{"type": "FeatureCollection", "features": [{"id": "10.1111/gcb.12819", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:18:44Z", "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": "10.3389/fpls.2019.00191", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:20:50Z", "type": "Journal Article", "created": "2019-02-22", "title": "Interannual and Seasonal Dynamics of Volatile Organic Compound Fluxes From the Boreal Forest Floor", "description": "In the northern hemisphere, boreal forests are a major source of biogenic volatile organic compounds (BVOCs), which drive atmospheric processes and lead to cloud formation and changes in the Earth's radiation budget. Although forest vegetation is known to be a significant source of BVOCs, the role of soil and the forest floor, and especially interannual variations in fluxes, remains largely unknown due to a lack of long-term measurements. Our aim was to determine the interannual, seasonal and diurnal dynamics of boreal forest floor volatile organic compound (VOC) fluxes and to estimate how much they contribute to ecosystem VOC fluxes. We present here an 8-year data set of forest floor VOC fluxes, measured with three automated chambers connected to the quadrupole proton transfer reaction mass spectrometer (quadrupole PTR-MS). The exceptionally long data set shows that forest floor fluxes were dominated by monoterpenes and methanol, with relatively comparable emission rates between the years. Weekly mean monoterpene fluxes from the forest floor were highest in spring and in autumn (maximum 59 and 86 \u03bcg m-2 h-1, respectively), whereas the oxygenated VOC fluxes such as methanol had highest weekly mean fluxes in spring and summer (maximum 24 and 79 \u03bcg m-2 h-1, respectively). Although the chamber locations differed from each other in emission rates, the inter-annual dynamics were very similar and systematic. Accounting for this chamber location dependent variability, temperature and relative humidity, a mixed effects linear model was able to explain 79-88% of monoterpene, methanol, acetone, and acetaldehyde fluxes from the boreal forest floor. The boreal forest floor was a significant contributor in the forest stand fluxes, but its importance varies between seasons, being most important in autumn. The forest floor emitted 2-93% of monoterpene fluxes in spring and autumn and 1-72% of methanol fluxes in spring and early summer. The forest floor covered only a few percent of the forest stand fluxes in summer.", "keywords": ["VOC EMISSIONS", "Plant Science", "ATMOSPHERIC OH", "01 natural sciences", "forest floor", "SB1-1110", "MONOTERPENE EMISSIONS", "vegetation", "biogenic volatile organic compound", "11. Sustainability", "SCOTS PINE", "EXCHANGE", "0105 earth and related environmental sciences", "decomposition", "CLIMATE-CHANGE", "seasonality", "temperature", "Plant culture", "Forestry", "15. Life on land", "SOIL", "MODEL", "Environmental sciences", "flux", "13. Climate action", "PTR-TOF", "METHANOL"]}, "links": [{"href": "https://doi.org/10.3389/fpls.2019.00191"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fpls.2019.00191", "name": "item", "description": "10.3389/fpls.2019.00191", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fpls.2019.00191"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-22T00:00:00Z"}}, {"id": "10.5281/zenodo.15096788", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:22:57Z", "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": "2026-07-25T16:23:43Z", "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": "1871.1/0b041c5c-edd1-45f1-895d-546207d34a0a", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:25:17Z", "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": "10.1007/s13595-016-0547-4", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:15:29Z", "type": "Journal Article", "created": "2016-03-24", "title": "Effects Of Experimental Warming On Soil Respiration And Biomass In Quercus Variabilis Blume And Pinus Densiflora Sieb. Et Zucc. Seedlings", "description": "AbstractKey messageIn the open-field warming experiment using infrared heaters, 3\u00a0\u00b0C warming affected soil respiration more in the deciduousQuercus variabilisBlume plot than in the evergreenPinus densifloraSieb. et Zucc. plot, but did not affect the plant biomass in either species.ContextUnderstanding the species-specific responses of belowground carbon processes to warming is essential for the accurate prediction of forest carbon cycles in ecosystems affected by future climate change.AimsThis study aimed to investigate the effect of experimental warming on soil CO2 efflux, soil-air CO2 concentration, and plant biomass for two taxonomically different temperate tree species.MethodsExperimental warming was conducted in an open-field planted with Q. variabilis and P. densiflora seedlings. Infrared heaters increased the air temperature by 3\u00a0\u00b0C in the warmed plots compared with the air temperature in the control plots over a 2-year period.ResultsThe increase in air and soil temperature stimulated soil CO2 efflux by 29 and 22\u00a0% for the Q. variabilis and P. densiflora plots, respectively. Seasonal variation in the warming effect on soil CO2 efflux was species-specific. Soil CO2 efflux was also positively related to both soil temperature and soil water content. The soil moisture deficit decreased the difference in soil CO2 efflux between the control and warmed plots. Warming did not affect soil CO2 concentration and plant biomass in either species; however, the mean soil CO2 concentration was positively correlated with root and total biomass.ConclusionWarming increased soil CO2 efflux in both Q. variabilis and P. densiflora plots, while the increase showed remarkable seasonal variations and different magnitudes for the two species.", "keywords": ["0106 biological sciences", "soil temperature", "evergreen tree", "soil water", "Red pine", "seedling", "soil respiration", "01 natural sciences", "experimental study", "Pinus resinosa", "Climate change", "Pinus densiflora", "seasonal variation", "concentration (composition)", "Quercus variabilis", "Oriental oak", "carbon dioxide", "Soil respiration", "04 agricultural and veterinary sciences", "15. Life on land", "air temperature", "carbon flux", "[SDV] Life Sciences [q-bio]", "climate change", "13. Climate action", "coniferous tree", "phytomass", "0401 agriculture", " forestry", " and fisheries", "Experimental warming", "soil moisture", "deciduous tree"]}, "links": [{"href": "https://doi.org/10.1007/s13595-016-0547-4"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Annals%20of%20Forest%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s13595-016-0547-4", "name": "item", "description": "10.1007/s13595-016-0547-4", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s13595-016-0547-4"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-03-24T00:00:00Z"}}, {"id": "10.1016/j.agrformet.2018.04.010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:15:42Z", "type": "Journal Article", "created": "2018-04-19", "title": "A phenomenological model of soil evaporative efficiency using surface soil moisture and temperature data", "description": "Abstract   Modeling soil evaporation has been a notorious challenge due to the complexity of the phenomenon and the lack of data to constrain it. In this context, a parsimonious model is developed to estimate soil evaporative efficiency (SEE) defined as the ratio of actual to potential soil evaporation. It uses a soil resistance driven by surface (0\u20135\u202fcm) soil moisture, meteorological forcing and time (hour) of day, and has the capability to be calibrated using the radiometric surface temperature derived from remotely sensed thermal data. The new approach is tested over a rainfed semi-arid site, which had been under bare soil conditions during a 9-month period in 2016. Three calibration strategies are adopted based on SEE time series derived from (1) eddy-covariance measurements, (2) thermal measurements, and (3) eddy-covariance measurements used only over separate drying periods between significant rainfall events. The correlation coefficients (and slopes of the linear regression) between simulated and observed (eddy-covariance-derived) SEE are 0.85, 0.86 and 0.87 (and 0.91, 0.87 and 0.91) for calibration strategies 1, 2 and 3, respectively. Moreover, the correlation coefficient (and slope of the linear regression) between simulated and observed SEE is improved from 0.80 to 0.85 (from 0.86 to 0.91) when including hour of day in the soil resistance. The reason is that, under non-energy-limited conditions, the receding evaporation front during daytime makes SEE decrease at the hourly time scale. The soil resistance formulation can be integrated into state-of-the-art dual-source surface models and has calibration capabilities across a range of spatial scales from spaceborne microwave and thermal data.", "keywords": ["550", "0207 environmental engineering", "Soil resistance", "02 engineering and technology", "Remote sensing", "15. Life on land", "calibration", "surface temperature", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Surface temperature", "remote sensing", "Calibration", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "soil resistance", "Soil moisture", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "soil moisture", "environment", "Soil evaporation"]}, "links": [{"href": "https://doi.org/10.1016/j.agrformet.2018.04.010"}, {"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.2018.04.010", "name": "item", "description": "10.1016/j.agrformet.2018.04.010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2018.04.010"}, {"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.agwat.2017.08.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:15:44Z", "type": "Journal Article", "created": "2017-08-10", "title": "Performance of the two-source energy budget (TSEB) model for the monitoring of evapotranspiration over irrigated annual crops in North Africa", "description": "Abstract   The main objective of this study was to evaluate the performance and the domain of validity of the two-source energy balance model (TSEB) for the monitoring of actual evapotranspiration ( ET a  ) as a first step towards its use for irrigation planning. Secondary objectives were to analyze the ability of TSEB model to detect water stress and to evaluate evapotranspiration partition between evaporation (E) and transpiration (T) over irrigated annual crops. Within this context, TSEB was compared to the calibrated FAO-56 dual approach, taken as a reference tool for the monitoring of crop water consumption. TSEB computes  ET a   as the residual of a double component energy balance driven by the radiative surface temperature ( T s  ) used as a proxy of crop hydric conditions; the FAO-56 dual crop coefficient approach uses the Normalized Difference Vegetation Index (NDVI) as a proxy of Basal Crop Coefficient ( K cb  ) and assesses the hydric status directly by solving a two layer soil water budget. Both approaches were evaluated over four plots of wheat and sugar beet located in the Haouz plain (Marrakech, Morocco) that were instrumented with eddy covariance systems during the 2012 and 2013 growing seasons. Series of ASTER images were acquired during the first agricultural season. Both models offered fair performances compared to  ET a   observations with Root Mean Square Error (RMSE) lower than 1\u00a0mm\u00a0day \u22121  apart from the FAO-56 dual approach on the sugar beet plot because of uncertain irrigation inputs. This highlights a major weakness of this model when water inputs are uncertain; a very likely case at the plot scale. By contrast, the TSEB model offered smoother performances in all cases. The potentialities of both approaches to predict a water stress index based on the departure from potential evapotranspiration ( ET  c ) was evaluated: although the FAO-56 dual was better suited to detect high water stresses, the TSEB model was able to detect moderate stresses without a need to prescribe water inputs. Finally, the partition of  ET a   between soil evaporation and plant transpiration was estimated indirectly by confrontation between simulated soil evaporation and surface (0\u20135\u00a0cm) soil moisture acquired spatially with Theta Probe sensors and taken as a proxy of soil evaporation. TSEB evaporation was well correlated to surface soil moisture (r\u00a0=\u00a00.82) for low Leaf Area Index (LAI) values ( 2 \u00a0m \u22122 ). In addition, TSEB predicted partition compared well to snapshot measurements based on the stable isotope method. This in-depth comparison of two simple tools to monitor  ET a   leads us to the conclusion that the TSEB model can reasonably be used to map  ET a   on large scale and possibly for the decision-making process of irrigation scheduling.", "keywords": ["FAO-56", "2. Zero hunger", "550", "Evapotranspiration", "NDVI", "Water stress", "0207 environmental engineering", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "6. Clean water", "Surface temperature", "0401 agriculture", " forestry", " and fisheries", "TSEB"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2017.08.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2017.08.007", "name": "item", "description": "10.1016/j.agwat.2017.08.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2017.08.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-11-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2011.04.003", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:17:04Z", "type": "Journal Article", "created": "2011-05-01", "title": "Effects Of Elevated Atmospheric Co2, Prolonged Summer Drought And Temperature Increase On N2o And Ch4 Fluxes In A Temperate Heathland", "description": "Abstract   In temperate regions, climate change is predicted to increase annual mean temperature and intensify the duration and frequency of summer droughts, which together with elevated atmospheric carbon dioxide (CO 2 ) concentrations, may affect the exchange of nitrous oxide (N 2 O) and methane (CH 4 ) between terrestrial ecosystems and the atmosphere. We report results from the CLIMAITE experiment, where the effects of these three climate change parameters were investigated solely and in all combinations in a temperate heathland. Field measurements of N 2 O and CH 4  fluxes took place 1\u20132 years after the climate change manipulations were initiated. The soil was generally a net sink for atmospheric CH 4 . Elevated temperature (T) increased the CH 4  uptake by on average 10\u00a0\u03bcg C\u00a0m \u22122 \u00a0h \u22121 , corresponding to a rise in the uptake rate of about 20%. However, during winter elevated CO 2  (CO 2 ) reduced the CH 4  uptake, which outweighed the positive effect of warming when analyzed across the study period. Emissions of N 2 O were generally low ( \u22122 \u00a0h \u22121 ). As single experimental factors, elevated CO 2 , temperature and summer drought (D) had no major effect on the N 2 O fluxes, but the combination of CO 2  and warming (TCO 2 ) stimulated N 2 O emission, whereas the N 2 O emission ceased when CO 2  was combined with drought (DCO 2 ). We suggest that these N 2 O responses are related to increased rhizodeposition under elevated CO 2  combined with increased and reduced nitrogen turnover rates caused by warming and drought, respectively. The N 2 O flux in the multifactor treatment TDCO 2  was not different from the ambient control treatment. Overall, our study suggests that in the future, CH 4  uptake may increase slightly, while N 2 O emission will remain unchanged in temperate ecosystems on well-aerated soils. However, we propose that continued exposure to altered climate could potentially change the greenhouse gas flux pattern in the investigated heathland.", "keywords": ["summer", "FLUXES", "ELEVATED ATMOSPHERIC CO2", "CH4", "CH4 FLUX", "N2O", "temperature", "/dk/atira/pure/sustainabledevelopmentgoals/life_on_land; name=SDG 15 - Life on Land", "drought", "Environment and climate", "04 agricultural and veterinary sciences", "heathland", "15. Life on land", "Milj\u00f8 og klima", "6. Clean water", "flux", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "CO2", "/dk/atira/pure/sustainabledevelopmentgoals/climate_action; name=SDG 13 - Climate Action", "ATMOSPHERIC CO2", "temperate"]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2011.04.003"}, {"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.2011.04.003", "name": "item", "description": "10.1016/j.soilbio.2011.04.003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2011.04.003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-08-01T00:00:00Z"}}, {"id": "10.1016/j.chemosphere.2013.12.024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:01Z", "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": "oai:digibug.ugr.es:10481/73202", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:32:27Z", "type": "Report", "title": "Global maps of soil temperature", "description": "Atribuci\u00f3n-NoComercial 3.0 Espa\u00f1aResearch 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 p ixels ( summarized f rom 8 519 u nique t emperature 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": ["Bioclimatic variables", "Global maps", "Soil temperature", "Temperature offset", "Weather stations", "Microclimate", "Near-surface temperatures", "Soil-dwelling organisms"], "contacts": [{"organization": "Lembrechts, Jonas J., Fern\u00e1ndez Calzado, Mar\u00eda Rosa, Lorite Moreno, Juan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/oai:digibug.ugr.es:10481/73202"}, {"rel": "self", "type": "application/geo+json", "title": "oai:digibug.ugr.es:10481/73202", "name": "item", "description": "oai:digibug.ugr.es:10481/73202", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/oai:digibug.ugr.es:10481/73202"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-08T00:00:00Z"}}, {"id": "oai:DiVA.org:umu-219790", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:32:26Z", "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/oai:DiVA.org:umu-219790"}, {"rel": "self", "type": "application/geo+json", "title": "oai:DiVA.org:umu-219790", "name": "item", "description": "oai:DiVA.org:umu-219790", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/oai:DiVA.org:umu-219790"}, {"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": "oai:serval.unil.ch:BIB_38E93A02220B", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:32:32Z", "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": "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. 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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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In this study, we investigated the differences in the stability (resistance and resilience) of microbial community composition and enzyme activities in adjacent soils under either native tropical forest (FST) or in agricultural cropping use for 14 years (AGR). Mineral soil samples (0 to 5 cm) from both areas were incubated at 40 degrees C, 50 degrees C, 60 degrees C, or 70 degrees C for 15 min in order to successively reduce the microbial biomass. Three and 30 days after the heat shocks, fluorescein diacetate (FDA) hydrolysis, cellulase and laccase activities, and phospholipid-derived fatty acids-based microbial community composition were measured. Microbial biomass was reduced up to 25% in both soils 3 days after the heat shocks. The higher initial values of microbial biomass, enzyme activity, total and particulate soil organic carbon, and aggregate stability in the FST soil coincided with higher enzymatic stability after heat shocks. FDA hydrolysis activity was less affected (more resistance) and cellulase and laccase activities recovered more rapidly (more resilience) in the FST soil relative to the AGR counterpart. In the AGR soil, laccase activity did not show resilience to any heat shock level up to 30 days after the disturbance. Within each soil type, the microbial community composition did not differ between heat shock and control samples at day 3. However, at day 30, FST soil samples treated at 60 degrees C and 70 degrees C contained a microbial community significantly different from the control and with lower biomass regardless of high enzyme resilience. Results of this study show that deforestation followed by long-term cultivation changed microbial community composition and had differential effects on microbial functional stability. Both soils displayed similar resilience to FDA hydrolysis, a composite measure of a broad range of hydrolases, supporting the concept of high functional redundancy in soil microbial communities. In contrast, the resilience of the substrate-specific activities of laccase and cellulase were lower in AGR soils, indicating a less diverse community of microorganisms capable of producing these enzymes and confirming that specific microbial functions are more sensitive measurements for evaluating change in the ecological stability of soils.", "keywords": ["2. Zero hunger", "Hot Temperature", "Laccase", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Fluoresceins", "6. 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INSPIRE themes, version 1.0"}, {"concepts": [{"id": "Soil"}, {"id": "soil respiration"}, {"id": "soil air"}, {"id": "soil temperature"}, {"id": "soil water content"}, {"id": "Fagus sylvatica"}, {"id": "Pinus sylvestris"}, {"id": "measurement"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Soil"}, {"id": "soil respiration"}, {"id": "soil air"}, {"id": "soil temperature"}, {"id": "soil water content"}, {"id": "Fagus sylvatica"}, {"id": "Pinus sylvestris"}, {"id": "measurement"}], "scheme": "AGROVOC Multilingual agricultural thesaurus"}, {"concepts": [{"id": "Germany"}, {"id": "Brandenburg"}, {"id": "Barnim"}, {"id": "Ostprignitz-Ruppin"}], "scheme": "individual"}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=0d41a483-52b2-464f-b526-3ae29e6ad089", "rel": "information"}, {"href": "https://maps.bonares.de/wss/service/ags-relay/ags/guest/arcgis/rest/services/Zalf/ID_4731_both_sites/MapServer/WMSServer?request=GetCapabilities&service=WMS"}, {"rel": "self", "type": "application/geo+json", "title": "0d41a483-52b2-464f-b526-3ae29e6ad089", "name": "item", "description": "0d41a483-52b2-464f-b526-3ae29e6ad089", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/0d41a483-52b2-464f-b526-3ae29e6ad089"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-05T00:00:00Z"}}, {"id": "10.1002/2015gb005239", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:19Z", "type": "Journal Article", "created": "2015-12-19", "title": "Toward More Realistic Projections Of Soil Carbon Dynamics By Earth System Models", "description": "Abstract<p>Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). 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": "2026-07-25T16:14:19Z", "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": "2026-07-25T16:14:19Z", "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": "2026-07-25T16:14:22Z", "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": "2026-07-25T16:14:21Z", "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": "10.1002/joc.1276", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:24Z", "type": "Journal Article", "created": "2005-11-30", "title": "Very High Resolution Interpolated Climate Surfaces For Global Land Areas", "description": "(Uploaded by Plazi for the Bat Literature Project) We developed interpolated climate surfaces for global land areas (excluding Antarctica) at a spatial resolution of 30 arc s (often referred to as 1-km spatial resolution). 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. Climate action", "Mammalia", "sistemas de informaci\u00f3n geogr\u00e1fica", "data processing"]}, "links": [{"href": "https://doi.org/10.1002/joc.1276"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/International%20Journal%20of%20Climatology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/joc.1276", "name": "item", "description": "10.1002/joc.1276", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/joc.1276"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2005-01-01T00:00:00Z"}}, {"id": "10.1016/j.chemosphere.2018.01.019", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:01Z", "type": "Journal Article", "created": "2018-01-08", "title": "Toxicokinetics of Zn and Cd in the earthworm Eisenia andrei exposed to metal-contaminated soils under different combinations of air temperature and soil moisture content", "description": "This study evaluated how different combinations of air temperature (20\u202f\u00b0C and 25\u202f\u00b0C) and soil moisture content (50% and 30% of the soil water holding capacity, WHC), reflecting realistic climate change scenarios, affect the bioaccumulation kinetics of Zn and Cd in the earthworm Eisenia andrei. Earthworms were exposed for 21\u202fd to two metal-contaminated soils (uptake phase), followed by 21\u202fd incubation in non-contaminated soil (elimination phase). Body Zn and Cd concentrations were checked in time and metal uptake (k1) and elimination (k2) rate constants determined; metal bioaccumulation factor (BAF) was calculated as k1/k2. Earthworms showed extremely fast uptake and elimination of Zn, regardless of the exposure level. Climate conditions had no major impacts on the bioaccumulation kinetics of Zn, although a tendency towards lower k1 and k2 values was observed at 25\u00a0\u00b0C\u00a0+\u00a030% WHC. Earthworm Cd concentrations gradually increased with time upon exposure to metal-contaminated soils, especially at 50% WHC, and remained constant or slowly decreased following transfer to non-contaminated soil. Different combinations of air temperature and soil moisture content changed the bioaccumulation kinetics of Cd, leading to higher k1 and k2 values for earthworms incubated at 25\u00a0\u00b0C\u00a0+\u00a050% WHC and slower Cd kinetics at 25\u00a0\u00b0C\u00a0+\u00a030% WHC. This resulted in greater BAFs for Cd at warmer and drier environments which could imply higher toxicity risks but also of transfer of Cd within the food chain under the current global warming perspective.", "keywords": ["Soil invertebrates", "Bioavailability", "Climate Change", "0211 other engineering and technologies", "02 engineering and technology", "Global Warming", "01 natural sciences", "Soil", "Metals", " Heavy", "SDG 13 - Climate Action", "Climate change", "Animals", "Soil Pollutants", "Oligochaeta", "0105 earth and related environmental sciences", "2. Zero hunger", "Triazines", "Temperature", "Water", "Bioaccumulation", "Mining wastes", "Toxicokinetics", "Zinc", "Heavy metals", "Metals", "13. Climate action", "Environmental Pollution", "Cadmium"]}, "links": [{"href": "https://doi.org/10.1016/j.chemosphere.2018.01.019"}, {"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.2018.01.019", "name": "item", "description": "10.1016/j.chemosphere.2018.01.019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.chemosphere.2018.01.019"}, {"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": "10.1007/s00248-007-9295-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:41Z", "type": "Journal Article", "created": "2007-08-31", "title": "Plfa Profiling Of Microbial Community Structure And Seasonal Shifts In Soils Of A Douglas-Fir Chronosequence", "description": "The impact and frequency of forest harvesting could significantly affect soil microbial community (SMC) structure and functioning. The ability of soil microorganisms to perform biogeochemical processes is critical for sustaining forest productivity and has a direct impact on decomposition dynamics and carbon storage potential. The Wind River Canopy Crane Research Forest in SW, WA, provided a unique opportunity to study a forest chronosequence and the residual effects of harvesting on the SMC in comparison to old-growth forests. The objective of this study was to determine the effect of clear-cutting and stand age on temporal dynamics of SMC and physiological stress markers using phospholipid fatty acid (PLFA) profiling. Soil microbial PLFA profiles were determined seven times over 22 months (Nov. 02 to Sep. 04) in old-growth coniferous forest stands (300-500 years) and 8 (CC8)- or 25 (CC25)-year-old replanted clear-cuts. PLFA patterns of the SMC shifted because of clear-cutting, but seasonal temporal changes had greater shifts than differences among stand age. The microbial biomass (total PLFA) and bacterial, fungal, and selected other PLFAs were significantly reduced in CC8 but not in CC25 sites relative to the old-growth sites. An increase in stress indicators [PLFA ratios of saturated/monsaturated and (cy17:0 + cy19:0)/(16:1omega7 + 18:1omega7)] in late summer was related to water stress. Although the canopy and litter input are quite different for a 25-year clear-cut compared to virgin old-growth forest, we conclude that the composition of the microbial communities, 25 years after clear-cutting, has recovered sufficiently to be much more similar to old-growth forests than a recent clear-cut at this Pacific Northwest forest site. The study shows the potential of PLFA analysis for profiling microbial communities and their stress status under field conditions, but wide temporal shifts emphasize the need for sampling over seasons to fully interpret ecosystem management impacts on microbial populations.", "keywords": ["Washington", "Time Factors", "Bacteria", "Fatty Acids", "Fungi", "Temperature", "Eukaryota", "Water", "04 agricultural and veterinary sciences", "15. Life on land", "Pseudotsuga", "Trees", "Soil", "13. Climate action", "Animals", "0401 agriculture", " forestry", " and fisheries", "Biomass", "Seasons", "Phospholipids", "Soil Microbiology"]}, "links": [{"href": "https://doi.org/10.1007/s00248-007-9295-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microbial%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00248-007-9295-1", "name": "item", "description": "10.1007/s00248-007-9295-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00248-007-9295-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-08-31T00:00:00Z"}}, {"id": "10.1007/s00253-011-3535-5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:14:41Z", "type": "Journal Article", "created": "2011-08-17", "title": "Methanotrophic Community Structure And Activity Under Warming And Grazing Of Alpine Meadow On The Tibetan Plateau", "description": "Knowledge about methanotrophs and their activities is important to understand the microbial mediation of the greenhouse gas CH(4) under climate change and human activities in terrestrial ecosystems. The effects of simulated warming and sheep grazing on methanotrophic abundance, community composition, and activity were studied in an alpine meadow soil on the Tibetan Plateau. There was high abundance of methanotrophs (1.2-3.4\u2009\u00d7\u200910(8)                         pmoA gene copies per gram of dry weight soil) assessed by real-time PCR, and warming significantly increased the abundance regardless of grazing. A total of 64 methanotrophic operational taxonomic units (OTUs) were obtained from 1,439 clone sequences, of these OTUs; 63 OTUs (98.4%) belonged to type I methanotrophs, and only one OTU was Methylocystis of type II methanotrophs. The methanotroph community composition and diversity were not apparently affected by the treatments. Warming and grazing significantly enhanced the potential CH(4) oxidation activity. There were significantly negative correlations between methanotrophic abundance and soil moisture and between methanotrophic abundance and NH(4)-N content. The study suggests that type I methanotrophs, as the dominance, may play a key role in CH(4) oxidation, and the alpine meadow has great potential to consume more CH(4) under future warmer and grazing conditions on the Tibetan Plateau.", "keywords": ["DNA", " Bacterial", "0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Sheep", "Bacteria", "Molecular Sequence Data", "Temperature", "Sequence Analysis", " DNA", "15. Life on land", "Real-Time Polymerase Chain Reaction", "Tibet", "Biota", "Soil", "03 medical and health sciences", "Ammonia", "13. Climate action", "Animals", "Methane", "Oxidation-Reduction", "Soil Microbiology"]}, "links": [{"href": "https://doi.org/10.1007/s00253-011-3535-5"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20Microbiology%20and%20Biotechnology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00253-011-3535-5", "name": "item", "description": "10.1007/s00253-011-3535-5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00253-011-3535-5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-08-17T00:00:00Z"}}], "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": 728, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-07-26T08:19:07.488328Z"}