Soil collection: Soil samples were collected from 30 cashew orchards, using soil core sampler. The diameter of the core sampler was measured before soil collection. All soil samples were collected from 10 cm depth after removing all the leaf litter from the ground. From each orchard, 10 soil columns were collected for analysis of chemical properties.  Chemical Properties: We estimated thirteen soil chemical properties for all soil samples collected. The following parameters were analyzed by Zuari Farmhubs Laboratory: pH, electrical conductivity (E.C.) at 25\u00b0C, organic carbon (O.C.), available phosphorus (P\u2082O\u2085), available potassium (K\u2082O), available calcium (Ca), magnesium (Mg), sulfur (S), boron (B), zinc (Zn), iron (Fe), copper (Cu), and manganese (Mn).  More details about the data can be obtained from Aditya Satish (adityasatish@ncf-india.org) and Rohit Naniwadekar (rohit@ncf-india.org) from the Nature Conservation Foundation (www.ncf-india.org).  File Descriptions:  Data file: Dodamarg_2025_Cashew_Soil_Properties.csv  We have also included a ReadMe.txt file that explains the data file, akin to the description in the metadata.  Description of the columns of the data file:    Sl no: Serial number  Site: Site ID  Code: Site code (General location)  Latitude: latitude co-ordinate of the plot (in decimal degrees, \u00b0N)  Longitude: longitude co-ordinate of the plot (in decimal degrees, \u00b0E)  pH: pH of the soil  E.C.: Electrical Conductivity at 25\u00b0C (in dS/m)  O.C.: Organic Carbon (in %)  P\u2082O\u2085: Available P\u2082O\u2085 (in Kg /acre)  K\u2082O: Available Potassium (in Kg /acre)  Ca: Available Calcium (in mg/Kg)  Mg: Available Magnesium (in mg/Kg)  S: Available Sulphur (in mg/Kg)  B: Available Boron (in mg/Kg)  Zn: Available Zinc (in mg/Kg)  Fe: Available Iron (in mg/Kg)  Cu: Available Copper (in mg/Kg)  Mn: Available Manganese (in mg/Kg)   Funding:\u00a0  Godrej Consumer Products Limited  Arvind Datar  Rohini Nilekani Philanthropies", "keywords": ["Soil chemical properties", "Cashew orchards", "Ecology", "FOS: Biological sciences", "Northern Western Ghats"], "contacts": [{"organization": "Sadekar, Vishal, Satish, Aditya, Naniwadekar, Rohit,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16017208"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16017208", "name": "item", "description": "10.5281/zenodo.16017208", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16017208"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-17T00:00:00Z"}}, {"id": "2078.1/284215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:26:02Z", "type": "Journal Article", "created": "2023-11-17", "title": "Comparison of nitrogen fertilisation recommendations of West European Countries", "description": "Abstract                   <p>                     Nitrogen (N) budgets at farm level are influenced by N fertilisation recommendations. In this study, we reviewed and analysed the underlying principles and methods of N fertilisation recommendations in 10 West European countries, to identify similarities and differences, and develop suggestions for reconsideration and improvement. An analysis of national official documents on N fertilisation recommendations revealed that there were three main categories of calculation methods: (i) \uffe2\uff80\uff98N mass balances\uffe2\uff80\uff99 (France, Italy, Spain), (ii) \uffe2\uff80\uff98Corrected standards\uffe2\uff80\uff99 (Germany, Netherlands, Switzerland, Luxembourg), and (iii) \uffe2\uff80\uff98Pre\uffe2\uff80\uff90parameterised calculations\uffe2\uff80\uff99, which rely on a soil N supply typology (United Kingdom, Ireland, Belgium). In total 16 variables were identified in the calculation methods. The more complex methods use 10 (Italy, France), while the simplest only rely on 3 (Luxembourg). The most common variables include the availability of N in manure, the N uptake by a crop, and the N released by crop residues. Few countries explicitly consider N losses to ground and surface waters or to the atmosphere in the calculation methods. In some countries, the N fertilisation recommendation has a voluntary status, and in other countries, a legal one (caps on maximum allowable N rates). We compared the N fertiliser recommendations for a wheat crop grown on a farm with livestock, and for a farm with a diverse arable crop rotation without livestock. Across the 10 countries, large differences in the N fertilisation calculation methods and resulting N recommendations existed for the two management scenarios, ranging from almost no fertilisation to 135\uffe2\uff80\uff89kg\uffe2\uff80\uff89N\uffe2\uff80\uff89ha                     \uffe2\uff88\uff921                     , and from 111 to 210\uffe2\uff80\uff89kg\uffe2\uff80\uff89N\uffe2\uff80\uff89ha                     \uffe2\uff88\uff921                     , respectively. The differences were not accounted for by the complexity of the equations used, but rather resulted from contrasting reference values for N availability in manure, N uptake by crop and N leaching. However, the study concluded that standardisation of the method to calculate N fertilisation recommendations is likely to be counterproductive as there are no objective reasons to favour one method more than the others. Nonetheless, improvements in N use efficiency are necessary. Farm scale mass balance, combined with parameters such as minimum residual soil mineral N test at harvest, was suggested as being an important consideration.                   </p", "keywords": ["2. Zero hunger", "advice; fertiliser guide; harmonisation; innovative approaches; mass balance; nitrate; regulation", "harmonisation", "Soil Science", "regulation", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "innovative approaches", "advice", "nitrate", "fertiliser guide", "0401 agriculture", " forestry", " and fisheries", "mass balance", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/1032329/2/2023_EuropeanJSoilScience-2023-JordanMeille-ComparisonofnitrogenfertilisationrecommendationsofWestEuropean_acceptedversion.pdf"}, {"href": "https://doi.org/2078.1/284215"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Soil%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2078.1/284215", "name": "item", "description": "2078.1/284215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2078.1/284215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-01T00:00:00Z"}}, {"id": "10.5281/zenodo.17067648", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:39Z", "type": "Dataset", "title": "Potential annual soil loss by erosion (RUSLE), Ethiopia", "description": "unspecifiedAverage annual soil loss (t ha-1 yr-1) calculated using the Revised Universal Soil Loss Equation (RUSLE): A = R \u00d7 K \u00d7 LS \u00d7 C \u00d7 P. This model estimates sheet and rill erosion risk based on five factors: rainfall erosivity (R), soil erodibility (K), topography (LS), cover-management (C), and support practices (P). The resulting map supports erosion risk assessment and soil conservation planning in Ethiopia. Each input layer (R, K, LS, C, P) was derived as a separate spatial dataset as follows:        R factor: Rainfall erosivity factor (MJ mm ha\u207b\u00b9 h\u207b\u00b9 yr\u207b\u00b9). Derived by clipping the global rainfall erosivity dataset of Panagos et al. (2017, https://doi.org/10.1038/s41598-017-04282-8), as published in Panagos et al. (2023, https://doi.org/10.1016/j.dib.2023.1094820), to the administrative country boundry of Ethiopia.  K factor:\u00a0 Soil erodibility factor ((Mg/ha)[(MJ/ha)(mm/h)]\u207b\u00b9), calculated following the method of Torri et al. (1997, https://doi.org/10.1016/S0341-8162(97)00036-2).\u00a0    The input sand, silt, clay and soil organic carbon maps were obtained from SoilGrids (https://doi.org/10.5194/soil-7-217-2021)          LS factor: Topographic factor computed using slope and flow accumulation following the method of Luvai et al. (2021, https://doi.org/10.7176/JEES/11-16-06), and applied to areas with slope <50% in accordance with Panagos, Borrelli, and Meusburger (2015, https://doi.org/10.1016/j.scitotenv.2015.01.008). The LS factor was derived from the MERIT Digital Elevation Model (https://doi.org/10.1002/2017GL072874).  C factor: Cover-management factor, calculated following the method of Negese (2024: https://doi.org/10.1016/j.rsase.2023.101089), using NDVI data derived from Landsat 8 Surface Reflectance Tier 1 Collection 2 imagery (2018\u20132023) (https://www.usgs.gov/landsat-missions/landsat-8).  P factor: Support practices factor. P = 1 due to data gaps.     This research was carried out for the LSC-IS hubs project under the funding program Development Smart Innovation through Research in Agriculture (DeSIRA), European Union. EU Contribution Agreement to MinBUZA: FOOD/2020/419-433 ; MinBUZA to WUR\u00a0Grant number: 4000004100.  \u00a0    Coordinate Reference System -\u00a0EPSG:20138", "keywords": ["Soil", "Land", "Mapping", "Soil erosion", "RUSLE", "Agriculture", "Ethiopia", "Crop production", "Modelling"], "contacts": [{"organization": "Colman, Betony", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17067648"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17067648", "name": "item", "description": "10.5281/zenodo.17067648", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17067648"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-06T00:00:00Z"}}, {"id": "10.5281/zenodo.16814380", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Dataset", "title": "Assessing CO2 fluxes during enhanced weathering from soils through a mesocosm lens", "description": "It is becoming increasingly accepted that annual gigatonne-scale CO2 removal, in conjunction with rapid decarbonization, is necessary to meet international climate goals and limit global warming below 2\u00b0C. This is going to require the development and rapid scaling of new forms of carbon management. When developing new CDR techniques, it is essential to ensure that there is complete accounting of how the process affects greenhouse gas fluxes. Enhanced weathering (EW), the spreading of finely ground weatherable, cation-rich crushed rocks to soils, has the potential to sequester significant amounts of CO2 while improving soil health. However, the effect of EW affiliated increases in soil pH on soil organic carbon (SOC) decomposition and CO2 efflux from soils remain debated. It has been proposed that increasing soil pH can lead to enhanced SOC remineralization. To move forward this debate, we present CO2 flux and soil carbon pool data from a greenhouse study in large mesocosms. We focused on mildly acidic soil in which, on short time scales, cations from weathering quantitively move into the exchangeable fraction in soils. Therefore, gas fluxes changes should be largely linked to changes in SOC stores. We find no significant correlation between CO2 fluxes and soil pH and no significant correlation between CO2 fluxes and rock application. Although this does not rule out a link between soil pH and SOC remineralization rates, the effect is small relative to other factors, like temperature and soil moisture. Although minor increases in total inorganic carbon were observed in basalt-amended soils, these increases did not support a direct link between soil pH and increased CO2 emissions. We observed a small increase in soil total organic carbon stocks in basalt amended mesocosms, but this change was also not significant enough to drive a shift in observed soil CO2 fluxes.", "keywords": ["soil organic carbon", "enhanced weathering", "carbon dioxide removals", "co2", "CO2", "Enhanced weathering"], "contacts": [{"organization": "Chiaravalloti, Isabella, Zhang, Shuang, Planavsky, Noah,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16814380"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16814380", "name": "item", "description": "10.5281/zenodo.16814380", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16814380"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-04T00:00:00Z"}}, {"id": "10.5281/zenodo.16842801", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Journal Article", "created": "2022-06-17", "title": "Natural Time Series Parameters Forecasting: Validation of the Pattern-Sequence-Based Forecasting (PSF) Algorithm; A New Python Package", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Climate change has contributed substantially to the weather and land characteristic phenomena. Accurate time series forecasting for climate and land parameters is highly essential in the modern era for climatologists. This paper provides a brief introduction to the algorithm and its implementation in Python. The pattern-sequence-based forecasting (PSF) algorithm aims to forecast future values of a univariate time series. The algorithm is divided into two major processes: the clustering of data and prediction. The clustering part includes the selection of an optimum value for the number of clusters and labeling the time series data. The prediction part consists of the selection of a window size and the prediction of future values with reference to past patterns. The package aims to ease the use and implementation of PSF for python users. It provides results similar to the PSF package available in R. Finally, the results of the proposed Python package are compared with results of the PSF and ARIMA methods in R. One of the issues with PSF is that the performance of forecasting result degrades if the time series has positive or negative trends. To overcome this problem difference pattern-sequence-based forecasting (DPSF) was proposed. The Python package also implements the DPSF method. In this method, the time series data are first differenced. Then, the PSF algorithm is applied to this differenced time series. Finally, the original and predicted values are restored by applying the reverse method of the differencing process. The proposed methodology is tested on several complex climate and land processes and its potential is evidenced.</p></article>", "keywords": ["Technology", "330", "QH301-705.5", "univariate", "T", "Physics", "QC1-999", "forecasting", "02 engineering and technology", "Engineering (General). Civil engineering (General)", "forecasting; univariate; time series; Python; PSF", "Chemistry", "0203 mechanical engineering", "13. Climate action", "0202 electrical engineering", " electronic engineering", " information engineering", "time series", "TA1-2040", "Biology (General)", "QD1-999", "PSF", "Python"]}, "links": [{"href": "http://www.mdpi.com/2076-3417/12/12/6194/pdf"}, {"href": "https://www.mdpi.com/2076-3417/12/12/6194/pdf"}, {"href": "https://research.usq.edu.au/download/a41f7e6afaf72d3aab08e4fbf5850ce9baed364db9cd274b284e7956b4aa1a6e/1339682/applsci-12-06194-v3.pdf"}, {"href": "https://doi.org/10.5281/zenodo.16842801"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16842801", "name": "item", "description": "10.5281/zenodo.16842801", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16842801"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-17T00:00:00Z"}}, {"id": "10.5281/zenodo.17187559", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:39Z", "type": "Dataset", "title": "Gap-filled subset of the Peatland Mid-Infrared Database (1.0.0)", "description": "Introduction  This is a gap-filled subset of the Peatland Mid-Infrared Database (1.0.0) (pmird database) stored in the rds format from the R programming language. Measurements for some peat properties were gap-filled using mid-infrared spectra (MIRS) prediction models described in Teickner and Knorr (2025) or calculated from element contents or bulk densities using auxiliary models.     Format  File irp_pmird_gap_filled.rds contains a list with the following elements:    meta: A data frame with a row for each record (id_measurement) in the pmird database for which attributes were gap-filled and three columns: id_measurement, id_sample, id_measurement. Values of these columns identify unique records in the pmird database.   The remaining elements are all data frames with a row for each row in meta and each column representing a peat property.      yhat: A data frame with gap-filled values predicted from the MIRS prediction models. For the meaning of the variables, please see Teickner and Knorr (2025) and the documentation of the prediction models in the R packages irpeatmodels (Teickner 2025a) and irpeat (Teickner 2025b).     yhat_auxilliary: A data frame with gap-filled values computed without MIRS prediction models. Gap-filled values are available for the following peat properties:    C_to_N_3 (C/N), O_to_C_3 (O/C), H_to_C_3 (H/C), nosc_2 (nominal oxidation state of carbon, NOSC): Values are computed from element contents measured with elemental analyzers.  dgf0_3 (standard Gibbs free enrgy of formation): Values are computed from element contents measured with elemental analyzers with auxiliary models as described in Teickner and Knorr (2025).  volume_fraction_solids_1 (volume fraction of solids), non_macroporosity_1 (volume fraction of non-macropores), macroporosity_1 (volume fraction of macropores), saturated_hydraulic_conductivity_1 (saturated hydraulic conductivity), dry_thermal_conductivity_1 (dry thermal conductivity): Values are estimated with pedotransfer functions described in Teickner and Knorr (2025) from bulk density measurements.  specific_heat_capacity_1 (specific heat capacity): Values are estimated with a pedotransfer function described in Teickner and Knorr (2025) from N content measurements.      is_in_training_pd: A data frame with a logical value for each entry indicating whether the MIRS used for gap-filling of values in yhat is within the training prediction domain of the respective MIRS prediction model (TRUE) or not (FALSE). For the definition of training prediction domain, see Teickner and Knorr (2025).     is_in_testing_pd: A data frame with a logical value for each entry indicating whether the MIRS used for gap-filling of values in yhat is within the testing prediction domain of the respective MIRS prediction model (TRUE) or not (FALSE). For the definition of training prediction domain, see Teickner and Knorr (2025).       Usage notes  To load the data within an R session, the following R packages need to be installed: tibble, posterior, and units. The rds file containing the data can be loaded as follows:  d <- readRDS(file = file, refhook =  (x) new.env())  Here, file is the path to the rds file.  The columns in yhat and yhat_auxilliary are rvar objects from the posterior\u00a0package (https://mc-stan.org/posterior/articles/rvar.html).     Data sources  Data in the database were derived from the following sources: De la Cruz, Osborne, and Barlaz (2016), Hodgkins et al. (2018), Knierzinger et al. (2020), Knierzinger (2020), M\u00fcnchberger (2019), M\u00fcnchberger et al. (2019), Schuster et al. (2022), Drollinger, Kuzyakov, and Glatzel (2019), Drollinger et al. (2020), Agethen and Knorr (2018), Kendall (2020), L. I. Harris et al. (2023), L. Harris and Olefeldt (2023), Pelletier et al. (2017), Teickner, Gao, and Knorr (2021), Teickner, Gao, and Knorr (2022), Heffernan (2019), Heffernan et al. (2020), Broder et al. (2012), Anzenhofer (2014, unpublished), Mathijssen et al. (2019), Wagner (2013), H\u00f6mberg (2014), Berger et al. (2017), Berger et al. (2018), T. R. Moore et al. (2019), Diaconu et al. (2020), Ga\u0142ka, H\u00f6lzer, et al. (2022), Ga\u0142ka, Diaconu, et al. (2022), L. I. Harris et al. (2018), L. I. Harris et al. (2019), Boothroyd et al. (2021), Worrall (2021), Reuter et al. (2019b), Reuter et al. (2019a), Reuter et al. (2020), T. Moore et al. (2005), Turunen et al. (2004).     Acknowledgements  Development of this database was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) grant no. KN 929/23-1 to Klaus-Holger Knorr and grant no. PE 1632/18-1 to Edzer Pebesma.     References    Agethen, Svenja, and Klaus-Holger Knorr. 2018. \u201cJuncus Effusus Mono-Stands in Restored Cutover Peat Bogs \u2013 Analysis of Litter Quality, Controls of Anaerobic Decomposition, and the Risk of Secondary Carbon Loss.\u201d Soil Biology and Biochemistry 117: 139\u201352. https://doi.org/10.1016/j.soilbio.2017.11.020.  Anzenhofer, Regina. 2014, unpublished. \u201cBiogeochemical Characterization of Peat Profiles Along a Vegetation Gradient in an Ombrotrophic Bog, Patagonia.\u201d Master\u2019s thesis.  Berger, Sina, Gerhard Gebauer, Christian Blodau, and Klaus-Holger Knorr. 2017. \u201cPeatlands in a Eutrophic World \u2013 Assessing the State of a Poor Fen-Bog Transition in Southern Ontario, Canada, After Long Term Nutrient Input and Altered Hydrological Conditions.\u201d Soil Biology and Biochemistry 114 (November): 131\u201344. https://doi.org/10.1016/j.soilbio.2017.07.011.  Berger, Sina, Leandra S. E. Praetzel, Marie Goebel, Christian Blodau, and Klaus-Holger Knorr. 2018. \u201cDifferential Response of Carbon Cycling to Long-Term Nutrient Input and Altered Hydrological Conditions in a Continental Canadian Peatland.\u201d Biogeosciences 15 (3): 885\u2013903. https://doi.org/10.5194/bg-15-885-2018.  Boothroyd, I. M., F. Worrall, C. S. Moody, G. D. Clay, G. D. Abbott, and R. Rose. 2021. \u201cSulfur Constraints on the Carbon Cycle of a Blanket Bog Peatland.\u201d Journal of Geophysical Research: Biogeosciences 126 (8). https://doi.org/10.1029/2021JG006435.  Broder, T., C. Blodau, H. Biester, and K. H. Knorr. 2012. \u201cPeat Decomposition Records in Three Pristine Ombrotrophic Bogs in Southern Patagonia.\u201d Biogeosciences 9 (4): 1479\u201391. https://doi.org/10.5194/bg-9-1479-2012.  De la Cruz, Florentino B., Jason Osborne, and Morton A. Barlaz. 2016. \u201cDetermination of Sources of Organic Matter in Solid Waste by Analysis of Phenolic Copper Oxide Oxidation Products of Lignin.\u201d Journal of Environmental Engineering 142 (2): 04015076. https://doi.org/10.1061/(ASCE)EE.1943-7870.0001038.  Diaconu, Andrei-Cosmin, Ioan Tan\u0163\u0103u, Klaus-Holger Knorr, Werner Borken, Angelica Feurdean, Andrei Panait, and Mariusz Ga\u0142ka. 2020. \u201cA Multi-Proxy Analysis of Hydroclimate Trends in an Ombrotrophic Bog over the Last Millennium in the Eastern Carpathians of Romania.\u201d Palaeogeography, Palaeoclimatology, Palaeoecology 538 (January): 109390. https://doi.org/10.1016/j.palaeo.2019.109390.  Drollinger, Simon, Klaus-Holger Knorr, Wolfgang Knierzinger, and Stephan Glatzel. 2020. \u201cPeat Decomposition Proxies of Alpine Bogs Along a Degradation Gradient.\u201d Geoderma 369 (June): 114331. https://doi.org/10.1016/j.geoderma.2020.114331.  Drollinger, Simon, Yakov Kuzyakov, and Stephan Glatzel. 2019. \u201cEffects of Peat Decomposition on 13C and 15N Depth Profiles of Alpine Bogs.\u201d CATENA 178 (July): 1\u201310. https://doi.org/10.1016/j.catena.2019.02.027.    Ga\u0142ka, Mariusz, Andrei-Cosmin Diaconu, Angelica Feurdean, Julie Loisel, Henning Teickner, Tanja Broder, and Klaus-Holger Knorr. 2022. \u201cRelations of Fire, Palaeohydrology, Vegetation Succession, and Carbon Accumulation, as Reconstructed from a Mountain Bog in the Harz Mountains (Germany) During the Last 6200 Years.\u201d Geoderma 424 (October): 115991. https://doi.org/10.1016/j.geoderma.2022.115991.  Ga\u0142ka, Mariusz, Adam H\u00f6lzer, Angelica Feurdean, Julie Loisel, Henning Teickner, Andrei-Cosmin Diaconu, Marta Szal, Tanja Broder, and Klaus-Holger Knorr. 2022. \u201cInsight into the Factors of Mountain Bog and Forest Development in the Schwarzwald Mts.: Implications for Ecological Restoration.\u201d Ecological Indicators 140 (July): 109039. https://doi.org/10.1016/j.ecolind.2022.109039.  Harris, Lorna I., Tim R. Moore, Nigel T. Roulet, and Andrew J. Pinsonneault. 2018. \u201cLichens: A Limit to Peat Growth?\u201d Edited by John Lee. Journal of Ecology 106 (6): 2301\u201319. https://doi.org/10.1111/1365-2745.12975.  \u2014\u2014\u2014. 2019. \u201cData from: Lichens: A Limit to Peat Growth?\u201d Data. https://doi.org/10.5061/dryad.s136dc8.  Harris, Lorna I., David Olefeldt, Nicolas Pelletier, Christian Blodau, Klaus-Holger Knorr, Julie Talbot, Liam Heffernan, and Merritt Turetsky. 2023. \u201cPermafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited.\u201d Global Change Biology, August, gcb.16894. https://doi.org/10.1111/gcb.16894.  Harris, Lorna, and David Olefeldt. 2023. \u201cPermafrost Thaw Causes Large Carbon Loss in Boreal Peatlands While Changes to Peat Quality Are Limited.\u201d Dryad. https://doi.org/10.5061/DRYAD.47D7WM3KK.  Heffernan, Liam. 2019. \u201cPeat Carbon, \u03b4  14C, Macrofossil, and Humification Data from a Thawing Permafrost Peatland in Western Canada.\u201d UAL Dataverse. https://doi.org/10.7939/DVN/MKM0ZE.  Heffernan, Liam, Cristian Estop-Aragon\u00e9s, Klaus-Holger Knorr, Julie Talbot, and David Olefeldt. 2020. \u201cLong-Term Impacts of Permafrost Thaw on Carbon Storage in Peatlands: Deep Losses Offset by Surficial Accumulation.\u201d Journal of Geophysical Research: Biogeosciences 125 (3). https://doi.org/10.1029/2019JG005501.  Hodgkins, Suzanne B., Curtis J. Richardson, Ren\u00e9 Dommain, Hongjun Wang, Paul H. Glaser, Brittany Verbeke, B. Rose Winkler, et al. 2018. \u201cTropical Peatland Carbon Storage Linked to Global Latitudinal Trends in Peat Recalcitrance.\u201d Nature Communications 9 (1): 3640. https://doi.org/10.1038/s41467-018-06050-2.  H\u00f6mberg, Annkathrin. 2014. \u201cGeochemische Charakterisierung von Mooren der Changbai Mountains.\u201d {Bachelor thesis}, M\u00fcnster: M\u00fcnster.  Kendall, Rachel Anne. 2020. \u201cMicrobial and Substrate Decomposition Factors in Commercially Extracted Peatlands in Canada.\u201d Master\u2019s thesis, Montr\u00e9al: McGill University.  Knierzinger, Wolfgang. 2020. \u201c(Bio)geochemical Data P\u00fcrgschachen Moor.\u201d Pangaea.  Knierzinger, Wolfgang, Ruth Drescher-Schneider, Klaus-Holger Knorr, Simon Drollinger, Andreas Limbeck, Lukas Brunnbauer, Felix Horak, Daniela Festi, and Michael Wagreich. 2020. \u201cAnthropogenic and Climate Signals in Late-Holocene Peat Layers of an Ombrotrophic Bog in the Styrian Enns Valley (Austrian Alps).\u201d E&G Quaternary Science Journal 69 (2): 121\u201337. https://doi.org/10.5194/egqsj-69-121-2020.  Mathijssen, Paul J. H., Mariusz Ga\u0142ka, Werner Borken, and Klaus-Holger Knorr. 2019. \u201cPlant Communities Control Long Term Carbon Accumulation and Biogeochemical Gradients in a Patagonian Bog.\u201d Science of The Total Environment 684 (September): 670\u201381. https://doi.org/10.1016/j.scitotenv.2019.05.310.  Moore, Tim R., Klaus-Holger Knorr, Lauren Thompson, Cameron Roy, and Jill L. Bubier. 2019. \u201cThe Effect of Long-Term Fertilization on Peat in an Ombrotrophic Bog.\u201d Geoderma 343 (June): 176\u201386. https://doi.org/10.1016/j.geoderma.2019.02.034.  Moore, Tim, Christian Blodau, Jukka Turunen, Nigel T. Roulet, and Pierre J. H. Richard. 2005. \u201cPatterns of Nitrogen and Sulfur Accumulation and Retention in Ombrotrophic Bogs, Eastern Canada.\u201d Global Change Biology 11 (2): 356\u201367. https://doi.org/10.1111/j.1365-2486.2004.00882.x.  M\u00fcnchberger, Wiebke. 2019. \u201cPast and Present Carbon Dynamics in Contrasting South Patagonian Bog Ecosystems.\u201d PhD thesis, M\u00fcnster: University M\u00fcnster.  M\u00fcnchberger, Wiebke, Klaus-Holger Knorr, Christian Blodau, Ver\u00f3nica A. Pancotto, and Till Kleinebecker. 2019. \u201cZero to Moderate Methane Emissions in a Densely Rooted, Pristine Patagonian Bog \u2013 Biogeochemical Controls as Revealed from Isotopic Evidence.\u201d Biogeosciences 16 (2): 541\u201359. https://doi.org/10.5194/bg-16-541-2019.  Pelletier, Nicolas, Julie Talbot, David Olefeldt, Merritt Turetsky, Christian Blodau, Oliver Sonnentag, and William L Quinton. 2017. \u201cInfluence of Holocene Permafrost Aggradation and Thaw on the Paleoecology and Carbon Storage of a Peatland Complex in Northwestern Canada.\u201d The Holocene 27 (9): 1391\u20131405. https://doi.org/10.1177/0959683617693899.  Reuter, Hendrik, Julia Gensel, Marcus Elvert, and Dominik Zak. 2019a. \u201cCuO Lignin, and Bulk Decomposition Data of a 75-Day Anoxic Phragmites Australis Litter Decomposition Experiment in Soil Substrates from Three Northeast German Wetlands.\u201d PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.902176.  \u2014\u2014\u2014. 2019b. \u201cInfrared Spectra (FTIR) of Phragmites Australis Litter, Initial and After Anoxic Decomposition in Three Wetland Substrates.\u201d PANGAEA - Data Publisher for Earth & Environmental Science. https://doi.org/10.1594/PANGAEA.902069.  \u2014\u2014\u2014. 2020. \u201cEvidence for Preferential Protein Depolymerization in Wetland Soils in Response to External Nitrogen Availability Provided by a Novel FTIR Routine.\u201d Biogeosciences 17 (2): 499\u2013514. https://doi.org/10.5194/bg-17-499-2020.  Schuster, Wiebke, Klaus-Holger Knorr, Christian Blodau, Mariusz Ga\u0142ka, Werner Borken, Ver\u00f3nica A. Pancotto, and Till Kleinebecker. 2022. \u201cControl of Carbon and Nitrogen Accumulation by Vegetation in Pristine Bogs of Southern Patagonia.\u201d Science of The Total Environment 810 (March): 151293. https://doi.org/10.1016/j.scitotenv.2021.151293.  Teickner, Henning. 2025a. \u201cirpeatmodels: Mid-infrared Prediction Models for Peat.\u201d  \u2014\u2014\u2014. 2025b. \u201cpmird: R Interface to the Peatland Mid-Infrared Database.\u201d  Teickner, Henning, Chuanyu Gao, and Klaus-Holger Knorr. 2021. \u201cReproducible Research Compendium with R Code and Data for: \u2019Electrochemical Properties of Peat Particulate Organic Matter on a Global Scale: Relation to Peat Chemistry and Degree of Decomposition\u2019.\u201d Zenodo. https://doi.org/10.5281/zenodo.5792970.  \u2014\u2014\u2014. 2022. \u201cElectrochemical Properties of Peat Particulate Organic Matter on a Global Scale: Relation to Peat Chemistry and Degree of Decomposition.\u201d Global Biogeochemical Cycles 36 (2): e2021GB007160. https://doi.org/10.1029/2021GB007160.  Teickner, Henning, and Klaus-Holger Knorr. 2025. \u201cPrediction of Peat Properties from Transmission Mid-Infrared Spectra in the Peatland Mid-Infrared Spectra Database.\u201d  Turunen, Jukka, Nigel T. Roulet, Tim R. Moore, and Pierre J. H. Richard. 2004. \u201cNitrogen Deposition and Increased Carbon Accumulation in Ombrotrophic Peatlands in Eastern Canada: N Deposition and Peat Accumulation.\u201d Global Biogeochemical Cycles 18 (3). https://doi.org/10.1029/2003GB002154.  Wagner, Sindy. 2013. \u201cAnalysis of Peat Decomposition, Element Distribution Patterns and Element Output of Two Peat Bogs in the Thuringian Forest.\u201d Master\u2019s thesis, University Bayreuth.  Worrall, Fred. 2021. \u201cSulphur Constraints on the Carbon Cycle of a Blanket Bog Peatland [Dataset].\u201d Durham University. https://doi.org/10.15128/R2PK02C9794.", "keywords": ["nominal oxidation state of carbon", "bogs", "porosity", "element content", "peat", "Gibbs free enrgy of formation", "thermal conductivity", "specific heat capacity", "mid-infrared spectra", "pmird", "peatlands", "hydraulic conductivity"], "contacts": [{"organization": "Teickner, Henning, Knorr, Klaus-Holger,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17187559"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17187559", "name": "item", "description": "10.5281/zenodo.17187559", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17187559"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-25T00:00:00Z"}}, {"id": "10.5281/zenodo.16895081", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Report", "created": "2021-06-25", "title": "51. Real-time spectral information to measure crop water stress for variable rate irrigation scheduling", "keywords": ["0301 basic medicine", "03 medical and health sciences", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences"], "contacts": [{"organization": "Nagy, Attila, Szab\u00f3, Andrea, Farkasn\u00e9 Dr. G\u00e1lya, Bernadett, Tamas, Janos,", "roles": ["creator"]}]}, "links": [{"href": "https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-916-9"}, {"href": "https://www.wageningenacademic.com/doi/pdf/10.3920/978-90-8686-916-9_51"}, {"href": "https://doi.org/10.5281/zenodo.16895081"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16895081", "name": "item", "description": "10.5281/zenodo.16895081", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16895081"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-19T00:00:00Z"}}, {"id": "10.5281/zenodo.16895135", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Journal Article", "created": "2023-08-31", "title": "Comparing the environmental impact of poultry manure and chemical fertilizers", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>One of the challenges in livestock production is the significant volume of manure generated, which must be appropriately managed to mitigate its environmental impacts. Untreated manure poses a potential hazard to soil, surface water, groundwater, and human and animal health. Based on the life cycle assessment (LCA) method, the research aims to evaluate the ecological load of composted-pelletized poultry litter (CPPL) in maize and winter wheat production. Furthermore, the environmental loads of CPPL applications are compared with those of other N, P, and K fertilizers. The research study utilized the openLCA software with the Agribalyse 3.1 database to calculate eleven impact categories. In the case of maize, only ozone depletion has higher emissions. For winter wheat production, scenarios where the P fertilizer was MAP had lower impacts for NPK combinations. While for the CPPL, fuel was the main contributor to loads, for the NPK fertilizer scenarios, energy use for fertilizer production contributed more. The results can be relevant to the burdens of using different nutrient replacement products and creating diverse feed mixtures. The application of CPPL promises to reduce the burden of crop production and, consequently, feed production. Additionally, it allows for the recovery of manure not useable by the livestock industry.</p></article>", "keywords": ["2. Zero hunger", "0211 other engineering and technologies", "environmental impacts", "02 engineering and technology", "15. Life on land", "maize", "Engineering (General). Civil engineering (General)", "7. Clean energy", "winter wheat", "12. Responsible consumption", "life cycle assessment", "HT165.5-169.9", "13. Climate action", "composted-pelletized poultry litter", "0202 electrical engineering", " electronic engineering", " information engineering", "TA1-2040", "City planning", "chemical fertilizers"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16895135"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Built%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16895135", "name": "item", "description": "10.5281/zenodo.16895135", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16895135"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-31T00:00:00Z"}}, {"id": "10.5281/zenodo.16926945", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:38Z", "type": "Dataset", "title": "Adjusted bulk density data in the Hungarian Soil Information and Monitoring System", "description": "This dataset provides corrected bulk density (BD) values and their associated uncertainty estimates for 4,340 soil genetic horizons across 1,236 monitoring sites of the Hungarian Soil Information and Monitoring System. The correction was achieved by developing a pedotransfer function (PTF) based on the Hungarian Detailed Soil Hydro-physical Database (Hungarian acronym: MARTHA) and advanced machine learning algorithms. Soil properties (i.e., soil organic carbon, pH in water, and sand, silt, and clay content) together with environmental covariates, used as proxies for the soil forming factors, were integrated into the PTF development to improve predictive performance.  Uncertainty of the BD predictions is provided in two forms: (1) the 90% prediction interval (defined by its lower and upper limits, within which the true value is expected to occur nine times out of ten), and (2) the standard error of the corrected BD values. To ensure transparency, reproducibility, and open access, the corrected BD values, their corresponding uncertainty estimates, and the developed code are publicly available.  For more details / to cite this dataset please use:  Sohrab, S., Szab\u00f3, B., P\u00e1sztor, L., Mak\u00f3, A., Szatm\u00e1ri, G. (2025). Adjusting bulk density observations in the Hungarian Soil Information and Monitoring System using advanced pedotransfer functions. European Journal of Soil Science (submitted manuscript)  Codes are available on GitHub:  https://github.com/Mehrsoh/Soil-BD-Correction  Description of the files:  Two versions of the same dataset are provided, differing only in file format: (1) 'HUN-SIMS_BD_corrected.csv' \u2013 CSV format (separated by semicolon), and (2) 'HUN-SIMS_BD_corrected.xlsx' \u2013 Microsoft Excel format. The table below summarizes the column names, units, and data formats, and also provides a description for each column. Note that the coordinate reference system is the Hungarian Unified National Projection System (HD72/EOV; EPSG: 23700). For more details, see https://epsg.io/23700.       Column name    Format    Unit    Description      PROFILE_ID    string    -    Identifier of monitoring sites in the Hungarian Soil Information and Monitoring System      LAYER_ID    string    -    Identifier of soil genetic horizons at a monitoring site      X    numeric    [m]    X coordinate      Y    numeric    [m]    Y coordinate      TOP    numeric    [cm]    Upper depth boundary of soil genetic horizons      BOTTOM    numeric    [cm]    Lower depth boundary of soil genetic horizons      BD_CORRECTED    numeric    [g\u00b7cm-3]    Bias-corrected bulk density value      Q_05    numeric    [g\u00b7cm-3]    5th quantile; lower limit of the 90% prediction interval      Q_95    numeric    [g\u00b7cm-3]    95th quantile; upper limit of the 90% prediction interval      SE    numeric    [g\u00b7cm-3]    Standard error of the bias-corrected bulk density value", "keywords": ["Soil sciences", "Soil health", "Earth and related environmental sciences", "Soil physics", "Soil monitoring", "FOS: Earth and related environmental sciences", "Pedotransfer function"], "contacts": [{"organization": "Sohrab, Seyedehmehrmanzar, Szab\u00f3, Brigitta, P\u00e1sztor, L\u00e1szl\u00f3, Mak\u00f3, Andr\u00e1s, Szatm\u00e1ri, G\u00e1bor,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16926945"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16926945", "name": "item", "description": "10.5281/zenodo.16926945", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16926945"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-04T00:00:00Z"}}, {"id": "11573/1419330", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:25:29Z", "type": "Journal Article", "created": "2020-06-05", "title": "Variability in pulmonary diffusing capacity in heart failure", "description": "As pulmonary diffusing capacity is related to mortality risk and prognosis in patients with heart failure (HF), it is measured frequently. As such, it would be essential to know the week-to-week variability (reproducibility) of pulmonary diffusing capacity for carbon monoxide (DLCO) and nitric oxide (DLNO). This variability would let clinicians understand what a clinically measurable change in DLCO and DLNO would be in these patients.On three different days spanning over ten weeks, 40\u2009H\u2009F patients underwent testing for DLCO and DLNO. DLCO was determined after a 4\u2009s and 10\u2009s breath-hold maneuver, while DLNO was determined after a 4\u2009s breath-hold maneuver.Forty heart failure patients (66\u2009\u00b1\u200910 years; BMI\u2009=\u200928.4\u2009\u00b1\u20094.6\u2009kg\u2219m-2; 28 males), that were referred to our clinic were able to complete the protocol. DLCO (4\u2009s breath-hold) and DLNO (4\u2009s breath-hold) were 79\u2009\u00b1\u200919 % and 59\u2009\u00b1\u200914 % predicted, respectively. Fifty percent of patients (n\u2009=\u200920) were below the lower limit of normal (LLN, below the 5th percentile) for predicted DLCO (4\u2009s), while 78 % of patients (n\u2009=\u200931) were below the LLN for predicted DLNO. All 16 patients that were below the LLN for DLCO were also below the LLN for DLNO. Over a ten week period, the reproducibility of DLNO (4\u2009s) DLCO (4\u2009s) and DLCO (10\u2009s) was 18.9, 8.2, and 5.9\u2009mL\u2009min\u2009mmHg-1, respectively.The week-to-week fluctuation in DLNO (4\u2009s), as a percentage, is less than DLCO (4\u2009s) in patients with HF. The reproducibility of DLNO in patients with HF is like that of healthy subjects.", "keywords": ["Male", "DLCO; DLNO; lung function; heart failure; reproducibility", "Physiology (science-metrix)", "Heart Disease (rcdc)", "Pulmonary Diffusing Capacity (mesh)", "3208 Medical physiology (for-2020)", "Heart failure", "Nitric Oxide", "Lung (rcdc)", "DLCO", "DLCO; DLNO; Heart failure; Lung function; Reproducibility;", "Clinical Research (rcdc)", "03 medical and health sciences", "0302 clinical medicine", "1102 Cardiorespiratory Medicine and Haematology (for)", "Middle Aged (mesh)", "Reproducibility of Results (mesh)", "Humans", "32 Biomedical and Clinical Sciences (for-2020)", "Male (mesh)", "3202 Clinical Sciences (for-2020)", "Carbon Monoxide (mesh)", "Aged", "DLNO", "Heart Failure", "Humans (mesh)", "Carbon Monoxide", "Cardiovascular (hrcs-hc)", "Aged (mesh)", "3201 Cardiovascular medicine and haematology (for-2020)", "Reproducibility of Results", "Heart Failure (mesh)", "Middle Aged", "1109 Neurosciences (for)", "Lung function", "Reproducibility", "3. Good health", "1116 Medical Physiology (for)", "4.2 Evaluation of markers and technologies (hrcs-rac)", "Female (mesh)", "Nitric Oxide (mesh)", "Pulmonary Diffusing Capacity", "Cardiovascular (rcdc)", "Female"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/743296/2/agostoni%203.pdf"}, {"href": "https://doi.org/11573/1419330"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Respiratory%20Physiology%20%26amp%3B%20Neurobiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11573/1419330", "name": "item", "description": "11573/1419330", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11573/1419330"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-09-01T00:00:00Z"}}, {"id": "10.5281/zenodo.17206462", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:40Z", "type": "Dataset", "title": "Polyaromatic Hydrocarbon (PAHs) Concentration and Peak intensities Data", "description": "This data set is published as Wildfire, ecosystem, and climate interactions in the Early Triassic in Communication Earth and Enivronment (https://doi.org/10.1038/s43247-025-02789-x).  Wildfires are an important component of Earth system dynamics particularly with respect to nutrient- and carbon cycling. The\u00a0 occurrence of wildfires is linked to complex feedbacks between climate, vegetation and landscape structure. It is therefore crucial to understand wildfire activity in the context of (paleo-)climatic and environmental change. In this study, we explore wildfire activity during the Early Triassic (Smithian and Spathian substages, ca. 250 million years ago) \u2013 a time interval characterized by large global carbon cycle perturbation, climatic oscillations, prominent terrestrial vegetation succession, along with radiation and extinction pulses \u2013 using polyaromatic hydrocarbon (PAH) biomarkers, which serve as a robust indicator of fire in sedimentary geologic archives. PAH abundances in shales from Spitsbergen show a prominent increase after the Smithian-Spathian boundary. Further, diagnostic ratios of PAHs suggest that these compounds were derived from relatively unaltered biomass as opposed to soil erosion and petrogenic carbon inputs or coal combustion vis-\u00e0-vis a coincidental Siberian Trap volcanism. Instead, our data indicates that as sea surface temperatures decline during the late Smithian, the hydrological cycle becomes less intense and large-scale changing vegetation successions become amenable to wildfire activity. From our results, we hypothesize that the change in regional wildfire regime would have exerted influence on other regional biogeochemical cycles, especially pyrogenic carbon, which in turn may have impacted long-term carbon sequestration dynamics. The coupled behavior of this water-vegetation-wildfire system amid key perturbations in Earth\u2019s history provides new insights into imminent future consequences of human activities and the related impacts on climate.", "keywords": ["Environmental sciences", "Earth Sciences", "Organic geochemistry"], "contacts": [{"organization": "Blattmann, Franziska, Ragon, Charline, Vennemann, Torsten W., Schneebeli-Hermann, Elke, V\u00e9rard, Christian, Kasparian, J\u00e9r\u00f4me, Brunetti, Maura, Bucher, Hugo F.R., Adatte, Thierry, Magill, Clayton,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17206462"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17206462", "name": "item", "description": "10.5281/zenodo.17206462", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17206462"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-26T00:00:00Z"}}, {"id": "10.5281/zenodo.16927293", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:39Z", "type": "Dataset", "title": "Soil gas analyses and geochemistry in B\u0103ile L\u0103z\u0103re\u0219ti, Harghita, Romania, August 2022", "description": "For given locations, results of soil gas analyses, TOC, CaCO3, Na2O, MgO, SiO2, P2O5, K2O, CaO, Ti, V, Cr, MnO, Fa2O3, Ni, Cu, Zn, As, Sr, Zr, Sn, Hg, Pb, water content, dry matter, total organic carbon, carbonates, siliciclastic.", "keywords": ["Geochemistry", "Metals", " Heavy", "Soil gas flux", "Oxides", "FOS: Earth and related environmental sciences", "TOC"], "contacts": [{"organization": "Dudu, Alexandra, Naliana, Lupascu, GeoEcoMar,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16927293"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16927293", "name": "item", "description": "10.5281/zenodo.16927293", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16927293"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-08-22T00:00:00Z"}}, {"id": "10.5281/zenodo.17064291", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-04-04T16:23:39Z", "type": "Dataset", "title": "Soil organic carbon and soil organic matter measurements across habitats from the UK and Spain", "description": "This dataset includes measurements of total soil carbon, soil organic carbon and soil organic matter for soil samples from Spain (AI4SoilHealth project), England (Biosoil project) and the UK (CINAg project). Soils were sampled to different depths based on the project\u2019s requirements.  The datasets is part of a bigger dataset to investigate the fraction of soil organic carbon (SOC) in soil organic matter (SOM), denoted as , as a national-scale soil process indicator.", "keywords": ["soil organic carbon", "soil health", "soil organic matter", "indicator"], "contacts": [{"organization": "Reinsch, Sabine", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17064291"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17064291", "name": "item", "description": "10.5281/zenodo.17064291", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17064291"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-05T00:00:00Z"}}, {"id": "10.5281/zenodo.17326891", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:23:40Z", "type": "Report", "title": "Cyrtolabulus emirufus Selis, 2025, sp. nov.", "description": "unspecifiedPublished as part of Selis, Marco, 2025, The solitary vespid wasps of Madagascar (Hymenoptera: Vespidae: Eumeninae, Raphiglossinae and Zethinae), pp. 1-171 in Zootaxa 5705 (1) on pages 53-56, DOI: 10.11646/zootaxa.5705.1.1, http://zenodo.org/record/17326767", "keywords": ["Cyrtolabulus", "Insecta", "Eumenidae", "Cyrtolabulus emirufus", "Arthropoda", "Animalia", "Biodiversity", "Hymenoptera", "Taxonomy"], "contacts": [{"organization": "Selis, Marco", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17326891"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17326891", "name": "item", "description": "10.5281/zenodo.17326891", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17326891"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-10-08T00:00:00Z"}}, {"id": "2078.1/249652", "type": "Feature", "geometry": null, "properties": {"updated": "2026-04-04T16:26:02Z", "type": "Journal Article", "created": "2021-07-23", "title": "Iron Redistribution Upon Thermokarst Processes in the Yedoma Domain", "description": "<p>Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R2 = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.</p", "keywords": ["ddc:550", "Science", "Q", "04 agricultural and veterinary sciences", "subarctic", "carbon stabilization", "01 natural sciences", "redox processes", "subarctic ; redox processes ; carbon stabilization ; thaw ; permafrost ; arctic ; Earth Science", "13. Climate action", "arctic", "0401 agriculture", " forestry", " and fisheries", "Institut f\u00fcr Geowissenschaften", "thaw", "permafrost", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/2078.1/249652"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Earth%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2078.1/249652", "name": "item", "description": "2078.1/249652", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2078.1/249652"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-23T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TH&offset=6300&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=TH&offset=6300&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "prev", "title": "items (prev)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TH&offset=6250", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=TH&offset=6350", "hreflang": "en-US"}], "numberMatched": 10325, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-04-05T06:07:09.436583Z"}