{"type": "FeatureCollection", "features": [{"id": "10.1016/j.gca.2024.07.026", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:41Z", "type": "Journal Article", "created": "2024-07-27", "title": "Stability and transformation of jarosite and Al-substituted jarosite in an acid sulfate paddy soil under laboratory and field conditions", "description": "Open AccessGeochimica et Cosmochimica Acta, 382", "keywords": ["Redox", "2. Zero hunger", "Soil incubation", "Mossbauer spectroscopy", "Iron minerals; Mossbauer spectroscopy; Redox; Rice paddy; Soil incubation", "Rice paddy", "15. Life on land", "Iron minerals", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.gca.2024.07.026"}, {"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.2024.07.026", "name": "item", "description": "10.1016/j.gca.2024.07.026", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.gca.2024.07.026"}, {"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": "10.1016/j.geoderma.2019.114061", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:44Z", "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/10.1016/j.geoderma.2019.114061"}, {"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.2019.114061", "name": "item", "description": "10.1016/j.geoderma.2019.114061", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2019.114061"}, {"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": "10.1016/j.jenvman.2024.121882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:50Z", "type": "Journal Article", "created": "2024-07-17", "title": "A systematic benchmarking framework for future assessments of soil health: An example from Denmark", "description": "Based on current evidence and established critical thresholds for soil degradation indicators, it is concerning that over 60-70% of European soils are unhealthy due to unsustainable management and the impact of climate change. Despite European and national efforts to improve soil health, significant gaps remain. The proposal for a Soil Monitoring and Resilience Law, to be implemented by the European Union, seeks to establish a framework for soil monitoring and promote sustainable management practices to achieve healthy soils by 2050. This requires extensive data collection and soil monitoring systems to accurately estimate soil health across Europe, considering the diversity of soil types, climates, and land uses. To establish a framework for soil monitoring, we must understand the site-specific status of soil and the ranges of soil health indicators across specific pedoclimatic regions. In our study, we evaluated the soil status in agricultural areas in Denmark using soil health indicators and a site-specific benchmarking approach. We compiled nationally representative datasets, combining point and model-informed data of soil parameters such as organic carbon content, bulk density, pH, electrical conductivity, clay-to-soil organiccarbon ratio, water erosion, and nitrogen leaching. By categorizing Danish agricultural soils into monitoring units based on textural classes, landscape elements, and wetland types, we calculated benchmarks for these indicators, considering different cropping systems. Our approach provided detailed point-based results and a spatially explicit overview of the status of soil health indicators in Denmark. We identified areas where soil deviates from the benchmarks of different indicators. Such deviations might indicate soil functions operating outside the normal range, posing potential threats to soil health. This proposed framework could support the establishment of a baseline for assessing the directionality of future changes in soil health. Moreover, it is adaptable for implementation by other countries to support assessments of soil health.", "keywords": ["2. Zero hunger", "Conservation of Natural Resources", "European soil monitoring and resilience law", "Soil monitoring units", "Denmark", "Climate Change", "Agriculture", "15. Life on land", "6. Clean water", "12. Responsible consumption", "Soil districts", "Soil", "13. Climate action", "11. Sustainability", "Soil health indicators", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1016/j.jenvman.2024.121882"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jenvman.2024.121882", "name": "item", "description": "10.1016/j.jenvman.2024.121882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jenvman.2024.121882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-01T00:00:00Z"}}, {"id": "10.1016/j.jhydrol.2021.126551", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:51Z", "type": "Journal Article", "created": "2021-06-08", "title": "Smartphone-based tension disc infiltrometer for soil hydraulic characterisation", "description": "31 Pags.- 18 Figs.- 1 Tabl.  The definitive version is available at: https://www.sciencedirect.com/science/journal/00221694 The tension disc infiltrometer has become a widespread method to measure soil hydraulic properties under unsaturated conditions. Although several automated devices have been developed, most designs include an elongated water reservoir and a pressure transducer with electronic components to register the water level, increasing its cost and limiting its application. The objective of this work is to present a new tension disc infiltrometer with a compact design of 10 cm diameter and height, where the water level is monitored by a smartphone camera. The infiltration curve is determined from the automated analysis of the images recorded by the smartphone without additional electronic components. The device was first validated in the laboratory by comparing visual measurements (V), the camera imagery (Ca) and a pressure transducer (PT). Next, it was tested on field infiltration experiments. Robust fits (R2 = 0.99) were found between the water level measured with Ca in the laboratory and those obtained with V and PT procedures. The Ca method is accurate, robust and independent of the relative camera position. Good fits were also observed between Ca water level and those obtained with PT in the field experiments. Similar hydraulic conductivity and sorptivity values were obtained with both sensors using the numerical solution of the Haverkamp (NSH) equation. The compact infiltrometer, in conjunction with the smartphone camera, is an accurate, accessible, portable and easy-to-use field-based device for soil hydraulic characterisation. This research was supported by the MINECO project ASBIO (PGC2018-094332-B-100) and the European Union\u2019s Horizon 2020 research and innovation program under grant agreement No [H2020-MSCA-RISE-777803]. Peer reviewed", "keywords": ["Automated single-ring infiltrometer", "Compact design", "0207 environmental engineering", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "02 engineering and technology", "Soil hydraulic properties", "Infiltration rate measurements", "NSH", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.jhydrol.2021.126551"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hydrology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhydrol.2021.126551", "name": "item", "description": "10.1016/j.jhydrol.2021.126551", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhydrol.2021.126551"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-01T00:00:00Z"}}, {"id": "10.1071/sr13043", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:16:49Z", "type": "Journal Article", "created": "2013-12-20", "title": "Impact Of Carbon Farming Practices On Soil Carbon In Northern New South Wales", "description": "<p>This study sought to quantify the influence of \uffe2\uff80\uff98carbon farming\uffe2\uff80\uff99 practices on soil carbon stocks, in comparison with conventional grazing and cropping, in northern New South Wales. The study had two components: assessment of impacts of organic amendments on soil carbon and biological indicators in croplands on Vertosols of the Liverpool Plains; and assessment of the impact of grazing management on soil carbon in Chromosols of the Northern Tablelands. The organic amendment sites identified for the survey had been treated with manures, composts, or microbial treatments, while the conventional management sites had received only chemical fertilisers. The rotational grazing sites had been managed so that grazing was restricted to short periods of several days, followed by long rest periods (generally several months) governed by pasture growth. These were compared with sites that were grazed continuously. No differences in total soil carbon stock, or soil carbon fractions, were observed between sites treated with organic amendments and those treated with chemical fertiliser. There was some evidence of increased soil carbon stock under rotational compared with continuous grazing, but the difference was not statistically significant. Similarly, double-stranded DNA (dsDNA) stocks were not significantly different in either of the management contrasts, but tended to show higher values in organic treatments and rotational grazing. The enzymatic activities of \uffce\uffb2-glucosidase and leucine-aminopeptidase were significantly higher in rotational than continuous grazing but statistically similar for the cropping site treatments. Relative abundance and community structure, measured on a subset of the cropping sites, showed a higher bacteria\uffe2\uff80\uff89:\uffe2\uff80\uff89fungi ratio and provided evidence that microbial process rates were significantly higher in chemically fertilised sites than organic amendment sites, suggesting enhanced mineralisation of organic matter under conventional management. The higher enzyme activity and indication of greater efficiency of microbial populations on carbon farming sites suggests a greater potential to build soil carbon under these practices. Further research is required to investigate whether the indicative trends observed reflect real effects of management.</p>", "keywords": ["2. Zero hunger", "Land Capability and Soil Degradation", "550", "XXXXXX - Unknown", "0401 agriculture", " forestry", " and fisheries", "Carbon Sequestration Science", "04 agricultural and veterinary sciences", "15. Life on land", "Land capability and soil productivity"]}, "links": [{"href": "https://doi.org/10.1071/sr13043"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1071/sr13043", "name": "item", "description": "10.1071/sr13043", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1071/sr13043"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-01-01T00:00:00Z"}}, {"id": "10.1111/gcb.12819", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:16Z", "type": "Journal Article", "created": "2014-12-05", "title": "Soil Warming And Co2 Enrichment Induce Biomass Shifts In Alpine Tree Line Vegetation", "description": "Abstract<p>Responses of alpine tree line ecosystems to increasing atmospheric CO2 concentrations and global warming are poorly understood. We used an experiment at the Swiss tree line to investigate changes in vegetation biomass after 9\uffc2\uffa0years of free air CO2 enrichment (+200\uffc2\uffa0ppm; 2001\uffe2\uff80\uff932009) and 6\uffc2\uffa0years of soil warming (+4\uffc2\uffa0\uffc2\uffb0C; 2007\uffe2\uff80\uff932012). The study contained two key tree line species, Larix decidua and Pinus uncinata, both approximately 40\uffc2\uffa0years old, growing in heath vegetation dominated by dwarf shrubs. In 2012, we harvested and measured biomass of all trees (including root systems), above\uffe2\uff80\uff90ground understorey vegetation and fine roots. Overall, soil warming had clearer effects on plant biomass than CO2 enrichment, and there were no interactive effects between treatments. Total plant biomass increased in warmed plots containing Pinus but not in those with Larix. This response was driven by changes in tree mass (+50%), which contributed an average of 84% (5.7\uffc2\uffa0kg\uffc2\uffa0m\uffe2\uff88\uff922) of total plant mass. Pinus coarse root mass was especially enhanced by warming (+100%), yielding an increased root mass fraction. Elevated CO2 led to an increased relative growth rate of Larix stem basal area but no change in the final biomass of either tree species. Total understorey above\uffe2\uff80\uff90ground mass was not altered by soil warming or elevated CO2. However, Vaccinium myrtillus mass increased with both treatments, graminoid mass declined with warming, and forb and nonvascular plant (moss and lichen) mass decreased with both treatments. Fine roots showed a substantial reduction under soil warming (\uffe2\uff88\uff9240% for all roots &lt;2\uffc2\uffa0mm in diameter at 0\uffe2\uff80\uff9320\uffc2\uffa0cm soil depth) but no change with CO2 enrichment. Our findings suggest that enhanced overall productivity and shifts in biomass allocation will occur at the tree line, particularly with global warming. However, individual species and functional groups will respond differently to these environmental changes, with consequences for ecosystem structure and functioning.</p>", "keywords": ["0106 biological sciences", "2. Zero hunger", "Models", " Statistical", "Temperature", "Larix", "Carbon Dioxide", "15. Life on land", "Pinus", "Global Warming", "01 natural sciences", "Soil", "Species Specificity", "13. Climate action", "Biomass", "Tundra", "Switzerland"]}, "links": [{"href": "https://doi.org/10.1111/gcb.12819"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.12819", "name": "item", "description": "10.1111/gcb.12819", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.12819"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-01-30T00:00:00Z"}}, {"id": "10.1111/j.1365-2486.2009.02121.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:23Z", "type": "Journal Article", "created": "2009-12-22", "title": "Functional Changes In The Control Of Carbon Fluxes After 3 Years Of Increased Drought In A Mediterranean Evergreen Forest?", "description": "Abstract<p>Our objective was to test how a long\uffe2\uff80\uff90term increased water limitation affects structural and functional properties of a Mediterranean ecosystem, and how these changes modify the response of the main carbon fluxes to climatic controls. In 2003, a 27% throughfall exclusion experiment was installed in a Quercus ilex L. forest in France. Gross primary production (GPP), ecosystem respiration (RECO) and net ecosystem exchange (NEE) were estimated in a control and a dry treatment. Decreasing throughfall decreased GPP by 14% and had a smaller effect on RECO (\uffe2\uff88\uff9212%), especially soil respiration RS (\uffe2\uff88\uff9211%). Interannual variability of GPP (29%) was higher than for RECO (12%). Error propagation was used to estimates uncertainties in the NEE fluxes, which ranged from 3% to 10% in the control treatment but up to 167% for NEE in the dry treatment because more steps and data types were involved in the scaling. After 3 years of throughfall exclusion, we found no acclimation of RS to climatic drivers. Functional properties of the response of RS to soil water, temperature and rain pulse remained similar in the control and the dry treatments. A diurnal clockwise hysteresis in RS was probably controlled by canopy photosynthesis with a 3\uffe2\uff80\uff83h lag. The proportion of diurnal variation of respiration due to photosynthesis was similar in all treatments (4\uffe2\uff80\uff935%). Because of the characteristic of rain in Mediterranean climates, a continuous decrease of water input in these environments have an effect on topsoil water and consequently on RS only during short periods when rainfall is characterized by infrequent and small events that does not allow the topsoil to reach field capacity and does not allow to dry completely. However, in the longer term, we expect a stronger decrease in RS in the dry treatment driven by the decrease in GPP.</p>", "keywords": ["0106 biological sciences", "550", "15. Life on land", "gross primary production", "soil respiration", "01 natural sciences", "630", "6. Clean water", "Quercus ilex", "throughfall exclusion", "13. Climate action", "rain pulse", "eddy-covariance", "Q(10)", "error propagation", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2009.02121.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2486.2009.02121.x", "name": "item", "description": "10.1111/j.1365-2486.2009.02121.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2009.02121.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-08-01T00:00:00Z"}}, {"id": "10.15454/SVDTOU", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:53Z", "type": "Dataset", "title": "Statistiques spatio-temporelles sur les propri\u00e9t\u00e9s agronomiques des sols agricoles en France issues de la Base de Donn\u00e9es d'Analyses de Terre (BDAT)", "description": "In France, farmers commission about 250,000 soil-testing analyses per year to assist them managing soil fertility. The number and diversity of origin of the samples make these analyses an interesting and original information source regarding cultivated topsoil variability. Moreover, these analyses relate to several parameters strongly influenced by human activity (macronutrient contents, pH...), for which existing cartographic information is not very relevant. Compiling the results of these analyses into a database makes it possible to re-use these data within both a national and temporal framework. A database compilation relating to data collected over the period 1990-2014 has been recently achieved. So far, commercial soil-testing laboratories approved by the Ministry of Agriculture have provided analytical results from more than 3,600,000 samples. After the initial quality control stage, analytical results from more than 1,900,000 samples were available in the database. The anonymity of the landholders seeking soil analyses is perfectly preserved, as the only identifying information stored is the location of the nearest administrative city to the sample site. We present in this dataset a set of statistical parameters of the spatial distributions for several agronomic soil properties. These statistical parameters are calculated for 4 different nested spatial entities (administrative areas: e.g. regions, departments, counties and agricultural areas) and for 5 time periods (1990-1994, 1995-1999, 2000-2004, 2005-2009, 2010-2014). Two kinds of agronomic soil properties are available: the first one correspond to the quantitative variables like the organic carbon content, and the second one corresponds to the qualitative variables like the texture class. For each spatial unit and temporal period, we calculated the following statistics sets: the first set is calculated for the quantitative variables and corresponds to the number of samples, the mean, the standard deviation and, the 2-,4-,10-quantiles; the second set is calculated for the qualitative variables and corresponds to the number of samples, the value of the dominant class, the number of samples of the dominant class, the second dominant class, the number of samples of the second dominant class.", "keywords": ["2. Zero hunger", "Earth and Environmental Science", "Soils and soil sciences", "Earth and Environmental Sciences", "Soil Sciences", "soil texture", "15. Life on land", "soil analysis", "Environmental Research", "Natural Sciences", "Geosciences"], "contacts": [{"organization": "Saby, Nicolas P.A., Lemercier, Blandine, Arrouays, Dominique, Walter, Christian, Gouny, Laetitia, Swidersky, Chlo\u00e9, Toutain, Beno\u00eet, Bispo, Antonio,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15454/SVDTOU"}, {"rel": "self", "type": "application/geo+json", "title": "10.15454/SVDTOU", "name": "item", "description": "10.15454/SVDTOU", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15454/SVDTOU"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.1590/s0100-06832009000100016", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:57Z", "type": "Journal Article", "created": "2009-03-11", "title": "Atributos F\u00edsicos, Qu\u00edmicos E Biol\u00f3gicos De Solo De Cerrado Sob Diferentes Sistemas De Uso E Manejo", "description": "<p>\uffc3\uff80 medida que o conhecimento do sistema plantio direto se amplia, verifica-se que o uso de indicadores qu\uffc3\uffadmicos isolados n\uffc3\uffa3o permite melhor caracteriza\uffc3\uffa7\uffc3\uffa3o dos solos, sendo necess\uffc3\uffa1rio utilizar um conjunto de indicadores da qualidade do solo com a entrada de outros atributos, entre eles os f\uffc3\uffadsicos e os biol\uffc3\uffb3gicos. Objetivou-se avaliar os efeitos de sistemas de manejo e uso do solo nos atributos f\uffc3\uffadsicos, qu\uffc3\uffadmicos e biol\uffc3\uffb3gicos de um Latossolo Vermelho distr\uffc3\uffb3fico e um Neossolo Quartzar\uffc3\uffaanico \uffc3\uffb3rtico sob Cerrado, no entorno do Parque Nacional das Emas. Os aspectos avaliados no Latossolo foram: Cerrado nativo, pastagem, milheto em preparo convencional, nabo forrageiro em plantio direto e sorgo em plantio direto. No Neossolo: Cerrado nativo, pastagem nativa, integra\uffc3\uffa7\uffc3\uffa3o agricultura-pecu\uffc3\uffa1ria, pastagem cultivada, plantio direto com soja no ver\uffc3\uffa3o e plantio direto com milho no ver\uffc3\uffa3o. As amostras de solo foram coletadas na profundidade de 0 a 10 cm. O delineamento experimental foi o inteiramente casualizado, com cinco parcelas de 150 m\uffc2\uffb2, sendo coletadas 10 subamostras aleat\uffc3\uffb3rias. As an\uffc3\uffa1lises qu\uffc3\uffadmicas, f\uffc3\uffadsicas e biol\uffc3\uffb3gicas foram realizadas no Laborat\uffc3\uffb3rio de Solos da UFG/CJ. Os manejos promoveram altera\uffc3\uffa7\uffc3\uffb5es na densidade do solo, volume total de poros, macroporos e resist\uffc3\uffaancia do solo \uffc3\uffa0 penetra\uffc3\uffa7\uffc3\uffa3o no Neossolo e no Latossolo, excetuando-se neste o volume total de poros. Houve pequena varia\uffc3\uffa7\uffc3\uffa3o nos atributos qu\uffc3\uffadmicos nos dois solos, com o Cerrado apresentando maior acidez potencial e menor teor de c\uffc3\uffa1tions troc\uffc3\uffa1veis e P. Os atributos biol\uffc3\uffb3gicos do solo foram alterados pelos sistemas de manejo, sendo mais prejudicados em sistemas com maior revolvimento do solo. A an\uffc3\uffa1lise can\uffc3\uffb4nica dos dados demonstrou que os atributos f\uffc3\uffadsicos foram os de menor import\uffc3\uffa2ncia por apresentar maior coeficiente de pondera\uffc3\uffa7\uffc3\uffa3o nas vari\uffc3\uffa1veis can\uffc3\uffb4nicas. Os atributos do solo, isoladamente, pouco contribu\uffc3\uffadram para a avalia\uffc3\uffa7\uffc3\uffa3o da qualidade do solo: no entanto, quando se usou a an\uffc3\uffa1lise multivariada, subsidiaram a constata\uffc3\uffa7\uffc3\uffa3o dos manejos do solo mais sustent\uffc3\uffa1veis.</p>", "keywords": ["C fra\u00e7\u00e3o leve", "multivariate analysis", "an\u00e1lise multivariada", "plantio direto", "light carbon fraction", "0401 agriculture", " forestry", " and fisheries", "soil quality", "04 agricultural and veterinary sciences"]}, "links": [{"href": "https://doi.org/10.1590/s0100-06832009000100016"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Revista%20Brasileira%20de%20Ci%C3%AAncia%20do%20Solo", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1590/s0100-06832009000100016", "name": "item", "description": "10.1590/s0100-06832009000100016", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1590/s0100-06832009000100016"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-02-01T00:00:00Z"}}, {"id": "10.2139/ssrn.4556085", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:24Z", "type": "Journal Article", "created": "2023-08-29", "title": "A Laser Diffractometry Technique for Determining the Soil Water Stable Aggregates Index", "description": "Open AccessPeer reviewed", "keywords": ["Water stable aggregates index", "Laser diffractometry", "Wet sieving", "Soil aggregates"]}, "links": [{"href": "https://doi.org/10.2139/ssrn.4556085"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2139/ssrn.4556085", "name": "item", "description": "10.2139/ssrn.4556085", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2139/ssrn.4556085"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.23986/afsci.148486", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:29Z", "type": "Journal Article", "created": "2025-05-26", "title": "Defining critical SOC/clay thresholds for soil health in boreal croplands using satellite-based NDVI proxies for productivity and resilience", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The European Union\u2019s soil strategy underscores the necessity for establishing feasible criteria to assess the soil health condition. In this study, we developed a method to define a critical threshold value for SOC/clay ratio on the basis of crop productivity and resilience. The study integrated data from national soil monitoring (NSM) of Finnish cropland soils (n=505) with satellite-based normalized difference vegetation index (NDVI) obtained from the EcoDataCube (EDC) portal. The study area was confined to the boreal environmental zone to ensure consistent pedo-climatic conditions. The results show that the interannual variation in crop productivity increases rapidly below SOC/clay ratio of 0.09 (95% confidence intervals ranging from 0.07 to 0.16), whereas the corresponding threshold for mean productivity was 0.13 (0.09\u20130.16). The observed threshold values were found applicable for both cereals and temporary ley. The SOC/clay ratio of 1:13 (=0.08), regarded as a criterion for healthy soil in the current Soil Monitoring Law proposal, based on studies by Johannes et al. (2017) and Prout et al. (2021), is lower than the mean thresholds estimated in this study but aligns close to the lower bound of the 95% confidence intervals. In this research, Finnish agricultural land served as the case study area, but the method is easily applicable to various pedo-climatic regions and potentially to different land use types.</p></article>", "keywords": ["S", "Soil Monitoring Law", " SOC/clay ratio", " cropland", " NDVI", " satellite data", " national soil monitoring", "Agriculture (General)", "Agriculture", "S1-972"], "contacts": [{"organization": "Heikkinen, Jaakko, Keskinen, Riikka, Ylivainio, Kari,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.23986/afsci.148486"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Food%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.23986/afsci.148486", "name": "item", "description": "10.23986/afsci.148486", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.23986/afsci.148486"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-05-26T00:00:00Z"}}, {"id": "10261/359343", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:11Z", "type": "Dataset", "title": "Plant affinity to extreme soils and foliar sulphur mediate species-specific responses to sheep grazing in gypsum systems [Dataset V2]", "description": "Open AccessPeer reviewed", "keywords": ["Semiarid systems", "Gypsophiles", "Elemental composition", "Gypsum soils", "Herbivory", "Functional traits"], "contacts": [{"organization": "Cera, Andreu, Montserrat-Mart\u00ed, Gabriel, Luzuriaga, Arantzazu L., Pueyo, Yolanda, Palacio, Sara,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10261/359343"}, {"rel": "self", "type": "application/geo+json", "title": "10261/359343", "name": "item", "description": "10261/359343", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/359343"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.3389/fmicb.2016.01446", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:36Z", "type": "Journal Article", "created": "2016-09-14", "description": "Soil management is fundamental to all agricultural systems and fertilization practices have contributed substantially to the impressive increases in food production. Despite the pivotal role of soil microorganisms in agro-ecosystems, we still have a limited understanding of the complex response of the soil microbiota to organic and mineral fertilization in the very long-term. Here, we report the effects of different fertilization regimes (mineral, organic and combined mineral and organic fertilization), carried out for more than a century, on the structure and activity of the soil microbiome. Organic matter content, nutrient concentrations, and microbial biomass carbon were significantly increased by mineral, and even more strongly by organic fertilization. Pyrosequencing revealed significant differences between the structures of bacterial and fungal soil communities associated to each fertilization regime. Organic fertilization increased bacterial diversity, and stimulated microbial groups (Firmicutes, Proteobacteria, and Zygomycota) that are known to prefer nutrient-rich environments, and that are involved in the degradation of complex organic compounds. In contrast, soils not receiving manure harbored distinct microbial communities enriched in oligotrophic organisms adapted to nutrient-limited environments, as Acidobacteria. The fertilization regime also affected the relative abundances of plant beneficial and detrimental microbial taxa, which may influence productivity and stability of the agroecosystem. As expected, the activity of microbial exoenzymes involved in carbon, nitrogen, and phosphorous mineralization were enhanced by both types of fertilization. However, in contrast to comparable studies, the highest chitinase and phosphatase activities were observed in the solely mineral fertilized soil. Interestingly, these two enzymes showed also a particular high biomass-specific activities and a strong negative relation with soil pH. As many soil parameters are known to change slowly, the particularity of unchanged fertilization treatments since 1902 allows a profound assessment of linkages between management and abiotic as well as biotic soil parameters. Our study revealed that pH and TOC were the majors, while nitrogen and phosphorous pools were minors, drivers for structure and activity of the soil microbial community. Due to the long-term treatments studied, our findings likely represent permanent and stable, rather than transient, responses of soil microbial communities to fertilization.", "keywords": ["Soil nutrients", "0301 basic medicine", "2. Zero hunger", "0303 health sciences", "long-term fertilization", "microbial biomass", "15. Life on land", "microbial activity", "Microbiology", "QR1-502", "03 medical and health sciences", "13. Climate action", "soil microbial communities", "soil nutrients", "454 pyrosequencing"]}, "links": [{"href": "https://doi.org/10.3389/fmicb.2016.01446"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fmicb.2016.01446", "name": "item", "description": "10.3389/fmicb.2016.01446", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fmicb.2016.01446"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-09-14T00:00:00Z"}}, {"id": "10.3390/proceedings2019030057", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:50Z", "type": "Journal Article", "created": "2020-05-20", "title": "Soil Structural Shifts Caused by Land Management Practices", "description": "Long-term agricultural practices have been shown to affect soil hydro-physical properties in multiple ways. They affect the stability and distribution of soil aggregates leading to changes in water retention, bulk density, hydraulic conductivity, and porosity. Aggregate stability is an indicator of the resilience of aggregates to external forces. Unstable aggregates can change rapidly under different land management practices and meteorological conditions. \u039cacro-aggregates (>250 \u03bcm) are formed more rapidly and are often more sensitive to management changes. Here, four different long-term experiments, run by the SoilCare Horizon 2020 Project partners, were sampled and analyzed, in order to evaluate the impact of different agricultural management practices in the water stability of soil aggregates and the fractions distribution. Different experiments selected, include control-conventional treatment and different treatments, which are considered soil improving. The treatments are about soil cultivation (conventional ploughing-control, zero tillage, minimum tillage, strip tillage, shallow tillage) and organic input (mineral fertilization-control, residue incorporation, farmyard manure) and are selected in areas with different climatic and soil conditions. Initial results indicate that treatments with less soil disturbance present more water stable aggregates (WSA) >250 \u03bcm and higher mean weight diameters (MWD), as well as the same trend following the treatments with increased organic input. According to Tukey\u2019s Honest Significance test (<i>p</i> < 0.05), management practices are shown to have a significant impact on the WSA and MWD in most cases, but not all similar treatments in the different areas present the same results. The large macro-aggregates (>2 mm) seem to be greatly sensitive to soil cultivation, whereas the results for the small macro-aggregates (250 \u03bcm\u20132 mm) are controversial among the different tillage experiments. The different organic inputs seems to affect more the small macro-aggregates than the larger. The initial results indicate that the shifts in the soil structure cannot only be justified by the different management practices. The interrelationships and potential links with other soil properties like texture, bulk density, particulate organic matter and climate will be taken into account in further steps in order to understand the mechanisms behind the aggregation shifts.", "keywords": ["long-term experiments", "2. Zero hunger", "13. Climate action", "soil cultivation", "A", "aggregates", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "soil structure", "SoilCare", "General Works", "6. Clean water"], "contacts": [{"organization": "Ioanna Panagea, Jan Diels, Guido Wyseure,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.3390/proceedings2019030057"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/TERRAenVISION%202019", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/proceedings2019030057", "name": "item", "description": "10.3390/proceedings2019030057", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/proceedings2019030057"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-19T00:00:00Z"}}, {"id": "10.3390/w12082160", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:55Z", "type": "Journal Article", "created": "2020-08-03", "title": "Soil Moisture Estimation Using Citizen Observatory Data, Microwave Satellite Imagery, and Environmental Covariates", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Soil moisture (SM) is a key variable in the climate system and a key parameter in earth surface processes. This study aimed to test the citizen observatory (CO) data to develop a method to estimate surface SM distribution using Sentinel-1B C-band Synthetic Aperture Radar (SAR) and Landsat 8 data; acquired between January 2019 and June 2019. An agricultural region of Tard in western Hungary was chosen as the study area. In situ soil moisture measurements in the uppermost 10 cm were carried out in 36 test fields simultaneously with SAR data acquisition. The effects of environmental covariates and the backscattering coefficient on SM were analyzed to perform SM estimation procedures. Three approaches were developed and compared for a continuous four-month period, using multiple regression analysis, regression-kriging and cokriging with the digital elevation model (DEM), and Sentinel-1B C-band and Landsat 8 images. CO data were evaluated over the landscape by expert knowledge and found to be representative of the major SM distribution processes but also presenting some indifferent short-range variability that was difficult to explain at this scale. The proposed models were evaluated using statistical metrics: The coefficient of determination (R2) and root mean square error (RMSE). Multiple linear regression provides more realistic spatial patterns over the landscape, even in a data-poor environment. Regression kriging was found to be a potential tool to refine the results, while ordinary cokriging was found to be less effective. The obtained results showed that CO data complemented with Sentinel-1B SAR, Landsat 8, and terrain data has the potential to estimate and map soil moisture content.</p></article>", "keywords": ["13. Climate action", "citizen science", "digital soil mapping", "Sentinel-1", "0401 agriculture", " forestry", " and fisheries", "synthetic aperture radar (SAR)", " soil moisture", "04 agricultural and veterinary sciences", "15. Life on land"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/12/8/2160/pdf"}, {"href": "https://doi.org/10.3390/w12082160"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/w12082160", "name": "item", "description": "10.3390/w12082160", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w12082160"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-30T00:00:00Z"}}, {"id": "10.5281/zenodo.10959077", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:34Z", "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.12515622", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:36Z", "type": "Report", "title": "NATI00NS Krajowe wydarzenie anga\u017cuj\u0105ce dotycz\u0105ce misji glebowej UE \u2013 Polska 2024", "description": "Unia Europejska uruchomi\u0142a misj\u0119 \u201eSoil Deal for Europe\u201d, kt\u00f3rej celem jest zapewnienie utworzenia 100 \u017cywych laboratori\u00f3w (LL- Living Labs) i latarni morskich (LH \u2013 Lighthouses) w Europie, prowadz\u0105cych do regeneracji i ochrony zdrowia gleby do 2030 roku.\u00a0Projekt NATI00NS, finansowany z programu Horyzont Europa, organizuje krajowe wydarzenia w ca\u0142ej Europie w celu promowania misji UE \u201eA Soil Deal for Europe\u201d poprzez zapewnienie dost\u0119pu do odpowiednich narz\u0119dzi i informacji oraz stymulowanie dyskusji na temat konfiguracji \u017bywych Laboratori\u00f3w w celu zaadresowania r\u00f3\u017cnych wyzwa\u0144 w zakresie gospodarowania glebami na poziomie lokalnym. Ostatecznym celem jest wsparcie jednostek krajowych w procesie sk\u0142adania wniosk\u00f3w\u00a0w konkursach Misji Gleba Horyzontu Europa, w tym w konkursach dotycz\u0105cych \u201e\u017bywych laboratori\u00f3w\u201d.Instytut Uprawy Nawo\u017cenia i Gleboznawstwa \u2014 Pa\u0144stwowy Instytut Badawczy w Pu\u0142awach w ramach projektu NATI00NS organizuje Krajowe Wydarzenie Anga\u017cuj\u0105ce w Lublinie, kt\u00f3re odb\u0119dzie si\u0119 7 czerwca 2024 r. w godz. 11:00-14:00 w Lubelskim Centrum Konferencyjnym w Lublinie z mo\u017cliwo\u015bci\u0105 uczestnictwa r\u00f3wnie\u017c online.Wydarzenie to jest otwarte dla wszystkich zainteresowanych stron, w tym: naukowc\u00f3w, rolnik\u00f3w, le\u015bnik\u00f3w, zarz\u0105dc\u00f3w teren\u00f3w miejskich, przedstawicieli stowarzysze\u0144, w\u0142a\u015bciciele grunt\u00f3w, planist\u00f3w przestrzenni, architekt\u00f3w krajobrazu, spo\u0142eczno\u015bci lokalnych, administracji, edukator\u00f3w, sektora przemys\u0142owego i konsultingu, organizacje pozarz\u0105dowyh oraz wszystkich zainteresowanych, kt\u00f3rzy chc\u0105 dowiedzie\u0107 si\u0119 wi\u0119cej o mo\u017cliwo\u015bciach, jakie daj\u0105 Misja Gleba, koncepcja \u017bywych Laboratori\u00f3wi projekt NATI00NS.W trakcie spotkania istnieje dla uczestnik\u00f3w spotkania mo\u017cliwo\u015b\u0107 kr\u00f3tkiej autoprezentacji (2-3 min.), jako potencjalnego partnera w projekcie lub inicjatora/uczestnika LL.", "keywords": ["Soil sciences"], "contacts": [{"organization": "Siebielec, Grzegorz, Wawer, Rafa\u0142, Kami\u0144ski, Jan, W\u00f3jcik, Ma\u0142gorzata, Podlaska, Bo\u017cena, ten Damme, Loraine, Cavallo, Dolinda, Ylla, Mar,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.12515622"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.12515622", "name": "item", "description": "10.5281/zenodo.12515622", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.12515622"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-15T00:00:00Z"}}, {"id": "10.5281/zenodo.13952097", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:43Z", "type": "Dataset", "created": "2024-01-01", "title": "SERENA EJPSoil Soil erosion control in Tuscany (Italy)", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national, and European scales.  One of the\u00a0objective of SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The present data was prepared according to the methodology of the SERENA Soil erosion and soil erosion control cookbook.\u00a0 Soil loss was used as an indicator for soil erosion (ST). The map of soil mass not eroded was based on the RUSLE model. Soil erosion control was calculated as the difference between potential and actual soil erosion (SES, ecosystem service of soil erosion protection, i.e. soil eroded mass retained by vegetation, Mg/ha/y). For Italy, the cookbook was applied in the Tuscany region. \u00a0     To create the soil loss map we used:\u00a0       for R-factor, not freely available database of meteorological parameters spatialized at 250 m (minimum and maximum daily air temperature; cumulate daily precipitation) over Tuscany region (period 1990\u20132022, Lamma Consortium)\u00a0 and a local linear equation between R and mean annual precipitation (P);   for C -factor, Regional Land use map 1:10.000 (2018, freely available at:\u00a0https://www502.regione.toscana.it/geoscopio/usocoperturasuolo.html) and ESDAC method (https://doi.org/10.1016/j.landusepol.2015.05.021) ; \u00a0  for K-factor, sand, silt, clay, and O.C. (%) maps (built from 4.000 soil profiles, following FAO\u2019s methodology in GSP-GSOC map, Lamma Consortium), and Torri et al. (1997) function;   for LS-factor, DEM 10 m of Tuscany, (freely available at\u00a0https://www502.regione.toscana.it/geoscopio/cartoteca.html99) and Desmet & Govers (1996) SAGA tool (applied at 10 m and upscaled);   for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor of\u00a0 0.5\u00a0 was considered, based on expert evaluation)   for P-factor, not freely available database 1:10.00 of terraced areas (Lamma Consortium, 2020) (for terraced areas a multiplication factor\u00a0of\u00a0 0.5\u00a0 was considered, based on expert evaluation)\u00a0      Maps was delivered in the GeoTIFF format in the resolution of 100m. \u00a0     Delivered data will be validated by stakeholders from Italy (scientist) in October, 2024.", "keywords": ["Italy", "Tuscany", "SERENA project", "Soil-based ecosystem service", "RUSLE", "soil erosion control", "Grant n. 862695", "EJP-Soil"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13952097"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13952097", "name": "item", "description": "10.5281/zenodo.13952097", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13952097"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-18T00:00:00Z"}}, {"id": "10.5281/zenodo.14044657", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:46Z", "type": "Dataset", "title": "SERENA EJPSOIL BE Flanders soil sealing cookbook", "description": "Open AccessThe internal EJP SOIL project SERENA contributed to the evaluation of soil multifunctionality aiming at providing assessment tools for land planning and soil policies at different scales. By co-working with relevant stakeholders, the project provided co-developed indicators and associated cookbooks to assess and map them, to report both on soil degradation, soil-based ecosystem services and their bundles, under actual conditions and for climate and land-use changes, at the regional, national and European scales.The data was prepared according to the Level 2 methodology of the SERENA soil sealing cookbook. For Belgium, the application was carried out at the regional scale for the Flanders region. \u00a0The automatically generated yearly soil sealing maps (1 m resolution GeoTIFF rasters)\u00a0combine \u201cknown\u201d sealing from administrative databases (buildings and transport infrastructure) with modelled sealing based on artificial intelligence. Administrative databases do not (adequately) cover parking lots, private driveways and garden terraces, which are a substantial part of the sealed area in Flanders. Hence, a machine learning model was built for deriving this remaining sealing from aerial imagery. For this purpose, an assessor manually labeled the sealed parts on a subset of the images. Based on this training set, a convolutional neural network model was used to produce a sealing probability map, which was converted to a binary modelled sealing map. Finally, a continuity correction was applied to ensure a temporally consistent result across the yearly maps. \u00a0The objective of the SERENA project was to develop methods to calculate and map soil-based ecosystem services and soil threats. The selected indicator was the degree of soil sealing. By evaluating this degree at two moments in time, the change in soil sealing can be determined. \u00a0\u00a0The following data were used:\u00a0         Large-scale Reference Database (Grootschalig Referentiebestand or Basiskaart), the digital topographic reference map for Flanders (vector)\u00a0           Medium-scale annual winter aerial images of Flanders (15 or 25 cm raster resolution)    This dataset is originally hosted at Geopunt (www.geopunt.be). For the most up-to-date version of the dataset, please access the data from the Geopunt repository.", "keywords": ["soil sealing", "remote sensing", "BELGIUM (FLANDERS)", "aerial images", "SERENA", "EJP-Soil", "photointerpretation"], "contacts": [{"organization": "Cockx, Kasper, Oorts, Katrien,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14044657"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14044657", "name": "item", "description": "10.5281/zenodo.14044657", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14044657"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-10-30T00:00:00Z"}}, {"id": "10.5281/zenodo.14036322", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:46Z", "type": "Dataset", "created": "2024-11-04", "title": "Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting", "description": "1. Introduction  This dataset comes from a research project entitled 'Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network ' supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n\u00b010/0034-0). The project was carried out between 2010 and 2014 under the coordination of Jos\u00e9 Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Concei\u00e7\u00e3o and Guapor\u00e9 river basins.  2. Material and Methods  The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Concei\u00e7\u00e3o catchment has a drainage area of 804 km2 (28\u00b027\u203222\u2033S and 53\u00b058\u203224\u2033 W). According to K\u00f6ppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6\u20139 %) on top and hillside slopes and higher steepness (10\u201314%) near the drainage channels. Farming based on the production of soybeans (Glycine max) in summer and wheat (Triticumspp.), oats (Avena strigosa), and ryegrass (Lolium multiflorum) in winter. The Guapor\u00e9 catchment has a drainage area of 1,980 km2 (28\u00b054\u203241\u2033S and 51\u00b057\u203210\u2033W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (Nicotiana tabacum) and maize (Zea mays) crops, Eucalyptus (Eucalyptus spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didon\u00e9 et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0\u20130.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment\u2019s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven\u2010dried at 50 \u00b0C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 \u03bcm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K2Cr2O7 + H2SO4) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave\u2010assisted digestion with concentrated HCl and HNO3 (ratio 3:1) for 9.5 min at 182 \u00b0C (Tiecher, 2015; Tiecher et al. 2017, 2018).  \u00a0 3. Final remarks  \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didon\u00e9 et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).  \u00a04. References  \u00a0Didon\u00e9, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287\u20131297.  Didon\u00e9, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011  Didon\u00e9, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0  le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662  Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800  Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS.  Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guapor\u00e9 River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004  Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didon\u00e9, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Concei\u00e7\u00e3o River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917.  Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28\u201345.", "keywords": ["No-tiilage", "Fingerprinting approach", "Soil erosion", "Sediment yield", "Sediment quality", "Brazil"], "contacts": [{"organization": "Tiecher, Tales, Minella, Jean P G, Reichert, Jos\u00e9 Miguel, dos Santos, Danilo R, Bender, Marcos, Didon\u00e9, Elizeu, Barros, Cl\u00e1udia A., Dalbianco, Leandro, Ramon, Rafael, Capone, Viviane,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14036322"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14036322", "name": "item", "description": "10.5281/zenodo.14036322", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14036322"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-04T00:00:00Z"}}, {"id": "10.5281/zenodo.14252610", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:50Z", "type": "Dataset", "title": "Data from: Turfgrass pedogenesis under low maintenance: an experimental analysis with Festuca rubra subspecies at different fertilization levels", "description": "unspecifiedThatchMatThickeness.csv  (Frc = Festuca rubra commutata, Frt = Festuca rubra trichophylla, Frr = Festuca rubra rubra)    spec = subspecies  var = variety  rep = replicate number  Nfert = N fertilization (kg N ha-1)  thatch1 = thatch thickness at 18-5-2018 (cm)  thatch2 = thatch thickness at 26-10-2018 (cm)  thatch3 = thatch thickness at 17-5-2019 (cm)  thatch4 =\u00a0 thatch thickness at 29-10-2019 (cm)  thatch5 = thatch thickness at 10-6-2020 (cm)  thatch6 = thatch tcicknesss at 16-6-2021 (cm)  mat1 = mat thickness at 18-5-2018 (cm)  mat2 = mat thickness at 26-10-2018 (cm)  mat3 = mat thickness at 17-5-2019 (cm)  mat4 =\u00a0 mat thickness at 29-10-2019 (cm)  mat5 = mat thickness at 10-6-2020 (cm)  mat6 = mat tcicknesss at 16-6-2021 (cm)", "keywords": ["Festuca rubra", "festuca rubra", "fertilization", "carbon", "soil layers", "pedogenesis", "turfgrass", "microbes", "Turfgrass", "nitrogen", "Carbon", "organic matter"], "contacts": [{"organization": "Evers, Maurice, De Caluwe, Hannie, Visser, Eric J.W., De Kroon, Hans,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14252610"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14252610", "name": "item", "description": "10.5281/zenodo.14252610", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14252610"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14812135", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:55Z", "type": "Other", "title": "Deliverable D2.3 - Supplementary material : 3D simulations of PFAS transport in the soil-groundwater continuum", "description": "This model is part of the toolbox built within the framework of the PROMISCES project (Deliverable D2.3).    A model train combining 1D-Hydrus, MODFLOW and MTD3MS software has been developed/updated to simulate water flow and PFAS transport in the soil groundwater continuum. The model train allowed to couple one or several vertical 1D models (1D-Hydrus) to simulate water flow and reactive solute transport in unsaturated zone with a 3D groundwater flow and transport models (MODFLOW and MT3DMS). The basic framework for numerical coupling is the information exchange between software.\u00a0     The model train is started by first running a stand-alone executable coupling 1D-Hydrus and MODFLOW (HYDMOD_OWHM.exe). It calculates water flow in the unsaturated and saturated zones. 1D-Hydrus model provides water fluxes from the bottom of the unsaturated zone as input values for recharge at the top of the MODFLOW model at appropriate time steps. In turn, water table depth is updated in the 1D-Hydrus model based on the outputs of the simulated hydraulic head using MODFLOW model. The coupling scheme developped by Beegum et al. (2018) has been used. The same input files as those required for MODFLOW and 1D-Hydrus are needed. \u00a0     Then, solute transport is calculated by exchanging information between the 1D-Hydrus-MODFLOW model train and MT3DMS (mt3dms5.3.exe). The 1D-Hydrus-MODFLOW model train simulated water flow and PFAS concentration at the bottom of the unsaturated zone. These outputs are then provided as input soluted fluxes at the top of the the MT3DMS model at each time step. A dedicated tool called Process 1D-Hydrus-MODFLOW to MT3DMS (postproces_hydrus_modflow2mt3dms.exe) has been developed to process time series of water fluxes and PFAS concentrations calculated by the 1D-Hydrus-MODFLOW model train at the bottom of the unsaturated zone to input files for MT3DMS model to simulate PFAS transport in the saturated zone. The source code, written in Fortran, an executable, documentation and an example are available at: https://github.com/JohanValstar/Process-1D-HYDRUS-MODFLOW-to-MT3DMS or https://zenodo.org/records/14929813. \u00a0     The three executables needed to run the model train are provided in the present repository. The associated input files describe a theoretical example simulating long-term non-reactive tracer migration in an unsaturated-saturated continuum considering transient boundary conditions. The features of the model including geometry of the simulated domain, the meshing, the boundary conditions and their change with time, the values of the input parameters describing the hydrodynamic and transport properties in the unsaturated and saturated zones are identical to the ones mentionned in the modelling work explained in the Chapter 3.1. of the Deliverable D2.4 of the PROMISCES project.", "keywords": ["Soil", "PFAS", "Groundwater", "Model"], "contacts": [{"organization": "Devau, Nicolas, Valstar, Johan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14812135"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14812135", "name": "item", "description": "10.5281/zenodo.14812135", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14812135"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-05T00:00:00Z"}}, {"id": "10.5281/zenodo.14875898", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:56Z", "type": "Other", "title": "Les mod\u00e8les de COS doivent \u00eatre valid\u00e9s par des s\u00e9ries temporelles ind\u00e9pendantes pour permettre une pr\u00e9diction fiable", "description": "Les efforts visant \u00e0 maintenir les jeux de donn\u00e9es sont imp\u00e9ratifs pour obtenir des projections et des pr\u00e9visions pr\u00e9cises en mati\u00e8re de COS.", "keywords": ["[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study"], "contacts": [{"organization": "Le No\u00eb, Julia, Manzoni, Stefano, Abramoff, Rose, B\u00f6lscher, Tobias, Bruni, Elisa, Cardinael, R\u00e9mi, Ciais, Philippe, Chenu, Claire, Clivot, Hugues, Derrien, Delphine, Ferchaud, Fabien, Garnier, Patricia, Goll, Daniel, Lashermes, Gwena\u00eblle, Martin, Manuel, Rasse, Daniel, Rees, Fr\u00e9d\u00e9ric, Sainte-Marie, Julien, Salmon, \u00c9lodie, Schiedung, Marcus, Schimel, Josh, Wieder, William, Abiven, Samuel, Barr\u00e9, Pierre, C\u00e9cillon, Lauric, Guenet, Bertrand, Delahaie, Amicie,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14875898"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14875898", "name": "item", "description": "10.5281/zenodo.14875898", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14875898"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14936177", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:58Z", "type": "Dataset", "title": "Precision Liming Soil Datasets (LimeSoDa) Zenodo Repository", "description": "Overview  Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1) soil organic matter (SOM) or soil organic carbon (SOC), (2) pH, and (3) clay content, while the features for modeling are dataset-specific. The primary goal of `LimeSoDa` is to enable more reliable benchmarking of machine learning methods in digital soil mapping and pedometrics. All the associated materials and data from LimeSoDa can be downloaded in this data repository. However, for a more in-depth analysis, we refer to the published paper 'LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping' by Schmidinger et al. (2025). You may also use our R\u00a0and Python package likewise called LimeSoDa.  \u00a0  Citation  Upon usage of datasets from LimeSoDa, please cite our associated paper:  Schmidinger, J., Vogel, S., Barkov, V., Pham, A.-D., Gebbers, R., Tavakoli, H., Correa, J., Tavares, T.R., Filippi, P., Jones, E. J., Lukas, V., Boenecke, E., Ruehlmann, J., Schroeter, I., Kramer, E., Paetzold, S., Kodaira, M., Wadoux, A.M.J.-C., Bragazza, L., Metzger, K., Huang, J., Valente, D.S.M., Safanelli, J.L., Bottega, E.L., Dalmolin, R.S.D., Farkas, C., Steiger, A., Horst, T. Z., Ramirez-Lopez, L., Scholten, T., Stumpf, F., Rosso, P., Costa, M.M., Zandonadi, R.S., Wetterlind, J. & Atzmueller, M. (2025). LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping.", "keywords": ["Environmental sciences", "Soil Organic Carbon", "Pedometrics", "pH", "Soil Organic Matter", "Clay", "Remote sensing", "Digital Soil Mapping"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14936177"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14936177", "name": "item", "description": "10.5281/zenodo.14936177", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14936177"}, {"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": "10.5281/zenodo.15096788", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:00Z", "type": "Dataset", "title": "HWSD2_Climate_and_Socioeconomic_agriculturalsoil_dataset_mainland_portugal", "description": "The study uses the Harmonized World Soil Database (HWSD v2.0) developed by FAO and IIASA for biophysical models and agroecological queries. This database consolidates information from various sources, including the European Soil Database, the 1:1 million soil map of China, and national soil maps from Afghanistan, Ghana, and T\u00fcrkiye. It has a spatial resolution of around 1 km and is revised in 2013 and 2023. HWSD v2.0 includes detailed information on soil mapping units, general soil unit information, and specific physical and chemical soil unit characteristics across seven depth layers.  The database fields cover a wide range of attributes, such as soil texture, bulk density, organic carbon content, pH, and cation exchange capacity. The harmonization process ensures that data from different sources is standardized and integrated, providing a consistent and reliable dataset for various applications. However, the HWSD v2.0 has some limitations, such as combining soil inventories gathered at different times, scales, and precision, which may affect its reliability for national studies. It is recommended to use national-level harmonized soil databases for more accurate results in specific regions.  For Portugal's mainland, the data presented in the HWSD v2.0 dataset is sourced from the European Soil Data Centre (ESDAC), which contains various metrics of chemical and physical soil properties. Out of the 2882 Portuguese parishes, only 22 are left out, representing 0.76% percent of the total number of parishes.  The study uses several datasets to analyze land use and occupation in Portugal. The Land Use and Occupation Map (COS2007v3.0) is a detailed thematic map of land use and occupation for mainland Portugal, developed by the Directorate-General for Territory (DGT). The data is organized hierarchically and includes 83 classes of land use and occupation. The CHELSA database, maintained by the Swiss Federal Institute for Forest, Snow, and Landscape Research (WSL), provides bioclimatic indexes for precipitation and average temperature over various temporal intervals and variables.  The National Institute of Statistics (INE) provides data on agricultural machinery distribution across different geographical locations. The dataset covers the total number of agricultural machines, as well as specific categories such as wheeled and tracked tractors, motor cultivators, power hoes, motor mowers, and combine harvesters. The dataset also examines the distribution of farms with access to irrigation based on geographical location.  The burned land data from 1975 to 2023 provides a comprehensive overview of fire occurrences and their impact over time. This data is crucial for understanding long-term patterns, assessing the effectiveness of fire prevention measures, and informing future land management and policy decisions.  Lastly, the population density dataset from the 2021 Census and the 2011 Census provides a decennial comparison of total population density across different geographical regions. These data are essential for understanding the evolution of land use and occupation in Portugal and their implications for environmental and agricultural consequences.", "keywords": ["Soil", "Total organic carbon", "Land use", "Soil use", "Atmospheric precipitation", "Soil type", "Organic carbon", "Land surface temperature"], "contacts": [{"organization": "Almeida Santos, R. G. F.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15096788"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15096788", "name": "item", "description": "10.5281/zenodo.15096788", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15096788"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-03-27T00:00:00Z"}}, {"id": "10.5281/zenodo.15772619", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:10Z", "type": "Dataset", "title": "Dataset to: Foundation for an Austrian NIR Soil Spectral Library for Soil Health Assessments", "description": "Dataset description  This is the corresponding dataset to the publication 'Foundation for an Austrian NIR Soil Spectral Library for Soil Health Assessments' by Fohrafellner et al. (2025). In this publication, we created the first Near-Infrared (NIR) Austrian Soil Spectral Library (ASSL, 680 \u2013 2500 nm) using 2,129 legacy samples from all environmental zones of Austria. Additionally, we utilized partial least squares regression modeling to evaluate the dataset's current effectiveness for soil health assessments. The dataset contains three tabs, 'Document meta data', 'Legend' and 'Dataset'. Tab 'Document meta data' gives information on the authors, the data collection time frame, terms of use, etc. In 'Legend', each column of the 'Dataset' is described. The 'Dataset' contains information on the legacy soil samples including:\u00a0    meta data (e.g. sample number, sampling year, zip code, environmental zone, land use),   soil properties (soil organic carbon [SOC], SOC to clay ratio, total carbon, labile carbon, CaCO3, total nitrogen, plant available phosphorus, pH measured in CaCl2 and acetate, cation exchange capacity, texture [sand, silt, clay content], and clay content measured by density in suspension), and  measured NIR soil spectra, also for the standards.   Project description  This Austrian Soil Spectral Library was built within the ProbeField project (November 2021 \u2013 January 2025), which was part of the European Joint Program for SOIL \u2018Towards climate-smart sustainable management of agricultural soils\u2019 (EJP SOIL) funded by the European Union Horizon 2020 research and innovation programme (Grant Agreement N\u00b0 862695). The project aimed to create a protocol detailing procedures and methodologies for accurately estimating fertility-related properties in agricultural soils in the field. Additionally, the potential for extending this data to two- and three-dimensional mapping using co-variates was demonstrated. ProbeField further collected field spectra that closely match laboratory spectra, enabling the prediction of soil properties using models calibrated with soil spectral libraries.  References  Fohrafellner, J., Lippl, M., Bajraktarevic, A., Baumgarten, A., Spiegel, H., K\u00f6rner, R. and Sand\u00e9n, T.: Foundation for an Austrian NIR Soil Spectral Library for Soil Health Assessments, 2025, in review.", "keywords": ["EJP SOIL", "ProbeField", "Spectroscopy", " Near-Infrared", "data"], "contacts": [{"organization": "Fohrafellner, Julia", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15772619"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15772619", "name": "item", "description": "10.5281/zenodo.15772619", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15772619"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-07T00:00:00Z"}}, {"id": "10.5281/zenodo.15797289", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:10Z", "type": "Dataset", "title": "Database of soil characteristics under specific pesticide management", "description": "Database of soil characteristics under specific pesticide management  Contributors: Mark\u00e9ta Mayerov\u00e1 and Veronika \u0158ez\u00e1\u010dov\u00e1  Affiliation: Czech Agrifood Research Center, Drnovsk\u00e1 507/73, CZ-160 00 Prague 6, Czech Republic  Database of soil characteristics will contribute to the realization of the project\u00b4s goal to identify appropriate and inappropriate pesticides from the point of the view of their impact on the non-target organisms and soil characteristics.  Field I.  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The experiment took place at the site of the experiment that had been running there since 2013 and included 5 different herbicide treatments in 4 replications (Mayerov\u00e1 et al. 2018)  The new trial area was split into 20 randomised plots with 2 different herbicide treatments in 8 replications and control without herbicides in 4 replications. Herbicide treatments differed in the mode of action (Table 1)  Table 1. Summary of the herbicides and active ingredients used in the trial. Classification Group by Herbicide Resistance Action Committee (HRAC).       herbicide     dose    formulation    active ingredient    content of a.i.    HRAC group    target weeds      Agritox 50 SL    1.5 l/ha    EC    MCPA    500 g/l    O    dicot      Glean 75 PX    15 g/ha    WG    chlorsulfuron    750 g/l    B    dicot + annual grasses       \u00a0  The area of each plot was 100 m2 and the 10 by 10 m plots were separated from field boundaries and from each other by 2 m on all sides to eliminate interaction between plots. Herbicides were applied post emergency in spring (April 26, 2024) from the tillering crop stage to the beginning of stem elongation (BBCH 21\u201331) by the Agrio-Napa 12 sprayer. Winter wheat was grown in the experimental field in 2024. At the beginning of March, it was mineral fertilized with LAD (ammonium nitrate with dolomite - NH4NO3\u00a0+\u00a0CaMg (CO3)2; 27 % N) at a dose 100 kg/ha.   Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer in each replication before herbicide application (April 24, 2024), 14 days after herbicide application (May 9, 2024) and 7 weeks after herbicide application (June 14, 2024). \u00a0A total of 20 soil samples were collected at each sampling. The soil samples were subsequently dried and sieved through a 2 mm sieve, thus simultaneously homogenised. The following soil properties were determined: pH (H2O), electric conductivity, available P and K, concentration NH4 and NO3, soil organic carbon, and total organic nitrogen content. Available P and K were assessed according to the Mehlich III method (Mehlich, 1984) on an Agilant ICP-OES 5110 VDV instrument. NO3 and NH4 were determined using calcium chloride solution as extractant according to ISO 14255:1998 on automated chemistry analyser SKALAR. Soil organic carbon and soil organic matter content were determined by sulfochromic oxidation according to ISO 14235:1998.   Field II  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The total area of the experiment is about 11 ha including the protective area around the entire experiment. The experimental area is divided into two halves, 120m wide and 300m long.\u00a0 One half was treated on June 17, 2024, with insecticide Decis forte (active ingredient deltamethrin) at a dose 62.5ml/ha, the other half was without insecticide treatment. Both areas are further divided into other halves. One half was treated on May 15, 2024, with herbicide Agritox (active ingredient MCPA) at a dose 1.5l/ha, the other was treated with hoeing only. We thus obtained 4 strips 60m wide with following treatment combinations: (A) herbicide + insecticide; (B) hoeing + insecticide; (C) hoeing; (D) herbicide. Spring wheat was grown in the experimental field in 2024. It was fertilized with mineral nitrogen at a dose of 150 kg N/ha before sowing and with 39 kg N/ha (DAM 390 - ammonium nitrate with urea) in the tillering phenophase.  In the middle of each strip (i.e. treatment), 8 sampling sites were marked in a row, 20 m apart from each other. Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer at each sampling site 14 days after herbicide application and 14 days after insecticide application. A total of 32 soil samples were collected at each sampling. Further sample processing was the same as for Field I.  The database will be gradually supplemented in the following years.   Funding: Development for this work is funded primarily by the Technology Agency of the Czech Republic, project SS07020100: \u201cThe impact of plant protection products on non-target biodiversity: soil microorganisms, invertebrates and wild plants\u201d, and the Ministry of Agriculture of the Czech Republic, institutional support MZE-RO0425.  The database was approved on September 2, 2025, by the Ministry of Agriculture of the Czech Republic.  References:  Mayerov\u00e1 M., Mikulka J., Soukup J. (2018): Effects of selective herbicide treatment on weed community in cereal crop rotation. Plant Soil Environ., 64: 413\u2013420. https://doi.org/10.17221/289/2018-PSE  \u00a0Mehlich A. (1984): Mehlich 3 Soil Test Extractant. A Modification of the Mehlich 2 Extractant. Commun. Soil Sci. Plant Anal. 15, 1409-1416. http://dx.doi.org/10.1080/00103628409367568.", "keywords": ["field trial", " herbicides", " insecticides", " soil properties"], "contacts": [{"organization": "Mayerov\u00e1, Mark\u00e9ta, \u0158ez\u00e1\u010dov\u00e1, Veronika,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15797289"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15797289", "name": "item", "description": "10.5281/zenodo.15797289", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15797289"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-03T00:00:00Z"}}, {"id": "10.5281/zenodo.17397628", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:13Z", "type": "Dataset", "title": "Database of soil characteristics under specific pesticide management", "description": "Database of soil characteristics under specific pesticide management  Contributors: Mark\u00e9ta Mayerov\u00e1 and Veronika \u0158ez\u00e1\u010dov\u00e1  Affiliation: Czech Agrifood Research Center, Drnovsk\u00e1 507/73, CZ-160 00 Prague 6, Czech Republic  Database of soil characteristics will contribute to the realization of the project\u00b4s goal to identify appropriate and inappropriate pesticides from the point of the view of their impact on the non-target organisms and soil characteristics.  Field I.  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The experiment took place at the site of the experiment that had been running there since 2013 and included 5 different herbicide treatments in 4 replications (Mayerov\u00e1 et al. 2018)  The new trial area was split into 20 randomised plots with 2 different herbicide treatments in 8 replications and control without herbicides in 4 replications. Herbicide treatments differed in the mode of action (Table 1)  Table 1. Summary of the herbicides and active ingredients used in the trial. Classification Group by Herbicide Resistance Action Committee (HRAC).       herbicide     dose    formulation    active ingredient    content of a.i.    HRAC group    target weeds      Agritox 50 SL    1.5 l/ha    EC    MCPA    500 g/l    O    dicot      Glean 75 PX    15 g/ha    WG    chlorsulfuron    750 g/l    B    dicot + annual grasses       \u00a0  The area of each plot was 100 m2 and the 10 by 10 m plots were separated from field boundaries and from each other by 2 m on all sides to eliminate interaction between plots. Herbicides were applied post emergency in spring (April 26, 2024) from the tillering crop stage to the beginning of stem elongation (BBCH 21\u201331) by the Agrio-Napa 12 sprayer. Winter wheat was grown in the experimental field in 2024. At the beginning of March, it was mineral fertilized with LAD (ammonium nitrate with dolomite - NH4NO3\u00a0+\u00a0CaMg (CO3)2; 27 % N) at a dose 100 kg/ha.   Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer in each replication before herbicide application (April 24, 2024), 14 days after herbicide application (May 9, 2024) and 7 weeks after herbicide application (June 14, 2024). \u00a0A total of 20 soil samples were collected at each sampling. The soil samples were subsequently dried and sieved through a 2 mm sieve, thus simultaneously homogenised. The following soil properties were determined: pH (H2O), electric conductivity, available P and K, concentration NH4 and NO3, soil organic carbon, and total organic nitrogen content. Available P and K were assessed according to the Mehlich III method (Mehlich, 1984) on an Agilant ICP-OES 5110 VDV instrument. NO3 and NH4 were determined using calcium chloride solution as extractant according to ISO 14255:1998 on automated chemistry analyser SKALAR. Soil organic carbon and soil organic matter content were determined by sulfochromic oxidation according to ISO 14235:1998.   Field II  The field experiment was established in 2024 in the experimental area of the Czech Agrifood Research Center in Prague \u2013 Ruzyn\u011b (previously Crop Research Institute). The total area of the experiment is about 11 ha including the protective area around the entire experiment. The experimental area is divided into two halves, 120m wide and 300m long.\u00a0 One half was treated on June 17, 2024, with insecticide Decis forte (active ingredient deltamethrin) at a dose 62.5ml/ha, the other half was without insecticide treatment. Both areas are further divided into other halves. One half was treated on May 15, 2024, with herbicide Agritox (active ingredient MCPA) at a dose 1.5l/ha, the other was treated with hoeing only. We thus obtained 4 strips 60m wide with following treatment combinations: (A) herbicide + insecticide; (B) hoeing + insecticide; (C) hoeing; (D) herbicide. Spring wheat was grown in the experimental field in 2024. It was fertilized with mineral nitrogen at a dose of 150 kg N/ha before sowing and with 39 kg N/ha (DAM 390 - ammonium nitrate with urea) in the tillering phenophase.  In the middle of each strip (i.e. treatment), 8 sampling sites were marked in a row, 20 m apart from each other. Mixed disturbed soil samples for microbiological and physicochemical analyses were taken from the 0-15cm upper soil layer at each sampling site 14 days after herbicide application and 14 days after insecticide application. A total of 32 soil samples were collected at each sampling. Further sample processing was the same as for Field I.  The database will be gradually supplemented in the following years.   Funding: Development for this work is funded primarily by the Technology Agency of the Czech Republic, project SS07020100: \u201cThe impact of plant protection products on non-target biodiversity: soil microorganisms, invertebrates and wild plants\u201d, and the Ministry of Agriculture of the Czech Republic, institutional support MZE-RO0425.  The database was approved on September 2, 2025, by the Ministry of Agriculture of the Czech Republic.  \u00a0Update for 2025  Both experiments were conducted in the same mode as in 2024 with a few changes listed below.  Field I.  Spring barley was cultivated here. Herbicides were applied 19.5.2025. Tribenuron methyl was used instead of chlorsulfuron at a dose 18.75 g/ha, however both herbicides to the group with the same mechanism of action (HRAC group 2B; sulfonylureas). \u00a0  Unlike in 2025, mixed disturbed soil samples were taken only once, 14 days after herbicide application (June 3, 2025).   Field II.  Winter triticale was cultivated here. Herbicide was applied 24.2.2025 and insecticide was applied 3.6. 2025. Soil samples were taken 14 days after herbicide application (May 6, 2025) and 14 days after insecticide application (June 17, 2025).  References:  Mayerov\u00e1 M., Mikulka J., Soukup J. (2018): Effects of selective herbicide treatment on weed community in cereal crop rotation. Plant Soil Environ., 64: 413\u2013420. https://doi.org/10.17221/289/2018-PSE  \u00a0Mehlich A. (1984): Mehlich 3 Soil Test Extractant. A Modification of the Mehlich 2 Extractant. Commun. Soil Sci. Plant Anal. 15, 1409-1416. http://dx.doi.org/10.1080/00103628409367568.", "keywords": ["field trial", " herbicides", " insecticides", " soil properties"], "contacts": [{"organization": "Mayerov\u00e1, Mark\u00e9ta, \u0158ez\u00e1\u010dov\u00e1, Veronika,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17397628"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17397628", "name": "item", "description": "10.5281/zenodo.17397628", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17397628"}, {"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": "10.5281/zenodo.17941270", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:15Z", "type": "Dataset", "title": "Dataset to: Austrian NIR Soil Spectral Library for Soil Health Assessments", "description": "Dataset description  This is the corresponding dataset to the publication 'Austrian NIR Soil Spectral Library for Soil Health Assessments' by Fohrafellner et al. (2025). In this publication, we created the first Austrian Near-Infrared (NIR) Soil Spectral Library (680 \u2013 2500 nm) using 2,129 legacy samples from all environmental zones of Austria. Additionally, we utilized partial least squares regression modeling to evaluate the dataset's current effectiveness for soil health assessments. The dataset contains three tabs, 'Document meta data', 'Legend' and 'Dataset'. Tab 'Document meta data' gives information on the authors, the data collection time frame, terms of use, etc. In 'Legend', each column of the 'Dataset' is described. The 'Dataset' contains information on the legacy soil samples including:\u00a0    meta data (e.g. sample number, sampling year, zip code, environmental zone, land use),   soil properties (soil organic carbon [SOC], SOC to clay ratio, total carbon, labile carbon, CaCO3, total nitrogen, plant available phosphorus, pH measured in CaCl2 and acetate, cation exchange capacity, texture [sand, silt, clay content], and clay content measured by density in suspension), and  measured NIR soil spectra, also for the standards.   Project description  This Austrian NIR Soil Spectral Library was built within the ProbeField project (November 2021 \u2013 January 2025), which was part of the European Joint Program for SOIL 'Towards climate-smart sustainable management of agricultural soils' (EJP SOIL) funded by the European Union Horizon 2020 research and innovation programme (Grant Agreement N\u00b0 862695). The project aimed to create a protocol detailing procedures and methodologies for accurately estimating fertility-related properties in agricultural soils in the field. Additionally, the potential for extending this data to two- and three-dimensional mapping using co-variates was demonstrated. ProbeField further collected field spectra that closely match laboratory spectra, enabling the prediction of soil properties using models calibrated with soil spectral libraries.  References  Fohrafellner, J., Lippl, M., Bajraktarevic, A., Baumgarten, A., Spiegel, H., K\u00f6rner, R. and Sand\u00e9n, T.: Austrian NIR Soil Spectral Library for Soil Health Assessments, 2025, in review.", "keywords": ["EJP SOIL", "ProbeField", "spectroscopy", "data", "near-infrared"], "contacts": [{"organization": "Fohrafellner, Julia, Lippl, Maximilian, Bajraktarevic, Armin, Baumgarten, Andreas, Spiegel, Heide, K\u00f6rner, Robert, Sand\u00e9n, Taru,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17941270"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17941270", "name": "item", "description": "10.5281/zenodo.17941270", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17941270"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-21T00:00:00Z"}}, {"id": "10.5281/zenodo.3247592", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:16Z", "type": "Dataset", "title": "Daily cycles in soil carbon flux", "description": "<strong>Description: </strong> Measurements of 24 hour cycles in soil CO2 flux taken from soil collars in the Belian Carbon plot at Maliau. Measurements were taken from 12 subplots over four days at 5-hourly intervals, ensuring good coverage of the complete 24 hour cycle. Air and soil temperatures, soil moisture content and CO2 flux were taken from each plot at each visit. 9 subplots only have a single total soil respiration collar, but 3 subplots also have soil flux partitioning treatments to separate contributions to total respiration from soil organic matter, mycorrhizae and roots.<br> <br> This data was collected by the 2019 cohort of the Tropical Forest Ecology MRes at Imperial College London. <strong>Project: </strong>This dataset was collected as part of the following SAFE research project: <strong>MRes Tropical Forest Ecology Field Course</strong> <strong>XML metadata: </strong>GEMINI compliant metadata for this dataset is available here <strong>Files: </strong>This dataset consists of 2 files: Carbon_corrected_slopes.xlsx, raw_egm.zip <strong>Carbon_corrected_slopes.xlsx</strong> This file contains dataset metadata and 2 data tables: <strong>24 hour observations of CO2 flux patterns</strong> (described in worksheet Carbon_flux_data) Description: Estimated CO2 flux values, soil moisture and air and soil temperatures from Carbon subplots Number of fields: 14 Number of data rows: 296 Fields: <strong>record_no</strong>: EGM 'Plot' value - record number on EGM machine for this collar (Field type: ID) <strong>plot</strong>: Carbon subplot number (Field type: Location) <strong>date</strong>: Calendar date that measurements taken (Field type: Date) <strong>time</strong>: Time that measurements taken (Field type: Time) <strong>soil_wmc</strong>: Soil water moisture content (Field type: Numeric) <strong>soil_temp</strong>: Soil temperature (Field type: Numeric) <strong>air_temp</strong>: Air temperature (Field type: Numeric) <strong>treatment</strong>: Exclusion treatments for partitioning soil respiration components (Field type: Categorical) <strong>field_flux</strong>: CO2 flux reported in the field by EGM (Field type: Numeric) <strong>Source</strong>: EGM dat file of source data used for corrected fluxes where available (Field type: File) <strong>corrected_flux</strong>: Corrected flux measurements using by eye exclusion of raw flux data (Field type: Numeric) <strong>n_points</strong>: Number of points in EGM record (Field type: Numeric) <strong>n_used</strong>: Number of points used for corrected slope estimation (Field type: Numeric) <strong>flux</strong>: Final flux values, using corrected values where available (Field type: Numeric) <strong>EGM raw data</strong> (described in worksheet EGM_raw_data) Description: Duplicates key information from raw EGM files and indicates points excluded in calculation of corrected flux values Number of fields: 7 Number of data rows: 7114 Fields: <strong>Plot</strong>: EGM recorder 'plot' code, actually just the record sequence number. (Field type: ID) <strong>RecNo</strong>: EGM record number - time points of gas measurement at a single plot (Field type: ID) <strong>Datetime</strong>: Time of gas concentration measurement (Field type: Datetime) <strong>CO2.Ref</strong>: Measured CO2 (Field type: Numeric) <strong>Input.E</strong>: EGM internal variable used in slope estimation (Field type: Numeric) <strong>Source</strong>: Original EGM dat file containing the flux data (Field type: File) <strong>ignore</strong>: Indicates where points from raw data excluded from corrected slope calculations (Field type: Categorical) <strong>raw_egm.zip</strong> Description: Zipfile of raw EGM dat files <strong>Date range: </strong>2019-02-18 to 2019-02-21 <strong>Latitudinal extent: </strong>4.7467 to 4.7480 <strong>Longitudinal extent: </strong>116.9693 to 116.9704", "keywords": ["2. Zero hunger", "550", "soil CO2 flux", "24 hour cycle", "partitioning", "15. Life on land", "6. Clean water", "630"], "contacts": [{"organization": "Orme, C David L, Riutta, Terhi, Fraser, Adam, Mackintosh, Emma, Vollans, Maisie, Graves, Kristina, Roxby, Gabrielle, Baynham, Georgina, Noble, Ciar, Adzhar, Rahayu, MacLean, Catherine, Martin, Stephanie, McKinlay, Amelia, Poznansky, Frederica, Prairie, Aaron, Brasington, Ella, Wiederkehr, Fabienne,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3247592"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3247592", "name": "item", "description": "10.5281/zenodo.3247592", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3247592"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-06-17T00:00:00Z"}}, {"id": "10.5281/zenodo.3591992", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:18Z", "type": "Dataset", "title": "Organic matter content (om) soil maps of the Upper Colorado River Basin", "description": "UPDATE: WE FOUND A RENDERING ERROR IN MANY AREAS OF THE 5 CM MAP. WE HAVE RECREATED THE MAP AND INCLUDED IN A NEW VERSION OF THE REPOSITORY. Repository includes maps of organic matter content (% wt) as defined by United States soil survey program. These data are preliminary or provisional and are subject to revision. They are being provided to meet the need for timely best science. The data have not received final approval by the U.S. Geological Survey (USGS) and are provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the data. This data should be used in combination with a soil depth or depth to restriction layer map (both layers that will be released soon as part of this project) to eliminate areas mapped at deeper depths than the soil actually goes. This is a limitation of this data which will hopefully be updated in future updates. The creation and interpretation of this data is documented in the following article. Please note this article has not been reviewed yet and this citation will be updated as the peer review process proceeds. Nauman, T. W., Duniway, M. C., In Preparation. Predictive reconstruction of soil survey property maps for field scale adaptive land management. Soil Science Society of America Journal. File Name Details: ACCURACY!! Please see manuscript and Github repository (https://github.com/naumi421/SoilReconProps) for full details on accuracy. We do provide cross validation (CV) accuracy plots in this repository for both the overall sample (_CV_plots.tif). These plots compare CV predictions with observed values relative to a 1:1 line. Values plotted near the 1:1 line are more accurate. Note that values are plotted in hex-bin density scatter plots because of the large number of observations (most are &gt;3000). Predictions are also evaluated with the U.S. soil survey laboratory database soil organic carbon (SOC) data. The SOC measurements were coverted to OM matter values using the common 1.724 conversion factor. The converted OM values are compared to predicted OM values using an accuracy plot (OM_SOC_plots.tif). Elements are separated by underscore (_) in the following sequence: property_r_depth_cm_geometry_model_additional_elements.extension Example: om_r_0_cm_2D_QRF_bt.tif Indicates soil organic matter content (om) at 0 cm depth using a 2D model (separate model for each depth) employing a quantile regression forest. This file is the raster prediction map for this model. There may be additional GIS files associated with this file (e.g. pyramids) that have the same file name, but different extensions. The _bt indicates that the map has been back transformed from ln or sqrt transformation used in modeling. The following elements may also exist on the end of filenames indicating other spatial files that characterize a given model's uncertainty (see below). _95PI_h: Indicates the layer is the upper 95% prediction interval value. _95PI_l: Indicates the layer is the lower 95% prediction interval value. _95PI_relwidth: Indicates the layer is the 95% relative prediction interval (RPI). The RPI is a standardization of the prediction interval that indicates that model is constraining uncertainty relative to the original sample. RPI values less than one represent uncertainty is being improved by the model relative to the original sample, and values less than 0.5 indicate low uncertainty in predictions. See paper listed above and also Nauman and Duniway (In revision) for more details on RPI. References Nauman, T. W., and Duniway, M. C., In Revision, Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data: Geoderma", "keywords": ["2. Zero hunger", "13. Climate action", "soil organic matter", "digital soil mapping", "15. Life on land", "6. Clean water", "predictive soil mapping", "soil property mapping"], "contacts": [{"organization": "Nauman, Travis", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.3591992"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.3591992", "name": "item", "description": "10.5281/zenodo.3591992", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.3591992"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-28T00:00:00Z"}}, {"id": "10.5281/zenodo.7307470", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:29Z", "type": "Dataset", "title": "Soil biological, chemical and physical parameters and herbage yield in a field experiment with organic and inorganic fertilizers on peat grassland in the Netherlands", "description": "Open AccessTo evaluate the performance of organic and inorganic fertilizers for regeneration of ecosystem services in peat grasslands with biodiversity goals, we carried out a field experiment in the western peat district in the Netherlands. The fertilizers tested represent the current practice and potential alternatives for regenerative grassland management on drained peat. <strong>Experimental setup</strong> The field experiment (2013 \u2013 2015) was conducted on a permanent grassland on peat soil (Terric Histosol; SOM 56 g 100 g<sup>\u22121</sup> and pH<sub>KCl</sub> of 4.5 in 0-10 cm) at the experimental dairy farm at Zegveld (the Netherlands). In March 2013, a randomized block experiment (six blocks) was laid out with six fertilizer treatments and a control treatment (no fertilizer: \u201cContr\u201d). The fertilizer used were: conventional dairy cattle slurry manure (\u201cSlurry\u201d), mature compost of kitchen and garden waste (\u201cComp\u201d), dairy cattle farmyard manure (\u201cFYM\u201d), solid fraction of the cattle slurry manure (\u201cSFrac\u201d, obtained by pressurized filtration), inorganic N fertilizer (\u201cIF\u201d; calcium ammonium nitrate, 27% N) and a combination of inorganic N fertilizer and sawdust (\u201cIF+SD\u201d). Plot size was 4 \u00d7 10 m; for the Slurry treatment plots were 5.2 \u00d7 10 m. Slurry was applied by slit injection, the other fertilizers were applied by hand. Target application rate was 120 kg total N ha<sup>\u22121</sup> yr<sup>\u22121</sup>, divided in two applications per year (February/March and May). This is relatively low for conventional grasslands but usual for grasslands with biodiversity goals (Kleijn et al., 2004). The amount of C<sub>total</sub> applied in Comp was taken for the rate of sawdust to be applied. All plots were fertilized with 200 kg K<sub>2</sub>O ha<sup>\u22121</sup> yr<sup>\u22121</sup> (applications in March and May) (Commissie Bemesting Grasland en Voedergewassen, 2019). Fertilizer application quantities and organic matter and nutrient inputs are provided in Fertilizer_intput.csv (dataset). The grassland had an history of conventional management with mainly cutting, winter grazing with sheep and a normal fertilization regime with both slurry manure and inorganic fertilizer. The normal cutting and grazing regime was continued in the first two years of the experiment; during 2015, the monitoring year, the plots were not grazed and only cut for herbage measurements. <strong>Measurements</strong> From April to October 2015, soil and aboveground measurements were carried out. Most soil parameters were measured in October. Earthworms and insect larvae are an important food source for meadow birds during the pre-breeding period in spring (Galbraith, 1989) and were therefore sampled in April. Soil moisture and penetration resistance were measured both in April and October. <em>Soil biological parameters</em> Earthworms and insect larvae were sampled in the top soil layer in two soil cubes (20 \u00d7 20 \u00d7 20 cm) per plot. Earthworms were hand-sorted, counted, weighed and fixed in alcohol prior to identification. Both adults and juveniles were identified to species (Sims and Gerard, 1985; St\u00f6p-Bowitz, 1969) and classified into functional groups (Bouch\u00e9, 1977). Crane flies (Tipulidae; leatherjackets) or click beetles (Elateridae; wireworms) larvae were counted. Phospholipid fatty acids (PLFA) were measured in October. PLFA were extracted from 4 g of fresh soil (Paloj\u00e4rvi, 2006), and analyzed by gas chromatography (Hewlett-Packard, USA). PLFA i15:0, a15:0, 15:0, i16:0, 16:1\u03c99, i17:0, a17:0, cy17:0, 18:1\u03c97 and cy19:0 were chosen to represent bacteria and PLFA 18:2\u03c96 was used as a marker of saprotrophic fungi (Hedlund, 2002). The neutral lipid fatty acid (NLFA) 16:1\u03c95 occurs in storage lipids of arbuscular mycorrhizal fungi (AMF) and was used as marker of AMF (Vestberg et al., 2012). PLFA i15:0, a15:0, i16:0, i17:0 and a17:0 were used as a measure of Gram-positive bacteria, and cy17:0 and cy19:0 for Gram-negative bacteria. PLFA 10Me16:0, 10Me17:0 and 10Me18:0 represented actinomycetes. <em>Soil chemical parameters</em> A soil sample from the 0\u221210 cm layer (c. 50 randomly taken soil cores) per experimental plot was collected in October (auger diameter 2.3 cm; Eijkelkamp grass plot sampler, Giesbeek, the Netherlands), was sieved (1 cm mesh size) and homogenized. One sub-sample was taken for analysis of hot water extractable carbon (HWC) according to Ghani et al. (2003) and one for chemical analysis. Prior to analysis of soil acidity (pH<sub>KCl</sub>), soil organic matter (SOM), total carbon (C<sub>total</sub>), total nitrogen (N<sub>total</sub>), total phosphorus (P<sub>total</sub>) and ammonium-lactate extractable P (P<sub>AL</sub>) by Eurofins Agro (Wageningen, the Netherlands), the sub sample was dried at 40\u00b0C. Soil pH<sub>KCl</sub> was measured according to NEN-ISO 10390 2005. SOM was determined by loss-on-ignition (NEN 5754 2005). C<sub>total</sub> was measured by incineration at 1150\u00b0C, and determination of the CO<sub>2</sub> produced by an infrared detector (LECO Corporation, St. Joseph, Mich., USA). For N<sub>total</sub>, evolved gasses after incineration were reduced to N<sub>2</sub> and measured with a thermal-conductivity detector (LECO Corporation, St. Joseph, Mich., USA). P<sub>total</sub> was analysed with Fleishmann acid (Houba et al., 1997). P<sub>AL</sub> is used to assess the P supply capacity of grassland soils (Reijneveld et al., 2014) and was determined according to Egn\u00e9r et al. (1960) (NEN 5793). <em>Soil physical parameters</em> Soil moisture was determined in April and October in a homogenized 0\u221210 cm soil sample after drying at 105\u00b0C for 24 hrs. Moisture content was expressed as percentage of fresh soil weight. Penetration resistance was measured (April and October) with a penetrologger (Eijkelkamp, Giesbeek, the Netherlands; cone of 2.0 cm<sup>2</sup> penetration surface and 60\u00b0 apex angle. Penetration resistance was expressed as an average of 7 penetrations per plot and per soil layer of 0\u221210, 10\u221220, and 20\u221230 cm. Soil structure and rooting density were assessed in October in the 0\u221210 cm and 10\u221225 cm layers. The percentage of crumbs, sub-angular blocky elements and angular blocky elements was estimated by one experienced person as described by Peerlkamp (1959) and Shepherd (2000), Root density was estimated by scoring visible roots (score 1\u201310; 1 for no roots and 10 for above average). Water infiltration rate was measured in October at three spots per experimental plot in 5 of the 6 blocks (35 plots). A PVC pipe (15 cm high, 15 cm diameter) was pushed into the soil to a depth of 10 cm. 500 ml water was poured into each pipe and the infiltration time was recorded. If the infiltration time exceeded 15 min, the remaining water volume was estimated to calculate the infiltration rate (mm min<sup>\u22121</sup>). <em>Grass yield and botanical composition</em> Grass dry matter (DM) and N yield were determined during 2015 with a Haldrup plot harvester (J. Haldrup a/s, L\u00f8gst\u00f8r, Denmark). The four harvest dates were May 15, June 29, August 19 and September 30. Fresh biomass, DM content (70\u00b0C for 24 hrs) and total N content (Kjeldahl) were determined for each harvest. Herbage DM yield (Mg DM ha<sup>\u22121</sup>) and herbage N yield (kg N ha<sup>\u22121</sup>) were calculated. Apparent N recovery (ANR; kg N.kg N<sup>\u22121</sup>) was calculated as (N yield<sub>(fertilized)</sub> \u2013 N yield<sub>(non-fertilized)</sub>)/(N fertilization rate) (Vellinga and Andr\u00e9, 1999). In June 2015, botanical composition was measured by visually estimating the relative soil cover of the sward and the proportion of each species therein (Sikkema, 1997). <strong>Data files</strong> <em><strong>Data_soil_grass.csv</strong></em> <em>Content:</em> Dataset with soil biological (earthworms, microbial PLFA), soil chemical, soil physical parameters, herbage dry matter and N yields, and botanical parameters. <em>Column names and units:</em> plot: Experimental plot number (1-42) treatment: Treatment code (see text) block: Block number (1-6) EW_species_number: Earthworm - number of species EW_totalnumber: Earthworm - total number per m2 EW_epigeic: Earthworm - number of epigeic adults and juveniles per m2 EW_endogeic: Earthworm - number of endogeic adults and juveniles per m2 EW_adults: Earthworm - number of adults per m2 EW_juveniles: Earthworm - number of juveniles per m2 EW_adult_epigeic: Earthworm - number of epigeic adults per m2 EW_adult_endogeic: Earthworm - number of endogeic adults per m2 EW_juven_epigeic: Earthworm - number of epigeic juveniles per m2 EW_juven_endogeic: Earthworm - number of endogeic juveniles per m2 EW_L_rubellus: Earthworm - number of L. rubellus adults and juveniles per m2 EW_A_chlorotica: Earthworm - number of A. chlorotica adults and juveniles per m2 EW_A_caliginosa: Earthworm - number of A. caliginosa adults and juveniles per m2 EW_O_lacteum: Earthworm - number of O. lacteum adults and juveniles per m2 EW_A_rosea: Earthworm - number of A. rosea adults and juveniles per m2 EW_O_cyaenum: Earthworm - number of O. cyaneum adults and juveniles per m2 EW_L_castaneus: Earthworm - number of L. castaneus adults and juveniles per m2 EW_D_rubida: Earthworm - number of D. rubida adults and juveniles per m2 EW_adult_L_rubellus: Earthworm - number of L. rubellus adults per m2 EW_adult_A_chlorotica: Earthworm - number of A. chlorotica adults per m2 EW_adult_A_caliginosa: Earthworm - number of A. caliginosa adults per m2 EW_adult_O_lacteum: Earthworm - number of O. lacteum adults per m2 EW_adult_A_rosea: Earthworm - number of A. rosea adults per m2 EW_adult_O_cyaenum: Earthworm - number of O. cyaneum adults per m2 EW_adult_L_castaneus: Earthworm - number of L. castaneus adults per m2 EW_adult_D_rubida: Earthworm - number of D. rubida adults per m2 EW_juven_L_rubellus: Earthworm - number of L. rubellus juveniles per m2 EW_juven_A_chlorotica: Earthworm - number of A. chlorotica juveniles per m2 EW_juven_A_caliginosa: Earthworm - number of A. caliginosa juveniles per m2 EW_non_determined: Earthworm - number of non determined individuals per m2 EW_total_biomass: Earthworm - total fresh biomass per m2 Leatherjackets: number of leatherjackets per m2 Wireworms: number of wireworms per m2 TOTmicrPLFA: total microbial PLFA in nmol.g-1 dry soil bactPLFA: bacterial PLFA in nmol.g-1 dry soil saprofungPLFA: saprotrophic fungal PLFA in nmol.g-1 dry soil Fung_bactPLAF_ratio: ratio of fungal to bacterial PLFA GramPLUSplfa: gram positive PLFA in nmol.g-1 dry soil GramMINplfa: gram negative PLFA in nmol.g-1 dry soil ratioGram_PLUS_MIN: ratio of gram positive to gram negative PLFA AMFsporNLFA: AMF spores NLFA in nmol.g-1 dry soil ActinomPLFA: Actinomycetes PLFA in nmol.g-1 dry soil ShannonPLFA: PLFA shannon diversity index SOM: soil organic matter in g.100 g-1 dry soil Ctotal: total C in g.100 g-1 dry soil HWC: hot water extractable C in \u03bcg.100 g-1 dry soil Ntotal: total N in g.100 g-1 dry soil Ptotal: total P2O5 in mg.100 g-1 dry soil P_AL: total P-AL in mg.100 g-1 dry soil pH_KCl: pH-KCl CN_ratio: C:N ratio C_SOM: C:SOM ratio Soilmoisture_April: soil moisture content in April in g.100g-1 fresh soil Penetrationresistance_April_cm010: penetration resistance in April in 10-20 cm in Newton Penetrationresistance_April_cm1020: penetration resistance in April in 20-30 cm in Newton Penetrationresistance_April_cm2030: penetration resistance in April in 0-10 cm in Newton Soilmoisture_October: soil moisture content in October in g.100g-1 fresh soil Penetrationresistance_October_cm010: penetration resistance in October in 10-20 cm in Newton Penetrationresistance_October_cm1020: penetration resistance in October in 20-30 cm in Newton Penetrationresistance_October_cm2030: penetration resistance in October in 0-10 cm in Newton crumb_struct_cm010: percentage of crumb elements in 0-10 cm round_struct_cm011: percentage of sub-angular elements in 0-10 cm rootdensity_cm010: score (1-10) of root density in 0-10 cm crumb_struct_cm1025: percentage of crumb elements in 10-25 cm round_struct_cm1025: percentage of sub-angular elements in 10-25 cm sharp_struct_cm1025: percentage of angular elements in 10-25 cm rootdensity_cm1025: score (1-10) of root density in 10-25 cm water_infiltration: water infiltration rate in mm per minute DM_yield_year: total herbage dry matter yield in kg.ha-1 per year DM_yield_H1: herbage dry matter yield of harvest 1 in kg.ha-1 DM_yield_H2: herbage dry matter yield of harvest 2 in kg.ha-1 DM_yield_H3: herbage dry matter yield of harvest 3 in kg.ha-1 DM_yield_H4: herbage dry matter yield of harvest 4 in kg.ha-1 N_yield_year: total herbage N yield in kg.ha-1 per year N_yield_H1: herbage N yield of harvest 1 in kg.ha-1 N_yield_H2: herbage N yield of harvest 2 in kg.ha-1 N_yield_H3: herbage N yield of harvest 3 in kg.ha-1 N_yield_H4: herbage N yield of harvest 4 in kg.ha-1 DMperc_yield_year: herbage dry matter content (per year; weighed average over the 4 harvests) in g.100g-1 fresh weight DMperc_yield_H1: herbage dry matter content of harvest 1 in g.100g-1 fresh weight DMperc_yield_H2: herbage dry matter content of harvest 2 in g.100g-1 fresh weight DMperc_yield_H3: herbage dry matter content of harvest 3 in g.100g-1 fresh weight DMperc_yield_H4: herbage dry matter content of harvest 4 in g.100g-1 fresh weight Ncontent_yield_year: herbage N content (per year; weighed average over the 4 harvests) in g.kg-1 dry matter Ncontent_yield_H1: herbage N content of harvest 1 in g.kg-1 dry matter Ncontent_yield_H2: herbage N content of harvest 2 in g.kg-1 dry matter Ncontent_yield_H3: herbage N content of harvest 3 in g.kg-1 dry matter Ncontent_yield_H4: herbage N content of harvest 4 in g.kg-1 dry matter fresh_yield_H1: herbvage fresh yield of harvest 1 in Mg.ha-1 ANR: apparent N recovery in kg N.kg N-1 productive_grasses: cover percentage of L. perenne and P trivialis monocotyledons: cover percentage of monocotyledons dicotyledons: cover percentage of dicotyledons plant_species: number of plant species monocot_species: number of monocotyledon species dicot_species: number of dicotyledon species Lolium_perenne: plant cover % Poa_trivialis: plant cover % Phleum_pratense: plant cover % Elytrigia_repens: plant cover % Poa_annua: plant cover % Agrostis_stolonifera: plant cover % Holcus_lanatus: plant cover % Alopecurus_pratensis: plant cover % Alopecurus_geniculatus: plant cover % Trifolium_repens: plant cover % Taraxacum_officinale: plant cover % Ranunculus_arvensis: plant cover % Rumex_obtusifolius: plant cover % Rumex_crispus: plant cover % Ranunculus_acris: plant cover % Stellaria_media: plant cover % Cardamine_pratensis: plant cover % Bellis_perennis: plant cover % Rumex_acetosa: plant cover % Ranunculus_sceleratus: plant cover % Polygonum_aviculare: plant cover % Capsella_bursa-pastoris: plant cover % Glechoma_hederacea: plant cover % Geranium_molle: plant cover % <em><strong>Fertilizer_input.csv</strong></em> <em>Content:</em> Application quantities of fertilizers and ash, organic matter, C and mineral inputs, and fertilizer C:N ratio. Total N input is the sum of mineral N (Nmin) and organic N (Norg). Average values per hectare and per year over the years 2013\u22122015. <em>Column names and units:</em> Treatment: Treatment code (see text) Fertilizer_fresh: Applied fertilizer in Mg.ha<sup>-1</sup> per year (fresh weight) Fertilizer_DM: Applied fertilizer in Mg.ha<sup>-1</sup> per year (dry matter weight); for IF+SD this is the sum of 2.72 Mg sawdust + 0.45 Mg N fertilizer Ash: Mineral fraction in kg.ha<sup>-1</sup> per year OM: Organic matter in kg.ha<sup>-1</sup> per year C: Total C in kg.ha<sup>-1</sup> per year Nmin: Mineral N in kg.ha<sup>-1</sup> per year Norg: Organic N in kg.ha<sup>-1</sup> per year P2O5: kg.ha<sup>-1</sup> per year C_N_ratio: C:N ratio", "keywords": ["2. Zero hunger", "herbage production", "manure", "PLFA", "Life Science", "earthworms", "soil quality", "15. Life on land", "regenerative farming", "6. Clean water"], "contacts": [{"organization": "Deru, Joachim, Bloem, Jaap, De Goede, Ron, Brussaard, Lijbert, Van Eekeren, Nick,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7307470"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7307470", "name": "item", "description": "10.5281/zenodo.7307470", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7307470"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.7656722", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:30Z", "type": "Dataset", "title": "Data for: The effect of land-use change on soil C, N, P, and their stoichiometries: A global synthesis", "description": "Open Access<strong><em>Data description</em></strong> 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<sup>-1</sup>) 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 <em><strong>Data collection method</strong></em> 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. <em><strong>Acknowledgements</strong></em> 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": "2026-09-19T16:20:31Z", "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": "2026-09-19T16:20:32Z", "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.8109600", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:34Z", "type": "Dataset", "title": "Data on soil compounds, respiration and incorporation of 13C-labeled substrate", "description": "Open AccessSee Readme.pdf", "keywords": ["2. Zero hunger", "microdialysis", "respiration rates", "compound concentration in soil solution", "PLFA and NLFA", "13C isotopic labeling", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Wiesenbauer, Julia, Kaiser, Christina,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8109600"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8109600", "name": "item", "description": "10.5281/zenodo.8109600", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8109600"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-07-18T00:00:00Z"}}, {"id": "11379/629705", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:22Z", "type": "Journal Article", "created": "2025-07-19", "title": "Role of Biodegradable and Non-Biodegradable Microplastic in Modulating the toxicological Effects of Organic Pollutants in the Soil Organism Folsomia candida", "description": "Abstract                   <p>                     The ecotoxicological effects of microplastics in soil ecosystems are complex, particularly in areas of intensive agriculture and livestock production, where plant protection products and veterinary drugs commonly coexist with plastic residues. In this study, we investigated the impact, under laboratory conditions, of 3 MP types (non-biodegradable low-density polyethylene (LDPE) and biodegradable polybutylene adipate terephthalate-based (PBAT-based) and a starch-based polymer) on the soil-dwelling species                     Folsomia candida                     (Willem, 1902) in soils contaminated with the anthelmintic albendazole and the fungicide pyraclostrobin. These organic pollutants (OPs) are frequently found in areas of intensive agriculture and livestock production.                     F. candida                     individuals were exposed for 28\uffc2\uffa0days to soils contaminated by the OPs at 0.0001 w/w% (1\uffc2\uffa0mg/kg), with and without MPs at 0.01 and 0.1 w/w% concentrations (100 and 1000\uffc2\uffa0mg/kg respectively), under laboratory conditions (21\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff891 C\uffc2\uffb0, 80%\uffe2\uff80\uff89\uffc2\uffb1\uffe2\uff80\uff891 RH). Adults\uffe2\uff80\uff99 survival, egg production, and juveniles\uffe2\uff80\uff99 occurrence were recorded as endpoints. Our findings indicate that microplastics alone did not significantly affect the survival and reproductive outcomes of                     F. candida                     . However, in soils contaminated with albendazole and pyraclostrobin, the presence of biodegradable MPs resulted in significant effects compared to the control and the treatment with only microplastics. Specifically, PBAT-based MPs significantly impacted adult survival, juvenile occurrence, and egg counts, while starch-based MPs primarily affected egg counts. On the contrary, co-exposure to OPs and LDPE MPs did not show significant effects. These results suggest that different MPs influence the bioavailability and toxicity of co-occurring fungicides and veterinary drug in soil ecosystems in different ways, with implications for assessing the ecological risks of biodegradable and non-biodegradable plastics in contaminated soils. The potential of MPs to influence the spatial distribution and bioavailability of organic pollutants for soil mesofauna needs further investigation.                   </p", "keywords": ["Soil ecotoxicology", "Pyraclostrobin", "Microplastics (MPs)", "Organic pollutants (OPs)", "Albendazole", "Biodegradable plastics", "Microplastics (MPs)", " Biodegradable plastics", " Organic pollutants (OPs)", " Albendazole", " Pyraclostrobin", " Soil ecotoxicology", " Folsomia candida", "Folsomia candida"]}, "links": [{"href": "https://iris.unibs.it/bitstream/11379/629705/1/s11270-025-08351-x.pdf"}, {"href": "https://doi.org/11379/629705"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%2C%20Air%2C%20%26amp%3B%20Soil%20Pollution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11379/629705", "name": "item", "description": "11379/629705", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11379/629705"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-07-19T00:00:00Z"}}, {"id": "11585/996230", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:25Z", "type": "Journal Article", "created": "2023-10-10", "title": "Beyond PLFA: Concurrent extraction of neutral and glycolipid fatty acids provides new insights into soil microbial communities", "description": "The analysis of phospholipid fatty acids (PLFAs) is one of the most common methods used to quantify the abundance, and analyse the community structure, of soil microbes. The PLFA extraction method can yield two additional lipid fractions\u2014neutral lipids and glycolipids\u2014which potentially hold additional, valuable information on soil microbial communities. Yet its quantitative sensitivity on complete neutral lipid (NLFA) and glycolipid fatty acid (GLFA) profiles has never been validated. In this study we tested (i) if the high-throughput PLFA method can be expanded to concurrently extract complete NLFA and GLFA profiles, as well as sterols, (ii) whether taxonomic specificities of signature fatty acids are retained across the three lipid fractions in pure culture strains, and (iii) whether NLFAs and GLFAs allow soil-specific fingerprinting to the same extent as PLFA analysis. By adjusting the polarity of chloroform with 2% ethanol for solid phase extraction, pure lipid standards were fully fractionated into neutral lipids, glycolipids, and phospholipids. Sterols eluted in the neutral lipid fraction, and a betaine lipid co-eluted with phospholipids. We found consistent taxonomic specificities of fatty acid markers across the three lipid fractions by analysing pure culture extracts representative of soil microbes. Fatty acid profiles from soil extracts, however, showed stronger differences between PLFAs, NLFAs, and GLFAs than between soil types. This indicates that PLFAs and NLFAs signify different community properties (biomass vs. carbon storage, putatively), and that GLFAs are sensitive markers for community traits which behave differently than PLFAs. Although we consistently found high abundances of characteristic sterols in fungal extracts, the PLFA extraction method only yielded miniscule amounts of ergosterol from soil extracts. We argue that concomitant measurement of fatty acid profiles from all three lipid fractions is a low-effort and potentially information-rich addition to the PLFA method, and discuss its applicability for soil microbial community analyses.", "keywords": ["0301 basic medicine", "2. Zero hunger", "106022 Mikrobiologie", "0303 health sciences", "15. Life on land", "Soil lipids", "03 medical and health sciences", "106026 \u00d6kosystemforschung", "NLFA", "Ergosterol", "Ergosterol; GLFA; NLFA; Phospholipid fatty acids; Soil lipids", "Phospholipid fatty acid", "soil lipids", "Phospholipid fatty acids", "106022 Microbiology", "GLFA", "106026 Ecosystem research"]}, "links": [{"href": "https://doi.org/11585/996230"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Biology%20and%20Biochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11585/996230", "name": "item", "description": "11585/996230", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11585/996230"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-01T00:00:00Z"}}, {"id": "1295b9994deae0387c2be67c1d753988", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:27Z", "type": "Report", "title": "Global maps of soil temperature", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0\u20135 and 5\u201315 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-km2 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 (\u22120.7 \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": ["near-surface temperatures", "bioclimatic variables", "soil temperature", "temperature offset", "global maps", "soil-dwelling organisms", "weather stations", "microclimate", "Climate Science", "Klimatvetenskap"], "contacts": [{"organization": "Lembrechts, Jonas J., van den Hoogen, Johan, Dorrepaal, Ellen, Larson, Keith, Sarneel, Judith M., Walz, Josefine, Nijs, Ivan, Lenoir, Jonathan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/1295b9994deae0387c2be67c1d753988"}, {"rel": "self", "type": "application/geo+json", "title": "1295b9994deae0387c2be67c1d753988", "name": "item", "description": "1295b9994deae0387c2be67c1d753988", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1295b9994deae0387c2be67c1d753988"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "-15d66dac-a389-4330-94c5-31b2ef12f9b6-", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:27:13Z", "type": "Dataset", "language": "is", "title": "Jar\u00f0vegur", "description": "\u00cdslenskur jar\u00f0vegur telst til eldfjallajar\u00f0ar (Andosol) a\u00f0 langmestum hluta, en eldfjallaj\u00f6r\u00f0 er jar\u00f0vegur sem myndast \u00e1 eldvirkum sv\u00e6\u00f0um heimsins. Eldfjallaj\u00f6r\u00f0 hefur afar s\u00e9rst\u00e6\u00f0a eiginleika sem greina hana fr\u00e1 \u00f6\u00f0rum jar\u00f0vegsger\u00f0um. \u00datb\u00fain var einf\u00f6ld flokkun fyrir \u00edslenskan jar\u00f0veg, sem m.a. byggist \u00e1 al\u00fej\u00f3\u00f0legum flokkunarkerfum en einnig \u00e1 vinnu Bj\u00f6rns J\u00f3hannessonar og \u00deorsteins Gu\u00f0mundssonar. Flokkunin gerir greinarmun \u00e1 i) jar\u00f0vegi au\u00f0na (glerj\u00f6r\u00f0 sem skiptist \u00ed melaj\u00f6r\u00f0, malarj\u00f6r\u00f0, sandj\u00f6r\u00f0 og vikurj\u00f6r\u00f0; ii) jar\u00f0vegi gr\u00f3ins lands me\u00f0 sortueiginleika (sortuj\u00f6r\u00f0, sem skiptist \u00ed br\u00fanj\u00f6r\u00f0, votj\u00f6r\u00f0 og svartj\u00f6r\u00f0), iii) l\u00edfr\u00e6nni m\u00f3j\u00f6r\u00f0 og a\u00f0 s\u00ed\u00f0ustu iv) \u00f6\u00f0rum jar\u00f0vegi sem er margv\u00edslegur a\u00f0 ger\u00f0. \u00cd s\u00ed\u00f0asta flokknum er bergj\u00f6r\u00f0 \u00fatbreiddust, en auk \u00feess m\u00e1 nefna freraj\u00f6r\u00f0 s\u00edfrerasv\u00e6\u00f0a og kalkj\u00f6r\u00f0. Jar\u00f0vegskorti\u00f0 var unni\u00f0 \u00e1 grundvelli sni\u00f0a og jar\u00f0vegss\u00fdna sem safna\u00f0 hefur veri\u00f0 v\u00ed\u00f0a um landi\u00f0. Korti\u00f0 er \u00e1 vektora formi og \u00ed m\u00e6likvar\u00f0a 1:500 000. \u00dea\u00f0 er m.a. hluti evr\u00f3pska jar\u00f0vegskortsins.  A soil map of Iceland: The Soil map classification separates between; 1) andic soils, which are Brown Andosols, Gleyic Andosols and Histic Andosols; 2) Vitrisols, soils of deserts, which are divided into Cambic Vitrisols, Gravelly Vitrisols, Arenic Vitrisols and Pumice Vitrisols iii) Histosols, and iv) other soil types such as Cryosols and Leptosols. The classification system is in part based on WRB system and Soil Taxonomy and earlier work by Bj\u00f6rn J\u00f3hannesson and \u00deorsteinn Gu\u00f0mundsson (see English Summary and 1. table in http://www.moldin.net/uploads/3/9/3/3/39332633/jardvegskort_2.pdf).  The map is in a coarse scale (1:500 000) and is not intended to use for particular points on the landscape.  It is rather an overview.  It has been incorporated into the EU soil database and the Circumpolar soil map.", "formats": [{"name": "WFS_SRVC"}], "keywords": ["gsl", "inspire", "is", "jarvegsflokkun", "jar\u00f0vegskort", "jar\u00f0vegur", "soil", "soil-map"], "contacts": [{"organization": "Landb\u00fana\u00f0arh\u00e1sk\u00f3li \u00cdslands", "roles": ["creator"]}]}, "links": [{"href": "https://gis.is/geoserver/lbhi/wfs?service=wfs&request=getcapabilities&version=1.1.0"}, {"href": "https://gis.is/geoserver/lbhi/wms?service=wms&request=getcapabilities"}, {"href": "http://data.europa.eu/88u/dataset/-15d66dac-a389-4330-94c5-31b2ef12f9b6-"}, {"rel": "self", "type": "application/geo+json", "title": "-15d66dac-a389-4330-94c5-31b2ef12f9b6-", "name": "item", "description": "-15d66dac-a389-4330-94c5-31b2ef12f9b6-", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/-15d66dac-a389-4330-94c5-31b2ef12f9b6-"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "1854/LU-8732814", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:31Z", "type": "Journal Article", "created": "2021-11-09", "title": "Litter quality, mycorrhizal association, and soil properties regulate effects of tree species on the soil fauna community", "description": "Abstract   Forest management, including selection of appropriate tree species to mitigate climate change and sustain biodiversity, requires a better understanding of factors that affect the composition of soil fauna communities. These communities are an integral part of the soil ecosystem and play an essential role in forest ecosystem functioning related to carbon and nitrogen cycling. Here, by performing a field study across six common gardens in Denmark, we evaluated the effects of tree species identity and mycorrhizal association (i.e., arbuscular mycorrhiza (AM) and ectomycorrhiza (ECM)) on soil fauna (meso- and macrofauna) taxonomic and functional community composition by using diversity, abundance, and biomass as proxies. We found that (1) tree species identity and mycorrhizal association both showed significant effects on soil fauna communities, but the separation between community characteristics in AM and ECM tree species was not entirely consistent; (2) total soil fauna abundance, biomass, as well as taxonomic and functional diversity were generally significantly higher under AM tree species, as well as lime, with higher litter quality (high N and base cation and low lignin:N ratio); (3) tree species significantly influenced the properties of litter, forest floor, and soil, among which litter and/or forest floor N, P, Ca, and Mg concentrations, soil pH, and soil moisture predominantly affected soil fauna abundance, biomass, and taxonomic and functional diversity. Our results from this multisite common garden experiment provide strong and consistent evidence of positive effects of tree species with higher litter quality on soil fauna communities in general, which helps to better understand the effects of tree species selection on soil biodiversity and its functions related to forest soil carbon sequestration.", "keywords": ["DECOMPOSITION", "EARTHWORMS", "Diversity", "PH", "FOREST FLOOR", "Common garden experiment", "Soil meso- and macrofauna", "DIVERSITY", "Biology and Life Sciences", "04 agricultural and veterinary sciences", "15. Life on land", "NITROGEN", "CARBON", "Taxonomic group", "FUNCTIONAL TRAITS", "Abundance", "13. Climate action", "Earth and Environmental Sciences", "Functional group", "0401 agriculture", " forestry", " and fisheries", "BIODIVERSITY", "ABUNDANCE", "Biomass"]}, "links": [{"href": "https://doi.org/1854/LU-8732814"}, {"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": "1854/LU-8732814", "name": "item", "description": "1854/LU-8732814", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8732814"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "1F20D517-4F12-4194-B9EC-544A45676839", "type": "Feature", "geometry": null, "properties": {"updated": "2020-02-11T00:00:00Z", "type": "Dataset", "language": "de", "title": "Boden\u00fcbersichtskarte 1:200.000 (B\u00dcK200) - CC7110 Mannheim", "description": "Die Boden\u00fcbersichtskarte 1:200.000 (B\u00dcK200) wird von der Bundesanstalt f\u00fcr Geowissenschaften und Rohstoffe (BGR) in Zusammenarbeit mit den Staatlichen Geologischen Diensten (SGD) der Bundesl\u00e4nder im Blattschnitt der Topographischen \u00dcbersichtskarte 1:200.000 (T\u00dcK200) erarbeitet und in 55 einzelnen Kartenbl\u00e4ttern herausgegeben. Die digitale, blattschnittfreie Datenhaltung bildet eine detaillierte, bundesweit einheitliche und fl\u00e4chendeckende Informationsgrundlage f\u00fcr L\u00e4nder \u00fcbergreifende Aussagen zu Bodennutzung und Bodenschutz. \u00dcber den aktuellen Bearbeitungsstand des Kartenwerks informieren die Internetseiten der BGR zum Thema Boden. Die Verbreitung und Vergesellschaftung der B\u00f6den auf dem Gebiet dieses Kartenblattes wird anhand von 97 Legendeneinheiten (gegliedert nach Bodenregionen und Bodengro\u00dflandschaften) beschrieben. Jede Legendeneinheit beinhaltet bodensystematische Informationen (Bodensubtyp) und Informationen zum Bodenausgangsgestein sowohl f\u00fcr die Leitb\u00f6den als auch f\u00fcr deren Begleiter. Im Rahmen der Qualit\u00e4tssicherung wurde die Linienf\u00fchrung der Bodengrenzen im gesamten Blattgebiet verbessert (Stand 12. Juli 2016).", "formats": [{"name": "PDF"}], "keywords": ["ackerbauliches-ertragspotential", "baden-wu\u0308rttemberg", "boden", "bodenart", "bodenausgangsgestein", "bodenauslaugung", "bodenbearbeitung", "bodenbelastung", "bodenbildung", "bodenbiologie", "bodenchemie", "bodendegradation", "bodendekontamination", "bodeneigenschaften", "bodenerosion", "bodenfeuchtigkeit", "bodenform", "bodenfruchtbarkeit", "bodenfunktion", "bodengefu\u0308ge", "bodengesellschaft", "bodengestaltung", "bodengruppe", "bodengu\u0308te", "bodenhorizont", "bodeninformationssystem", "bodenkarte", "bodenluft", "bodenmechanik", "bodenmineralogie", "bodennutzbarkeit", "bodennutzung", "bodenphysikalische-eigenschaften", "bodenprofil", "bodenskelett", "bodensubstrat", "bodensystematik", "bodentyp", "bodenverbreitung", "de", "durchla\u0308ssigkeit", "effektive-durchwurzelungstiefe", "fachinformationssystem", "hessen", "mannheim", "opendata", "rheinland-pfalz", "saarland", "soil"], "contacts": [{"organization": "Bundesanstalt f\u00fcr Geowissenschaften und Rohstoffe (BGR)", "roles": ["creator"]}]}, "links": [{"href": "https://download.bgr.de/bgr/Boden/BUEK200/7110/jpg/buek200_7110.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/7110/pdf/buek200_7110.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/7110/png/buek200_7110.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/7110/shp/buek200_7110.zip"}, {"href": "https://download.bgr.de/bgr/Boden/BUEK200/7110/tiff/buek200_7110.zip"}, {"href": "http://data.europa.eu/88u/dataset/1f20d517-4f12-4194-b9ec-544a45676839"}, {"rel": "self", "type": "application/geo+json", "title": "1F20D517-4F12-4194-B9EC-544A45676839", "name": "item", "description": "1F20D517-4F12-4194-B9EC-544A45676839", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1F20D517-4F12-4194-B9EC-544A45676839"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "1fb8c60c-4140-4c8b-ba82-6cfd17bfaf91", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-24T06:22:31.561869Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-06-23 ore 12 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-06-23 ore 12 UTC - Valido dalle ore 12 UTC del 2025-06-23 alle ore 00 UTC del 2025-06-27. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-06-23", "20250623t120000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-06-23-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250623T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/1fb8c60c-4140-4c8b-ba82-6cfd17bfaf91"}, {"rel": "self", "type": "application/geo+json", "title": "1fb8c60c-4140-4c8b-ba82-6cfd17bfaf91", "name": "item", "description": "1fb8c60c-4140-4c8b-ba82-6cfd17bfaf91", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1fb8c60c-4140-4c8b-ba82-6cfd17bfaf91"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1016/j.apsoil.2014.12.005", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:16Z", "type": "Journal Article", "created": "2015-01-16", "title": "Short-Term Mesofauna Responses To Soil Additions Of Corn Stover Biochar And The Role Of Microbial Biomass", "description": "Biochar additions have been suggested to influence soil microbial communities that, through a cascade effect, may also impact soil fauna. In turn, any direct biochar effects on fauna can influence microbial communities through grazing, physical fragmentation of organic debris (and biochar) and modifying soil structure. If biochar creates a favorable environment for soil microorganisms, it is also plausible for fauna to be attracted to such microbially enriched habitats. However, how soil fauna respond to biochar addition to soil and what are the main factors that drive their behavior has rarely been experimentally addressed. Therefore, the behavior of two mesofauna species was assessed as a result of corn stover biochar (slow pyrolysis at 600 \u00b0C) additions to a loamy temperate soil, after preincubation for 2, 17, 31 and 61 d, and related to variations in microbial biomass and activity. Microbial biomass increased by 5-56% and activity by 6-156% with increasing biochar rates for the different preincubation times. Over the incubation time, microbial biomass did not change or increased at most 15% with the different biochar rates, while in turn microbial activity decreased steadily (around 70-80% at day 61). Enchytraeids generally did not show avoidance or preference to biochar when provided with an alternative unamended soil, while collembolans often showed avoidance responses. However, collembolan avoidance to biochar decreased or disappeared in biochar mixtures with higher microbial biomass and water extractable NH4-N content, agreeing with the plausible role of microorganisms to potentially attract soil fauna after biochar applications. Avoidance response was mainly explained by environmental preferences of the test species and not by any toxic effect of the biochar in this study. However, avoidance after the application of biochar may still need to be considered due to the potential negative impacts of individuals' migration on soil ecosystem functioning.", "keywords": ["2. Zero hunger", "Biochar", "Behavior", "Avoidance", "Microbial biomass", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Ammonium", "Soil fauna"]}, "links": [{"href": "https://doi.org/10.1016/j.apsoil.2014.12.005"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20Soil%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.apsoil.2014.12.005", "name": "item", "description": "10.1016/j.apsoil.2014.12.005", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.apsoil.2014.12.005"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-05-01T00:00:00Z"}}, {"id": "10.1007/s003740050411", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:32Z", "type": "Journal Article", "created": "2002-08-25", "title": "Soil Microbial And Extractable C And N After Wildfire", "description": "Open AccessPeer reviewed", "keywords": ["13. Climate action", "Temperate humid zone", "Microbial biomass", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Uncontrolled burning", "Forest soils", "15. Life on land", "Potassium-sulphate-soluble C and N", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1007/s003740050411"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biology%20and%20Fertility%20of%20Soils", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s003740050411", "name": "item", "description": "10.1007/s003740050411", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s003740050411"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1998-06-19T00:00:00Z"}}, {"id": "3211739244", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:22:15Z", "type": "Journal Article", "created": "2021-11-08", "title": "Quantifying Cereal Productivity on Sandy Soil in Response to Some Soil-Improving Cropping Systems", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Little information is available on the effect of soil-improving cropping systems (SICS) on crop productivity on low fertility sandy soils although they are increasingly being used in agriculture in many regions of the world due to the growing demand for food. The study aimed at quantifying the effect of four soil-improving cropping systems applied on sandy soil on cereal productivity (yield of grain and straw and plant height) in a 4-year field experiment conducted in Poland with spring cereal crops: oat (2017), wheat (2018), wheat (2019), and oat (2020). The experiment included the control (C) and the following SICS: liming (L), leguminous catch crops for green manure (LU), farmyard manure (M), and farmyard manure + liming + leguminous catch crops for green manure together (M + L + LU). To quantify the effect of the SICS, classic statistics and the Bland\u2013Altman method were used. It was shown that all yield trait components significantly increased in the last study year (2020) under SICS with M and M + L + LU. All yield trait components were significantly lower in the dry years (2018\u20132019) than in the wet years (2017 and 2020). The relatively large rainfall quantity in May during intensive growth at shooting and the scarce precipitation during later growth in the dry year 2019 resulted in a significantly greater straw yield compared to the other dry year 2018. The values of Bland\u2013Altman bias (mean difference between the particular SICS and the control) varied (in kg m\u22122) from \u22120.002 for LU in 2019 to 0.128 for M and 0.132 for M + L + LU in 2020. The highest limits of agreement (LoA) were in general noted for all yield trait components (the least even yield) in the most productive SICS including M and M + L + LU in the wet year 2020. The Bland\u2013Altman ratio (BAR) values indicate that quantification of the effects of all soil-improving practices was most uncertain in the dry year 2018 for the grain yield and in the wet year 2020 for the straw yield and much less uncertain for the plant height in all SICS and study years. The results of this study provide helpful information about the effect of the SICS on the different yield trait components depending on the period of their application and weather conditions prevailing during the growing season.</p></article>", "keywords": ["2. Zero hunger", "Bland\u2013Altman statistics", "S", "soil improving practices", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Podzol soil", "crop response", "weather conditions"]}, "links": [{"href": "http://www.mdpi.com/2073-445X/10/11/1199/pdf"}, {"href": "https://doi.org/3211739244"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3211739244", "name": "item", "description": "3211739244", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3211739244"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-05T00:00:00Z"}}, {"id": "10.1016/j.ejsobi.2013.10.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:29Z", "type": "Journal Article", "created": "2013-11-02", "title": "Effect Of Biochar Addition On Soil Microbial Community In A Wheat Crop", "description": "Biochar is known to enhance soil fertility and C sequestration, but relatively little information is currently available about its effect on soil microbial community, a component of terrestrial ecosystems that plays a key role in nutrient cycling. This study tested the effects of soil amendment with two loads of wood-derived biochar (30 and 60 t ha(-1)) in a wheat crop in Tuscany (Italy). Soil samples were collected 3 and 14 months after treatments over two successive growing seasons, and analysed for pH, total organic C (C-org), extractable C (C-ext), microbial biomass-C (C-mic), 25 specific microbial activities, mean substrate-induced respiration (mSIR) for 25 substrates, functional microbial diversity and bacterial genetic diversity. No significant effect of biochar treatment was observed on C-org, C-ext, C-mic, microbial quotient (C-mic % C-org) or genetic diversity. An increase in mSIR, some specific microbial activities and soil pH, and a significant change in functional diversity were observed 3 months after treatment. In contrast, no effect of biochar was detected 14 months after treatment for the parameters considered, except for a small but significant increase in pH. Our data suggest that biochar addition stimulated soil microbial activity without causing any apparent disturbance, but this positive effect was very short-lived. (C) 2013 Published by Elsevier Masson SAS.", "keywords": ["2. Zero hunger", "Soil management", "Wood-derived biochar", "Soil bacterial diversity; Soil management; Soil microbial activity; Soil microbial functional diversity; Wheat crop; Wood-derived biochar;", "Soil microbial functional diversity", "Wheat crop", "Soil microbial activity", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "Soil bacterial diversity", "15. Life on land", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.ejsobi.2013.10.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Journal%20of%20Soil%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ejsobi.2013.10.007", "name": "item", "description": "10.1016/j.ejsobi.2013.10.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ejsobi.2013.10.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-01-01T00:00:00Z"}}, {"id": "10.1002/2017JG004269", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:12Z", "type": "Journal Article", "created": "2017-12-18", "title": "Soil Carbon Dynamics in Soybean Cropland and Forests in Mato Grosso, Brazil", "description": "Abstract<p>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.</p>", "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": "10.1016/j.agee.2014.05.013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:07Z", "type": "Journal Article", "created": "2014-06-21", "title": "The Effect Of Pasture Utilization Rate On Stocks Of Soil Organic Carbon And Total Nitrogen In A Semi-Arid Tropical Grassland", "description": "The influence of grazing management on total soil organic carbon (SOC) and soil total nitrogen (TN) in tropical grasslands is an issue of considerable ecological and economic interest. Here we have used linear mixed models to investigate the effect of grazing management on stocks of SOC and TN in the top 0.5 m of the soil profile. The study site was a long-term pasture utilization experiment, 26 years after the experiment was established for sheep grazing on native Mitchell grass (Astrebla spp.) pasture in northern Australia. The pasture utilization rates were between 0% (exclosure) and 80%, assessed visually. We found that a significant amount of TN had been lost from the top 0.1 m of the soil profile as a result of grazing, with 80% pasture utilization resulting in a loss of 84 kg ha\u22121 over the 26-year period. There was no significant effect of pasture utilization rate on TN when greater soil depths were considered. There was no significant effect of pasture utilization rate on stocks of SOC and soil particulate organic carbon (POC), or the C:N ratio at any depth; however, visual trends in the data suggested some agreement with the literature, whereby increased grazing pressure appeared to: (i) decrease SOC and POC stocks; and, (ii) increase the C:N ratio. Overall, the statistical power of the study was limited, and future research would benefit from a more comprehensive sampling scheme. Previous studies at the site have found that a pasture utilization rate of 30% is sustainable for grazing production on Mitchell grass; however, given our results, we conclude that N inputs (possibly through management of native N2-fixing pasture legumes) should be made for long-term maintenance of soil health, and pasture productivity, within this ecosystem.", "keywords": ["2. Zero hunger", "Soil nitrogen", "Pasture utilization", "Tropical grassland", "04 agricultural and veterinary sciences", "15. Life on land", "Soil carbon", "630", "0401 agriculture", " forestry", " and fisheries", "Soils. Soil science", "1102 Agronomy and Crop Science", "Grazing management", "1103 Animal Science and Zoology", "Rangelands. Range management. Grazing", "2303 Ecology"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2014.05.013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2014.05.013", "name": "item", "description": "10.1016/j.agee.2014.05.013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2014.05.013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-10-01T00:00:00Z"}}, {"id": "10.1007/s10533-015-0169-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:43Z", "type": "Journal Article", "created": "2015-12-09", "title": "Elevated Co2 Increased Phosphorous Loss From Decomposing Litter And Soil Organic Matter At Two Face Experiments With Trees", "description": "Sustained increased productivity of trees growing in elevated CO2 depends in part on their stoichiometric flexibility, i.e., increasing their nutrient use efficiency, or on increased nutrient uptake from the soil. Phosphorus (P) may be a nutrient as limiting as nitrogen (N) in terrestrial ecosystems and may play a key-process in global terrestrial C storage. For this study archived litter and soil samples of two free air CO2 enrichment (FACE) experiments were analyzed for C, N and P. Populus euramericana, nigra and alba and Betula pendula, Alnus glutinosa and Fagus sylvatica were grown in ambient and elevated CO2 at respectively the Euro- and BangorFACE experiments. At EuroFACE, aboveground litter accumulated in L, F and H layers, while at BangorFACE almost all aboveground litter was incorporated into the mineral soil due to bioturbation. At EuroFACE, more P was lost from the F and H litter layers due to trees growing in elevated CO2, while at BangorFACE more P was lost from the mineral soil. Results of this study imply that trees growing in elevated CO2 were P limited at both experiments. Therefore, with increasing atmospheric CO2, P may play a more pronounced role than previous thought in regulating secondary forest growth. Moreover, increased atmospheric CO2 and ample N may allow a larger pool of P to become available for uptake due to, for instance, increased phosphatase activity resulting in increased organic matter turnover and biogenic weathering. Therefore, it may be postulated that under non-N-limited conditions, e.g., during regrowth, under high N deposition or in systems with high N2-fixation, increased P availability and uptake may allow P-limited forests to sustain increased growth under increasing atmospheric CO2.", "keywords": ["0106 biological sciences", "4. Education", "Litter and soil stoichiometry", "04 agricultural and veterinary sciences", "15. Life on land", "Soil phosphorous", "01 natural sciences", "Secondary forest growth", "13. Climate action", "Elevated CO", "Environmental Chemistry", "0401 agriculture", " forestry", " and fisheries", "FACE experiment", "Earth-Surface Processes", "Water Science and Technology"], "contacts": [{"organization": "Hoosbeek, Marcel R.", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s10533-015-0169-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10533-015-0169-1", "name": "item", "description": "10.1007/s10533-015-0169-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10533-015-0169-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-12-08T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Soil&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Soil&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Soil&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Soil&offset=50", "hreflang": "en-US"}], "numberMatched": 10387, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-09-20T13:01:37.570744Z"}