{"type": "FeatureCollection", "features": [{"id": "10.1016/j.gca.2019.06.035", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:15:38Z", "type": "Journal Article", "created": "2019-07-02", "title": "Experimentally determined Si isotope fractionation between zircon and quartz", "description": "Abstract The silicon isotope composition of detrital quartz and zircon have the potential to inform us about secular changes to the silica cycle and weathering reactions on Earth. However, inferring source melt Si isotope composition from out-of-context minerals is hampered by the fact that, to-date, there is limited Si isotope equilibrium fractionation data for minerals. Here, we report experimental data to constrain Si isotope equilibrium fractionation between zircon and quartz, using two fundamentally different strategies, but with the same experimental design. First, zircon and quartz were hydrothermally synthesized from Zr(OH)4 and SiO2 at 1.5\u202fGPa and temperatures of 725, 800, and 900\u202f\u00b0C. The second experimental strategy utilized the three-isotope method; the starting materials consisted of natural zircon and isotopically-labelled SiO2. Three sets of hydrothermal time-series experiments were conducted at the same pressure and temperatures as the direct synthesis experiments. For all experiments, quartz and zircon were separated and 30Si/28Si and 29Si/28Si ratios were measured by solution multi-collector inductively coupled plasma mass spectrometry. The three-isotope method, which provides the best indicator of equilibrium fractionations, yields the following relationship: \u0394 30 S i ( q t z - z r c ) = ( 0.53 \u00b1 0.14 ) \u00d7 10 6 / T 2 where \u039430Si(qtz-zrc) is the relative difference in 30Si/28Si between quartz and zircon in permil, T is temperature in K, and the error is 2\u202fs.e. This relationship can be used to calculate the fractionation between zircon and other phases, and to estimate the Si isotope composition of the melt from which a zircon crystallized. The results may be used to assess equilibrium-disequilibrium isotope fractionations between quartz and zircon and co-existing phases in igneous rocks. These data can also be applied to out-of-context zircon (and quartz) to estimate the isotope composition of the host rock. Zircons crystallizing from a melt derived from purely igneous sources \u2013 i.e., without the involvement of \u201cweathered\u201d material \u2013 are expected to display a \u03b430SiNBS-28 (permil deviation of the 30Si/28Si from the NBS-28 standard) range from \u22120.7 to \u22120.35\u2030. Deviations from this range indicate assimilation of non-igneous (i.e., sedimentary) material in the melt source.", "keywords": ["Zircon", "GE", "550", "NDAS", "Quartz", "Si isotopes", "7. Clean energy", "01 natural sciences", "Three-istope", "[SDU.STU.GC]Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "13. Climate action", "Igneous", "Three-isotope", "[SDU.STU.GC] Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "Fractionation", "GE Environmental Sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.gca.2019.06.035"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geochimica%20et%20Cosmochimica%20Acta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.gca.2019.06.035", "name": "item", "description": "10.1016/j.gca.2019.06.035", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.gca.2019.06.035"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-01T00:00:00Z"}}, {"id": "10.1016/j.radmeas.2019.106221", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:15:53Z", "type": "Journal Article", "created": "2019-11-19", "title": "Bleaching studies on Al-hole ([AlO4/h]0) electron spin resonance (ESR) signal in sedimentary quartz", "description": "Abstract Electron spin resonance (ESR) dating of sediments using quartz is most commonly used for older sediments (>100 ka), since large residuals render the ESR signal unsuitable for dating young sediments. The multiple-centre approach (utilising both Ti and [AlO4/h]0 signals) is usually used to test the resetting of the signals used for ESR dating. Here we work towards a better understanding of, and correction for, the residual signal in ESR samples of sedimentary quartz. We undertook multiple-centre ESR measurements using quartz [AlO4/h]0 and Ti signals on young aeolian samples of different grain sizes which have been independently dated using optically stimulated luminescence (OSL). Our results demonstrate that [AlO4/h]0 signal yields residuals indicating equivalent doses of about 500\u00a0Gy, substantially older than expected for the known OSL equivalent doses in the range of 8\u201337\u00a0Gy. The decay of [AlO4/h]0 signal as function of bleaching time can be represented by an exponential function. We investigate the dependence of the residual magnitude of the ESR signal as a function of the previous given dose and observe an exponential increase in the residual signal with dose. Such observations are consistent with the results of luminescence process modelling conducted for a model comprising two luminescence centres and several traps, one of which is a so-called deep disconnected trap that cannot be emptied during optical stimulation. We propose that bleaching occurs through an electron-hole recombination process with electrons released from optically sensitive traps. In addition to our new insights into the bleaching mechanisms of the [AlO4/h]0 ESR signal, we discuss the implications for the procedures used for performing residual dose corrections in ESR dating. We recommend that modern analogues be used in addition to laboratory-bleached samples when performing residual dose corrections.", "keywords": ["ESR dating", "Sedimentary quartz", "03 medical and health sciences", "0302 clinical medicine", "Residual", "Sedimentary quartz ESR dating[AlO4/h]0 Residual Bleaching Modelling", "[AlO4/h]0", "Bleaching", "01 natural sciences", "Modelling", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.radmeas.2019.106221"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Radiation%20Measurements", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.radmeas.2019.106221", "name": "item", "description": "10.1016/j.radmeas.2019.106221", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.radmeas.2019.106221"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2024.174325", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:15:59Z", "type": "Journal Article", "created": "2024-06-26", "title": "Production and characterisation of environmentally relevant microplastic test materials derived from agricultural plastics", "description": "Soil environments across the globe, particularly in agricultural settings, have now been shown to be contaminated with microplastics. Agricultural plastics - such as mulching films - are used in close or direct contact with soils and there is growing evidence demonstrating that they represent a potential source of microplastics. There is a demand to undertake fate and effects studies to understand the behaviour and potential long-term ecological risks of this contamination. Yet, there is a lack of test materials available for this purpose. This study describes the manufacture and characterisation of five large (1-40\u00a0kg) batches of microplastic test materials derived from agricultural mulching films. Batches were produced from either polyethylene-based conventional mulching films or starch-polybutadiene adipate terephthalate blend mulching films that are certified biodegradable in soil. Challenges encountered and overcome during the micronisation process provide valuable insights into the future of microplastic test material generation from these material types. This includes difficulties in micronising virgin polyethylene film materials. All five batches were subjected to a thorough physical and chemical characterisation - both of the original virgin films and the subsequent microplastic particles generated - including a screening for the presence of chemical additives. This is a critical step to provide essential information for interpreting particle fate or effects in scientific testing. Trade-offs between obtaining preferred particle typologies and time and cost constraints are elucidated. Several recommendations emerging from the experiences gained in this study are put forward to advance the research field towards greater harmonisation and utilisation of environmentally relevant test materials.", "keywords": ["Cryomilling", "Mulching film", "Microplastic", "500", "Micronisation", "Reference material", "630", "Plastic additives"]}, "links": [{"href": "https://iris.cnr.it/bitstream/20.500.14243/514125/1/1-s2.0-S0048969724044735-main.pdf"}, {"href": "https://doi.org/10.1016/j.scitotenv.2024.174325"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2024.174325", "name": "item", "description": "10.1016/j.scitotenv.2024.174325", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2024.174325"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-01T00:00:00Z"}}, {"id": "10.1029/2018wr024408", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:16:31Z", "type": "Journal Article", "created": "2019-10-23", "title": "Data Assimilation and Online Parameter Optimization in Groundwater Modeling Using Nested Particle Filters", "description": "Abstract

Over the past decades, advances in data collection and machine learning have paved the way for the development of autonomous simulation frameworks. Among these, many are capable not only of assimilating real\uffe2\uff80\uff90time data to correct their predictive shortcomings but also of improving their future performance through self\uffe2\uff80\uff90optimization. In hydrogeology, such techniques harbor great potential for informing sustainable management practices. Simulating the intricacies of groundwater flow requires an adequate representation of unknown, often highly heterogeneous geology. Unfortunately, it is difficult to reconcile the structural complexity demanded by realistic geology with the simplifying assumptions introduced in many calibration methods. The particle filter framework would provide the necessary versatility to retain such complex information but suffers from the curse of dimensionality, a fundamental limitation discouraging its use in systems with many unknowns. Due to the prevalence of such systems in hydrogeology, the particle filter has received little attention in groundwater modeling so far. In this study, we explore the combined use of dimension\uffe2\uff80\uff90reducing techniques and artificial parameter dynamics to enable a particle filter framework for a groundwater model. Exploiting freedom in the design of the dimension\uffe2\uff80\uff90reduction approach, we ensure consistency with a predefined geological pattern. The performance of the resulting optimizer is demonstrated in a synthetic test case for three such geological configurations and compared to two Ensemble Kalman Filter setups. Favorable results even for deliberately misspecified settings make us hopeful that nested particle filters may constitute a useful tool for geologically consistent real\uffe2\uff80\uff90time parameter optimization.Legume roots can be symbiotically colonized by arbuscular mycorrhizal (AM) fungi and nitrogen-fixing bacteria. In Lotus japonicus, the latter occurs intracellularly by the cognate rhizobial partner Mesorhizobium loti or intercellularly with the Agrobacterium pusense strain IRBG74. Although these symbiotic programs show distinctive cellular and transcriptome signatures, some molecular components are shared. In this study, we demonstrate that 3-deoxy-d-arabino-heptulosonate 7-phosphate synthase 1 (DAHPS1), the first enzyme in the biosynthetic pathway of aromatic amino acids (AAAs), plays a critical role in root hair development and for AM and rhizobial symbioses in Lotus. Two homozygous DAHPS1 mutants (dahps1-1 and dahps1-2) showed drastic alterations in root hair morphology, associated with alterations in cell wall dynamics and a progressive disruption of the actin cytoskeleton. The altered root hair structure was prevented by pharmacological and genetic complementation. dahps1-1 and dahps1-2 showed significant reductions in rhizobial infection (intracellular and intercellular) and nodule organogenesis and a delay in AM colonization. RNAseq analysis of dahps1-2 roots suggested that these phenotypes are associated with downregulation of several cell wall\uffe2\uff80\uff93related genes, and with an attenuated signaling response. Interestingly, the dahps1 mutants showed no detectable pleiotropic effects, suggesting a more selective recruitment of this gene in certain biological processes. This work provides robust evidence linking AAA metabolism to root hair development and successful symbiotic associations.Boreal forest regions, including East Siberia, have experienced elevated fire activity in recent years, leading to record\uffe2\uff80\uff90breaking greenhouse gas emissions and severe air pollution. However, our understanding of the factors that eventually halt fire spread and thus limit fire growth remains incomplete, hindering our ability to model their dynamics and predict their impacts. We investigated the locations and timing of 2.2 million fire stops\uffe2\uff80\uff94defined as 300\uffe2\uff80\uff89m unburned pixels along fire perimeters\uffe2\uff80\uff94across the vast East Siberian taiga. Fire stops were retrieved from remote sensing data covering over 27,000 individual fires that collectively burned 80 Mha between 2012 and 2022. Several geospatial datasets, including hourly fire weather data and landscape variables, were used to identify the factors contributing to individual fire stops. Our analysis attributed 87% of all fire stops to a statistically significant (p\uffe2\uff80\uff89<\uffe2\uff80\uff890.01) change in one or more of these drivers, with fire\uffe2\uff80\uff90weather drivers limiting fire growth over time and landscape drivers constraining it across space. We found clear regional and temporal variations in the importance of these drivers. For instance, landscape drivers\uffe2\uff80\uff94such as less flammable land cover and the presence of roads\uffe2\uff80\uff94were key constraints on fire growth in southeastern Siberia, where the landscape is more populated and fragmented. In contrast, fire weather was the primary constraint on fire growth in the remote northern taiga. Additionally, in central Yakutia, a major fire hotspot in recent years, fuel limitations from previous fires increasingly restricted fire spread. The methodology we present is adaptable to other biomes and can be applied globally, providing a framework for future attribution studies on global fire growth limitations. In northeast Siberia, we found that with increasing droughts and heatwaves, remote northern fires could potentially grow even larger in the future, with major implications for the global carbon cycle and climate.Forests provide important ecological, economic, and social services, and recent interest has emerged in the potential for using residue from timber harvest as a source of renewable woody bioenergy. The long\uffe2\uff80\uff90term consequences of such intensive harvest are unclear, particularly as forests face novel climatic conditions over the next century. We used a simulation model to project the long\uffe2\uff80\uff90term effects of management and climate change on above\uffe2\uff80\uff90 and belowground forest carbon storage in a watershed in northwestern Oregon. The multi\uffe2\uff80\uff90ownership watershed has a diverse range of current management practices, including little\uffe2\uff80\uff90to\uffe2\uff80\uff90no harvesting on federal lands, short\uffe2\uff80\uff90rotation clear\uffe2\uff80\uff90cutting on industrial land, and a mix of practices on private nonindustrial land. We simulated multiple management scenarios, varying the rate and intensity of harvest, combined with projections of climate change. Our simulations project a wide range of total ecosystem carbon storage with varying harvest rate, ranging from a 45% increase to a 16% decrease in carbon compared to current levels. Increasing the intensity of harvest for bioenergy caused a 2\uffe2\uff80\uff933% decrease in ecosystem carbon relative to conventional harvest practices. Soil carbon was relatively insensitive to harvest rotation and intensity, and accumulated slowly regardless of harvest regime. Climate change reduced carbon accumulation in soil and detrital pools due to increasing heterotrophic respiration, and had small but variable effects on aboveground live carbon and total ecosystem carbon. Overall, we conclude that current levels of ecosystem carbon storage are maintained in part due to substantial portions of the landscape (federal and some private lands) remaining unharvested or lightly managed.\uffc2\uffa0Increasing the intensity of harvest for bioenergy on currently harvested land, however,\uffc2\uffa0led to a relatively small reduction in the ability of forests to store carbon. Climate change is unlikely to substantially alter carbon storage in these forests, absent shifts in disturbance regimes.

", "keywords": ["0106 biological sciences", "Carbon dioxide mitigation", "Forest ecology -- Oregon -- Oregon Coast Range", "Forest biomass", "13. Climate action", "Carbon cycle (Biogeochemistry)", "Biomass energy", "Forest Biology", "15. Life on land", "01 natural sciences", "7. Clean energy", "Climatic change", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1111/gcbb.12255"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/GCB%20Bioenergy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcbb.12255", "name": "item", "description": "10.1111/gcbb.12255", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcbb.12255"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-05-25T00:00:00Z"}}, {"id": "10.1128/aem.02264-23", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:17:48Z", "type": "Journal Article", "created": "2024-02-19", "title": "Novel endolithic bacteria of phylum Chloroflexota reveal a myriad of potential survival strategies in the Antarctic desert", "description": "ABSTRACT

The ice-free McMurdo Dry Valleys of Antarctica are dominated by nutrient-poor mineral soil and rocky outcrops. The principal habitat for microorganisms is within rocks (endolithic). In this environment, microorganisms are provided with protection against sub-zero temperatures, rapid thermal fluctuations, extreme dryness, and ultraviolet and solar radiation. Endolithic communities include lichen, algae, fungi, and a diverse array of bacteria. Chloroflexota is among the most abundant bacterial phyla present in these communities. Among the Chloroflexota are four novel classes of bacteria, here named Candidatus Spiritibacteria class. nov. (=UBA5177), Candidatus Martimicrobia class. nov. (=UBA4733), Candidatus Tarhunnaeia class. nov. (=UBA6077), and Candidatus Uliximicrobia class. nov. (=UBA2235). We retrieved 17 high-quality metagenome-assembled genomes (MAGs) that represent these four classes. Based on genome predictions, all these bacteria are inferred to be aerobic heterotrophs that encode enzymes for the catabolism of diverse sugars. These and other organic substrates are likely derived from lichen, algae, and fungi, as metabolites (including photosynthate), cell wall components, and extracellular matrix components. The majority of MAGs encode the capacity for trace gas oxidation using high-affinity uptake hydrogenases, which could provide energy and metabolic water required for survival and persistence. Furthermore, some MAGs encode the capacity to couple the energy generated from H 2 and CO oxidation to support carbon fixation (atmospheric chemosynthesis). All encode mechanisms for the detoxification and efflux of heavy metals. Certain MAGs encode features that indicate possible interactions with other organisms, such as Tc-type toxin complexes, hemolysins, and macroglobulins.

IMPORTANCE

The ice-free McMurdo Dry Valleys of Antarctica are the coldest and most hyperarid desert on Earth. It is, therefore, the closest analog to the surface of the planet Mars. Bacteria and other microorganisms survive by inhabiting airspaces within rocks (endolithic). We identify four novel classes of phylum Chloroflexota , and, based on interrogation of 17 metagenome-assembled genomes, we predict specific metabolic and physiological adaptations that facilitate the survival of these bacteria in this harsh environment\uffe2\uff80\uff94including oxidation of trace gases and the utilization of nutrients (including sugars) derived from lichen, algae, and fungi. We propose that such adaptations allow these endolithic bacteria to eke out an existence in this cold and extremely dry habitat.

", "keywords": ["570", "Bacteria", "Fungi", "Antarctic Regions", "Chloroflexi", "15. Life on land", "Survival strategies", "Cold Temperature", "Extremophiles", "13. Climate action", "Antarctica", "Endolithic communities", "Metagenomics", "14. Life underwater", "Sugars", "Settore BIO/19 - MICROBIOLOGIA GENERALE"]}, "links": [{"href": "https://doi.org/10.1128/aem.02264-23"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.02264-23", "name": "item", "description": "10.1128/aem.02264-23", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.02264-23"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-19T00:00:00Z"}}, {"id": "10.1186/s12302-025-01141-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:17:56Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract Background

Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.

Results

The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.

Conclusions

The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.

", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1186/s12302-025-01141-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s12302-025-01141-6", "name": "item", "description": "10.1186/s12302-025-01141-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s12302-025-01141-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.2139/ssrn.5084742", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:18:50Z", "type": "Journal Article", "created": "2025-05-25", "title": "ZnO-nanostructured electrochemical sensor for efficient detection of glyphosate in water", "description": "Glyphosate is a widely used broad-spectrum herbicide for controlling grassy weeds, despite having potential health hazards. Herein, we report on a solid-state electrochemical sensor based on ZnO nanoparticles (ZnO NPs) for on-site detection of glyphosate. Accordingly, ZnO NPs was drop-cast on the surface of a disposable screen-printed carbon electrode. Eco-friendly ZnO NPs of only 7 nm crystallite sizes were obtained by green sol-gel synthesis using lemon (Citrus limon) waste aqueous extract as the green reducing and capping/stabilizing agent and Zn nitrate precursor as evidenced by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction and diffuse reflectance. SEM confirmed successful electrode functionalization with the synthesized nanoparticles. Under laboratory conditions in acetate buffer (pH 5), the sensor demonstrated excellent selectivity and sensitivity, with a detection limit of 0.648 \u00b5M, a wide linear detection range (0.5 \u00b5M to 7.5 mM), and a rapid detection time of 30 min. When tested in river water, the sensor achieved a detection limit of 0.96 \u00b5M using differential pulse voltammetry. It also exceptionally tolerated interference from similar organophosphorus compounds and ions commonly found in river water. The excellent detection performance of the sensor was attributed to the strong coordination interactions between Zn atoms and phosphonate/carboxylate groups that are enhanced by a hydrogen bond at acidic pH, as determined by chemical calculations. This disposable sensor offers a cost-effective, efficient, and environmentally friendly solution for monitoring glyphosate in water systems.", "keywords": ["QD71-142", "Environmental water", "Eco-friendly ZnO nanoparticles", "Computational modeling", "Pesticides", "Eco-friendly ZnO nanoparticles;", "[SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology", "Analytical chemistry", "Sensor"]}, "links": [{"href": "https://doi.org/10.2139/ssrn.5084742"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Talanta%20Open", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2139/ssrn.5084742", "name": "item", "description": "10.2139/ssrn.5084742", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.5084742"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.24193/subbphil.2021.2s.05", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:18:55Z", "type": "Journal Article", "created": "2021-11-11", "title": "EXP\u00c9RIMENTER LA PENS\u00c9E EN SCH\u00c9MAS-IMAGES. DES ADOLESCENTS S\u2019INTERROGENT \u00ab D\u2019O\u00d9 VIENNENT LES PENS\u00c9ES ? \u00bb", "description": "

Experimenting Thinking in Image Schemas. Teenagers are Wondering \u201cWhere Do Thoughts Come From?\u201d. An intellectual view of philosophy as an activity focusing on understanding abstract concepts and their relationships deprives philosophical exercise of the participation of the body and senses. If we reject the mind-body dualism, as Dewey, Johnson, etc. did, then we are constantly engaged in interactions with the world and others, and can thus consider the act of thinking from our own experiences. Inspired by an experimentalist conception of school and life, as well as the method of inquiry developed by Dewey, the Philosophy for Children program provides an inquiry process that invites participants to conceptualize and reason philosophically in a collaborative manner. Do these practices implement an embodied cognition? To find out, we selected a discussion as a case study and analyzed it based on the observation that the issue to be discussed by the participants - \u201cwhere do thoughts come from?\u201d contains two image schemas: path (come from) and source (where). We have noted a variety and a significant number of expressions (\u201cthey come from within\u201d, \u201cthey come from what happens outside\u201d, etc.) whose analysis enhances a better understanding of how an experience of understanding the origins of our thoughts fits into the discourse and contributes to a collective conceptualization of \u201cthinking\u201d.

", "keywords": ["4. Education", "B1-5802", "image schemas", " perceptual experience", " conceptualisation", " community of philosophical inquiry", " experimentalism.", "Philosophy (General)", "16. Peace & justice", "3. Good health"]}, "links": [{"href": "https://doi.org/10.24193/subbphil.2021.2s.05"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Studia%20Universitatis%20Babe%C8%99-Bolyai%20Philosophia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.24193/subbphil.2021.2s.05", "name": "item", "description": "10.24193/subbphil.2021.2s.05", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.24193/subbphil.2021.2s.05"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-30T00:00:00Z"}}, {"id": "10.4081/ija.2012.e26", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:27Z", "type": "Journal Article", "created": "2012-05-31", "description": "Interest in biochar (BC) has grown dramatically in recent years, due mainly to the fact that its incorporation into soil reportedly enhances carbon sequestration and fertility. Currently, BC types most under investigation are those obtained from organic matter (OM) of plant origin. As great amounts of manure solids are expected to become available in the near future, thanks to the development of technologies for the separation of the solid fraction of animal effluents, processing of manure solids for BC production seems an interesting possibility for the recycling of OM of high nutrient value. The aim of this study was to investigate carbon (C) sequestration and nutrient dynamics in soil amended with BC from dried swine manure solids. The experiment was carried out in laboratory microcosms on a silty clay soil. The effect on nutrient dynamics of interaction between BC and fresh digestate obtained from a biogas plant was also investigated to test the hypothesis that BC can retain nutrients. A comparison was made of the following treatments: soil amended with swine manure solids (LC), soil amended with charred swine manure solids (LT), soil amended with wood chip (CC), soil amended with charred wood chip (CT), soil with no amendment as control (Cs), each one of them with and without incorporation of digestate (D) for a total of 10 treatments. Biochar was obtained by treating OM (wood chip or swine manure) with moisture content of less than 10% at 420\u00b0C in anoxic conditions. The CO2-C release and organic C, available phosphorus (P) (Olsen P, POls) and inorganic (ammonium+nitrate) nitrogen (N) (Nmin) contents at the start and three months after the start of the experiment were measured in the amended and control soils. After three months of incubation at 30\u00b0C, the CO2-C emissions from soil with BC (CT and LT, \u00b1D) were the same as those in the control soil (Cs) and were lower than those in the soils with untreated amendments (CC and LC, \u00b1D). The organic C content decreased in CT and LT to a lesser extent than in CC and LC. In soils with D (+D), the CO2-C emissions were equal to or higher than those in soils without (-D). The Nmin content increased in all treatments; the POls content decreased in the +D treatments. The incorporation of BC into soil, by reducing CO2 emissions, actually contributes to C sequestration without modifying N availability for crops. For a given N content, the BC from swine manure solids supplies much more P than the non-treated OM and, therefore, represents an interesting source of P for crops.", "keywords": ["2. Zero hunger", "S", "emissions", "Plant culture", "Agriculture", "04 agricultural and veterinary sciences", "nitrogen", "6. Clean water", "SB1-1110", "13. Climate action", "manure", "0401 agriculture", " forestry", " and fisheries", "biochar", "phosphorus"]}, "links": [{"href": "https://doi.org/10.4081/ija.2012.e26"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Italian%20Journal%20of%20Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.4081/ija.2012.e26", "name": "item", "description": "10.4081/ija.2012.e26", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.4081/ija.2012.e26"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.5061/dryad.cz8w9gj78", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:36Z", "type": "Dataset", "title": "Soil microbial relative resource limitation exhibited contrasting seasonal patterns along an elevational gradient in Yulong snow mountain", "description": "unspecified", "keywords": ["2. Zero hunger", "mountain ecosystems", "13. Climate action", "microbial metabolic mechanisms", "microbial relative C limitation", "microbial relative P limitation", "C use efficiency", "FOS: Earth and related environmental sciences", "15. Life on land", "elevations"], "contacts": [{"organization": "Zhang, Dandan, Wu, Baoyun, Li, Jinsheng, Cheng, Xiaoli,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.cz8w9gj78"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.cz8w9gj78", "name": "item", "description": "10.5061/dryad.cz8w9gj78", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.cz8w9gj78"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-02T00:00:00Z"}}, {"id": "10.5061/dryad.h3r16", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:37Z", "type": "Dataset", "title": "Data from: The impact of environmental heterogeneity and life stage on the hindgut microbiota of Holotrichia parallela larvae (Coleoptera: Scarabaeidae)", "description": "unspecifiedGut microbiota has diverse ecological and evolutionary effects on their hosts. However, the ways in which it responds to environmental heterogeneity and host physiology remain poorly understood. To this end, we surveyed intestinal microbiota of Holotrichia parallela larvae at different instars and from different geographic regions. Bacterial 16S rRNA gene clone libraries were constructed and clones were subsequently screened by DGGE and sequenced. Firmicutes and Proteobacteria were the major phyla, and bacteria belonging to Ruminococcaceae, Lachnospiraceae, Enterobacteriaceae, Desulfovibrionaceae and Rhodocyclaceae families were commonly found in all natural populations. However, bacterial diversity (Chao1 and Shannon indices) and community structure varied across host populations, and the observed variation can be explained by soil pH, organic carbon and total nitrogen, and the climate factors (e.g., mean annual temperature) of the locations where the populations were sampled. Furthermore, increases in the species richness and diversity of gut microbiota were observed during larval growth. Bacteroidetes comprised the dominant group in the first instar; however, Firmicutes composed the majority of the hindgut microbiota during the second and third instars. Our results suggest that the gut\u2019s bacterial community changes in response to environmental heterogeneity and host\u2019s physiology, possibly to meet the host\u2019s ecological needs or physiological demands.", "keywords": ["Holotrichia parallela", "Cenozoic era", "15. Life on land"], "contacts": [{"organization": "Huang, Shengwei, Zhang, Hongyu,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.h3r16"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.h3r16", "name": "item", "description": "10.5061/dryad.h3r16", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.h3r16"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-05-20T00:00:00Z"}}, {"id": "10.5194/acp-10-7017-2010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:41Z", "type": "Journal Article", "created": "2010-04-29", "description": "

Abstract. We present and discuss a new dataset of gridded emissions covering the historical period (1850\uffe2\uff80\uff932000) in decadal increments at a horizontal resolution of 0.5\uffc2\uffb0 in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models is used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.

", "keywords": ["info:eu-repo/classification/ddc/550", "550", "IPCC", "[SDE.MCG]Environmental Sciences/Global Changes", "Physics", "QC1-999", "emissions", "551", "01 natural sciences", "7. Clean energy", "J", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "13. Climate action", "[SDE.ES] Environmental Sciences/Environment and Society", "CMIP5", "[SDE.ES]Environmental Sciences/Environment and Society", "QD1-999", "AR5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "https://doi.org/10.5194/acp-10-7017-2010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-10-7017-2010", "name": "item", "description": "10.5194/acp-10-7017-2010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-10-7017-2010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-02-19T00:00:00Z"}}, {"id": "10.5281/zenodo.10060810", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:19:53Z", "type": "Dataset", "title": "SoilCompDB: Global soil compressive properties database. Version 1.0", "description": "Data collection and processing Our data collection comprised published journal articles sourced from Web of Science and Scopus databases, using search terms such as 'soil precompression stress,' 'soil compression index,' 'soil compaction index,' 'soil recompression index,' 'soil swelling index,' 'soil precompaction stress,' and 'preconsolidation pressure' for articles published up to February 2022. \u00a0A total of 1235 publications were found. Duplicate records were eliminated using the Endnote Web citation management application. The remaining references were exported to Rayyan software for title and abstract screening based on predefined criteria for full-text selection. \u00a0After a careful review, we identified 128 papers where the data on soil compressive properties (precompression stress, compression index, and swelling index) were reported in numerical format or legible graphical format and considered suitable for inclusion in the database. \u00a0We employed the WebPlotDigitizer software to extract data from figures within the original publications. For each chosen study, we systematically recorded data concerning soil compressive properties and collected information on soil properties, soil conditions, site characteristics, and experimental settings. We compiled 4,743 individual data entries. Time and place The database includes data from 128 independent studies published between 1992 and 2021. Each study reported between 1 and 360 measurements, with a study median of 14 measurements and a mean of 38 measurements, totalling 4743 database entries. Our database includes data from 20 countries, with a significant concentration of the data originating from Brazil, followed by Germany, Switzerland, Sweden, and Denmark. The majority of the data came from arable soils, representing approximately 72% of data entries.\u00a0\u00a0 Instruments The soil compressive properties included in the database were based on soil compressive tests performed in the laboratory by uniaxial method. The procedure used for stress application on soil samples was mainly the stepwise stress application method, while the constant strain rate method was applied in few studies (less than 2% of the data). The component of the compressive curve related to the soil packing state was represented by soil bulk density, void ratio, and strain. The stress component of the curve was represented in a logarithmic form in the entirety of the database. The database also comprised eight different methods for calculating precompresion stress: Casagrande (1936), Dias Junior and Pierce (1995), Lamand\u00e9 et al. (2017), Sullivan and Robertson (1996), Casini (2012), Culley and Larson (1987), Pacheco Silva (1990), Gregory et al. (2006). Resources Web of Science, Scopus \u2013 literature search Endnote Web \u2013 removal of duplicates Rayyan software \u2013 initial paper selection based on title and abstract WebPlotDigitizer \u2013 data extraction from figures Microsoft Access \u2013 database platform Description of the collected data (column, unit, and description) Sample ID-\u00a0\u00a0\u00a0 A unique identification number assigned to each individual sample within the database\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Study ID- Identification number assigned to each research study in the database Reference - Research paper reference Year - Year of research paper publication \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Language - Language of the research paper \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Soil classification (SiBCS) - Soil Classification according to the Brazilian System (SiBCS), as described in portuguese-language papers Soil classification (original in paper) - Soil classification described in research paper\u00a0 Soil classification (convertion to Soil Taxonomy orders) -\u00a0 Soil classification aligned with the Soil Taxonomy system developed by the United States Department of Agriculture (USDA)\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Location - Study location country\u00a0\u00a0\u00a0 Texture classification (USDA) -\u00a0Soil textural classification according USDA Texture\u00a0 classification USDA (letter code) - Letter code for soil textural classification according USDA: S=sand; LS=loamy sand; SL=sandy loam; SiL=silt loam; Si=silt; L=loam; SCL= Sandy clay loam; SiCL=Silty clay loam; CL=clay loam; SC=Sandy clay; SiC=Silty clay; C=clay Clay (USDA) - % - Soil clay content (weight based) - (<0.002 mm) \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Silt (USDA) - % - Soil silt content (weight based) - (0.002 < x < 0.05 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006)\u00a0 Sand (USDA) - % - Soil sand content (weight based)\u00a0 - (0.05 < x < 2 mm, interpolated for European samples where needed using the k-nearest neighbor technique by Nemes et al. 2006) USDA PSD interpolated - =0 if the data was NOT interpolated; =1 if the data was interpolated Published texture class - Texture classification provided in the source publication when the values for clay, silt and sand were not available Clay - g kg-1 - Soil clay content - original in the paper Clay class upper boundary - \u00b5m - The clay class upper boundary informed in source publication Silt - g kg-1 - Silt clay content - original in the paper Silt class upper boundary - \u00b5m - The silt class upper boundary informed in source publication Sand - Soil sand content - original in the paper Sand class upper boundary - \u00b5m - The sand class upper boundary informed in source publication Particle size data flag - =0 if no issues; =1 if there are issues (summing) Sum particle size- g kg-1 - Sum of clay, silt, and sand content Soil depth FROM \u2013 cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the minimum depth at which soil samples were collected\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Soil depth TO \u2013 cm - When soil depth is presented as a range (e.g., 0-10cm), it indicates the maximum depth at which soil samples were collected\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Depth \u2013 cm -Specific depth value as presented in paper, or when soil depth is showed as a range (e.g., 0-10cm), it indicates the average depth at which soil samples were collected (e.g 5cm) \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 SOC - g kg-1 - Soil organic carbon content informed in research paper or soil organic carbon content calculate from soil organic matter content by multiplying by 0,58\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 SOC converted from SOM - 1= yes for soil organic carbon derived from soil organic matter content calculations Particle density - Mg m-3 - Soil particle density\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial matric potential \u2013 hPa - Soil water matric potential before loading log Initial matric potential - Soil water matric potential expressed by log\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Wetness (based on initial matric potential) - \u00a01=if initial matric potential (MP)<100 hPa; 2= if 100<=initial MP<1000 hPa; 3= initial MP>=1000 hPa Initial gravimetric water content - g g-1 - Gravimetric soil water content before loading provided by source publication, or calculated by volumetric water content divided by soil bulk density Initial volumetric water content - m3 m-3 - Volumetric soil water content before loading, when the soil bulk density was not reported Initial water content data source -\u00a0Graph or table from where the data was collected, or explanation on calculation used Matric potential type - Compressive tests performed on soil samples under different conditions: 1= equilibrated at matric potential; 2= field matric potential; 3= air-dried samples\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial bulk density - Mg m-3 - Soil bulk density before loading\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial BD data source - Graph or table from where the data was collected, or explanation on calculation used\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Initial volumetric water content calculated - m3 m-3 - Soil volumetric water content calculated by multiplying soil gravimetric water content by soil bulk density Precompression stress \u2013 kPa - Precompression stress \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Precompression stress (SD) \u2013 kPa - Standard deviation for precompression stress values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Precompression stress data source - Graph or table from where the data was collected, or explanation on calculation used Compression index - Compression index \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Compression index (SD) - Standard deviation of compression index values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Compression index data source - Graph or table from where the data was collected, or explanation on calculation used Swelling index - Swelling index\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Swelling index (SD) - Standard deviation of swelling index values reported in paper\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 Swelling index data source - Graph or table from where the data was collected, or explanation on calculation used N -\u00a0Number of replicates used for calculating precompression stress, compression index, and swelling index when mean values are reported Land use (paper) -\u00a0Land use described in the research paper Land use (categories) -\u00a0Land use categorized Land use standardized -\u00a0Land use classified as: arable, forest, grassland, and native vegetation. The latter includes forest, grassland, and savanna Land use (number code) -\u00a0Number code for land use: 1=Arable, 2= forest, 3= grassland, and 4= native vegetation Tillage system -\u00a0Tillage system Tillage system (arable soils) - Tillage system for arable soils classified as 'conventional' and 'conservation' Coordinates -\u00a0\u00a0Geographical coordinates\u00a0 of study location Climate -\u00a0Climatic region classification: temperate, tropical, subtropical Climatecod -\u00a0\u00a0\u00a0 Code number assigned to each climatic region: 1=temperate, 2=tropical, 3=subtropical Sampling position (paper) -\u00a0Field position where soil samples were collected with details described in the paper Sampling position -\u00a0Field position where soil samples were collected standardized Treatment -\u00a0Experimental treatment type where the soil samples were collected Stress rate - \u00a0kPa - Stress applied in compressive tests\u00a0 Minimum stress \u2013\u00a0kPa - Minimum stress applied in compressive tests Maximum stress \u2013\u00a0kPa - Maximum stress applied in compressive tests Number of stress rate steps -\u00a0Number of steps in stepwise stress application procedure Stess application type -\u00a01=Stepwise stress 2=one sample per stress 3=Strain controlled Stess application type \u2013\u00a0min - Time for stress application in each step in stepwise stress application procedure Degree of deformation at the end of loading -\u00a0% - Degree of deformation at the end of compressive test Sample diameter \u2013\u00a0cm - Diameter of the soil samples Sample height \u2013\u00a0cm - Height of the soil samples Ratio sample diameter and height\u00a0-\u00a0Ratio between diameter and height of the soil samples Sample volume -\u00a0cm3 -Sample volume when the sample diameter and height are nor presented Precompression stress calculation method -\u00a0Calculation method of precompression stress Precompression stress calculation method (number code) -\u00a0Number code for calculation method PC:1=Casagrande (1936); 2=Dias Junior and Pierce (1995); 3= Lamand\u00e9 et al. (2017); 4=O`Sullivan and Robertson (1996); 5=Casini (2012); 6=Culley and Larson (1987);7=ABNT (1990); 8=Gregory et al. (2006) Description of precompression stress calculation -\u00a0Brief explanation of precompression stress calculation Soil compressive curve components -\u00a0Component of the soil compression curve related to the soil packing state: soil bulk density, void ratio, and strain.\u00a0 Soil compressive curve components (number code) -\u00a0Number code for component of the soil compressive curve related to the soil packing state: 1= soil bulk density; 2= strain; 3= void ratio Curve components source -\u00a0Source of the component of the soil compressive curve related to the soil packing state: 1= showed in the paper, 2= according to original method for precompression stress calculation, 3= described in method, but not clear in the paper Compressive curve available -\u00a0Original soil compressive curve available in the paper: 1= No 2=Yes Comments -\u00a0Brief comments on the paper Issues and remarks We sought out important information not included in the paper by directly communicating with the authors whenever possible. In cases where multiple papers covered the same experiment, we prioritized the one offering more comprehensive details. If two papers complemented each other, we included both. When analyzing studies comparing various methods for calculating soil precompression stress, we exclusively gathered data calculated using the widely accepted Casagrande (1936) method. To ensure comparability across studies, we standardized the collected data by converting it to the same unit. The standardization process involved: i) assuming that 58% of soil organic matter (SOM) was soil organic carbon (SOC) when only SOM was reported, ii) calculating soil bulk density using a soil particle density of 2.65 Mg m-3 when only total porosity data were provided, and iii) harmonizing all texture data to the USDA classification system, which defines the silt/sand boundary as 50 \u03bcm, utilizing the k-nearest neighbor approach (referred to as 'similarity method' by Nemes et al. (1999). \u00a0 Reference Associa\u00e7\u00e3o Brasileira de Normas T\u00e9cnicas - ABNT. NBR 12007: Ensaio de adensamento unidimensional. Rio de Janeiro: 1990. Casagrande, A., 1936. Determination of the preconsolidation load and its practical significance. In: Proceedings of the International Conference on Soil Mechanics and Foundation Engineering, vol. III, Harvard University, Cambridge, MA, pp. 60\u201364.Casini, F. 2012. Deformation induced by wetting: A simple model. Can. Geotech. J. 49:954\u2013960 10.1139/T2012-054. doi:10.1139/t2012-054 Culley, J.L.B., Larson, W.E., 1987. Susceptibility to compression of a clay loam Haplaquoll. Soil Sci. Soc. Am. J. 51, 562\u2013567. Dias Junior, M.S., Pierce, F.J., 1995. A simple procedure for estimating preconsolidation pressure from soil compression curves. Soil Technology 8, 139\u2013151. doi:10.1016/0933-3630(95)00015-8 Gregory, A.S., Whalley, W.R., Watts, C.W., Bird, N.R.A., Hallett, P.D., Whitmore, A.P., 2006. Calculation of the compression index and pre-compression stress from soil compression test data. Soil Till Res. 89:45-57. doi:10.1016/j.still.2005.06.012 Lamand\u00e9, M., Schj\u00f8nning, P., Labouriau, R., 2017. A novel method for estimating soil precompression stress from uniaxial confined compression tests. Soil Sci. Soc. Am. J. 81 https://doi.org/10.2136/sssaj2016.09.0274. Nemes, A., \u00a0W\u00f6sten, J.H.M., Lilly, A., \u00a0Oude Voshaar, J.H., 1999. Evaluation of different procedures to interpolate the cumulative particle-size distribution to achieve compatibility within a soil database.\u00a0Geoderma 90: 187-202. 129\u00a0 O'Sullivan, M.F., Robertson, E.A.G., 1996. Critical state parameters from intact samples of two agricultural topsoils. Soil Tillage Res 39(3 \u2013 4):161 \u2013 173.", "keywords": ["2. Zero hunger", "soil compression curve", "precompression stress", "15. Life on land", "soil mechanical properties", "compression index", "soil moisture", "uniaxial compression test", "swelling index"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.10060810"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.10060810", "name": "item", "description": "10.5281/zenodo.10060810", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.10060810"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-06T00:00:00Z"}}, {"id": "10.5281/zenodo.10959077", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:04Z", "type": "Dataset", "created": "2023-10-30", "title": "Knowledge gaps on trade-offs of soil carbon sequestration related to soil management strategies", "description": "The database contains 87 unique literature items (29 reviews, 42 meta-analyses, 16 original papers) describing the effect of a soil management strategy (tillage management, cropping systems, water management, cover crops, crop residues, livestock manure, slurry, compost, biochar, liming) on the trade-offs between soil carbon sequestration or SOC change and N2O emission, CH4 emission and nitrogen leaching. Since some literature items describe effects of several SMS categories, the database_summary tab comprises a total of 112 unique inputs. For each input it is indicated in the Database_summary tab if it was used as input for the 'Soil management effect assessment' in Maenhout et al. (2024) [Maenhout, P., Di Bene, C., Cayuela, M. L., Diaz-Pines, E., Govednik, A., Keuper, F., Mavsar, S., Mihelic, R., O'Toole, A., Schwarzmann, A., Suhadolc, M., Syp, A., & Valkama, E. (2024). Trade-offs and synergies of soil carbon sequestration: Addressing knowledge gaps related to soil management strategies. European Journal of Soil Science, 75(3), e13515. https://doi.org/10.1111/ejss.13515] and/or to define knowledge gaps ('Knowledge gap in tab'-column). Knowledge gaps and research recommendations are gouped per soil management strategy in different tabs in this database. Per soil management strategy, knowledge gaps are clustered per theme in groups. These themes include: the specific soil management strategy, pedoclimatic conditions, establishment of experiments, other soil management strategies, meta-analysis, modelling and other", "keywords": ["Water management", "EJP SOIL", "Climate change mitigation", "Nitrogen leaching", "CH4", "Conservation agriculture", "Cropping systems", "SOMMIT", "N2O", "Organic matter inputs", "Tillage"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.10959077"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.10959077", "name": "item", "description": "10.5281/zenodo.10959077", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.10959077"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-13T00:00:00Z"}}, {"id": "10.5281/zenodo.11071095", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:04Z", "type": "Report", "title": "D4.2. Plan for exploitation and dissemination of the project results", "description": "This document is a deliverable of the Co-UDlabs project, funded under the European Union\u2019s Horizon 2020 research and innovation programme under grant agreement No 101008626. The aim of this document is to provide the first version of the Plan for Dissemination and Exploitation of Results (PEDR), produced at M6 as part of the Work Package 4 on communication, dissemination and exploitation of results. The aim of the PEDR is to provide the Co-UDlabs partners with guidelines on the different communication and dissemination activities that are planned and their schedule, who are the partners responsible for each activity and what tools and channels are available for dissemination. A section on exploitation will define the actions planned to achieve the exploitation of the results and impact of the project. More specifically, in terms of dissemination and communication the PEDR will: \u00a0Propose a communication and dissemination policy, and define the objectives of the actions; \u00a0Identify the target audience for each objective or main result; \u00a0List the communication and dissemination channels to be used for project promotion; \u00a0Present a schedule of the communication and dissemination actions throughout the project duration; \u00a0Define and monitor a series of Key Performance Indicators (KPIs) to assess the success of the implementation (e.g. number of publications, size of the audience reached, number of visits on the website, feedback received from audiences at conferences, etc.) and update the plan according to the evolution of the project. In terms of the exploitation of the results, the PEDR will contain the following information, if applicable and when relevant, especially within the final exploitation plan to be submitted at the end of the project: The identification of exploitable main outputs of the project; The identification of the factors influencing exploitation and wide deployment of the project\u2019s results The identification of new and existing measures for the project sustainability. The document is drafted by Euronovia, which is leader of this Work Package, with inputs from all partners. While Euronovia is the leading partner in charge of WP4, all partners have the responsibility to participate in the communication activities and dissemination of the results of the project. According to the grant agreement and unless it goes against their legitimate interests, each beneficiary must, as soon as possible, disseminate its results by disclosing them to the public by appropriate means (other than those resulting from protecting or exploiting the results), including in scientific publications. The PEDR is an evolving document which will be updated at the end of each reporting period (October 2022, April 2024 and April 2025).", "keywords": ["Research Infrastructure", "Co-UDlabs", "Urban Drainage Systems", "12. Responsible consumption"], "contacts": [{"organization": "De Nale, Laura, Guilloteau, Lucie, Anta, Jose,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.11071095"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.11071095", "name": "item", "description": "10.5281/zenodo.11071095", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.11071095"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-26T00:00:00Z"}}, {"id": "10.5281/zenodo.13374006", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:11Z", "type": "Dataset", "title": "Microbial biomass and water-extractable carbon on Mt. Kilimanjaro", "description": "This dataset presents the value of microbial biomass carbon (MBC) and water-extractable carbon (WOC) at study plots under KiLi project. Microbial biomass carbon (MBC) and water-extractable organic carbon (WOC) \u2013 as sensitive and important parameters for soil fertility and C turnover \u2013 are strongly affected by land-use changes all over the world. These effects are particularly distinct upon conversion of natural to agricultural ecosystems due to very fast carbon (C) and nutrient cycles and high vulnerability, especially in the tropics. The objective of this study was to use the unique advantage of Mt. Kilimanjaro \u2013 altitudinal gradient leading to different tropical ecosystems but developed all on the same soil parent material \u2013 to investigate the effects of land-use change and elevation on MBC and WOC contents during a transition phase from dry to wet season. Down to a soil depth of 50\u00a0cm, we compared MBC and WOC contents of 2 natural (Ocotea\u00a0and\u00a0Podocarpus forest), 3 seminatural (lower montane forest, grassland, savannah), 1 sustainably used (homegarden) and 2 intensively used (maize field, coffee plantation) ecosystems on an elevation gradient from 950 to 2850\u00a0m a.s.l. The KiLi project (2010-2018) is a German Science Foundation (DFG) funded research unit (DFG research unit FOR1246) that focuses on biodiversity and ecosystem processes along altitudinal and disturbance gradients on Mt. Kilimanjaro (Tanzania, Africa), capitalizing on its world-wide unique range of climatic and vegetation zones. The research unit comprises 2 central projects and 7 subprojects from various disciplines. On a total of 60 study sites in both natural and human-disturbed ecosystems biodiversity (e.g. plants, soil arthropods, ants, bees, frogs, lizards, bats, birds), related ecosystem processes (decomposition, seed dispersal, pollination, herbivory, predation), and biogeochemical processes and properties of ecosystems (climate, soil properties and nutrient status, regulation of water and carbon fluxes, trace gas emissions, primary productivity, functional diversity) are analyzed.", "keywords": ["land-use change", "microbial carbon dynamics", "tropical ecosystem", "andosol", "elevation gradient", "water-extractable carbon"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13374006"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13374006", "name": "item", "description": "10.5281/zenodo.13374006", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13374006"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-26T00:00:00Z"}}, {"id": "10.5281/zenodo.14280633", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:23Z", "type": "Software", "title": "Code files for \"Climate feedbacks from North American boreal forest fires\"", "description": "Computer code as part of the publication in review: 'Climate warming and cooling feedbacks from North American boreal forest fires' Max J. van Gerrevink1,\u00a0Sander Veraverbeke1,2,\u00a0Sol Cooperdock3,\u00a0Stefano Potter3,\u00a0Qirui Zhong1,4 Michael Moubarak5,\u00a0Scott J. Goetz6,\u00a0Michelle C. Mack7,\u00a0James T. Randerson8,\u00a0Nick Schutgens1, Merritt R. Turetsky9, Guido R. van der Werf10, and Brendan M. Rogers3 1Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands 2School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom 3Woodwell Climate Research Center, Falmouth, MA, USA 4College of Urban and Environmental Sciences, Peking University, Beijing, China 5Hamilton College, Hamilton, NY, USA 6School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA 7Center for Ecosystem Science and Society and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA 8Department of Earth System Science, University of California, Irvine, CA, USA 9Renewable and Sustainable Energy Institute, Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA 10Meteorology & Air Quality Group, Wageningen University and Research, Wageningen, The Netherlands \u00a0 Correspondence to: Max J. van Gerrevink (m.j.van.gerrevink@vu.nl) \u00a0 Files contain the computer code used to compute the climate radiative forcing from fire. The computer code is spilt into 7 different scripts: Well-mixed greenhouse gasses, precursors, and aerosol radiative forcing :\u00a0Radiative_forcing_GHG_precursors_aerosols_boxmodel.py Mapping and uncertainty of Well-mixed greenhouse gasses, precursors, and aerosol radiative forcing : Radiative_forcing_GHG_precursors_aerosols_Mapping_and_uncertainty.py Permafrost greenhouse gas emissions radiative forcing\u00a0: Radiative_Forcing_Permafrost_GHG.py Changes in surface albedo radiative forcing :\u00a0Radiative_Forcing_Albedo_change.py Uncertainty in surface albedo radiative forcing : Radiative_Forcing_Albedo_change_uncertainty.py Vegetation recovery radiative forcing :\u00a0Radiative_Forcing_vegetation_recovery.py Uncertainty in vegetation recovery radiative forcing : Radiative_Forcing_vegetation_recovery_uncertainty.py \u00a0 * The sensitivity analysis for Permafrost greenhouse gas emissions is included in the Radiative_Forcing_Permafrost_GHG.py script. Additionally, input files for atmospheric concentrations and impulse response function data are included as CSV files.", "keywords": ["Climate change", "Fires", "Radiative Forcing"], "contacts": [{"organization": "van Gerrevink, Max J., Veraverbeke, Sander, Cooperdock, Sol, Potter, Stefano, Zhong, Qirui, Moubarak, Michael, Goetz, Scott J., Mack, Michelle C., Randerson, James T., Schutgens, Nick, Turetsky, Merritt R., van der Werf, Guido R., Rogers, Brendan M.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14280633"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14280633", "name": "item", "description": "10.5281/zenodo.14280633", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14280633"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-05T00:00:00Z"}}, {"id": "10.5281/zenodo.15017546", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:31Z", "type": "Dataset", "title": "Global Rice Land Suitability and Adaptation Strategies Under Climate Change", "description": "This study evaluated the land suitability of irrigated and rainfed rice cultivation under current and projected climate change scenarios for the year 2050 on a global scale. , the climate and soil factors utilized for this purpose were obtained from the WorldClim website (https://www.worldclim.org/) and represent the historical monthly weather data for the period between 2001 and 2021 (https://worldclim.org/data/monthlywth.html). Moreover, future climate projections were sourced from the same source for the period 2041 to 2060 (centered around 2050).The projections are based on mean value of ten Global Climate Models (GCMs) from the CMIP6 dataset and two scenarios (SSP245 and SSP585), including models such as ACCESS-CM2, CanESM5-CanOE, EC-Earth3-Veg, FIO-ESM-2-0, GISS-E2-1-H, HadGEM3-GC31-LL, INM-CM4-8, IPSL-CM6A-LR, MRI-ESM2-0, and UKESM1-0-LL (https://worldclim.org/data/cmip6/cmip6_clim2.5m.html). The future climate scenarios were developed using a new set of integrated assessment models (IAMs) that incorporate the Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs), as outlined by O'Neill et al. (2016). Two integrated scenarios were considered in this study. SSP245 (a combination of SSP2 with RCP4.5) and SSP585 (a combination of SSP5 with RCP8.5). SSP2 represents a scenario characterized by a continuation of existing social, economic and technological trends, with minimal deviation from historical patterns. In contrast, SSP5 depicts a pathway of fossil-fuelled development, characterized by rapid technological advancement and human capital growth. With regard to radiative forcing, RCP4.5 represents a medium scenario (4.5 W m\u207b\u00b2 by 2100), whereas RCP8.5 represents a high-emission scenario (8.5 W m\u207b\u00b2 by 2100). To ensure the highest possible spatial accuracy, 2.5 minutes (~21 km2 at the equator) spatial resolution was applied to all maps. Furthermore, maps of rice cultivation area was obtained from the MAP SPAM2020 (Spatial Production Allocation Model) website (https://www.mapspam.info), which provides detailed spatial data on global rice production.Soil parameters were then determined for each point using soil information obtained from the FAO soil map. The FAO soil map provided vital parameters such as organic carbon (OC), exchangeable sodium percentage (ESP), cation exchange capacity (CEC), CaCO3, pH, EC which extracted from the Harmonized World Soil Database (HWSD) at a scale of 1:5,000,000, sourced from the FAO Soil Portal website. (Supplementary Figure 2). The slope map was created using the digital elevation model (for more details, see Guerra et al., 2020). The SPAM2020 for rainfed and irrigated rice was used to intersect the climate zones and soil layers, focusing specifically on the areas dedicated to this area.\u00a0 The final land suitability map was generated by overlaying the suitability output with raster files representing both irrigated and rainfed harvested areas, thus creating a composite map of land suitability . This stage ensured the precise delineation of areas suitable for rice cultivation. Following the creation of land suitability maps for a variety of scenarios and adaptation strategies, the results were compared in order to identify the optimal strategy. The final map identifies the most efficacious adaptation strategy for enhancing land suitability in each region in the context of projected climate change. Also, The overview of the status of rainfed and irrigated rice worldwide.", "keywords": ["Adaptation strategy", "Climate chnage", "Rice", "land suitablity"], "contacts": [{"organization": "Dadrasi, Amir, Va\u010dk\u00e1\u0159ov\u00e1, Davina, Fatemeh, Salmani, Nguyen, Trong Can, Weinzettel, Jan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15017546"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15017546", "name": "item", "description": "10.5281/zenodo.15017546", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15017546"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-15T00:00:00Z"}}, {"id": "10.5281/zenodo.15328215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:36Z", "type": "Dataset", "title": "1000 Soils Pilot Dataset, version 8, May 2025", "description": "This record hosts data generated by the 1000 Soils Pilot. Data will be updated as more become available. Please see the most recent data upload for current data. A beta visualization tool is available for some data types at\u00a0https://shinyproxy.emsl.pnnl.gov/app/1000soils. Please submit any suggestions or comments through the 'contact' tab. We are actively working to improve visualizations and value all feedback. Data completed include: Geochemistry, texture, respiration, and enzyme activities FTICR-MS organic matter chemistry Microbial biomass C and N TOC/TDN of water-extractable OM X-ray computed tomography (derived metrics available here, raw data available upon request) Metagenomes; a variety of data formats are available upon request Soil hydraulic properties Data in progress: LC-MS/MS in development, timeline TBD, inquire for status 1000S_processed_BGC_summary.csv contains all available biogeochemical data; microbial biomass C and N; and TOC/TDN of water-extractable OM; and\u00a0 1000S_Tomography.xslx contains a summary of data generated via X-ray computed tomography. icr_v2_corems2.csv contains FTICR-MS data processed by CoreMS version 2. These data are merged by formula across instrument runs to enable cross-sample comparisons. Technical replicates are merged by retaining peaks present in 2 out of 3 replicates. 1000Soils_Metadata_Site_Mastersheet_v1.csv contains site information. Soil Hydraulics_corrected_02042025.xlsx contains soil hydraulics information. Readme File_v4.xlsx is the readme file. Please contact the MONet project (monet.emsl@pnnl.gov) or Emily Graham (emily.graham@pnnl.gov) with questions. The following file and all raw data are\u00a0available upon request: icr_by_mass_for_single_sample_analysis_only.csv\u00a0contains FTICR-MS data processed by CoreMS and is intended for usage in the calculation of biochemical transformations within samples only. These data are not acceptable for cross-sample comparison of masses because they are from multiple instrument runs. For more information, please see: https://www.emsl.pnnl.gov/monet and https://sc-data.emsl.pnnl.gov/monet Acknowledgment:\u00a0 Soil data were provided by the Molecular Observation Network (MONet) at the Environmental Molecular Sciences Laboratory (https://ror.org/04rc0xn13), a DOE Office of Science user facility sponsored by the Biological and Environmental Research program under Contract No. DE-AC05-76RL01830. The work (proposal: 10.46936/10.25585/60008970) conducted by the U.S. Department of Energy, Joint Genome Institute (https://ror.org/04xm1d337), a DOE Office of Science user facility, is supported by the Office of Science of the U.S. Department of Energy operated under Contract No. DE-AC02-05CH11231.\u00a0 The Molecular Observation Network (MONet) database is an open, FAIR, and publicly available compilation of the molecular and microstructural properties of soil. Data in the MONet open science database can be found at\u00a0https://sc-data.emsl.pnnl.gov/.", "keywords": ["2. Zero hunger", "decomposition", "13. Climate action", "FTICR-MS", "biogeochemistry", "carbon", "molecular", "15. Life on land", "6. Clean water", "soil"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15328215"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15328215", "name": "item", "description": "10.5281/zenodo.15328215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15328215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-02T00:00:00Z"}}, {"id": "10.5281/zenodo.15680931", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:41Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract Background

Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.

Results

The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.

Conclusions

The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.

", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1186/s12302-025-01141-6.pdf"}, {"href": "https://doi.org/10.5281/zenodo.15680931"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15680931", "name": "item", "description": "10.5281/zenodo.15680931", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15680931"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.5281/zenodo.16017208", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:44Z", "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": "10.5281/zenodo.4287780", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:53Z", "type": "Dataset", "title": "Forest carbon prospecting for climate change mitigation: Version 1.0", "description": "This data package includes the two 1-km resolution global maps (.tif) of tropical forests between ~23.44\u00b0N and 23.44\u00b0S produced from the study: 1) investible forest carbon (in tCO2e ha-1y-1) and 2) forest carbon return-on-investment (Net Present Value in USD ha-1y-1) over a 30-year timeframe. It also includes the R script to reproduce these layers and their uncertainties. Investible Forest Carbon: The investible forest carbon map was produced based on the total volume of CO2e associated with the three main carbon pools in the tropics, namely aboveground carbon, belowground carbon and soil organic carbon. This is followed by the application of key Verified Carbon Standard (VCS) criteria including additionality, to determine the magnitude and areas of investible forest carbon across the tropics. Aboveground carbon. A stoichiometric factor of 0.475 was applied to recent spatial data on aboveground carbon biomass to obtain carbon stock based on established carbon accounting methodologies. An uncertainty analyses was also performed to account for potential variability in stoichiometric factor. Subsequently, a conversion factor of 3.67 was applied to the carbon stock layer to obtain the volume of CO2e associated with this carbon pool. Belowground carbon. Belowground carbon biomass was firstly derived by applying two allometric equations relating to root to shoot biomass to the most recent spatial dataset on aboveground carbon biomass following established carbon accounting methodologies. The two equations are: Belowground biomass = 0.489\u00d7aboveground biomass^0.89; and Belowground biomass = 0.26\u00d7aboveground biomass A stoichiometric factor of 0.475 was subsequently applied to the estimated belowground carbon biomass to obtain the carbon stock. An uncertainty analyses was then performed to determine the mean, minimum and maximum values for belowground carbon. Following that, a conversion factor of 3.67 was applied to the carbon stock layer to obtain the volume of CO2e associated with this carbon pool. Soil Organic Carbon. Organic carbon density of the topsoil layer (0-30 cm) was obtained from the European Soil Data Centre as it represented the best data available for soil organic carbon. A conversion factor of 3.67 was subsequently applied to derive the volume of CO2e associated with this carbon pool. Applying VCS criteria. The criterion of additionality is a pre-condition for carbon credits to be certified under the VCS. This implies that only the volume of forest carbon that are under imminent threat of decline or loss if left unprotected by a conservation intervention can be certified under the VCS. The volume of forest carbon under threat of loss was based on the best available data on predicted deforestation rates across the tropics (through to the year 2029), and annualized over predicted 15-year period. The estimated annual deforestation rates was then applied to the total volume of CO2e associated with tropical forests as estimated above, deriving the volume of CO2e that would be certifiable and thus investible under the VCS. In addition, a conservative 10-year decay estimate was assumed for the estimate of the belowground carbon pool, and lands that will likely not be certifiable for other reasons, including recently deforested areas (i.e. for the period of 2010-2017), a well as human settlements, were excluded. Lastly, the VCS requirement to set aside buffer credits of 20% was accounted for to consider the risk of non-permanence associated with Agriculture, Forestry and Other Land Use (AFOLU) projects. Return-on-Investment. From the investible forest carbon map, the relative profitability of these areas was then modelled to produce a global forest carbon return-on-investment map based on their NPV. The NPV of returns were based on several simplifying assumptions following established values from previous studies. Cost of project establishment. The cost of project establishment was estimated to be at $25 ha-1. This was based on a range of costs that are key to the development of a project, including but not limited to project design, governance and planning, enforcement, zonation, land tenure and acquisition, surveying and research. Cost for annual maintenance. The cost for annual maintenance was estimated to be $10 ha-1, which included aspects such as in education and communication, monitoring, sustainable livelihoods, marketing, finance and administration. Carbon price. A constant carbon price of $5.8 t-1CO\u00ad2e for the first five years was applied. This price was based on an average price of carbon for avoided deforestation projects reported recently by Forest Trends\u2019 Ecosystem Marketplace (i.e. for the period 2006 \u2013 2018). Subsequently, a 5% price appreciation was applied annually over a project timeframe of 30 years. Discount rate. We calculated NPV of annual and accumulated profits over 30 years based on a 10% risk-adjusted discount rate. Further details for these datasets and their uncertainties are presented in Koh et. al. For questions or issues on the spatial data layers, please contact Yiwen Zeng (zengyiwen@nus.edu.sg).", "keywords": ["Carbon stocks", "Climate change mitigation", "13. Climate action", "Carbon finance", "15. Life on land"], "contacts": [{"organization": "Koh, Lian Pin, Zeng, Yiwen, Sarira, Tasya Vadya, Siman, Kelly,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4287780"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4287780", "name": "item", "description": "10.5281/zenodo.4287780", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4287780"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-25T00:00:00Z"}}, {"id": "10.5281/zenodo.4487144", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:20:54Z", "type": "Dataset", "title": "Eddy Covariance data from ICOS-associated station IT-NIV \u2013 August-November 2019", "description": "RestrictedData stored here refer to Eddy Covariance (EC) data measured in 2019 between August and November at the Alpine CZO (Critical Zone Observatory, hereafter CZO@Nivolet) which was established at the Nivolet Plain (Piani del Nivolet) in the Gran Paradiso National Park (GPNP), located in the western Italian Alps. The EC site (IT-NIV) is an ICOS-associated station. CZO@Nivolet is aimed at investigating the cross-scale interactions between climatic shifts and ecosystem functions multiple scales, involving multidisciplinary studies. The main research questions that we aim to answer are concerning: (a) the effect of bedrock lithology, soil physics and chemisty, topographic hetereogenity, biotic components and meteo-climatic parameters in modulating CO2 flux in alpine grassland; and (b) what are the controlling factors of organic C and weathering under geologic substrates and different topographic positions. The investigations started in 2017. In 2019, the EC tower was added to deeply study CO2, H20, latent and sensible heat exchanges between soil, vegetation, and atmosphere. Carbon dioxide fluxes and environmental variables are recorded during the snow-free season to estimate carbon storage and explore CO2 fluxes drivers in high-altitude grasslands. Further developments will regard the integration of different techniques (Eddy Covariance, Remote Sensing, Flux chambers) to improve both spatial and temporal extent of carbon fluxes estimates to finally assess grasslands' productivity.", "keywords": ["13. Climate action", "alpine grassland", "15. Life on land", "Gran Paradiso National Park", "Mountain", "EO_Data", "Eddy Covariance", "Net Ecosystem Exchange", "ecosystem-atmosphere carbon exchange"], "contacts": [{"organization": "Vivaldo, Gianna, Raco, Brunella, Baneschi, Ilaria, Giamberini, Maria Silvia,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.4487144"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.4487144", "name": "item", "description": "10.5281/zenodo.4487144", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.4487144"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-20T00:00:00Z"}}, {"id": "10.5281/zenodo.7656722", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:05Z", "type": "Dataset", "title": "Data for: The effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis", "description": "Open AccessData description This dataset includes detailed information about five different types of land use change reported in \u201cThe effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis (Agriculture, Ecosystems and Environment; https://doi.org/10.1016/j.agee.2023.108402)\u201d. Lists of five different types of land use change 1) conversion of primary forest to cropland 2) conversion of primary forest to grassland 3) conversion of cropland to forest 4) conversion of grassland to forest 5) conversion of grassland to cropland Lists of detailed information Land use change (pre-LUC, post-LUC) Country, Location, Geographic position (Longitude, Latitude) Altitude (m) Climate zone Weather [rainfall (mm yr-1) and temperature (\u00b0C)] Reported time of change (years) Vegetation type (pre-LUC, post-LUC) Fertilizer (pre-LUC, post-LUC: type, application; change) Soil sampling depth (cm) Soil type [units, pre-LUC, post-LUC, change rate (%)] Soil pH, bulk density, CEC [units, pre-LUC, post-LUC, change rate (%)] Soil organic carbon [units, pre-LUC, post-LUC, change rate (%)] Soil total nitrogen [units, pre-LUC, post-LUC, change rate (%)] Soil total phosphorus [units, pre-LUC, post-LUC, change rate (%)] Soil C:N [units, pre-LUC, post-LUC, change rate (%)] Soil C:P [units, pre-LUC, post-LUC, change rate (%)] Soil N:P [units, pre-LUC, post-LUC, change rate (%)] Reference Data collection method We analyzed five different types of LUC: 1) conversion of primary forest to cropland, 2) conversion of primary forest to grassland, 3) conversion of cropland to forest, 4) conversion of grassland to forest, and 5) conversion of grassland to cropland. We classified primary forest as forest that had not previously been cleared and used for other land uses. The conversion of cropland or grassland to forest includes naturally generated and intentionally planted forest. Cropland is land used for growing agricultural crops and may include short pasture phases, and grassland is land used continuously for grazing purposes, but may include occasional and repeated pasture-renewal phases. While we tried to make categorical distinctions between these land-use types, land uses are often more fluid in practice, which may not always have been stated in the publications underlying our data compilation. When a paper reported both contents and stocks, we used the stock-based measure. We used reported stocks if the original work had already been corrected to equivalent soil mass (Ellert and Bettany, 1995) or if corrected stocks had been reported in previous reviews or meta-analyses (Don et al., 2011; Poeplau et al., 2011; Guo and Gifford, 2002). Where bulk-density correction had not been applied, we tried to make those corrections to estimate changes to equivalent soil mass if studies provided sufficient information on soil bulk density and depth, using the method of Zhang et al. (2004). If that was not possible, we used the reported SOC, TN, or TP contents. Acknowledgements We thank scientists who measured, analyzed, and published the data compiled for this study. We are especially grateful to Drs. Axel Don, Christopher Poeplau, Lex Bouwman, and Gaihe Yang, who provided their global meta-data through personal communication. D.-G.K. acknowledges support from the IAEA CRP D15020. M.U.F.K and L.L.L. were supported by the Strategic Science Investment Fund (SSIF) of New Zealand\u2019s Ministry of Business, Innovation and Employment.", "keywords": ["2. Zero hunger", "13. Climate action", "land-use change", " greenhouse gas emissions", " soil", " carbon", " nitrogen", " phosphorus", " stoichiometry", " time", " temperature", " rainfall", " forest type", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7656722"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7656722", "name": "item", "description": "10.5281/zenodo.7656722", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7656722"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-20T00:00:00Z"}}, {"id": "10.5281/zenodo.7856487", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:07Z", "type": "Dataset", "title": "HiLSS Project", "description": "This\u00a0repository is periodically updated. Historic Landscape and Soil Sustainability (MSCA-IF-2019 - Individual Fellowships) The HiLSS Project aims to investigate the relationships between sustainability and landscape heritage with particular reference to soil loss and degradation over the long term. The project will take a multidisciplinary approach that combines archaeology, Historical Landscape Characterisation (HLC), geosciences, and computer-based geospatial analysis (GIS - Geographical Information Systems) and modelling (RUSLE - Revisited Universal Soil Loss Equation). The research objectives of the HiLSS project are to quantify the impact of human activities during the Late Holocene in order to create spatial models which can inform the development of sustainable conservation strategies for rural landscape heritage. This project will focus on two mountainous regions that present historical and cultural similarities but located in different climatic zones of Europe (1- Tuscan-Emilian Apennines, Italy; 2- Northern-mid Galicia, Spain). In previous HLC studies, land-use has been evaluated from the perspective of cultural heritage, whereas RUSLE have used it as a proxy for the land-cover of an area and its effect on soil erosion. The HiLSS project will propose an innovative methodology that combines both the historic/cultural values and the environmental values of land-use to inform development of a model for the sustainable conservation. By considering the different agricultural land-use HLC types in GIS-RUSLE modelling, it will be possible to quantify the effect on soil loss for each HLC type and consequently to devise more environmentally sustainable management for each type. Environmental sustainability and historic landscape conservation are typically treated as two separate fields, but the HiLSS project will develop a transformative model for interdisciplinary research, proposing a new way to embrace both cultural and natural values as components of the same landscape management plans. HLC_RUSLE.zip The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: 'Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023)'. List of files included in HLC_RUSLE.zip: R_script_code named 'HLC_RUSLE'\u00a0in .rmd format Output folder: Figures folder: .png products of the R script code Rasters\u00a0folder: .png products of the R script code Tables\u00a0folder: .pdf\u00a0products of the R script code GeoTiff folder (.TIFF file format): Regional RUSLE\u00a0Data GPKG:\u00a0HLC dataset\u00a0and\u00a0Region Of Interest file in .gpkg format Spatial statistics to reveal patterns and connections in the historic landscape The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: '\u00a0F.\u00a0Brandolini & S.\u00a0Turner\u00a0(2022)\u00a0Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy),\u00a0Journal of Maps,\u00a0DOI:\u00a010.1080/17445647.2022.2088305.\u00a0'. It is available at:\u00a0https://doi.org/10.5281/zenodo.5907229 Supplementary material_Land _SI_Historic Landscape Evolution.zip Supplementary Materials to accompaing\u00a0the paper:\u00a0The evolution of historic agroforestry landscape in the Northern Apennines (Italy) and its consequences for slope geomorphic processes, submitted to\u00a0Land,\u00a0Special Issue\u00a0Historic Landscape Transformation. Project_Publications.zip List of .pdf file included in the folder:\u00a0 1) Brandolini F, Domingo-Ribas G, Zerboni A and Turner S. A Google Earth Engine-enabled Python approach for the identification of anthropogenic palaeo-landscape features [version 2; peer review: 2 approved, 1 approved with reservations]. Open Res Europe 2021,\u00a01:22\u00a0(https://doi.org/10.12688/openreseurope.13135.2) 2) Brandolini F., Turner S.\u00a0 2022 - Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), \u00a0Journal of Maps,\u00a0 (https://doi.org/10.1080/17445647.2022.2088305) 3) Brandolini, F., Kinnaird, T.C., Srivastava, A., Turner S. 2023 -\u00a0Modelling the impact of historic landscape change on soil erosion and degradation. Sci Rep 13, 4949 (2023), (https://doi.org/10.1038/s41598-023-31334-z) 4)\u00a0Brandolini, F., Compostella, C., Pelfini, M., and Turner, S. 2023 - 'The Evolution of Historic Agroforestry Landscape in the Northern Apennines (Italy) and Its Consequences for Slope Geomorphic Processes' Land 12, no. 5: 1054. (https://doi.org/10.3390/land12051054)", "keywords": ["2. Zero hunger", "13. Climate action", "Landscape Archaeology", "11. Sustainability", "RUSLE", "USPED", "15. Life on land", "Historic Landscape Characterisation", "Soil Sustainability", "Soil Erosion Modelling", "12. Responsible consumption"], "contacts": [{"organization": "Brandolini Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7856487"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7856487", "name": "item", "description": "10.5281/zenodo.7856487", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7856487"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-10T00:00:00Z"}}, {"id": "10.5281/zenodo.8089699", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:08Z", "type": "Journal Article", "created": "2019-11-28", "title": "High-resolution and three-dimensional mapping of soil texture of China", "description": "The lack of detailed three-dimensional soil texture information largely restricts many applications in agriculture, hydrology, climate, ecology and environment. This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8089699"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8089699", "name": "item", "description": "10.5281/zenodo.8089699", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8089699"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.5281/zenodo.8320433", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:11Z", "type": "Dataset", "title": "Carbon storage and carbon-equivalent albedo impact for US forests, by age and forest type", "description": "These tables document estimates of carbon storage (Mg/ha +/- Standard Error) and carbon-equivalent albedo impacts (same units) of US forests by age and forest type (Healey et al., in review). Carbon estimates are derived from field measurements made by the USDA Forest Service on approximately 125,000 forested field plots (Domke et al., 2022). Soil organic carbon is omitted from these estimates, but all other above- and below-ground pools are included. Albedo impacts (time-dependent emissions equivalent, TDEE; Bright et al., 2016) were developed by applying atmospheric kernels (Bright and O'Halloran) to a new Landsat blue sky albedo product for the Landsat archive (Erb et al., 2022), as described by Healey et al. (in review). Standard error is supplied for each age/forest type bin for carbon storage, but upper and lower standard error bounds are specified for TDEE because log transformation creates an asymmetrical uncertainty envelope. Bright, Bogren, Bernier, Astrup, (2016). Carbon-equivalent metrics for albedo changes in land management contexts: Relevance of the time dimension. Ecol. Appl. 26, 1868\u20131880 Bright, R. M., & O'Halloran, T. L. (2019). Developing a monthly radiative kernel for surface albedo change from satellite climatologies of Earth's shortwave radiation budget: CACK v1. 0. Geoscientific Model Development, 12(9), 3975-3990. Domke, Walters, Nowak, Greenfield, Smith, Nichols, Ogle, Coulston, Wirth (2022). Greenhouse Gas Emissions and Removals From Forest Land, Woodlands, Urban Trees, and Harvested Wood Products in the United States, 1990\u20132020. (US Dept. Ag. For. Service, Madison, WI; https://doi.org/10.2737/FS-RU-382). Erb, Li, Sun, Paynter, Wang, & Schaaf, (2022). Evaluation of the Landsat-8 Albedo Product across the Circumpolar Domain. Remote Sensing, 14(21), 5320. Healey, Yang, Erb, Bright, Domke, Frescino, Schaaf, (in review) New satellite observations expose albedo dynamics offsetting half of carbon storage benefits in US forests.", "keywords": ["climate change", "forest carbon", "13. Climate action", "15. Life on land", "Landsat", "albedo"], "contacts": [{"organization": "Healey, Sean, Yang, Zhiqiang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8320433"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8320433", "name": "item", "description": "10.5281/zenodo.8320433", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8320433"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-09-06T00:00:00Z"}}, {"id": "10.7910/DVN/HXAH87", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:21:40Z", "type": "Dataset", "title": "Arbuscular and ectomycorrhizal fungi diversity in the Indian subcontinent", "description": "Mycorrhizal fungi (MF) are below-ground organisms playing a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Arbuscular and ectomycorrhizal fungi are the two mycorrhizal types most relevant to worldwide ecosystems, but areas like the Indian sub-continent remain under-represented in global maps. The dataset presented here reports the available information regarding arbuscular and ectomycorrhizal fungi diversity in cultivated and natural ecosystems of the Indian subcontinent. We have selected studies published in English in ISI Web of Science during the years 2005 - 2020 that provided a taxonomic classification of MF and their associated abundance in terms of percentage of root colonization or number of spores per quantity of soil. From the screening of 74 studies, we have recorded: i. the scientific or common name of the plant or the generic habitat sampled for MF identification; ii the MF genus and species; iii. the location of the study with associated altitude and geographic coordinates; iv. main soil physico-chemical properties (soil pH, texture, organic Carbon, Total Nitrogen, available Phosphorus); climatic variables such as mean annual precipitation and temperature.<br><br>", "keywords": ["ecosystem management", "Asia", "Agricultural Sciences", "CGIAR Research Program on Water", " Land and Ecosystems", "Multifunctional Landscapes", "gesti\u00f3n de ecosistemas", "soil biology", "MYCORRHIZAE", "CGIAR Research Program", "Earth and Environmental Sciences", "SOIL BIOLOGY", "BIODIVERSITY", "mycorrhizae", "biolog\u00eda del suelo"], "contacts": [{"organization": "Beggi, Francesca, Dasgupta, Debarshi,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/HXAH87"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/HXAH87", "name": "item", "description": "10.7910/DVN/HXAH87", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/HXAH87"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "11245.1/e982467a-6b87-4f88-8ac3-53d0fb37aeb2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:06Z", "type": "Journal Article", "created": "2024-05-01", "title": "Arabinosylation of cell wall extensin is required for the directional response to salinity in roots", "description": "Abstract

Soil salinity is a major contributor to crop yield losses. To improve our understanding of root responses to salinity, we developed and exploited a real-time salt-induced tilting assay. This assay follows root growth upon both gravitropic and salt challenges, revealing that root bending upon tilting is modulated by Na+ ions, but not by osmotic stress. Next, we measured this salt-specific response in 345 natural Arabidopsis (Arabidopsis thaliana) accessions and discovered a genetic locus, encoding the cell wall-modifying enzyme EXTENSIN ARABINOSE DEFICIENT TRANSFERASE (ExAD) that is associated with root bending in the presence of NaCl (hereafter salt). Extensins are a class of structural cell wall glycoproteins known as hydroxyproline (Hyp)-rich glycoproteins, which are posttranslationally modified by O-glycosylation, mostly involving Hyp-arabinosylation. We show that salt-induced ExAD-dependent Hyp-arabinosylation influences root bending responses and cell wall thickness. Roots of exad1 mutant seedlings, which lack Hyp-arabinosylation of extensin, displayed increased thickness of root epidermal cell walls and greater cell wall porosity. They also showed altered gravitropic root bending in salt conditions and a reduced salt-avoidance response. Our results suggest that extensin modification via Hyp-arabinosylation is a unique salt-specific cellular process required for the directional response of roots exposed to salinity.Drylands (hyperarid, arid, semiarid, and dry subhumid ecosystems) cover almost half of Earth\uffe2\uff80\uff99s land surface and are highly vulnerable to environmental pressures. Here we provide an inventory of soil properties including carbon (C), nitrogen (N), and phosphorus (P) stocks within the current boundaries of drylands, aimed at serving as a benchmark in the face of future challenges including increased population, food security, desertification, and climate change. Aridity limits plant production and results in poorly developed soils, with coarse texture, low C:N and C:P, scarce organic matter, and high vulnerability to erosion. Dryland soils store 646 Pg of organic C to 2\uffe2\uff80\uff89m, the equivalent of 32% of the global soil organic C pool. The magnitude of the historic loss of C from dryland soils due to human land use and cover change and their typically low C:N and C:P suggest high potential to build up soil organic matter, but coarse soil textures may limit protection and stabilization processes. Restoring, preserving, and increasing soil organic matter in drylands may help slow down rising levels of atmospheric carbon dioxide by sequestering C, and is strongly needed to enhance food security and reduce the risk of land degradation and desertification.Plastics used in agriculture, commonly known as agriplastics (AP), offer numerous advantages in terrestrial agriculture, forestry, fisheries and aquaculture, but the diffusion of AP-intensive practices has led to extensive pollution. This review aims to synthesise scientific and policy discussions surrounding AP, examining evidence of their benefits and detrimental environmental and agricultural impacts. Following the proposal of a preliminary general taxonomy of AP, this paper presents the findings from a survey conducted among international experts from the plastic industry, farmer organisations, NGOs and environmental research institutes. This analysis highlights knowledge gaps, demands and perspectives for the sustainable future use of AP. Stakeholder positions vary on the options of \uffe2\uff80\uff98rejection\uffe2\uff80\uff99 or \uffe2\uff80\uff98reduction\uffe2\uff80\uff99 of AP, as well as the role of alternative materials such as (bio)degradable and compostable plastics. However, there is consensus on critical issues such as redesign, labelling, traceability, environmental safety standards, deployment and retrieval standards, as well as innovative waste management approaches. All stakeholders express concern for the environment. A \uffe2\uff80\uff98best practice\uffe2\uff80\uff99-based circular model was elaborated capturing these perspectives. In the context of global food systems increasingly reliant on AP, scientists emphasise the need to simultaneously preserve nature-based and traditional knowledge-based sustainable agricultural practices to enhance food system resilience.Fungi are major drivers of ecosystem functioning. Increases in aridity are known to negatively impact fungal community composition in dryland ecosystems globally; yet, much less is known on the potential influence of other environmental drivers, and whether these relationships are linear or nonlinear.

Time period

2017\uffe2\uff80\uff932021.

Location

Global.

Major taxa studied

Fungi.

Methods

We re\uffe2\uff80\uff90analysed multiple datasets from different dryland biogeographical regions, for a total of 912 samples and 1,483 taxa. We examined geographical patterns in community diversity and composition, and spatial, edaphic and climatic factors driving them.

Results

UV index, climate seasonality, and sand content were the most important environmental predictors of community shifts, showing the strongest association with the richness of putative plant pathogens and saprobes. Important nonlinear relationships existed with each of these fungal guilds, with increases in UV and temperature seasonality above 7.5 and 900 SD (standard deviation x 100 of the mean monthly temperature), respectively, being associated with an increased probability of plant pathogen and unspecified saprotroph occurrence. Conversely, these environmental parameters had a negative relationship with litter and soil saprotroph richness. Consequently, these ecological groups might be particularly sensitive to shifts in UV radiation and climate seasonality, which is likely to disturb current plant\uffe2\uff80\uff93soil dynamics in drylands.

Main conclusions

Our synthesis integrates fungal community data from drylands across the globe, allowing the investigation of fungal distribution and providing the first evidence of shifts in fungal diversity and composition of key fungal ecological groups along diverse spatial, climatic and edaphic gradients in these widely distributed ecosystems. Our findings imply that shifts in soil structure and seasonal climatic patterns induced by global change will have disproportionate consequences for the distribution of fungal groups linked to vegetation and biogeochemical cycling in drylands, with implications for plant\uffe2\uff80\uff93soil interactions in drylands.Proper assessment of environmental quality or degradation requires knowledge of how terrestrial C pools respond to land use change. Forest plantations offer a considerable potential to sequester C in aboveground biomass. However, their impact on initial levels of soil organic carbon (SOC) varies from strong losses to gains, possibly affecting C balances in afforestation or reforestation initiatives. We compiled paired\uffe2\uff80\uff90plot studies on how SOC stocks under native vegetation change after planting fast\uffe2\uff80\uff90growth Eucalyptus species in Brazil, where these plantations are becoming increasingly important. SOC changes for the 0\uffe2\uff80\uff9320 and 0\uffe2\uff80\uff9340\uffe2\uff80\uff89cm depths varied between \uffe2\uff88\uff9225 and 42\uffe2\uff80\uff89Mg\uffe2\uff80\uff89ha\uffe2\uff88\uff921, following a normal distribution centered near zero. After replacing native vegetation by Eucalyptus plantations, mean SOC changes were \uffe2\uff88\uff921\uffc2\uffb75 and 0\uffc2\uffb73\uffe2\uff80\uff89Mg\uffe2\uff80\uff89ha\uffe2\uff88\uff921 for the 0\uffe2\uff80\uff9320 and 0\uffe2\uff80\uff9340\uffe2\uff80\uff89cm depths, respectively. These are very low figures in comparison to C stocks usually sequestered in aboveground biomass and were statistically nonsignificant as demonstrated by a t\uffe2\uff80\uff90test at p\uffe2\uff80\uff89<\uffe2\uff80\uff890\uffc2\uffb705. Similar low, nonsignificant SOC changes were estimated after data were stratified into first or second rotation cycles, soil texture and biome (savanna, rainforest or grassland). Although strong SOC losses or gains effectively occurred in some cases, their underpinning causes could not be generally identified in the present work and must be ascribed in a case basis, considering the full set of environmental and management conditions. We conclude that Eucalyptus spp. plantations in average have no net effect on SOC stocks in Brazil. Copyright \uffc2\uffa9 2012 John Wiley & Sons, Ltd.

", "keywords": ["Soil organic matter", "Carbon stocks", "Tropical soils", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Fast-growth tree plantations", "Land use change"]}, "links": [{"href": "https://doi.org/10.1002/ldr.2158"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Degradation%20%26amp%3B%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ldr.2158", "name": "item", "description": "10.1002/ldr.2158", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ldr.2158"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-04-03T00:00:00Z"}}, {"id": "23546339ad735a64e55426484b88fe14", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:22:53Z", "type": "Report", "title": "Global maps of soil temperature.", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\u00b0C (mean = 3.0 \u00b1 2.1\u00b0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \u00b1 2.3\u00b0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 \u00b1 2.3\u00b0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["Climate Change; Ecosystem; Microclimate; Soil; Temperature; bioclimatic variables; global maps; microclimate; near-surface temperatures; soil temperature; soil-dwelling organisms; temperature offset; weather stations"], "contacts": [{"organization": "Lembrechts, J.J., van den Hoogen, J., Aalto, J., Ashcroft, M.B., De Frenne, P., Kemppinen, J., Kopeck\u00fd, M., Luoto, M., Maclean, IMD, Crowther, T.W., Bailey, J.J., Haesen, S., Klinges, D.H., Niittynen, P., Scheffers, B.R., Van Meerbeek, K., Aartsma, P., Abdalaze, O., Abedi, M., Aerts, R., Ahmadian, N., Ahrends, A., Alatalo, J.M., Alexander, J.M., Allonsius, C.N., Altman, J., Ammann, C., Andres, C., Andrews, C., Ard\u00f6, J., Arriga, N., Arzac, A., Aschero, V., Assis, R.L., Assmann, J.J., Bader, M.Y., Bahalkeh, K., Baran\u010dok, P., Barrio, I.C., Barros, A., Barthel, M., Basham, E.W., Bauters, M., Bazzichetto, M., Marchesini, L.B., Bell, M.C., Benavides, J.C., Benito Alonso, J.L., Berauer, B.J., Bjerke, J.W., Bj\u00f6rk, R.G., Bj\u00f6rkman, M.P., Bj\u00f6rnsd\u00f3ttir, K., Blonder, B., Boeckx, P., Boike, J., Bokhorst, S., Brum, BNS, Br\u016fna, J., Buchmann, N., Buysse, P., Camargo, J.L., Campoe, O.C., Candan, O., Canessa, R., Cannone, N., Carbognani, M., Carnicer, J., Casanova-Katny, A., Cesarz, S., Chojnicki, B., Choler, P., Chown, S.L., Cifuentes, E.F., \u010ciliak, M., Contador, T., Convey, P., Cooper, E.J., Cremonese, E., Curasi, S.R., Curtis, R., Cutini, M., Dahlberg, C.J., Daskalova, G.N., de Pablo, M.A., Della Chiesa, S., Dengler, J., Deronde, B., Descombes, P., Di Cecco, V., Di Musciano, M., Dick, J., Dimarco, R.D., Dolezal, J., Dorrepaal, E., Du\u0161ek, J., Eisenhauer, N., Eklundh, L., Erickson, T.E., Erschbamer, B., Eugster, W., Ewers, R.M., Exton, D.A., Fanin, N., Fazlioglu, F., Feigenwinter, I., Fenu, G., Ferlian, O., Fern\u00e1ndez Calzado, M.R., Fern\u00e1ndez-Pascual, E., Finckh, M., Higgens, R.F., Forte, TGW, Freeman, E.C., Frei, E.R., Fuentes-Lillo, E., Garc\u00eda, R.A., Garc\u00eda, M.B., G\u00e9ron, C., Gharun, M., Ghosn, D., Gigauri, K., Gobin, A., Goded, I., Goeckede, M., Gottschall, F., Goulding, K., Govaert, S., Graae, B.J., Greenwood, S., Greiser, C., Grelle, A., Gu\u00e9nard, B., Guglielmin, M., Guillemot, J., Haase, P., Haider, S., Halbritter, A.H., Hamid, M., Hammerle, A., Hampe, A., Haugum, S.V., Hederov\u00e1, L., Heinesch, B., Helfter, C., Hepenstrick, D., Herberich, M., Herbst, M., Hermanutz, L., Hik, D.S., Hoffr\u00e9n, R., Homeier, J., H\u00f6rtnagl, L., H\u00f8ye, T.T., Hrbacek, F., Hylander, K., Iwata, H., Jackowicz-Korczynski, M.A., Jactel, H., J\u00e4rveoja, J., Jastrz\u0119bowski, S., Jentsch, A., Jim\u00e9nez, J.J., J\u00f3nsd\u00f3ttir, I.S., Jucker, T., Jump, A.S., Juszczak, R., Kanka, R., Ka\u0161par, V., Kazakis, G., Kelly, J., Khuroo, A.A., Klemedtsson, L., Klisz, M., Kljun, N., Knohl, A., Kobler, J., Koll\u00e1r, J., Kotowska, M.M., Kov\u00e1cs, B., Kreyling, J., Lamprecht, A., Lang, S.I., Larson, C., Larson, K., Laska, K., le Maire, G., Leihy, R.I., Lens, L., Liljebladh, B., Lohila, A., Lorite, J., Loubet, B., Lynn, J., Macek, M., Mackenzie, R., Magliulo, E., Maier, R., Malfasi, F., M\u00e1li\u0161, F.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/23546339ad735a64e55426484b88fe14"}, {"rel": "self", "type": "application/geo+json", "title": "23546339ad735a64e55426484b88fe14", "name": "item", "description": "23546339ad735a64e55426484b88fe14", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/23546339ad735a64e55426484b88fe14"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2012.01.038", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:15:40Z", "type": "Journal Article", "created": "2012-03-11", "title": "Land Degradation Impact On Soil Carbon Losses Through Water Erosion And Co2 Emissions", "description": "Abstract Worldwide concerns with global change and its effects on our future environment require an improved understanding of the impact of land cover changes on the global C cycle. Overgrazing causes a reduction in plant cover with accepted consequences on soil infiltration and soil erosion, yet the impact on the loss of soil organic carbon (SOC) and its associated processes remain unaccounted for. In this study performed in South Africa, our main objective was to evaluate the impact of plant cover reduction on (i) SOC erosion by water in both particulate (POC) and dissolved (DOC) forms, and (ii) soil CO 2 emissions to the atmosphere. The study performed under sandy-loam Acrisols investigated three proportions of soil surface coverage by plants (Cov), from 100% (Cov100) for the \u201cnon-degraded\u201d treatment to 25\u201350% (Cov50) and 0\u20135% (Cov5). POC and DOC losses were evaluated using an artificial rainfall of 30\u00a0mm\u00a0h \u2212\u00a01 applied for a period of 30\u00a0min on bounded 1\u00a0\u00d7\u00a01\u00a0m\u00b2 microplots (n\u00a0=\u00a03 per treatment). CO 2 emissions from undisturbed soil samples (n\u00a0=\u00a09) were evaluated continuously at the laboratory over a 6-month period. At the \u201cnon-degraded\u201d treatment of Cov100, plant-C inputs to the soil profile were 1950\u00a0\u00b1\u00a0180\u00a0gC\u00a0m \u2212\u00a02 \u00a0y \u2212\u00a01 and SOC stocks in the 0\u20130.02\u00a0m layer were 300.6\u00a0\u00b1\u00a016.2\u00a0gC\u00a0m \u2212\u00a02 . While soil-C inputs by plants significantly (P\u00a0 \u2212\u00a02 at Cov100 increased from 66% at Cov50 (i.e. 3.76\u00a0\u00b1\u00a01.8\u00a0gC\u00a0m \u2212\u00a02 ) to a staggering 213% at Cov5 (i.e. 7.08\u00a0\u00b1\u00a02.9\u00a0gC\u00a0m \u2212\u00a02 ). These losses were for the most part in particulate form (from 88.0% for Cov100 to 98.7% for Cov5). Plant cover reduction significantly decreased both the cumulative C\u2013CO 2 emissions (by 68% at Cov50 and 69% at Cov5) and the mineralization rate of the soil organic matter (from 0.039 gC\u2013CO 2 \u00a0gC \u2212\u00a01 at Cov100 to 0.031\u00a0gC\u2013CO 2 \u00a0gC \u2212\u00a01 at Cov5). These results are expected to increase our understanding of the impact of land degradation on the global C cycle. Further in-situ research studies, however, need to investigate whether or not grassland degradation induces net C-emissions to the atmosphere.", "keywords": ["2. Zero hunger", "550", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "12. Responsible consumption", "South Africa", "13. Climate action", "Particulate and dissolved SOC forms", "0401 agriculture", " forestry", " and fisheries", "Global C Cycle", "Water erosion", "Land use change"], "contacts": [{"organization": "McHunu, C., /Chaplot, Vincent,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2012.01.038"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2012.01.038", "name": "item", "description": "10.1016/j.geoderma.2012.01.038", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2012.01.038"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-05-01T00:00:00Z"}}, {"id": "10.1016/j.agrformet.2017.10.013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:15:05Z", "type": "Journal Article", "created": "2017-10-19", "title": "Climate-Smart Agroforestry: Faidherbia Albida Trees Buffer Wheat Against Climatic Extremes In The Central Rift Valley Of Ethiopia", "description": "Abstract Faidherbia albida parklands cover a large area of the Sudano-Sahelian zone of Africa, a region that suffers from soil fertility decline, food insecurity and climate change. The parklands deliver multiple benefits, including fuelwood, soil nutrient replenishment, moisture conservation, and improved crop yield underneath the canopy. Its microclimate modification may provide an affordable climate adaptation strategy which needs to be explored. We carried out an on-farm experiment for three consecutive seasons in the Ethiopian Central Rift Valley with treatments of Faidherbia trees with bare soil underneath, wheat grown beneath Faidherbia and wheat grown in open fields. We tested the sensitivity of wheat yield to tree-mediated variables of photosynthetically active radiation (PAR), air temperature and soil nitrogen, using APSIM-wheat model. Results showed that soil moisture in the sub-soil was the least for wheat with tree, intermediate for sole tree and the highest for open field. Presence of trees resulted in 35\u201355% larger available N close to tree crowns compared with sole wheat. Trees significantly reduced PAR reaching the canopy of wheat growing underneath to optimum levels. Midday air temperature was about 6\u00a0\u00b0C less under the trees than in the open fields. LAI, number of grains spike\u22121, plant height, total aboveground biomass and wheat grain yield were all significantly higher (P", "keywords": ["Crop physiology", "2. Zero hunger", "Competition", "13. Climate action", "Local adaptation", "Climate change", "0401 agriculture", " forestry", " and fisheries", "Facilitation", "04 agricultural and veterinary sciences", "15. Life on land", "Heat stress", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2017.10.013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2017.10.013", "name": "item", "description": "10.1016/j.agrformet.2017.10.013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2017.10.013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.1002/ecy.1539", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:14:06Z", "type": "Journal Article", "created": "2016-07-28", "title": "Chronic Warming Stimulates Growth Of Marsh Grasses More Than Mangroves In A Coastal Wetland Ecotone", "description": "Abstract

Increasing temperatures and a reduction in the frequency and severity of freezing events have been linked to species distribution shifts. Across the globe, mangrove ranges are expanding toward higher latitudes, likely due to diminishing frequency of freezing events associated with climate change. Continued warming will alter coastal wetland plant dynamics both above\uffe2\uff80\uff90 and belowground, potentially altering plant capacity to keep up with sea level rise. We conducted an in situ warming experiment, in northeast Florida, to determine how increased temperature (+2\uffc2\uffb0C) influences co\uffe2\uff80\uff90occurring mangrove and salt marsh plants. Warming was achieved using passive warming with three treatment levels (ambient, shade control, warmed). Avicennia germinans, the black mangrove, exhibited no differences in growth or height due to experimental warming, but displayed a warming\uffe2\uff80\uff90induced increase in leaf production (48%). Surprisingly, Distichlis spicata, the dominant salt marsh grass, increased in biomass (53% in 2013 and 70% in 2014), density (41%) and height (18%) with warming during summer months. Warming decreased plant root mass at depth and changed abundances of anaerobic bacterial taxa. Even while the poleward shift of mangroves is clearly controlled by the occurrences of severe freezes, chronic warming between these freeze events may slow the progression of mangrove dominance within ecotones.

", "keywords": ["0106 biological sciences", "Time Factors", "13. Climate action", "Climate Change", "Wetlands", "Florida", "Avicennia", "14. Life underwater", "15. Life on land", "Poaceae", "Plant Roots", "01 natural sciences", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1002/ecy.1539"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ecy.1539", "name": "item", "description": "10.1002/ecy.1539", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ecy.1539"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-11-01T00:00:00Z"}}, {"id": "10.1002/2017JD027346", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:14:04Z", "type": "Journal Article", "created": "2017-12-28", "title": "Soil Moisture-Temperature Coupling in a Set of Land Surface Models", "description": "Abstract

The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture\uffe2\uff80\uff90temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off\uffe2\uff80\uff90line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture\uffe2\uff80\uff90temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower\uffe2\uff80\uff90based results (r = 0.5\uffe2\uff80\uff930.7), with the multimodel mean performing similarly to the best\uffe2\uff80\uff90performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.

", "keywords": ["ENVIRONMENT SIMULATOR JULES", "FLUXES", "0207 environmental engineering", "02 engineering and technology", "01 natural sciences", "CO2 EXCHANGE", "models", "WATER", "SCALE", "Research Articles", "0105 earth and related environmental sciences", "land surface", "CARBON-DIOXIDE EXCHANGE", "eartH2Observe", "temperature", "15. Life on land", "DECIDUOUS FOREST", "CLIMATE", "EVAPORATION", "VARIABILITY", "13. Climate action", "Earth and Environmental Sciences", "BALANCE", "land surface models", "SENSIBLE HEAT", "land-atmosphere interactions", "soil moisture"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JD027346"}, {"href": "https://doi.org/10.1002/2017JD027346"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Atmospheres", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2017JD027346", "name": "item", "description": "10.1002/2017JD027346", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017JD027346"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-02-01T00:00:00Z"}}, {"id": "10.1002/2017JG004269", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:14:04Z", "type": "Journal Article", "created": "2017-12-18", "title": "Soil Carbon Dynamics in Soybean Cropland and Forests in Mato Grosso, Brazil", "description": "Abstract

Climate and land use models predict that tropical deforestation and conversion to cropland will produce a large flux of soil carbon (C) to the atmosphere from accelerated decomposition of soil organic matter (SOM). However, the C flux from the deep tropical soils on which most intensive crop agriculture is now expanding remains poorly constrained. To quantify the effect of intensive agriculture on tropical soil C, we compared C stocks, radiocarbon, and stable C isotopes to 2\uffc2\uffa0m depth from forests and soybean cropland created from former pasture in Mato Grosso, Brazil. We hypothesized that soil disturbance, higher soil temperatures (+2\uffc2\uffb0C), and lower OM inputs from soybeans would increase soil C turnover and deplete C stocks relative to nearby forest soils. However, we found reduced C concentrations and stocks only in surface soils (0\uffe2\uff80\uff9310\uffc2\uffa0cm) of soybean cropland compared with forests, and these differences could be explained by soil mixing during plowing. The amount and \uffce\uff9414C of respired CO2 to 50\uffc2\uffa0cm depth were significantly lower from soybean soils, yet CO2 production at 2\uffc2\uffa0m deep was low in both forest and soybean soils. Mean surface soil \uffce\uffb413C decreased by 0.5\uffe2\uff80\uffb0 between 2009 and 2013 in soybean cropland, suggesting low OM inputs from soybeans. Together these findings suggest the following: (1) soil C is relatively resistant to changes in land use and (2) conversion to cropland caused a small, measurable reduction in the fast\uffe2\uff80\uff90cycling C pool through reduced OM inputs, mobilization of older C from soil mixing, and/or destabilization of SOM in surface soils.

", "keywords": ["tropical forest", "2. Zero hunger", "Life on Land", "land use", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Soil carbon", "Geophysics", "Tropical forest", "Isotopes", "13. Climate action", "Land use", "Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon", "Brazil", "isotopes", "Research Articles", "agriculture"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JG004269"}, {"href": "https://escholarship.org/content/qt4jm295dz/qt4jm295dz.pdf"}, {"href": "https://doi.org/10.1002/2017JG004269"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2017JG004269", "name": "item", "description": "10.1002/2017JG004269", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017JG004269"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-01-01T00:00:00Z"}}, {"id": "10.1002/adma.202402907", "type": "Feature", "geometry": null, "properties": {"updated": "2026-08-24T16:14:04Z", "type": "Journal Article", "created": "2024-05-17", "title": "Ultrafast Laser Processing of 2D Materials: Novel Routes to Advanced Devices", "description": "Abstract

Ultrafast laser processing has emerged as a versatile technique for modifying materials and introducing novel functionalities. Over the past decade, this method has demonstrated remarkable advantages in the manipulation of 2D layered materials, including synthesis, structuring, functionalization, and local patterning. Unlike continuous\uffe2\uff80\uff90wave and long\uffe2\uff80\uff90pulsed optical methods, ultrafast lasers offer a solution for thermal heating issues. Nonlinear interactions between ultrafast laser pulses and the atomic lattice of 2D materials substantially influence their chemical and physical properties. This paper highlights the transformative role of ultrafast laser pulses in maskless green technology, enabling subtractive, and additive processes that unveil ways for advanced devices. Utilizing the synergetic effect between the energy states within the atomic layers and ultrafast laser irradiation, it is feasible to achieve unprecedented resolutions down to several nanometers. Recent advancements are discussed in functionalization, doping, atomic reconstruction, phase transformation, and 2D and 3D micro\uffe2\uff80\uff90 and nanopatterning. A forward\uffe2\uff80\uff90looking perspective on a wide array of applications of 2D materials, along with device fabrication featuring novel physical and chemical properties through direct ultrafast laser writing, is also provided.) Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), Journal of Maps, DOI: 10.1080/17445647.2022.2088305 Abstract In the Northern Apennines, significant modifications to the characteristic historic features of landscapes occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today European and national policies are promoting the repopulation of these regions in order to help preserve the cultural identity of territories and to reduce demographic pressure in urban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of a set of strategies to underpin the preservation of landscape heritage and to foster local development on the basis of the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components. Methods This dataset was explored with two spatial statistical tools using the programming language R (R Core Team 2021): Local Indicators for Categorical Data (LICD) and Point Pattern analysis (PPA). The LICD method is based on join-count statistics (JCS), a solid method to measure the correlation between binomial variables and the distance between observations. LICD has been recently employed in landscape archaeological studies for verifying visible patterns and disclosing hidden spatial relationships (article: Carrer et al. 2021, Data: Zenodo Repository) The application of PPA in landscape studies has been widely applied in Ecology and it is growing popular also in Archaeology (Knitter and Nakoinz 2018; Brandolini and Carrer 2020; Costanzo et al. 2021). In this study, PPA was employed to provide a quantitative assessment of the correlations between different components of the Vetto landscape. List of files included in Brandolini_Turner_tjom_2022.zip: R_script_code named 'tjom_supplementary' in .rmd format Output folder: png and .txt products of the R script code GeoTiff folder (.TIFF file format): Geomorphons Euclidean distances from Irregular Fields (IF) Euclidean distances from Combined Fields (CF) EsriSHP folder (.shp file format): H_sites folder: historic settlements (h_sites.shp) rural_ruins folder: abandoned rural ruins (rural_ruins.shp) hlc folder: HLC_periods.shp HLC_types.shp roi folder: Region Of Interest (roi.shp) Contacts dr. F. Brandolini: filippo.brandolini@newcastle.ac.uk Acknowledgements The authors would like to acknowledge the help of the mayor Mr Fabio Ruffini and all the staff of Vetto d\u2019 Enza, Dr. Alessandra Curotti and Dr. Chiara Cantini and (Unione Montana dei Comuni dell\u2019Appennino Reggiano) and Dott.ssa Annalisa Capurso (Soprintendenza Archeologia Belle Arti e Paesaggio per la citt\u00e0 metropolitana di Bologna e le province di Modena, Reggio Emilia e Ferrara) for their administrative assistance in preparation of the project fieldwork activities. Also, we wish to thank Dr Anna Campeol and Mr Davide Cavecchi (Provincia di Reggio Emilia - Ufficio Topografico) for their help in retrieving and digitising the Nuovo Catasto Terreni cadastral map. The authors also thank the AsRe (Archivio Stato di Reggio Emilia) and AsPr (Archivio Stato di Parma) administration and staff for giving the right to digitise the historical maps and for helping during the consultation at the archives. 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