{"type": "FeatureCollection", "features": [{"id": "10.3389/fbioe.2019.00378", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:35Z", "type": "Journal Article", "created": "2019-12-04", "title": "Thickness of Polyelectrolyte Layers of Separately Confined Bacteria Alters Key Physiological Parameters on a Single Cell Level", "description": "Confinement of bacterial cells in a matrix or in capsules is an integral part of many biotechnological applications. Here, the well-known layer-by-layer method of deposition of a polyelectrolyte film a few nanometers in thickness to confine separated bacterial cells in permeable and physically durable shells has been examined. Due to the physical properties of such a confinement, we found that this method enables investigation of effects of physical barriers against mass gain and cell division. Using the method of time-lapse confocal microscopy, we observed a prolonged lag phase, dependent on the number of polyelectrolyte layers. In the confinement, both the GFP fluorescent signal from the leaking T7 promoter and the cell size were increased by factors of more than five and two, respectively. This creates a paradigm shift that enables use of mechanical entrapment for control of bacterial cell physiology and opens possibilities of controlling the division rate as well as gene expression. These effects can be attributed to the perturbation of the sensing of the cell size, which results in disproportional synthesis of a cell envelope impinging the intracellular material and compels cells to grow rapidly. In addition, the charged surface of cells enables prolonged intercellular physical interaction and results in spherically shaped microcolonies.", "keywords": ["polyelectrolytes", "0301 basic medicine", "0303 health sciences", "03 medical and health sciences", "layer-by-layer encapsulation", "time-lapse confocal microscopy", " polyelectrolytes", " layer-by-layer encapsulation", " electrostatic interactions", " cell surface modification", "cell surface modification", "Bioengineering and Biotechnology", "electrostatic interactions", "time-lapse confocal microscopy", "TP248.13-248.65", "Biotechnology"]}, "links": [{"href": "https://doi.org/10.3389/fbioe.2019.00378"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Bioengineering%20and%20Biotechnology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fbioe.2019.00378", "name": "item", "description": "10.3389/fbioe.2019.00378", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fbioe.2019.00378"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-12-04T00:00:00Z"}}, {"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": "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": "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": "10.1007/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"}}, {"id": "10.1007/s10533-009-9381-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:42Z", "type": "Journal Article", "created": "2009-10-13", "title": "Plant-Soil Interactions And Acclimation To Temperature Of Microbial-Mediated Soil Respiration May Affect Predictions Of Soil Co2 Efflux", "description": "Open AccessPeer reviewed", "keywords": ["Life Sciences", " general", "Carbon cycle modeling", "2. Zero hunger", "Ecosystem ecology", "Life Sciences", "Soil respiration", "04 agricultural and veterinary sciences", "15. Life on land", "Biogeosciences", "Ecosystems", "6. Clean water", "general", "13. Climate action", "Earth Sciences", "Environmental Chemistry", "Climate change", "0401 agriculture", " forestry", " and fisheries", "Earth-Surface Processes", "Water Science and Technology"]}, "links": [{"href": "https://escholarship.org/content/qt74h8k7gh/qt74h8k7gh.pdf"}, {"href": "https://doi.org/10.1007/s10533-009-9381-1"}, {"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/s10533-009-9381-1", "name": "item", "description": "10.1007/s10533-009-9381-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10533-009-9381-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-10-14T00:00:00Z"}}, {"id": "10.1016/j.agrformet.2018.02.033", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:10Z", "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.eurpolymj.2019.03.002", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:33Z", "type": "Journal Article", "created": "2019-03-05", "title": "Exploring the potential of gas-phase esterification to hydrophobize the surface of micrometric cellulose particles", "description": "In order to lift the barrier of a poor interfacial interaction between cellulosic plant fibers and polymeric matrices in biocomposites, an eco-friendly surface modification of fibers was explored. A solvent-free gas-phase ester-ification applied to cellulose particles allowed to graft palmitoyl moieties on their surface in order to make them more compatible with non-polar polymers for composite applications. The efficiency of the treatment was evidenced from FT-IR analysis, and the degree of substitution (DS) was quantified by solid-state 13 C NMR spectroscopy. The effect of surface grafting on resulting intrinsic characteristics of cellulose particles, i.e. crys-tallinity, thermal stability, morphology, surface free energy and water vapor sorption were investigated respectively by X-ray diffraction, thermogravimetric analysis, SEM observations coupled with image analysis, contact angle measurements and dynamic vapor sorption system (DVS). It was shown that a DS as low as 0.01 was enough to drastically increase the hydrophobicity of cellulose particles without affecting the inner properties of cellulose.", "keywords": ["660", "Degree of substitution", "Surface free energy", "est\u00e9rification", "matrice polym\u00e9rique", "cristallinit\u00e9", "Ing\u00e9nierie des aliments", "Gas-phase esterification", "02 engineering and technology", "[SDV.IDA] Life Sciences [q-bio]/Food engineering", "540", "Water vapor sorption", "01 natural sciences", "Cellulose;Gas-phase esterification;Degree of substitution;Surface free energy;Crystallinity;Water vapor sorption", "sorption de l'eau", "0104 chemical sciences", "[SDV.IDA]Life Sciences [q-bio]/Food engineering", "biomat\u00e9riau", "Food engineering", "fibre cellulosique", "Cellulose", "0210 nano-technology", "Crystallinity"]}, "links": [{"href": "https://doi.org/10.1016/j.eurpolymj.2019.03.002"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/European%20Polymer%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.eurpolymj.2019.03.002", "name": "item", "description": "10.1016/j.eurpolymj.2019.03.002", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.eurpolymj.2019.03.002"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-06-01T00:00:00Z"}}, {"id": "012ce7af-7212-41e1-96da-a38fbd32fd7c", "type": "Feature", "geometry": null, "properties": {"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": {"updated": "2026-09-19T16:26:52Z", "type": "Report", "title": "Global maps of soil temperature.", "description": "Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km <sup>2</sup> resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km <sup>2</sup> pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10\u00b0C (mean = 3.0 \u00b1 2.1\u00b0C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 \u00b1 2.3\u00b0C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 \u00b1 2.3\u00b0C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.", "keywords": ["Climate Change; Ecosystem; Microclimate; Soil; Temperature; bioclimatic variables; global maps; microclimate; near-surface temperatures; soil temperature; soil-dwelling organisms; temperature offset; weather stations"], "contacts": [{"organization": "Lembrechts, J.J., van den Hoogen, J., Aalto, J., Ashcroft, M.B., De Frenne, P., Kemppinen, J., Kopeck\u00fd, M., Luoto, M., Maclean, IMD, Crowther, T.W., Bailey, J.J., Haesen, S., Klinges, D.H., Niittynen, P., Scheffers, B.R., Van Meerbeek, K., Aartsma, P., Abdalaze, O., Abedi, M., Aerts, R., Ahmadian, N., Ahrends, A., Alatalo, J.M., Alexander, J.M., Allonsius, C.N., Altman, J., Ammann, C., Andres, C., Andrews, C., Ard\u00f6, J., Arriga, N., Arzac, A., Aschero, V., Assis, R.L., Assmann, J.J., Bader, M.Y., Bahalkeh, K., Baran\u010dok, P., Barrio, I.C., Barros, A., Barthel, M., Basham, E.W., Bauters, M., Bazzichetto, M., Marchesini, L.B., Bell, M.C., Benavides, J.C., Benito Alonso, J.L., Berauer, B.J., Bjerke, J.W., Bj\u00f6rk, R.G., Bj\u00f6rkman, M.P., Bj\u00f6rnsd\u00f3ttir, K., Blonder, B., Boeckx, P., Boike, J., Bokhorst, S., Brum, BNS, Br\u016fna, J., Buchmann, N., Buysse, P., Camargo, J.L., Campoe, O.C., Candan, O., Canessa, R., Cannone, N., Carbognani, M., Carnicer, J., Casanova-Katny, A., Cesarz, S., Chojnicki, B., Choler, P., Chown, S.L., Cifuentes, E.F., \u010ciliak, M., Contador, T., Convey, P., Cooper, E.J., Cremonese, E., Curasi, S.R., Curtis, R., Cutini, M., Dahlberg, C.J., Daskalova, G.N., de Pablo, M.A., Della Chiesa, S., Dengler, J., Deronde, B., Descombes, P., Di Cecco, V., Di Musciano, M., Dick, J., Dimarco, R.D., Dolezal, J., Dorrepaal, E., Du\u0161ek, J., Eisenhauer, N., Eklundh, L., Erickson, T.E., Erschbamer, B., Eugster, W., Ewers, R.M., Exton, D.A., Fanin, N., Fazlioglu, F., Feigenwinter, I., Fenu, G., Ferlian, O., Fern\u00e1ndez Calzado, M.R., Fern\u00e1ndez-Pascual, E., Finckh, M., Higgens, R.F., Forte, TGW, Freeman, E.C., Frei, E.R., Fuentes-Lillo, E., Garc\u00eda, R.A., Garc\u00eda, M.B., G\u00e9ron, C., Gharun, M., Ghosn, D., Gigauri, K., Gobin, A., Goded, I., Goeckede, M., Gottschall, F., Goulding, K., Govaert, S., Graae, B.J., Greenwood, S., Greiser, C., Grelle, A., Gu\u00e9nard, B., Guglielmin, M., Guillemot, J., Haase, P., Haider, S., Halbritter, A.H., Hamid, M., Hammerle, A., Hampe, A., Haugum, S.V., Hederov\u00e1, L., Heinesch, B., Helfter, C., Hepenstrick, D., Herberich, M., Herbst, M., Hermanutz, L., Hik, D.S., Hoffr\u00e9n, R., Homeier, J., H\u00f6rtnagl, L., H\u00f8ye, T.T., Hrbacek, F., Hylander, K., Iwata, H., Jackowicz-Korczynski, M.A., Jactel, H., J\u00e4rveoja, J., Jastrz\u0119bowski, S., Jentsch, A., Jim\u00e9nez, J.J., J\u00f3nsd\u00f3ttir, I.S., Jucker, T., Jump, A.S., Juszczak, R., Kanka, R., Ka\u0161par, V., Kazakis, G., Kelly, J., Khuroo, A.A., Klemedtsson, L., Klisz, M., Kljun, N., Knohl, A., Kobler, J., Koll\u00e1r, J., Kotowska, M.M., Kov\u00e1cs, B., Kreyling, J., Lamprecht, A., Lang, S.I., Larson, C., Larson, K., Laska, K., le Maire, G., Leihy, R.I., Lens, L., Liljebladh, B., Lohila, A., Lorite, J., Loubet, B., Lynn, J., Macek, M., Mackenzie, R., Magliulo, E., Maier, R., Malfasi, F., M\u00e1li\u0161, F.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/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": {"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). Corsa del 2025-04-30 ore 00 UTC - Valido dalle ore 00 UTC del 2025-04-30 alle ore 00 UTC del 2025-05-03. 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", "2025-04-30", "20250430t000000000z", "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-2025-04-30-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_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_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_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_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_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_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_20250430T000000000Z/arw_3km_Soil_temperature_layer_between_two_depths_below_surface_layer_20250430T000000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/0233df11-412c-4c84-a9b2-7eb9dc3409d4"}, {"rel": "self", "type": "application/geo+json", "title": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "name": "item", "description": "0233df11-412c-4c84-a9b2-7eb9dc3409d4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0233df11-412c-4c84-a9b2-7eb9dc3409d4"}, {"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": "PMC11468586", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:23:33Z", "type": "Journal Article", "created": "2021-09-08", "title": "Wafer\u2010Scale Functional Metasurfaces for Mid\u2010Infrared Photonics and Biosensing", "description": "Abstract

Metasurfaces have emerged as a breakthrough platform for manipulating light at the nanoscale and enabling on\uffe2\uff80\uff90demand optical functionalities for next\uffe2\uff80\uff90generation biosensing, imaging, and light\uffe2\uff80\uff90generating photonic devices. However, translating this technology to practical applications requires low\uffe2\uff80\uff90cost and high\uffe2\uff80\uff90throughput fabrication methods. Due to the limited choice of materials with suitable optical properties, it is particularly challenging to produce metasurfaces for the technologically relevant mid\uffe2\uff80\uff90infrared spectral range. These constraints are overcome by realizing functional metasurfaces on almost completely transparent free\uffe2\uff80\uff90standing metal\uffe2\uff80\uff90oxide membranes. A versatile nanofabrication process is developed and implemented for highly efficient dielectric and plasmonic mid\uffe2\uff80\uff90infrared metasurfaces with wafer\uffe2\uff80\uff90scale and complementary metal\uffe2\uff80\uff93oxide\uffe2\uff80\uff93semiconductor (CMOS)\uffe2\uff80\uff90compatible manufacturing techniques. The advantages of this method are revealed by demonstrating highly uniform and functional metasurfaces, including high\uffe2\uff80\uff90Q structures enabling fine spectral selectivity, large\uffe2\uff80\uff90area metalenses\uffc2\uffa0with\uffc2\uffa0diffraction\uffe2\uff80\uff90limited focusing capabilities, and birefringent metasurfaces providing polarization control at record\uffe2\uff80\uff90high conversion efficiencies.\uffc2\uffa0 Aluminum plasmonic devices and their integration into microfluidics for real\uffe2\uff80\uff90time and label\uffe2\uff80\uff90free mid\uffe2\uff80\uff90infrared biosensing of proteins and lipid vesicles are further demonstrated. The versatility of this approach and its compatibility with mass\uffe2\uff80\uff90production processes bring infrared metasurfaces markedly closer to commercial applications, such as thermal imaging, spectroscopy, and biosensing.