{"type": "FeatureCollection", "features": [{"id": "10.1111/gcb.12819", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:17:29Z", "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": "10.1128/aem.02264-23", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:17:51Z", "type": "Journal Article", "created": "2024-02-19", "title": "Novel endolithic bacteria of phylum             Chloroflexota             reveal a myriad of potential survival strategies in the Antarctic desert", "description": "ABSTRACT                                     <p>               The ice-free McMurdo Dry Valleys of Antarctica are dominated by nutrient-poor mineral soil and rocky outcrops. The principal habitat for microorganisms is within rocks (endolithic). In this environment, microorganisms are provided with protection against sub-zero temperatures, rapid thermal fluctuations, extreme dryness, and ultraviolet and solar radiation. Endolithic communities include lichen, algae, fungi, and a diverse array of bacteria.               Chloroflexota               is among the most abundant bacterial phyla present in these communities. Among the               Chloroflexota               are four novel classes of bacteria, here named               Candidatus               Spiritibacteria class. nov. (=UBA5177),               Candidatus               Martimicrobia class. nov. (=UBA4733),               Candidatus               Tarhunnaeia class. nov. (=UBA6077), and               Candidatus               Uliximicrobia class. nov. (=UBA2235). We retrieved 17 high-quality metagenome-assembled genomes (MAGs) that represent these four classes. Based on genome predictions, all these bacteria are inferred to be aerobic heterotrophs that encode enzymes for the catabolism of diverse sugars. These and other organic substrates are likely derived from lichen, algae, and fungi, as metabolites (including photosynthate), cell wall components, and extracellular matrix components. The majority of MAGs encode the capacity for trace gas oxidation using high-affinity uptake hydrogenases, which could provide energy and metabolic water required for survival and persistence. Furthermore, some MAGs encode the capacity to couple the energy generated from H               2               and CO oxidation to support carbon fixation (atmospheric chemosynthesis). All encode mechanisms for the detoxification and efflux of heavy metals. Certain MAGs encode features that indicate possible interactions with other organisms, such as Tc-type toxin complexes, hemolysins, and macroglobulins.             </p>                            IMPORTANCE               <p>                 The ice-free McMurdo Dry Valleys of Antarctica are the coldest and most hyperarid desert on Earth. It is, therefore, the closest analog to the surface of the planet Mars. Bacteria and other microorganisms survive by inhabiting airspaces within rocks (endolithic). We identify four novel classes of phylum                 Chloroflexota                 , and, based on interrogation of 17 metagenome-assembled genomes, we predict specific metabolic and physiological adaptations that facilitate the survival of these bacteria in this harsh environment\uffe2\uff80\uff94including oxidation of trace gases and the utilization of nutrients (including sugars) derived from lichen, algae, and fungi. We propose that such adaptations allow these endolithic bacteria to eke out an existence in this cold and extremely dry habitat.               </p>", "keywords": ["570", "Bacteria", "Fungi", "Antarctic Regions", "Chloroflexi", "15. Life on land", "Survival strategies", "Cold Temperature", "Extremophiles", "13. Climate action", "Antarctica", "Endolithic communities", "Metagenomics", "14. Life underwater", "Sugars", "Settore BIO/19 - MICROBIOLOGIA GENERALE"]}, "links": [{"href": "https://doi.org/10.1128/aem.02264-23"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.02264-23", "name": "item", "description": "10.1128/aem.02264-23", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.02264-23"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-19T00:00:00Z"}}, {"id": "10.5281/zenodo.15096788", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:20:25Z", "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.7656722", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:20:58Z", "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": "1295b9994deae0387c2be67c1d753988", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:22:00Z", "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": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-20T16:22:05Z", "type": "Journal Article", "created": "2024-03-21", "title": "Environmental drivers and remote sensing proxies of post-fire thaw depth in Eastern Siberian larch forests", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Boreal fire regimes are intensifying because of climate change and the northern parts of boreal forests are underlain by permafrost. Boreal fires combust vegetation and organic soils, which insulate permafrost, and as such deepen the seasonally thawed active layer and can lead to further carbon emissions to the atmosphere. Current understanding of the environmental drivers of post-fire thaw depth is limited but of critical importance. In addition, mapping thaw depth over fire scars may enable a better understanding of the spatial variability in post-fire responses of permafrost soils. We assessed the environmental drivers of post-fire thaw depth using field data from a fire scar in a larch-dominated forest in the continuous permafrost zone in Eastern Siberia. Particularly, summer thaw depth was deeper in burned (mean = 127.3 cm, standard deviation (sd) = 27.7 cm) than in unburned (98.1 cm, sd = 26.9 cm) landscapes one year after the fire, yet the effect of fire was modulated by landscape and vegetation characteristics. We found deeper thaw in well-drained landscape positions, in open larch forest often intermixed with Scots pine, and in high severity burns. The environmental drivers, site moisture, forest type and density, and fire severity explained 73.4 % of the measured thaw depth variability at the study sites. In addition, we evaluated the relationships between field-measured thaw depth and several remote sensing proxies. Albedo, the differenced Normalized Burn Ratio (dNBR), land surface temperature (LST), and pre-fire Normalized Difference Vegetation Index (NDVI) derived from Landsat 8 imagery together explained 66.3 % of the variability in field-measured thaw depth. Based on these remote sensing proxies and multiple linear regression analysis, we estimated thaw depth over the entire fire scar, and found that LST displayed particularly strong correlations with post-fire thaw depth (r = 0.65, p &lt; 0.01). Our study reveals some of the governing processes of post-fire thaw depth development and shows the capability of Landsat imagery to estimate thaw depth at a landscape scale.                         </p></article>", "keywords": ["Dynamic and structural geology", "QE1-996.5", "13. Climate action", "Science", "Q", "Geology", "QE500-639.5", "Deforestation", "15. Life on land", "Landsat", "Multiple linear regression", "Atmospheric temperature"]}, "links": [{"href": "https://esd.copernicus.org/articles/15/1459/2024/esd-15-1459-2024.pdf"}, {"href": "https://doi.org/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Dynamics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "name": "item", "description": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-21T00:00:00Z"}}, {"id": "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.agrformet.2018.02.033", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:06Z", "type": "Journal Article", "created": "2018-03-20", "title": "Calibrating an evapotranspiration model using radiometric surface temperature, vegetation cover fraction and near-surface soil moisture data", "description": "An accurate representation of the partitioning between soil evaporation and plant transpiration is an asset for modeling crop evapotranspiration (ET) along the agricultural season. The Two-Surface energy Balance (TSEB) model operates the ET partitioning by using the land surface temperature (LST), vegetation cover fraction (fc), and the Priestley Taylor (PT) assumption that relates transpiration to net radiation via a fixed PT coefficient (\u03b1PT). To help constrain the evaporation/transpiration partition of TSEB, a new model (named TSEB-SM) is developed by using, in addition to LST and fc data, the near-surface soil moisture (SM) as an extra constraint on soil evaporation. An innovative calibration procedure is proposed to retrieve three key parameters: \u03b1PT and the parameters (arss and brss) of a soil resistance formulation. Specifically, arss and brss are retrieved at the seasonal time scale from SM and LST data with fc\u202f \u202f0.5. The new ET model named TSEB-SM is tested over 1 flood- and 2 drip-irrigated wheat fields using in situ data collected during two field experiments in 2002\u20132003 and 2016\u20132017. The calibration algorithm is found to be remarkably stable as \u03b1PT, arss and brss parameters converge rapidly in few (2\u20133) iterations. Retrieved values of \u03b1PT, arss and brss are in the range 0.0\u20131.4, 5.7\u20139.5, and 1.4\u20136.9, respectively. Calibrated daily \u03b1PT mainly follows the phenology of winter wheat crop with a maximum value coincident with the full development of green biomass and a minimum value reached at harvest. The temporal variations of \u03b1PT before senescence are attributed to the dynamics of both root-zone soil moisture. Moreover, the overall (for the three sites) root mean square difference between the ET simulated by TSEB-SM and eddy-covariance measurements is 67\u202fW\u202fm\u22122 (24% relative error), compared to 108\u202fW\u202fm\u22122 (38% relative error) for the original version of TSEB using default parameterization (\u03b1PT\u202f=\u202f1.26). Such a calibration strategy has great potential for applications at multiple scales using remote sensing data including thermal-derived LST, solar reflectance-derived fc and microwave-derived SM.", "keywords": ["Priestley-taylor coefficient", "2. Zero hunger", "550", "TSEB modifid", "[SDE.IE]Environmental Sciences/Environmental Engineering", "0207 environmental engineering", "02 engineering and technology", "Vegetation cover fraction", "15. Life on land", "01 natural sciences", "630", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Turbulent heat fluxes", "Soil moisture", "[SDE.IE] Environmental Sciences/Environmental Engineering", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Land surface temperature", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2018.02.033"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2018.02.033", "name": "item", "description": "10.1016/j.agrformet.2018.02.033", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2018.02.033"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2007.04.019", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:06Z", "type": "Journal Article", "created": "2007-05-31", "title": "Interannual And Interseasonal Soil Co2 Efflux And Voc Exchange Rates In A Mediterranean Holm Oak Forest In Response To Experimental Drought", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "Drought", "Seasonality", "Soil VOCs", "15. Life on land", "01 natural sciences", "6. Clean water", "13. Climate action", "CO2 efflux", "Soil monoterpenes", "Soil temperature", "Soil moisture", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2007.04.019"}, {"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": "10.1016/j.soilbio.2007.04.019", "name": "item", "description": "10.1016/j.soilbio.2007.04.019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2007.04.019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-10-01T00:00:00Z"}}, {"id": "10.1016/j.chemosphere.2013.12.024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:19Z", "type": "Journal Article", "created": "2014-01-04", "title": "Carbon Mineralization In Two Ultisols Amended With Different Sources And Particle Sizes Of Pyrolyzed Biochar", "description": "Biochar produced during pyrolysis has the potential to enhance soil fertility and reduce greenhouse gas emissions. The influence of biochar properties (e.g., particle size) on both short- and long-term carbon (C) mineralization of biochar remains unclear. There is minimal information on the potential effects of biochar particle sizes on their breakdowns by soil microorganism, so it is unknown if the particle size of biochar influences C mineralization rate and/or stability in soils. In order to evaluate the effect of different sources (BS) and particle sizes (BF) of biochar on C loss and/or stability in soils, an incubation study on C mineralization of different biochar sources and particle sizes was established using two soils (ST): Norfolk soil (fine loamy, kaolinitic, thermic, typic Kandiudults) and Coxville soil (fine loamy kaolinitic, thermic, Paleaquults). In separate incubation vessels, these soils were amended with one of two manure-based biochars (poultry litters, PL; swine solids, SS) or one of two lignocellulosic-based biochars (switchgrass, SG; pine chips, PC) which were processed into two particle sizes (dust, <0.42 mm; pellet, >2 mm). The amount of CO2 evolved varied significantly between soils (p\u22640.0001); particle sizes (p\u22640.0001) and the interactions of biochar source (p\u22640.001) and forms of biochars (p\u22640.0001) with soil types. Averaged across soils and sources of biochar, CO2-C evolved from dust-sized biochar (281 mg kg(-1)) was significantly higher than pellet-sized biochar (226 mg kg(-1)). Coxville soils with SS biochar produced the greatest average CO2-C of 428 mg kg(-1) and Norfolk soils with PC had the lowest CO2-C production (93 mg kg(-1)). Measured rates of carbon mineralization also varied with soils and sources of biochar (Norfolk: PL>SS>SG\u2265PC; Coxville: PC>SG>SS>PL). The average net CO2-C evolved from the Coxville soils (385 mg kg(-1)) was about threefold more than the CO2-C evolved from the Norfolk soils (123 mg kg(-1)). Our results suggest different particle sizes and sources of biochar as well as soil type influence biochar stability.", "keywords": ["2. Zero hunger", "Minerals", "Hot Temperature", "Swine", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "Carbon", "Poultry", "6. Clean water", "Manure", "Soil", "13. Climate action", "Charcoal", "11. Sustainability", "Animals", "0401 agriculture", " forestry", " and fisheries", "Particle Size", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.chemosphere.2013.12.024"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chemosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.chemosphere.2013.12.024", "name": "item", "description": "10.1016/j.chemosphere.2013.12.024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.chemosphere.2013.12.024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-05-01T00:00:00Z"}}, {"id": "10.15454/J9H4BS", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-20T16:18:10Z", "type": "Dataset", "title": "Donn\u00e9es de r\u00e9plication pour\u00a0: Biogeography of soil bacteria and archaea across France", "description": "These data concern the study 'Biogeography of soil bacteria and archaea across France' Karimi B, Terrat S, Dequiedt S, Saby NPA, Horrigue W, Leli\u00e8vre M, Nowak V, Jolivet C, Arrouays D, Wincker P, Cruaud C, Bispo A, Maron PA, Bour\u00e9 NCP, Ranjard L. Sci Adv. 2018 Jul 4;4(7):eaat1808. doi: 10.1126/sciadv.aat1808 and is based on data from the RMQS program (French Soil Quality Monitoring Network). The French Soil Quality Monitoring Network (RMQS) is a national program for the assessment and long-term monitoring of the quality of French soils. This network is based on the monitoring of 2240 sites representative of French soils and their land use. These sites are spread over the whole French territory (metropolitan and overseas) along a systematic square grid of 16 km x 16 km cells. The network covers a broad spectrum of climatic, soil and land-use conditions (croplands, permanent grasslands, woodlands, orchards and vineyards, natural or scarcely anthropogenic land and urban parkland). The physical, chemical and biological properties of the soil are measured on each site. These soil analyses were carried out by the Soil Analysis Laboratory of INRAE (Arras, France). The spatial and temporal variability of soil properties are explained by biophysical variables, sources of contamination, history of land-use and management practices on each plot. The first sampling campaign in metropolitan France took place from 2000 to 2009 and the second campaign has begun in 2016. At each site, 25 core samples were taken by layer with an auger within a 20 m \u00d7 20 m plot and combined into a composite sample. Analyses used in this study only concern the surface layer (generally 0\u201330 cm layer) of samplings from the first campaign in metropolitan France. The dataset published contains all the raw data used in the statistical analysis in order to make them available for any further study. The table contains soil properties, observations on land use, and coordinates. We warn the user that coordinates published here are not the right coordinates, the RMQS site can be located until 1 km around this point. Real coordinates can not be made publicly available because of confidential information.", "keywords": ["2. Zero hunger", "silt", "Earth and Environmental Science", "cation exchange capacity", "Evapotranspiration", "Soils and soil sciences", "pH", "land use", "clay", "sand", "15. Life on land", "6. Clean water", "soil", "air temperature", "soil organic carbon", "Earth and Environmental Sciences", "Land Use", "Soil Sciences", "calcium carbonate", "phosphorus content", "Environmental Research", "Natural Sciences", "Geosciences", "altitude"], "contacts": [{"organization": "Saby, Nicolas, Boulonne, Line, Rati\u00e9, C\u00e9line, Arrouays, Dominique, Chenu, Jean-Philippe, Toutain, Beno\u00eet, Bispo, Antonio, Jolivet, Claudy,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15454/J9H4BS"}, {"rel": "self", "type": "application/geo+json", "title": "10.15454/J9H4BS", "name": "item", "description": "10.15454/J9H4BS", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15454/J9H4BS"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.1016/j.foodres.2018.01.020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:15:33Z", "type": "Journal Article", "created": "2018-01-12", "title": "The impact of newly produced protein and dietary fiber rich fractions of yellow pea ( Pisum sativum L.) on the structure and mechanical properties of pasta-like sheets", "description": "Two fractions from pea (Pisum sativum L.), protein isolate (PPI) and dietary fiber (PF), were newly produced by extraction-fractionation method and characterized in terms of particle size distribution and structural morphology using SEM. The newly produced PPI and PF fractions were processed into pasta-like sheets with varying protein to fiber ratios (100/0, 90/10, 80/20, 70/30 and 50/50, respectively) using high temperature compression molding. We studied protein polymerization, molecular structure and protein-fiber interactions, as well as mechanical performance and cooking characteristics of processed PPI-PF blends. Bi-modal particle size distribution and chemical composition of the PPI and PF fractions influenced significantly the physicochemical properties of the pasta-like sheets. Polymerization was most pronounced for the 100 PPI, 90/10 and 80/20 PPI-PF samples as studied by SE-HPLC, and polymerization decreased with addition of the PF fraction. The mechanical properties, as strength and extensibility, were likewise the highest for the 100 PPI and 90/10 PPI-PF blends, while the E-modulus was similar for all the studied blends (around 38\u202fMPa). The extensibility decreased with the increasing amount of PF in the blend. The highest amounts of \u03b2-sheets were found in the pasta-like sheets with high amounts of PPI (100, 90 and 80%), by FT-IR. An increase in PF fraction in the blend, resulted into the high amounts of unordered structures as observed by FT-IR, as well as in an increase in the molecular scattering distances observed by SAXS. The water uptake increased and cooking loss decreased with increased proportions of the PF fraction, and the consistency of 10\u202fmin cooked pasta-like sheets were alike al dente texture. The new knowledge obtained in this study on the use of extraction-fractionation method to produce novel PPI and PF fractions for developing innovative high nutritious food can be of a great importance. The obtained knowledge on the pea protein and fiber processing behaviour could greatly contribute to a better control of functional properties of various temperature-processed products from yellow pea.", "keywords": ["Dietary Fiber", "2. Zero hunger", "Hot Temperature", "Food Handling", "Protein Conformation", "04 agricultural and veterinary sciences", "Plant Proteins", " Dietary", "Polymerization", "Structure-Activity Relationship", "0404 agricultural biotechnology", "Functional Food", "Elastic Modulus", "Scattering", " Small Angle", "Spectroscopy", " Fourier Transform Infrared", "Carbohydrate Conformation", "Chromatography", " Gel", "Dietary Carbohydrates", "Microscopy", " Electron", " Scanning", "Cooking", "Particle Size", "Nutritive Value", "Chromatography", " High Pressure Liquid", "Pisum sativum"]}, "links": [{"href": "https://doi.org/10.1016/j.foodres.2018.01.020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Food%20Research%20International", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.foodres.2018.01.020", "name": "item", "description": "10.1016/j.foodres.2018.01.020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.foodres.2018.01.020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-01T00:00:00Z"}}, {"id": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "type": "Feature", "geometry": null, "properties": {"license": "https://spdx.org/licenses/CC-BY-4.0.html", "updated": "2025-08-09T09:20:29.683803", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-08-09 ore 00 UTC).", "description": "Temperatura del suolo (C). Corsa del 2025-08-09 ore 00 UTC - Valido dalle ore 00 UTC del 2025-08-09 alle ore 00 UTC del 2025-08-12. Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["000000", "2025-08-09", "20250809t000000000z", "3km", "arw", "below", "between", "depths", "it", "lamma", "layer", "soil", "surface", "temperature", "two"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN00/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-temperatura-del-suolo-c-2025-08-09-ore-00-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run00/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250809T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/012ce7af-7212-41e1-96da-a38fbd32fd7c"}, {"rel": "self", "type": "application/geo+json", "title": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "name": "item", "description": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/012ce7af-7212-41e1-96da-a38fbd32fd7c"}, {"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": "oai:serval.unil.ch:BIB_38E93A02220B", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-09-20T16:27:53Z", "type": "Report", "title": "Global maps of soil temperature.", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km &lt;sup&gt;2&lt;/sup&gt; resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km &lt;sup&gt;2&lt;/sup&gt; pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\u00b0C (mean = 3.0 \u00b1 2.1\u00b0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \u00b1 2.3\u00b0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 \u00b1 2.3\u00b0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["Climate Change; Ecosystem; Microclimate; Soil; Temperature; bioclimatic variables; global maps; microclimate; near-surface temperatures; soil temperature; soil-dwelling organisms; temperature offset; weather stations"], "contacts": [{"organization": "Lembrechts, J.J., van den Hoogen, J., Aalto, J., Ashcroft, M.B., De Frenne, P., Kemppinen, J., Kopeck\u00fd, M., Luoto, M., Maclean, IMD, Crowther, T.W., Bailey, J.J., Haesen, S., Klinges, D.H., Niittynen, P., Scheffers, B.R., Van Meerbeek, K., Aartsma, P., Abdalaze, O., Abedi, M., Aerts, R., Ahmadian, N., Ahrends, A., Alatalo, J.M., Alexander, J.M., Allonsius, C.N., Altman, J., Ammann, C., Andres, C., Andrews, C., Ard\u00f6, J., Arriga, N., Arzac, A., Aschero, V., Assis, R.L., Assmann, J.J., Bader, M.Y., Bahalkeh, K., Baran\u010dok, P., Barrio, I.C., Barros, A., Barthel, M., Basham, E.W., Bauters, M., Bazzichetto, M., Marchesini, L.B., Bell, M.C., Benavides, J.C., Benito Alonso, J.L., Berauer, B.J., Bjerke, J.W., Bj\u00f6rk, R.G., Bj\u00f6rkman, M.P., Bj\u00f6rnsd\u00f3ttir, K., Blonder, B., Boeckx, P., Boike, J., Bokhorst, S., Brum, BNS, Br\u016fna, J., Buchmann, N., Buysse, P., Camargo, J.L., Campoe, O.C., Candan, O., Canessa, R., Cannone, N., Carbognani, M., Carnicer, J., Casanova-Katny, A., Cesarz, S., Chojnicki, B., Choler, P., Chown, S.L., Cifuentes, E.F., \u010ciliak, M., Contador, T., Convey, P., Cooper, E.J., Cremonese, E., Curasi, S.R., Curtis, R., Cutini, M., Dahlberg, C.J., Daskalova, G.N., de Pablo, M.A., Della Chiesa, S., Dengler, J., Deronde, B., Descombes, P., Di Cecco, V., Di Musciano, M., Dick, J., Dimarco, R.D., Dolezal, J., Dorrepaal, E., Du\u0161ek, J., Eisenhauer, N., Eklundh, L., Erickson, T.E., Erschbamer, B., Eugster, W., Ewers, R.M., Exton, D.A., Fanin, N., Fazlioglu, F., Feigenwinter, I., Fenu, G., Ferlian, O., Fern\u00e1ndez Calzado, M.R., Fern\u00e1ndez-Pascual, E., Finckh, M., Higgens, R.F., Forte, TGW, Freeman, E.C., Frei, E.R., Fuentes-Lillo, E., Garc\u00eda, R.A., Garc\u00eda, M.B., G\u00e9ron, C., Gharun, M., Ghosn, D., Gigauri, K., Gobin, A., Goded, I., Goeckede, M., Gottschall, F., Goulding, K., Govaert, S., Graae, B.J., Greenwood, S., Greiser, C., Grelle, A., Gu\u00e9nard, B., Guglielmin, M., Guillemot, J., Haase, P., Haider, S., Halbritter, A.H., Hamid, M., Hammerle, A., Hampe, A., Haugum, S.V., Hederov\u00e1, L., Heinesch, B., Helfter, C., Hepenstrick, D., Herberich, M., Herbst, M., Hermanutz, L., Hik, D.S., Hoffr\u00e9n, R., Homeier, J., H\u00f6rtnagl, L., H\u00f8ye, T.T., Hrbacek, F., Hylander, K., Iwata, H., Jackowicz-Korczynski, M.A., Jactel, H., J\u00e4rveoja, J., Jastrz\u0119bowski, S., Jentsch, A., Jim\u00e9nez, J.J., J\u00f3nsd\u00f3ttir, I.S., Jucker, T., Jump, A.S., Juszczak, R., Kanka, R., Ka\u0161par, V., Kazakis, G., Kelly, J., Khuroo, A.A., Klemedtsson, L., Klisz, M., Kljun, N., Knohl, A., Kobler, J., Koll\u00e1r, J., Kotowska, M.M., Kov\u00e1cs, B., Kreyling, J., Lamprecht, A., Lang, S.I., Larson, C., Larson, K., Laska, K., le Maire, G., Leihy, R.I., Lens, L., Liljebladh, B., Lohila, A., Lorite, J., Loubet, B., Lynn, J., Macek, M., Mackenzie, R., Magliulo, E., Maier, R., Malfasi, F., M\u00e1li\u0161, F.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/oai:serval.unil.ch:BIB_38E93A02220B"}, {"rel": "self", "type": "application/geo+json", "title": "oai:serval.unil.ch:BIB_38E93A02220B", "name": "item", "description": "oai:serval.unil.ch:BIB_38E93A02220B", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/oai:serval.unil.ch:BIB_38E93A02220B"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-01T00:00:00Z"}}, {"id": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "type": "Feature", "geometry": null, "properties": {"license": "https://spdx.org/licenses/CC-BY-4.0.html", "updated": "2025-04-30T11:21:35.673675Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Temperatura del suolo (C) - (2025-04-30 ore 00 UTC).", "description": "Temperatura del suolo (C). 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(e.g. Reports, articles, papers, scientific and non-scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \u201cData re-used from the BonaRes Data Centre www.bonares.de. This data were created as part of BonaRes Module A-Project - SUSALPS's research activities.\u201d Although every care has been taken in preparing and testing the data, BonaRes Module A-Project- SUSALPS and BonaRes Data Centre cannot guarantee that the data are correct; neither does BonaRes Module A-Project-SUSALPS and BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project-SUSALPS and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner/author.)", "updated": "2020-02-14", "type": "Dataset", "created": "2018-12-05", "language": "eng", "title": "SUSALPS temperature and volumetric soil water content Graswang Subplot 1 in Fendt intensiv", "description": "Grassland is a precious good. Grassland contributes to food security by providing fodder for dairy and beef farming, storing nutrients and increasing biodiversity. These functions that secure the fertility and yields of soil are jeopardized by climate change, especially in monane and alpine areas. In SUSALPS, scientists, authorities and farmers work together to investigate the influence of climate change on i) plant biodiversity, ii) C and N storage, iii) greenhouse gas exchange, iv) socio economic conditions that influence decision making of farmers. A central experimental aspect is the translocation of soil mesocosms from higher elevation to lower elevation (Esterberg site at 1200m, Graswang site at 860m, Fendt at 600m, Bayreuth at 300m). To reflect the spatial heterogeneity of soils, mesocosms from three different subplots approx. 100-300m apart from each other are translocated. Since temperatures are higher and precipitation is lower in lower elevation, the translocated mesocosms experience climate change. This dataset contains daily average soil temperature and volumetric soil water content in 5 and 15 cm depth. 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The climate elements considered were monthly precipitation and mean, minimum, and maximum temperature. Input data were gathered from a variety of sources and, where possible, were restricted to records from the 1950\u20132000 period. We used the thin-plate smoothing spline algorithm implemented in the ANUSPLIN package for interpolation, using latitude, longitude, and elevation as independent variables. We quantified uncertainty arising from the input data and the interpolation by mapping weather station density, elevation bias in the weather stations, and elevation variation within grid cells and through data partitioning and cross validation. Elevation bias tended to be negative (stations lower than expected) at high latitudes but positive in the tropics. Uncertainty is highest in mountainous and in poorly sampled areas. Data partitioning showed high uncertainty of the surfaces on isolated islands, e.g. in the Pacific. Aggregating the elevation and climate data to 10 arc min resolution showed an enormous variation within grid cells, illustrating the value of high-resolution surfaces. A comparison with an existing data set at 10 arc min resolution showed overall agreement, but with significant variation in some regions. A comparison with two high-resolution data sets for the United States also identified areas with large local differences, particularly in mountainous areas. Compared to previous global climatologies, ours has the following advantages: the data are at a higher spatial resolution (400 times greater or more); more weather station records were used; improved elevation data were used; and more information about spatial patterns of uncertainty in the data is available. Owing to the overall low density of available climate stations, our surfaces do not capture of all variation that may occur at a resolution of 1 km, particularly of precipitation in mountainous areas. In future work, such variation might be captured through knowledgebased methods and inclusion of additional co-variates, particularly layers obtained through remote sensing. Copyright \uf6d9 2005 Royal Meteorological Society.", "keywords": ["0106 biological sciences", "0301 basic medicine", "550", "Climate", "bats", "bat", "Precipitation", "precipitation", "01 natural sciences", "Error", "geographical information systems", "03 medical and health sciences", "precipitaci\u00f3n atmosf\u00e9rica", "Chiroptera", "1902 Atmospheric Science", "Animalia", "Chordata", "temperatura", "factores clim\u00e1ticos", "procesamiento de datos", "Temperature", "Uncertainty", "temperature", "Biodiversity", "15. Life on land", "GIS", "climatic factors", "Interpolation", "ANUSPLIN", "13. 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Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real\uffe2\uff80\uff90world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first\uffe2\uff80\uff90order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth\uffe2\uff80\uff90dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool\uffe2\uff80\uff90 and flux\uffe2\uff80\uff90based data sets through data assimilation is among the highest priorities for near\uffe2\uff80\uff90term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.</p>", "keywords": ["550", "LAND MODELS", "Oceanography", "HETEROTROPHIC RESPIRATION", "01 natural sciences", "Atmospheric Sciences", "LITTER DECOMPOSITION", "ORGANIC-CARBON", "Geoinformatics", "GLOBAL CLIMATE-CHANGE", "DATA-ASSIMILATION", "Meteorology & Atmospheric Sciences", "TEMPERATURE SENSITIVITY", "CMIP5", "MICROBIAL MODELS", "0105 earth and related environmental sciences", "2. Zero hunger", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "500", "Earth system models", "04 agricultural and veterinary sciences", "15. Life on land", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "TERRESTRIAL ECOSYSTEMS", "Climate Action", "Geochemistry", "Climate change impacts and adaptation", "realistic projections", "13. Climate action", "recommendations", "Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "soil carbon dynamics", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "environment", "Climate Change Impacts and Adaptation", "Environmental Sciences", "PARAMETER-ESTIMATION"]}, "links": [{"href": "https://escholarship.org/content/qt1pw7g2r2/qt1pw7g2r2.pdf"}, {"href": "https://doi.org/10.1002/2015gb005239"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Biogeochemical%20Cycles", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2015gb005239", "name": "item", "description": "10.1002/2015gb005239", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2015gb005239"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-01T00:00:00Z"}}, {"id": "10.1002/2017JD027346", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:02Z", "type": "Journal Article", "created": "2017-12-28", "title": "Soil Moisture-Temperature Coupling in a Set of Land Surface Models", "description": "Abstract<p>The land surface controls the partitioning of water and energy fluxes and therefore plays a crucial role in the climate system. The coupling between soil moisture and air temperature, in particular, has been shown to affect the severity and occurrence of temperature extremes and heat waves. Here we study soil moisture\uffe2\uff80\uff90temperature coupling in five land surface models, focusing on the terrestrial segment of the coupling in the warm season. All models are run off\uffe2\uff80\uff90line over a common period with identical atmospheric forcing data, in order to allow differences in the results to be attributed to the models' partitioning of energy and water fluxes. Coupling is calculated according to two semiempirical metrics, and results are compared to observational flux tower data. Results show that the locations of the global hot spots of soil moisture\uffe2\uff80\uff90temperature coupling are similar across all models and for both metrics. In agreement with previous studies, these areas are located in transitional climate regimes. The magnitude and local patterns of model coupling, however, can vary considerably. Model coupling fields are compared to tower data, bearing in mind the limitations in the geographical distribution of flux towers and the differences in representative area of models and in situ data. Nevertheless, model coupling correlates in space with the tower\uffe2\uff80\uff90based results (r = 0.5\uffe2\uff80\uff930.7), with the multimodel mean performing similarly to the best\uffe2\uff80\uff90performing model. Intermodel differences are also found in the evaporative fractions and may relate to errors in model parameterizations and ancillary data of soil and vegetation characteristics.</p>", "keywords": ["ENVIRONMENT SIMULATOR JULES", "FLUXES", "0207 environmental engineering", "02 engineering and technology", "01 natural sciences", "CO2 EXCHANGE", "models", "WATER", "SCALE", "Research Articles", "0105 earth and related environmental sciences", "land surface", "CARBON-DIOXIDE EXCHANGE", "eartH2Observe", "temperature", "15. Life on land", "DECIDUOUS FOREST", "CLIMATE", "EVAPORATION", "VARIABILITY", "13. Climate action", "Earth and Environmental Sciences", "BALANCE", "land surface models", "SENSIBLE HEAT", "land-atmosphere interactions", "soil moisture"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017JD027346"}, {"href": "https://doi.org/10.1002/2017JD027346"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Atmospheres", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2017JD027346", "name": "item", "description": "10.1002/2017JD027346", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017JD027346"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-02-01T00:00:00Z"}}, {"id": "10.1002/2016rg000543", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:02Z", "type": "Journal Article", "created": "2017-03-23", "title": "A review of spatial downscaling of satellite remotely sensed soil moisture", "description": "Abstract<p>Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.</p", "keywords": ["TIME-DOMAIN REFLECTOMETRY", "550", "IN-SITU", "downscaling", "MODIS TOA RADIANCES", "AMSR-E", "15. Life on land", "551", "01 natural sciences", "LAND-SURFACE TEMPERATURE", "REMEDHUS NETWORK SPAIN", "6. Clean water", "3. Good health", "[SDU] Sciences of the Universe [physics]", "L-BAND RADIOMETER", "remote sensing", "EVAPORATIVE FRACTION", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "Earth and Environmental Sciences", "soil moisture", "SOUTHERN GREAT-PLAINS", "spatial resolution", "HIGH-RESOLUTION", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2016RG000543"}, {"href": "https://doi.org/10.1002/2016rg000543"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Reviews%20of%20Geophysics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/2016rg000543", "name": "item", "description": "10.1002/2016rg000543", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2016rg000543"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-04-18T00:00:00Z"}}, {"id": "10.1002/ecy.2199", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:04Z", "type": "Journal Article", "created": "2018-02-27", "title": "Temperature and aridity regulate spatial variability of soil multifunctionality in drylands across the globe", "description": "Abstract<p>The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.</p", "keywords": ["Abiotic component", "Atmospheric sciences", "Physical geography", "Arid", "Climate Change", "Soil Science", "Spatial variability", "Environmental science", "Agricultural and Biological Sciences", "Soil", "Biodiversity Conservation and Ecosystem Management", "Soil texture", "Aridity index", "XXXXXX - Unknown", "Soil water", "FOS: Mathematics", "Pathology", "Climate change", "Biology", "Ecosystem", "Nature and Landscape Conservation", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Soil Fertility", "Ecology", "Geography", "Global Forest Drought Response and Climate Change", "Statistics", "Temperature", "Life Sciences", "Cycling", "Geology", "FOS: Earth and related environmental sciences", "04 agricultural and veterinary sciences", "Plants", "15. Life on land", "Archaeology", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Medicine", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Ecosystem Functioning", "Vegetation (pathology)", "Mathematics", "carbon cycling; climate change; multifunctionality; nitrogen cycling; phosphorous cycling; spatial heterogeneity"]}, "links": [{"href": "https://eprints.whiterose.ac.uk/128150/8/Dur-n_et_al-2018-Ecology.pdf"}, {"href": "https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1002/ecy.2199"}, {"href": "https://doi.org/10.1002/ecy.2199"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ecy.2199", "name": "item", "description": "10.1002/ecy.2199", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ecy.2199"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-01T00:00:00Z"}}, {"id": "10.1002/ece3.1867", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:03Z", "type": "Journal Article", "created": "2016-01-11", "title": "Grazing Exclusion Reduced Soil Respiration But Increased Its Temperature Sensitivity In A Meadow Grassland On The Tibetan Plateau", "description": "Abstract<p>Understanding anthropogenic influences on soil respiration (Rs) is critical for accurate predictions of soil carbon fluxes, but it is not known how Rs responds to grazing exclusion (GE). Here, we conducted a manipulative experiment in a meadow grassland on the Tibetan Plateau to investigate the effects of GE on Rs. The exclusion of livestock significantly increased soil moisture and above\uffe2\uff80\uff90ground biomass, but it decreased soil temperature, microbial biomass carbon (MBC), and Rs. Regression analysis indicated that the effects of GE on Rs were mainly due to changes in soil temperature, soil moisture, and MBC. Compared with the grazed blocks, GE significantly decreased soil carbon release by 23.6% over the growing season and 21.4% annually, but it increased the temperature sensitivity (Q10) of Rs by 6.5% and 14.2% for the growing season and annually respectively. Therefore, GE may reduce the release of soil carbon from the Tibetan Plateau, but under future climate warming scenarios, the increases in Q10 induced by GE could lead to increased carbon emissions.</p>", "keywords": ["570", "MICROBIAL RESPIRATION", "Environmental Sciences & Ecology", "Plant Productivity", "Temperature Sensitivity", "ALPINE GRASSLAND", "630", "Microbial Biomass Carbon", "NORTHERN CHINA", "SEASONAL PATTERNS", "MOUNTAIN GRASSLANDS", "Grazing Exclusion", "Tibetan Plateau", "PLANT-COMMUNITIES", "Original Research", "2. Zero hunger", "Science & Technology", "CLIMATE-CHANGE", "CO2 EFFLUX", "Ecology", "04 agricultural and veterinary sciences", "15. Life on land", "INNER-MONGOLIA", "BELOW-GROUND BIOMASS", "Soil Respiration", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "Life Sciences & Biomedicine"]}, "links": [{"href": "https://doi.org/10.1002/ece3.1867"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecology%20and%20Evolution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ece3.1867", "name": "item", "description": "10.1002/ece3.1867", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ece3.1867"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-01-11T00:00:00Z"}}, {"id": "10.1007/s00442-009-1392-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:25Z", "type": "Journal Article", "created": "2009-06-24", "title": "Plant Community Responses To 5 Years Of Simulated Climate Change In Meadow And Heath Ecosystems At A Subarctic-Alpine Site", "description": "Climate change was simulated by increasing temperature and nutrient availability in an alpine landscape. We conducted a field experiment of BACI-design (before/after control/impact) running for five seasons in two alpine communities (heath and meadow) with the factors temperature (increase of ca. 1.5-3.0 degrees C) and nutrients (5 g N, 5 g P per m(2)) in a fully factorial design in northern Swedish Lapland. The response variables were abundances of plant species and functional types. Plant community responses to the experimental perturbations were investigated, and the responses of plant functional types were examined in comparison to responses at the species level. Nutrient addition, exclusively and in combination with enhanced temperature increase, exerted the most pronounced responses at the species-specific and community levels. The main responses to nutrient addition were increases in graminoids and forbs, whereas deciduous shrubs, evergreen shrubs, bryophytes, and lichens decreased. The two plant communities of heath or meadow showed different vegetation responses to the environmental treatments despite the fact that both communities were located on the same subarctic-alpine site. Furthermore, we showed that the abundance of forbs increased in response to the combined treatment of temperature and nutrient addition in the meadow plant community. Within a single-plant functional type, most species responded similarly to the enhanced treatments although there were exceptions, particularly in the moss and lichen functional types. Plant community structure showed BACI responses in that vegetation dominance relationships in the existing plant functional types changed to varying degrees in all plots, including control plots. Betula nana and lichens increased in the temperature-increased enhancements and in control plots in the heath plant community during the treatment period. The increases in control plots were probably a response to the observed warming during the treatment period in the region.", "keywords": ["Sweden", "0106 biological sciences", "Species Specificity", "13. Climate action", "Climate", "Temperature", "Plant Development", "15. Life on land", "Fertilizers", "01 natural sciences", "Ecosystem", "Statistics", " Nonparametric", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s00442-009-1392-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Oecologia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00442-009-1392-z", "name": "item", "description": "10.1007/s00442-009-1392-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00442-009-1392-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-06-25T00:00:00Z"}}, {"id": "10.1007/s00442-009-1435-5", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-09-20T16:14:25Z", "type": "Journal Article", "created": "2009-08-18", "title": "Net Nitrogen Mineralization And Leaching In Response To Warming And Nitrogen Deposition In A Temperate Old Field: The Importance Of Winter Temperature", "description": "While climate warming can increase plant N availability over the growing season by increasing rates of N mineralization, increased N mineralization over winter at a time when plant roots are largely inactive, coupled with an increased frequency of soil freeze-thaw cycles, may increase soil N leaching losses. We examined changes in soil net N mineralization and N leaching in response to warming and N addition (6 g m(-2) year(-1)) in a factorial experiment conducted in a temperate old field. We used two warming treatments, year-round and winter-only warming, to isolate the effects of winter warming on soil N dynamics from the year-round warming effects. We estimated net N mineralization using in situ soil cores with resin bags placed at the bottom to catch throughput, and we measured N leaching using lysimeters located below the plant rooting zone at a depth of 50 cm. There were minor effects of warming on changes in soil extractable N and resin N in the soil cores over winter. Nevertheless, the overall effects of both warming and N addition on net N mineralization (the sum of changes in soil extractable N and resin N) were not significant over this period. Likewise, there were no significant treatment effects on the concentration of N in leachate collected below the plant rooting zone. However, in response to winter warming, net N mineralization over summer was approximately double that of both the ambient and year-round warming treatments. This result demonstrates a potentially large and unexpected effect of winter warming on soil N availability in this old field system.", "keywords": ["Soil", "Nitrogen", "13. Climate action", "Climate Change", "Temperature", "0401 agriculture", " forestry", " and fisheries", "Seasons", "04 agricultural and veterinary sciences", "Plants", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s00442-009-1435-5"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Oecologia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00442-009-1435-5", "name": "item", "description": "10.1007/s00442-009-1435-5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00442-009-1435-5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-08-19T00:00:00Z"}}, {"id": "10.1007/s00442-013-2833-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:14:26Z", "type": "Journal Article", "created": "2013-11-19", "title": "Response Of Grassland Biomass Production To Simulated Climate Change And Clipping Along An Elevation Gradient", "description": "Changes in rainfall and temperature regimes are altering plant productivity in grasslands worldwide, and these climate change factors are likely to interact with grassland disturbances, particularly grazing. Understanding how plant production responds to both climate change and defoliation, and how this response varies among grassland types, is important for the long-term sustainability of grasslands. For 4 years, we manipulated temperature [ambient and increased using open-top chambers (OTC)], water (ambient, reduced using rainout shelters and increased using hand watering) and defoliation (clipped, and unclipped) in three grassland types along an elevation gradient. We monitored plant cover and biomass and found that OTC reduced biomass by 15%, but clipping and water treatments interacted with each other and their effects varied in different grassland types. For example, total biomass did not decline in the higher elevation grasslands due to clipping, and water addition mitigated the effects of clipping on subordinate grasses in the lower grasslands. The response of total biomass was driven by dominant plant species while subordinate grasses and forbs showed more variable responses. Overall, our results demonstrate that biomass in the highest elevation grassland was least effected by the treatments and the response of biomass tended to be dependent on interactions between climate change treatments and defoliation. Together, the results suggest that ecosystem function of these grasslands under altered climate patterns will be dependent on site-specific management.", "keywords": ["0106 biological sciences", "0301 basic medicine", "2. Zero hunger", "British Columbia", "Altitude", "Climate", "Climate Change", "Temperature", "Water", "15. Life on land", "Poaceae", "01 natural sciences", "03 medical and health sciences", "13. Climate action", "Biomass", "Herbivory", "Ecosystem"]}, "links": [{"href": "https://doi.org/10.1007/s00442-013-2833-2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Oecologia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00442-013-2833-2", "name": "item", "description": "10.1007/s00442-013-2833-2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00442-013-2833-2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-11-19T00:00:00Z"}}, {"id": "10.1007/s00442-013-2845-y", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-09-20T16:14:26Z", "type": "Journal Article", "created": "2013-12-20", "title": "Climate Change Interactions Affect Soil Carbon Dioxide Efflux And Microbial Functioning In A Post-Harvest Forest", "description": "Forest disturbances, including whole-tree harvest, will increase with a growing human population and its rising affluence. Following harvest, forests become sources of C to the atmosphere, partly because wetter and warmer soils (relative to pre-harvest) increase soil CO2 efflux. This relationship between soil microclimate and CO2 suggests that climate changes predicted for the northeastern US may exacerbate post-harvest CO2 losses. We tested this hypothesis using a climate-manipulation experiment within a recently harvested northeastern US forest with warmed (H; +2.5 \u00b0C), wetted (W; +23% precipitation), warmed + wetted (H+W), and ambient (A) treatments. The cumulative soil CO2 effluxes from H and W were 35% (P = 0.01) and 22% (P = 0.07) greater than A. However, cumulative efflux in H+W was similar to A and W, and 24% lower than in H (P = 0.02). These findings suggest that with higher precipitation soil CO2 efflux attenuates rapidly to warming, perhaps due to changes in substrate availability or microbial communities. Microbial function measured as CO2 response to 15 C substrates in warmed soils was distinct from non-warmed soils (P < 0.001). Furthermore, wetting lowered catabolic evenness (P = 0.04) and fungi-to-bacteria ratios (P = 0.03) relative to non-wetted treatments. A reciprocal transplant incubation showed that H+W microorganisms had lower laboratory respiration on their home soils (i.e., home substrates) than on soils from other treatments (P < 0.01). We inferred that H+W microorganisms may use a constrained suite of C substrates that become depleted in their 'home' soils, and that in some disturbed ecosystems, a precipitation-induced attenuation (or suppression) of soil CO2 efflux to warming may result from fine-tuned microbe-substrate linkages.", "keywords": ["2. Zero hunger", "Bacteria", "Climate", "Climate Change", "Fungi", "Temperature", "04 agricultural and veterinary sciences", "Carbon Dioxide", "Pennsylvania", "15. Life on land", "Trees", "Soil", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "Ecosystem", "Soil Microbiology"], "contacts": [{"organization": "Marshall D. McDaniel, Mary Ann Bruns, Jason P. Kaye, Margot W. Kaye,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s00442-013-2845-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Oecologia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00442-013-2845-y", "name": "item", "description": "10.1007/s00442-013-2845-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00442-013-2845-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-12-21T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Temperature&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=Temperature&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=Temperature&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Temperature&offset=50", "hreflang": "en-US"}], "numberMatched": 727, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-09-20T17:57:02.242909Z"}