{"type": "FeatureCollection", "features": [{"id": "10.1016/j.foreco.2010.07.002", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:11Z", "type": "Journal Article", "created": "2010-08-04", "title": "Thinning Method And Intensity Influence Long-Term Mortality Trends In A Red Pine Forest", "description": "Tree mortality shapes forest development, but rising mortality can represent lost production or an adverse response to changing environmental conditions. Thinning represents a strategy for reducing mortality rates, but different thinning techniques and intensities could have varying impacts depending on how they alter stand structure. We analyzed trends in stand structure, relative density, stand-scale mortality, climate, and correlations between mortality and climate over 46 years of thinning treatments in a red pine forest in Northern Minnesota, USA to examine how thinning techniques that remove trees of different crown classes interact with growing stock manipulation to impact patterns of tree mortality. Relative density in unharvested plots increased during the first 25 years of the study to around 80%, then began to plateau, but was lower (12-62%) in thinned stands. Mortality in unharvested plots claimed 2.5 times more stems yr\u22121 and 8.6 times as large a proportion of annual biomass increment during the last 21 years of the study compared to the first 25 years, but showed few temporal trends in thinned stands. Mortality in thinning treatments was generally lower than in controls, particularly during the last 21 years of the study when mortality averaged about 0.1% of stems yr \u22121 and 4% of biomass increment across thinning treatments, but 0.8% of stems yr \u22121 and 49% of biomass increment in unharvested plots. Treatments that combined thinning from above with low growing stock levels represented an exception, where mortality exceeded biomass production after initial thinning. Mortality averaged less than 0.1% of stems yr\u22121 and less than 1% of annual biomass production in stands thinned from below. These trends suggest thinning from below minimizes mortality across a wide range of growing stock levels while thinning from above to low growing stock levels can result in dramatic short-term increases in mortality. Moderate to high growing stock levels (21-34 m 2 ha \u22121 ) may offer greater flexibility for limiting mortality across a range of thinning methods. Mean and maximum annual and growing season temperatures rose by 0.6-1.8 \u25e6C during the study, and temperature variables were positively correlated with mortality in unharvested plots. Mortality increases in unharvested plots, however, were consistent with self-thinning principles and probably not driven by rising temperatures. These results suggest interactions between thinning method and intensity influence mortality reductions associated with thinning, and demonstrate the need for broader consideration of developmental processes as potential explanations for increased", "keywords": ["0106 biological sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.foreco.2010.07.002"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Forest%20Ecology%20and%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.foreco.2010.07.002", "name": "item", "description": "10.1016/j.foreco.2010.07.002", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.foreco.2010.07.002"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-08-01T00:00:00Z"}}, {"id": "10.1016/j.gca.2017.04.040", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:14Z", "type": "Journal Article", "created": "2017-05-08", "title": "Tracing metal\u2013silicate segregation and late veneer in the Earth and the ureilite parent body with palladium stable isotopes", "description": "Abstract   Stable isotope studies of highly siderophile elements (HSE) have the potential to yield valuable insights into a range of geological processes. In particular, the strong partitioning of these elements into metal over silicates may lead to stable isotope fractionation during metal\u2013silicate segregation, making them sensitive tracers of planetary differentiation processes. We present the first techniques for the precise determination of palladium stable isotopes by MC-ICPMS using a 106Pd\u2013110Pd double-spike to correct for instrumental mass fractionation. Results are expressed as the per mil (\u2030) difference in the 106Pd/105Pd ratio (\u03b4106Pd) relative to an in-house solution standard (Pd_IPGP) in the absence of a certified Pd isotopic standard. Repeated analyses of the Pd isotopic composition of the chondrite Allende demonstrate the external reproducibility of the technique of \u00b10.032\u2030 on \u03b4106Pd. Using these techniques, we have analysed Pd stable isotopes from a range of terrestrial and extraterrestrial samples. We find that chondrites define a mean \u03b4106Pdchondrite\u00a0=\u00a0\u22120.19\u00a0\u00b1\u00a00.05\u2030. Ureilites reveal a weak trend towards heavier \u03b4106Pd with decreasing Pd content, similar to recent findings based on Pt stable isotopes (Creech et al., 2017), although fractionation of Pd isotopes is significantly less than for Pt, possibly related to its weaker metal\u2013silicate partitioning behaviour and the limited field shift effect. Terrestrial mantle samples have a mean \u03b4106Pdmantle\u00a0=\u00a0\u22120.182\u00a0\u00b1\u00a00.130\u2030, which is consistent with a late-veneer of chondritic material after core formation.", "keywords": ["[SDU] Sciences of the Universe [physics]", "Terrestrial planet accretion", "13. Climate action", "01 natural sciences", "Late-veneer", "Palladium", "Meteorites", "Stable isotopes", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.gca.2017.04.040"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geochimica%20et%20Cosmochimica%20Acta", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.gca.2017.04.040", "name": "item", "description": "10.1016/j.gca.2017.04.040", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.gca.2017.04.040"}, {"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.jhazmat.2021.125292", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:27Z", "type": "Journal Article", "created": "2021-02-05", "title": "Reactive-transport modelling of Enterococcus faecalis JH2-2 passage through water saturated sediment columns", "description": "The reuse of treated wastewater (e.g. for irrigation) is a common practice to combat water scarcity problems world-wide. However, the potential spread of opportunistic pathogens and fecal contaminants like Enterococci within the subsoil could pose serious health hazards. Additional sources (e.g., leaky sewer systems, livestock farming) aggravate this situation. This study contributes to an understanding of pathogen spread in the environment, using a combined modelling and experimental approach. The impact of quartz sediment and certain wastewater characteristics on the dissemination of Enterococcus faecalis JH2-2 is investigated. The transport processes of advection-dispersion and straining were studied by injecting conservative saline tracer and fluorescent microspheres through sediment packed columns, and evaluating resulting breakthrough curves using models. Similarly, simultaneously occurring reactive processes of microbial attachment, decay, respiration and growth were studied by injecting Enterococcus faecalis JH2-2 suspended in water with or without dissolved oxygen (DO) and nutrients through sediment, and evaluating resulting inlet and outlet concentration curves. The processes of straining, microbial decay and growth, were important when DO was absent. Irreversible attachment was important when DO was present. Sensitivity analysis of each parameter was conducted, and field scale behavior of the processes was predicted, to facilitate future work.", "keywords": ["Physical Phenomena", "13. Climate action", "Enterococcus faecalis", "Water Movements", "0207 environmental engineering", "Water", "02 engineering and technology", "01 natural sciences", "Enterococcus", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.jhazmat.2021.125292"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hazardous%20Materials", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhazmat.2021.125292", "name": "item", "description": "10.1016/j.jhazmat.2021.125292", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhazmat.2021.125292"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2019.05.236", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:36Z", "type": "Journal Article", "created": "2019-05-22", "title": "A review of threats to groundwater quality in the anthropocene", "description": "Awareness concerning sustainable groundwater consumption under the context of land use and climate change is gaining traction, raising the bar for adequate understanding of the complexities of natural and anthropogenic processes and how they affect groundwater quality. The heterogeneous characteristics of aquifers have hampered comprehensive source, transport and contaminant identification. As questions remain about the behavior and prediction of well-known groundwater contaminants, new concerns around emerging contaminants are on the increase. This review highlights some of the key contaminants that originate from anthropogenic activities, organized based on land use categories namely agricultural, urban and industrial. It further highlights the extensive overlap, in terms of both provenance as well as contaminant type, between the different land use sectors. A selection of case studies from literature that describe the continued concern of established contaminants, as well as new and emerging compounds, are presented to illustrate the many qualitative threats to global groundwater resources. In some cases, the risk of groundwater contamination lacks adequate gravity, while in others the underlying physical and societal processes are not fully understood and activities may commence without adequately considering potential impacts. In the agricultural context, the historic and current application of fertilizers and plant protectants, use of veterinary pharmaceuticals and hormones, strives to safeguard the growing food demands. In the context of a sprawling urban environment, waste, human pharmaceuticals, and urban pesticide outputs are increasing, with adequate runoff and sanitation infrastructure often lagging. Finally, industrial activities are associated with accidental leaks and spills, while the large-scale storage of industrial byproducts has led to legacy contaminants such as those stemming from raw mineral extraction. With this review paper, we aim to underscore the need for transdisciplinary research, along with transboundary communication, using sound science and adaptive policy and management practice in order to procure sustainable groundwater quality.", "keywords": ["2. Zero hunger", "13. Climate action", "11. Sustainability", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences", "12. Responsible consumption"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2019.05.236"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2019.05.236", "name": "item", "description": "10.1016/j.scitotenv.2019.05.236", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2019.05.236"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2014.02.017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:45Z", "type": "Journal Article", "created": "2014-03-11", "title": "Microbial Interactions Affect Sources Of Priming Induced By Cellulose", "description": "Abstract   The recently developed 3-source-partitioning approach: addition of  14 C labeled organics to soil after C3\u2013C4 vegetation changes, was used to distinguish C sources in three compartments, namely CO 2 , microbial biomass and dissolved organic C (DOC) during decomposition of labeled cellulose. Microbial community structure (based on PLFA composition) and functions (based on enzyme activities and on microbial growth parameters) revealed mechanisms and drivers of priming effects (PE) induced by cellulose addition.   14 C-cellulose input caused negative PE within the first week and was accompanied by fast consumption of unlabelled DOC and its incorporation into microbial biomass. Microbial activation however, was not confirmed by substrate-induced respiration, nor by hydrolytic enzymes activity or by PLFA changes. A remarkable exception was a 2-fold increase in protozoan PLFA. Such an increase indicates that microorganisms feeding on cellulose and on DOC were quickly grazed by protozoans acting as a driver of microbial succession. This experimentally demonstrates the functioning of the microbial interactions: protozoan grazers provided for rapid recycling of nutrients and facilitated the succession of cellulose-degrading microorganisms during the second week of cellulose decomposition. An increase in the activity of cellulolytic enzymes caused short-term real PE accompanied by increase in abundance of slow-growing fungi and G(\u2212) bacteria. Long-term real PE observed between 14 and 60 days after cellulose input was due to decomposition of SOM-originated hemicelluloses by fungi and G(+) bacteria. The CO 2  released by primed soil organic matter (SOM) decomposition was originated mainly from C younger than 12 years (63%) and only 37% were older than 12 years despite the recent and old C contributed almost equally (51 and 49%, respectively) to SOM under  Miscanthus giganteus . This indicates that the SOM pools are involved in PE according to their availability. Despite 71% of the applied cellulose-C was sequestered in the soil, the net soil C-gain amounted only for 28% of the applied cellulose-C after factoring in the C losses by the PE. Our study emphasizes the role of food webs in the PE dynamics: cellulose input served as a driver activating the food chain through the microbial loop.", "keywords": ["2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences", "12. Responsible consumption"]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2014.02.017"}, {"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.2014.02.017", "name": "item", "description": "10.1016/j.soilbio.2014.02.017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2014.02.017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-07-01T00:00:00Z"}}, {"id": "10.1023/a:1013072519889", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:17:08Z", "type": "Journal Article", "created": "2002-12-23", "title": "Soil Freezing Alters Fine Root Dynamics In A Northern Hardwood Forest", "description": "The retention of nutrients within an ecosystem depends on temporal andspatial synchrony between nutrient availability and nutrient uptake, anddisruption of fine root processes can have dramatic impacts on nutrientretention within forest ecosystems. There is increasing evidence thatoverwinter climate can influence biogeochemical cycling belowground,perhaps by disrupting this synchrony. In this study, we experimentallyreduced snow accumulation in northern hardwood forest plots to examinethe effects of soil freezing on the dynamics of fine roots (< 1 mm diameter)measured using minirhizotrons. Snow removal treatment during therelatively mild winters of 1997\u20131998 and 1998\u20131999 induced mild freezingtemperatures (to \u22124 \u00b0C) lasting approximately three months atshallow soil depths (to \u221230 cm) in sugar maple and yellow birch stands.This treatment resulted in elevated overwinter fine root mortality in treatedcompared to reference plots of both species, and led to an earlier peak infine root production during the subsequent growing season. These shiftsin fine root dynamics increased fine root turnover but were not largeenough to significantly alter fine root biomass. No differences inmorality response were found between species. Laboratory tests on pottedtree seedlings exposed to controlled freezing regimes confirmed that mildfreezing temperatures (to \u22125 \u00b0C) were insufficient to directlyinjure winter-hardened fine roots of these species, suggesting that themarked response recorded in our forest plots was caused indirectly bymechanical damage to roots in frozen soil. Elevated fine root necromass intreated plots decomposed quickly, and may have contributed an excess fluxof about 0.5 g N/m2\u00b7yr, which is substantial relative tomeasurements of N fluxes from these plots. Our results suggest elevatedoverwinter mortality temporarily reduced fine root length in treatmentplots and reduced plant uptake, thereby disrupting the temporalsynchrony between nutrient availability and uptake and enhancing ratesof nitrification. Increased frequency of soil freezing events, as may occurwith global change, could alter fine root dynamics within the northernhardwood forest disrupting the normally tight coupling between nutrientmineralization and uptake.", "keywords": ["0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1023/a:1013072519889"}, {"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": "10.1023/a:1013072519889", "name": "item", "description": "10.1023/a:1013072519889", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1023/a:1013072519889"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2001-11-01T00:00:00Z"}}, {"id": "10.1098/rstb.2011.0313", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:17:50Z", "type": "Journal Article", "created": "2012-03-26", "title": "The Role Of N2o Derived From Crop-Based Biofuels, And From Agriculture In General, In Earth'S Climate", "description": "<p>             In earlier work, we compared the amount of newly fixed nitrogen (N, as synthetic fertilizer and biologically fixed N) entering agricultural systems globally to the total emission of nitrous oxide (N             2             O). We obtained an N             2             O emission factor (EF) of 3\uffe2\uff80\uff935%, and applied it to biofuel production. For \uffe2\uff80\uff98first-generation\uffe2\uff80\uff99 biofuels, e.g. biodiesel from rapeseed and bioethanol from corn (maize), that require N fertilizer, N             2             O from biofuel production could cause (depending on N uptake efficiency) as much or more global warming as that avoided by replacement of fossil fuel by the biofuel. Our subsequent calculations in a follow-up paper, using published life cycle analysis (LCA) models, led to broadly similar conclusions. The N             2             O EF applies to agricultural crops in general, not just to biofuel crops, and has made possible a top-down estimate of global emissions from agriculture. Independent modelling by another group using bottom-up IPCC inventory methodology has shown good agreement at the global scale with our top-down estimate. Work by Davidson showed that the rate of accumulation of N             2             O in the atmosphere in the late nineteenth and twentieth centuries was greater than that predicted from agricultural inputs limited to fertilizer N and biologically fixed N (Davidson, E. A. 2009             Nat. Geosci             .             2             , 659\uffe2\uff80\uff93662.). However, by also including soil organic N mineralized following land-use change and NO                            x                          deposited from the atmosphere in our estimates of the reactive N entering the agricultural cycle, we have now obtained a good fit between the observed atmospheric N             2             O concentrations from 1860 to 2000 and those calculated on the basis of a 4 per cent EF for the reactive N.           </p>", "keywords": ["2. Zero hunger", "Air Pollutants", "330", "Climate", "Nitrous Oxide", "Agriculture", "15. Life on land", "Nitrification", "01 natural sciences", "7. Clean energy", "630", "Soil", "13. Climate action", "Biofuels", "Denitrification", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1098/rstb.2011.0313"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Philosophical%20Transactions%20of%20the%20Royal%20Society%20B%3A%20Biological%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1098/rstb.2011.0313", "name": "item", "description": "10.1098/rstb.2011.0313", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1098/rstb.2011.0313"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-05-05T00:00:00Z"}}, {"id": "10.1111/gcbb.12255", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:04Z", "type": "Journal Article", "created": "2015-02-19", "title": "Bioenergy Harvest, Climate Change, And Forest Carbon In The Oregon Coast Range", "description": "Abstract<p>Forests provide important ecological, economic, and social services, and recent interest has emerged in the potential for using residue from timber harvest as a source of renewable woody bioenergy. The long\uffe2\uff80\uff90term consequences of such intensive harvest are unclear, particularly as forests face novel climatic conditions over the next century. We used a simulation model to project the long\uffe2\uff80\uff90term effects of management and climate change on above\uffe2\uff80\uff90 and belowground forest carbon storage in a watershed in northwestern Oregon. The multi\uffe2\uff80\uff90ownership watershed has a diverse range of current management practices, including little\uffe2\uff80\uff90to\uffe2\uff80\uff90no harvesting on federal lands, short\uffe2\uff80\uff90rotation clear\uffe2\uff80\uff90cutting on industrial land, and a mix of practices on private nonindustrial land. We simulated multiple management scenarios, varying the rate and intensity of harvest, combined with projections of climate change. Our simulations project a wide range of total ecosystem carbon storage with varying harvest rate, ranging from a 45% increase to a 16% decrease in carbon compared to current levels. Increasing the intensity of harvest for bioenergy caused a 2\uffe2\uff80\uff933% decrease in ecosystem carbon relative to conventional harvest practices. Soil carbon was relatively insensitive to harvest rotation and intensity, and accumulated slowly regardless of harvest regime. Climate change reduced carbon accumulation in soil and detrital pools due to increasing heterotrophic respiration, and had small but variable effects on aboveground live carbon and total ecosystem carbon. Overall, we conclude that current levels of ecosystem carbon storage are maintained in part due to substantial portions of the landscape (federal and some private lands) remaining unharvested or lightly managed.\uffc2\uffa0Increasing the intensity of harvest for bioenergy on currently harvested land, however,\uffc2\uffa0led to a relatively small reduction in the ability of forests to store carbon. Climate change is unlikely to substantially alter carbon storage in these forests, absent shifts in disturbance regimes.</p>", "keywords": ["0106 biological sciences", "Carbon dioxide mitigation", "Forest ecology -- Oregon -- Oregon Coast Range", "Forest biomass", "13. Climate action", "Carbon cycle (Biogeochemistry)", "Biomass energy", "Forest Biology", "15. Life on land", "01 natural sciences", "7. Clean energy", "Climatic change", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1111/gcbb.12255"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/GCB%20Bioenergy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcbb.12255", "name": "item", "description": "10.1111/gcbb.12255", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcbb.12255"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-05-25T00:00:00Z"}}, {"id": "10.1111/j.1365-2486.2009.02121.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:09Z", "type": "Journal Article", "created": "2009-12-22", "title": "Functional Changes In The Control Of Carbon Fluxes After 3 Years Of Increased Drought In A Mediterranean Evergreen Forest?", "description": "Abstract<p>Our objective was to test how a long\uffe2\uff80\uff90term increased water limitation affects structural and functional properties of a Mediterranean ecosystem, and how these changes modify the response of the main carbon fluxes to climatic controls. In 2003, a 27% throughfall exclusion experiment was installed in a Quercus ilex L. forest in France. Gross primary production (GPP), ecosystem respiration (RECO) and net ecosystem exchange (NEE) were estimated in a control and a dry treatment. Decreasing throughfall decreased GPP by 14% and had a smaller effect on RECO (\uffe2\uff88\uff9212%), especially soil respiration RS (\uffe2\uff88\uff9211%). Interannual variability of GPP (29%) was higher than for RECO (12%). Error propagation was used to estimates uncertainties in the NEE fluxes, which ranged from 3% to 10% in the control treatment but up to 167% for NEE in the dry treatment because more steps and data types were involved in the scaling. After 3 years of throughfall exclusion, we found no acclimation of RS to climatic drivers. Functional properties of the response of RS to soil water, temperature and rain pulse remained similar in the control and the dry treatments. A diurnal clockwise hysteresis in RS was probably controlled by canopy photosynthesis with a 3\uffe2\uff80\uff83h lag. The proportion of diurnal variation of respiration due to photosynthesis was similar in all treatments (4\uffe2\uff80\uff935%). Because of the characteristic of rain in Mediterranean climates, a continuous decrease of water input in these environments have an effect on topsoil water and consequently on RS only during short periods when rainfall is characterized by infrequent and small events that does not allow the topsoil to reach field capacity and does not allow to dry completely. However, in the longer term, we expect a stronger decrease in RS in the dry treatment driven by the decrease in GPP.</p>", "keywords": ["0106 biological sciences", "550", "15. Life on land", "gross primary production", "soil respiration", "01 natural sciences", "630", "6. Clean water", "Quercus ilex", "throughfall exclusion", "13. Climate action", "rain pulse", "eddy-covariance", "Q(10)", "error propagation", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2009.02121.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/j.1365-2486.2009.02121.x", "name": "item", "description": "10.1111/j.1365-2486.2009.02121.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2009.02121.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-08-01T00:00:00Z"}}, {"id": "10.1175/bams-d-20-0086.1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:29Z", "type": "Journal Article", "created": "2020-08-20", "title": "Tundra greenness", "description": "Physical and Space Geodesy", "keywords": ["[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology", "[SDU.STU.ME] Sciences of the Universe [physics]/Earth Sciences/Meteorology", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://journals.ametsoc.org/downloadpdf/journals/bams/101/8/bamsD200086.xml"}, {"href": "https://doi.org/10.1175/bams-d-20-0086.1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bulletin%20of%20the%20American%20Meteorological%20Society", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1175/bams-d-20-0086.1", "name": "item", "description": "10.1175/bams-d-20-0086.1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1175/bams-d-20-0086.1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-01T00:00:00Z"}}, {"id": "10.1186/s12302-025-01141-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:30Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract                        Background             <p>Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.</p>                                   Results             <p>The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.</p>                                   Conclusions             <p>The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.</p>", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1186/s12302-025-01141-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s12302-025-01141-6", "name": "item", "description": "10.1186/s12302-025-01141-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s12302-025-01141-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.1360/n972019-00314", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:34Z", "type": "Journal Article", "created": "2019-07-16", "title": "Influence of different sputtering conditions on superconductivity of ultra-thin epitaxial niobium nitride film", "description": "Superconductors are used in military and commercial applications due to the full diamagnetic and zero resistance properties. Hereinto, niobium nitride (NbN) has been extensively studied for its excellent superconducting properties, such as high transition temperature ( T c), large superconducting energy gap, narrow transition width and good stability. Superconducting NbN films are widely used in low temperature superconducting devices, for instance, hot electron bolometer, superconducting quantum interference devices and rapid single flux quantum. Especially, in 2001 Gol\u2019tsman has successfully detected a single photon response of  810\u2005nm  near-infrared using an ultra-thin superconducting NbN, which proved that the high-quality growth of ultra-thin NbN film was the key step for high resolution and sensitivity of the superconducting detector. Up to now, atomic layer deposition (ALD), molecular beam epitaxy (MBE), pulsed laser deposition (PLD) and magnetron sputtering have been successfully used to grow NbN thin films. However,  T c is decreasing gradually as the reduced of thickness. Therefore, there is still a challenge to grow ultra-thin superconducting NbN film with high performance.   In this work,  5\u2005nm  thickness of superconducting epitaxial NbN film has been grown on MgO  substrate by magnetron sputtering. We systematically study the effect of different sputtering parameters on the superconductivity properties of the NbN film. The experiment results show that the high vacuum, high sputtering temperature and low working pressure are positively correlated with the superconducting transition temperature of NbN film under the premise of suitable argon-nitrogen ratio or magnetron power. The analyses of physical property measurement system (PPMS) indicate that as-grown 5 nm-thick NbN film has high performance with a superconducting transition temperature as high as 12.5\u2005K under the optimum condition. Morphologic characterizations show that the ultra-thin NbN films have high density and smoothness with  0.116\u2005nm  of the surface roughness. Microstructural measurements also illustrate the epitaxial growth of NbN on MgO substrate. This work demonstrates the ultra-thin NbN films can be well controllably grown with high quality and offers a platform to fabricate the ultra-thin superconducting devices in the coming future.", "keywords": ["7. Clean energy", "01 natural sciences", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Xiaohan Wang, Qianmei He, Zheng Lu, Tao Jin, Fengang Zheng, Jie Xiong, Guifu Zou,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1360/n972019-00314"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Chinese%20Science%20Bulletin", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1360/n972019-00314", "name": "item", "description": "10.1360/n972019-00314", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1360/n972019-00314"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-06-27T00:00:00Z"}}, {"id": "10.2111/08-106.1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:58Z", "type": "Journal Article", "created": "2010-01-22", "title": "Land Use Influences Carbon Fluxes In Northern Kazakhstan", "description": "A mobile, closed-chamber system (CC) was used to measure carbon and water fluxes on four land-use types common in the Kazakh steppe ecoregion. Land uses represented crop (wheat or barley, WB), abandoned land (AL), crested wheatgrass (CW), and virgin land (VL). Measurements were conducted during the growing season of 2002 in northern Kazakhstan at three locations (blocks) 15\u201320 km apart. The CC allowed the measurement of the carbon flux components of net ecosystem exchange (NEE), ecosystem respiration (RE) and soil respiration (RS), together with evapotranspiration (ET). Nonlinear regression analyse sw ere used to model gross primary production (GPP) and ET as a function of photosynthetically active radiation (Q); RE and RS were modeled based on air (Tair) and soil (Ts) temperature, respectively. GPP, RE, RS, and ET were estimated for the entire year with the use of continuous 20-min means of Q, Tair, and Ts. Annual NEE indicated that AL gained 536 g CO2 ? m 22 , WB lost 2 191 g CO2 ? m 22 , CW was near equilibrium (2 14 g CO2 ? m 22 ), and VL exhibited considerable carbon accumulation (153 g CO2 ? m 22 ). The lower GPP values of the land-use types dominated by native species (CW and VL) compared to WB and AL were compensated by positive NEE values that were maintained during a longer growing season. As expected, VL and CW allocated a larger proportion of their carbon assimilates belowground. Non\u2013growing-season RE accounted for about 19% of annual RE in all land-use types. The results of this landscape-level study suggest that carbon lost by cultivation of VLs is partially being restored when fields are left uncultivated, and that VLs are net sinks of carbon. Estimations of carbon balances have important management implications, such as estimation of ecosystem productivity and carbon credit certification. Resumen", "keywords": ["2. Zero hunger", "abandoned fields", "13. Climate action", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.2111/08-106.1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Rangeland%20Ecology%20%26amp%3B%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2111/08-106.1", "name": "item", "description": "10.2111/08-106.1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2111/08-106.1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-01-01T00:00:00Z"}}, {"id": "10261/179481", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:15Z", "type": "Journal Article", "created": "2018-07-19", "title": "Molecular Fingerprinting of14C Dated Soil Organic Matter Fractions from Archaeological Settings in NW Spain", "description": "Abstract<p>This paper evaluates the complexities of radiocarbon (14C) dates from soil organic matter (SOM) in archaeological scenarios. The aqueous NaOH-insoluble residual SOM from Neolithic to medieval sites in NW Spain produced consistently older calibrated14C ages than NaOH-extractable SOM. Using pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) and thermally assisted hydrolysis and methylation (THM-GC-MS), we analyzed the molecular composition of these SOM fractions, aiming to understand the differences in14C ages and to gain insight on SOM dynamics in relation to age fractionation. The molecular composition of the NaOH-extractable SOM, which accounts for roughly two-thirds of total SOM, has a larger proportion of microbial detritus than the NaOH-insoluble SOM. This might suggest that the discrepancies between the two fractions is due to microbial rejuvenation in the extractable fraction, leading to14C results that are younger than the activity that is to be dated. However, archaeological evidence presented here unambiguously shows that the14C age of the extractable SOM provides the more accurate age for the targeted activity, and that the insoluble fraction contains inherited old carbon. After statistical data evaluation using Partial Least Squares-Regression (PLS-R), it is concluded that this inherited SOM is a mixture of Black Carbon from wild and/or domestic fires and recalcitrant aliphatic SOM.</p", "keywords": ["Radiocarbon dating", "Molecular composition", "THM-GC-MS", "SOM fractions", "0601 history and archaeology", "06 humanities and the arts", "15. Life on land", "01 natural sciences", "Py-GC-MS", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10261/179481"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Radiocarbon", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/179481", "name": "item", "description": "10261/179481", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/179481"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-18T00:00:00Z"}}, {"id": "10.3402/tellusb.v54i5.16689", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:19:49Z", "type": "Journal Article", "created": "2012-12-17", "description": "We present a first analysis of data (June 1998 to December 2000) from the long-term eddy covariance site established in a\u00a0Pinus sylvestris stand near Zotino in central Siberia as part of the EUROSIBERIAN CARBONFLUX project. As well as examining seasonal patterns in net ecosystem exchange\u00a0(NE), daily, seasonal and annual estimates of the canopy photosynthesis (or gross primary productivity,\u00a0GP) were obtained using\u00a0NE and ecosystem respiration measurements.Although the forest was a small (but significant) source of CO2 throughout the snow season (typically mid-October to early May) there was a rapid commencement of photosynthetic capacity shortly following the commencement of above-zero air temperatures in spring: in 1999 the forest went from a quiescent state to significant photosynthetic activity in only a few days. Nevertheless, canopy photosynthetic capacity was observed to continue to increase slowly throughout the summer months for both 1999 and 2000, reaching a maximum capacity in early August. During September there was a marked decline in canopy photosynthesis which was only partially attributable to less favourable environmental conditions. This suggests a reduction in canopy photosynthetic capacity in autumn, perhaps associated with the cold hardening process. For individual time periods the canopy photosynthetic rate was mostly dependent upon incoming photon irradiance. However, reductions in both canopy conductance and overall photosynthetic rate in response to high canopy-to-air vapour differences were clearly evident on hot dry days. The relationship between canopy conductance and photosynthesis was examined using Cowan's notion of optimality in which stomata serve to maximise the marginal evaporative cost of plant carbon gain. The associated Lagrangian multiplier (\u03bb) was surprisingly constant throughout the growing season. Somewhat remarkably, however, its value was markedly different between years, being\u00a0416 mol mol\u22121 in 1999 but\u00a0815 mol mol\u22121 in 2000. Overall the forest was a substantial sink for CO2 in both 1999 and 2000: around\u00a013 mol C m\u22122 a\u22121. Data from this experiment, when combined with estimates of net primary productivity from biomass sampling suggest that about 20% of this sink was associated with increasing plant biomass and about 80% with an increase in the litter and soil organic carbon pools. This high implied rate of carbon accumulation in the litter soil organic matter pool seems unsustainable in the long term and is hard to explain on the basis of current knowledge.DOI:\u00a010.1034/j.1600-0889.2002.01487.x", "keywords": ["13. Climate action", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3402/tellusb.v54i5.16689"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Tellus%20B%3A%20Chemical%20and%20Physical%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3402/tellusb.v54i5.16689", "name": "item", "description": "10.3402/tellusb.v54i5.16689", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3402/tellusb.v54i5.16689"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2002-01-01T00:00:00Z"}}, {"id": "10.5061/dryad.cz8w9gj78", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:03Z", "type": "Dataset", "title": "Soil microbial relative resource limitation exhibited contrasting seasonal patterns along an elevational gradient in Yulong snow mountain", "description": "unspecified", "keywords": ["2. Zero hunger", "mountain ecosystems", "13. Climate action", "microbial metabolic mechanisms", "microbial relative C limitation", "microbial relative P limitation", "C use efficiency", "FOS: Earth and related environmental sciences", "15. Life on land", "elevations"], "contacts": [{"organization": "Zhang, Dandan, Wu, Baoyun, Li, Jinsheng, Cheng, Xiaoli,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.cz8w9gj78"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.cz8w9gj78", "name": "item", "description": "10.5061/dryad.cz8w9gj78", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.cz8w9gj78"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-02T00:00:00Z"}}, {"id": "10.5194/acp-10-7017-2010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:08Z", "type": "Journal Article", "created": "2010-04-29", "description": "<p>Abstract. We present and discuss a new dataset of gridded emissions covering the historical period (1850\uffe2\uff80\uff932000) in decadal increments at a horizontal resolution of 0.5\uffc2\uffb0 in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models is used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.                         </p>", "keywords": ["info:eu-repo/classification/ddc/550", "550", "IPCC", "[SDE.MCG]Environmental Sciences/Global Changes", "Physics", "QC1-999", "emissions", "551", "01 natural sciences", "7. Clean energy", "J", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "13. Climate action", "[SDE.ES] Environmental Sciences/Environment and Society", "CMIP5", "[SDE.ES]Environmental Sciences/Environment and Society", "QD1-999", "AR5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "https://doi.org/10.5194/acp-10-7017-2010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-10-7017-2010", "name": "item", "description": "10.5194/acp-10-7017-2010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-10-7017-2010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-02-19T00:00:00Z"}}, {"id": "10.5194/egusphere-2023-1681", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:14Z", "type": "Report", "created": "2023-08-14", "title": "The Effects of Land Use on Soil Carbon Stocks in the UK", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Greenhouse gas stabilisation in the atmosphere is one of the most pressing challenges of this century. Sequestering carbon in the soil by changing land use and management is increasingly proposed as part of climate mitigation strategies, but our understanding of this is limited in quantitative terms. Here we collate a substantial national and regional data set (15790 soil cores), and analyse it in an advanced statistical modelling framework. This produced new estimates of the effects of land use on soil carbon stocks in the UK, different in magnitude and ranking order from the previous best estimates. Soil carbon stocks were highest in woodlands, followed by rough grazing and semi-natural grasslands, then improved grasslands, and lowest in croplands. Estimates were smaller than the previous estimates, partly because of new data, but mainly because the effect is more reliably characterised using a logarithmic transformation of the data. With the very large data set analysed here, the uncertainty in the differences among land uses was small enough to identify consistent mean effects. However, the variability in these effects was large, and this was similar across all surveys. This has important implications for agri-environment schemes, seeking to sequester carbon in the soil by altering land use, because the effect of a given intervention is very hard to verify. We examined the validity of the 'space-for-time' substitution, and although the results were not unequivocal, we estimated that the effects are likely to be over-estimated by 5\u201333 %, depending upon land use.</p></article>", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/egusphere-2023-1681"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/egusphere-2023-1681", "name": "item", "description": "10.5194/egusphere-2023-1681", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/egusphere-2023-1681"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-14T00:00:00Z"}}, {"id": "10.5194/gmd-15-8411-2022", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:18Z", "type": "Journal Article", "created": "2022-11-21", "title": "Global biomass burning fuel consumption and emissions at 500\u2009m spatial resolution based on the Global Fire Emissions Database (GFED)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500\u2009m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e.\u00a0fire-related forest loss, was modelled based on the overlap between 30\u2009m forest loss data and MODIS burned area and active fire detections. Using this new 500\u2009m model, we calculated global average carbon emissions from fire of 2.1\u00b10.2 (\u00b11\u03c3 interannual variability, IAV)\u2009Pg\u2009C\u2009yr\u22121 during 2002\u20132020. Fire-related forest loss accounted for 2.6\u00b10.7\u2009% (uncertainty range =1.9\u2009%\u20133.3\u2009%) of global burned area and 24\u00b16\u2009% (uncertainty range =16\u2009%\u201331\u2009%) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13\u00b14\u2009% of global emissions. Our global fire emissions estimate was higher than the 1.5\u2009Pg\u2009C\u2009yr\u22121 from GFED4 and similar to 2.1\u2009Pg\u2009C\u2009yr\u22121 from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500\u2009m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30\u2009m and finer show a substantial amount of burned area that remains undetected with 500\u2009m sensors, suggesting that global carbon emissions from fire are likely higher than our 500\u2009m estimates. The ability to model fire emissions at 500\u2009m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.                     </p></article>", "keywords": ["QE1-996.5", "13. Climate action", "11. Sustainability", "Geology", "15. Life on land", "01 natural sciences", "7. Clean energy", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/gmd-15-8411-2022"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-15-8411-2022", "name": "item", "description": "10.5194/gmd-15-8411-2022", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-15-8411-2022"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-30T00:00:00Z"}}, {"id": "10.5194/gmd-17-8023-2024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:18Z", "type": "Journal Article", "created": "2024-11-11", "title": "Simulating Ips typographus L. outbreak dynamics and their influence on carbon balance estimates with ORCHIDEE r8627", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. New (a)biotic conditions resulting from climate change are expected to change disturbance dynamics, such as windthrow, forest fires, droughts, and insect outbreaks, and their interactions. These unprecedented natural disturbance dynamics might alter the capability of forest ecosystems to buffer atmospheric CO2 increases, potentially leading forests to transform from sinks into sources of CO2. This study aims to enhance the ORCHIDEE land surface model to study the impacts of climate change on the dynamics of the bark beetle, Ips typographus, and subsequent effects on forest functioning. The Ips typographus outbreak model is inspired by previous work from Temperli et al.\u00a0(2013) for the LandClim landscape model. The new implementation of this model in ORCHIDEE r8627 accounts for key differences between ORCHIDEE and LandClim: (1)\u00a0the coarser spatial resolution of ORCHIDEE; (2)\u00a0the higher temporal resolution of ORCHIDEE; and (3)\u00a0the pre-existing process representation of windthrow, drought, and forest structure in ORCHIDEE. Simulation experiments demonstrated the capability of ORCHIDEE to simulate a variety of post-disturbance forest dynamics observed in empirical studies. Through an array of simulation experiments across various climatic conditions and windthrow intensities, the model was tested for its sensitivity to climate, initial disturbance, and selected parameter values. The results of these tests indicated that with a single set of parameters, ORCHIDEE outputs spanned the range of observed dynamics. Additional tests highlighted the substantial impact of incorporating Ips typographus outbreaks on carbon dynamics. Notably, the study revealed that modeling abrupt mortality events as opposed to a continuous mortality framework provides new insights into the short-term carbon sequestration potential of forests under disturbance regimes by showing that the continuous mortality framework tends to overestimate the carbon sink capacity of forests in the 20- to 50-year range in ecosystems under high disturbance pressure compared to scenarios with abrupt mortality events. This model enhancement underscores the critical need to include disturbance dynamics in land surface models to refine predictions of forest carbon dynamics in a changing climate.                     </p></article>", "keywords": ["[SDE] Environmental Sciences", "QE1-996.5", "[SDE]Environmental Sciences", "Geology"]}, "links": [{"href": "https://doi.org/10.5194/gmd-17-8023-2024"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-17-8023-2024", "name": "item", "description": "10.5194/gmd-17-8023-2024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-17-8023-2024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-11T00:00:00Z"}}, {"id": "10.5281/zenodo.14027088", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:45Z", "type": "Dataset", "created": "2024-11-01", "title": "Per- and Polyfluoroalkyl Substances (PFAS) Concentrations in the Upper Danube Catchment: Integrated Dataset from H2020 Project PROMISCES - Case Study 2", "description": "Dataset Description  This dataset was produced within the framework of\u00a0Horizon 2020 Framework Programme, Project PROMISCES (Preventing Recalcitrant Organic Mobile Industrial chemicalS for Circular Economy in the Soil-sediment-water system). Project website: https://promisces.eu/  The dataset contains information on the environmental concentrations of Per- and Polyfluoroalkyl substances (PFASs) collected as part of the PROMISCES project's Case Study #2,\u00a0Subtask 2.2.4 \u2013 Large catchment scale monitoring in different environmental compartments. It also includes data gathered from various external sources.  Abstract  PFASs are a group of synthetic chemicals widely used in various household and industrial applications (Gl\u00fcge et al., 2020). Due to their high chemical stability, PFASs are resistant to natural degradation processes, leading to their accumulation in different environmental matrices and ultimately posing potential health risks to humans (Sunderland et al., 2019). PROMISCES CS#2 focused on understading the fate and transport of PFASs in the upper Danube catchment, covering the Danube from its source to the city of Budapest. Over approximately 1.5 years, a comprehensive monitoring campaign was conducted in this study area, across multiple environmental compartments:\u00a0    Atmopsheric Deposition:\u00a0  River water: including Danube mainstream and its tributaries.  Groundwater: including bank-filtered water from the Danube, and groundwater directly influenced by the landfills  Landfill leachate  Surface Runoff  Wastewater: Influent and effluent from municipal waterwater treatment plants (WWTPs) and direct industrial dischargers   Particularly, the case study placed a special focus on the Danube and its bank filtration sites at two major cities in the Upper Danube, Vienna and Budapest.  The dataset primarily consists results from targeted analysis of 32 individual PFAS substances. In addition, available data for these 32 PFASs in the study area were collected from various online resources or provided directly by project partners. For confidentiality reasons, some external data have been anonymized on names and locations.\u00a0  Partial of this dataset have already contributed to a 2023 publication (Liu et al.), which was based on preliminary data before the completion of the full monitoring campaign and external data collection.  The full dataset was analysed and discussed in the publication Liu et al. (2025): https://www.doi.org/10.1186/s12302-025-01141-6  Technical Details  This dataset includes:    A Zip file containing .accdb Microsoft Access database  A ZIP file containing .csv files structured to match the database   Notice that the .accdb version is out of maintance and removed in version 3.0. The only changes compared to version 2.0 was the substance short-names for two compounds:    substance with CAS number 2355-31-9 updated from \u201cMeFOSAA\u201d to \u201cN-MeFOSAA\u201d  substance with CAS number 2991-50-6 updated from \u201cEtFOSAA\u201d to \u201cN-EtFOSAA   Database structure  One query is created to show most important information:    Concentrations_PFAS: contains all PFAS concentration data.\u00a0   In addition, tables were provided with more infomation on the metadata:    Table1_measurements: concentrations data with units, values, limit of quantifications (LOQs); keys indicating relationships with other tables.  Table2_samplings: sample codes, sampling times (if available), sampling type, sampling techniques; key indicating relationships with Table7_analytical_methods.  Table3_samples: sample names, sample sites, coordinates and coordinate systems (if available).  Table4_compartments: sample matrices/compartments, more detailed sample types.  Table5_compounds: CAS numbers, substance short names, Sus Dat IDs, substance names in NORMAN database, substance group short names and long names.  Table6_datasources: data source names, organisations, countries, references, links.  Table7_analytical_methods: laboratories, preparation methods, analytical methods, analytical method standards.   References  Gl\u00fcge, J., Scheringer M., Cousins I., DeWitt J., Goldenman G., Herzke D., Lohmann R., Ng A., Trier X., Wang Z (2020) An Overview of the Uses of Per- and Polyfluoroalkyl Substances (PFAS). Environmental Science: Processes & Impacts 12. https://doi.org/10.1039/D0EM00291G  Liu, M., Saracevic, E., Kittlaus, S., Oudega, T., Obeid, A., Nagy-Kov\u00e1cs, Z., L\u00e1szl\u00f3, B., Krlovic, N., Saracevic, Z., Lindner, G., Rab, R., Derx, J., Zoboli, O., Zessner, M. (2023) PFAS-Belastungen im Einzugsgebiet der oberen Donau. \u00d6sterr Wasser- und Abfallw 75, 503\u2013514 . https://doi.org/10.1007/s00506-023-00973-x\u00a0  Sunderland, Elsie M., Xindi C. Hu, Clifton Dassuncao, Andrea K. Tokranov, Charlotte C. Wagner, and Joseph G. Allen. (2019) A Review of the Pathways of Human Exposure to Poly- and Perfluoroalkyl Substances (PFASs) and Present Understanding of Health Effects. Journal of Exposure Science & Environmental Epidemiology 29, no. 2 : 131\u201347. https://doi.org/10.1038/s41370-018-0094-1", "keywords": ["Water management", "Environmental sciences", "water pollution", "emerging pollutants", "PFAS", "hazardous substances", "Danube", "water quality", "Pollution", "environmental monitoring"], "contacts": [{"organization": "Liu, Meiqi", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14027088"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14027088", "name": "item", "description": "10.5281/zenodo.14027088", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14027088"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14936177", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:59Z", "type": "Dataset", "title": "Precision Liming Soil Datasets (LimeSoDa) Zenodo Repository", "description": "Overview  Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1) soil organic matter (SOM) or soil organic carbon (SOC), (2) pH, and (3) clay content, while the features for modeling are dataset-specific. The primary goal of `LimeSoDa` is to enable more reliable benchmarking of machine learning methods in digital soil mapping and pedometrics. All the associated materials and data from LimeSoDa can be downloaded in this data repository. However, for a more in-depth analysis, we refer to the published paper 'LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping' by Schmidinger et al. (2025). You may also use our R\u00a0and Python package likewise called LimeSoDa.  \u00a0  Citation  Upon usage of datasets from LimeSoDa, please cite our associated paper:  Schmidinger, J., Vogel, S., Barkov, V., Pham, A.-D., Gebbers, R., Tavakoli, H., Correa, J., Tavares, T.R., Filippi, P., Jones, E. J., Lukas, V., Boenecke, E., Ruehlmann, J., Schroeter, I., Kramer, E., Paetzold, S., Kodaira, M., Wadoux, A.M.J.-C., Bragazza, L., Metzger, K., Huang, J., Valente, D.S.M., Safanelli, J.L., Bottega, E.L., Dalmolin, R.S.D., Farkas, C., Steiger, A., Horst, T. Z., Ramirez-Lopez, L., Scholten, T., Stumpf, F., Rosso, P., Costa, M.M., Zandonadi, R.S., Wetterlind, J. & Atzmueller, M. (2025). LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping.", "keywords": ["Environmental sciences", "Soil Organic Carbon", "Pedometrics", "pH", "Soil Organic Matter", "Clay", "Remote sensing", "Digital Soil Mapping"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14936177"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14936177", "name": "item", "description": "10.5281/zenodo.14936177", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14936177"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15680931", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:10Z", "type": "Journal Article", "created": "2025-06-15", "title": "Investigating the extent of PFAS contamination in the Upper Danube Basin across environmental compartments", "description": "Abstract                        Background             <p>Per- and polyfluoroalkyl substances (PFAS) are emerging organic pollutants widely detected in environmental systems, posing risks to human health and the ecosystem. Despite increasing efforts to monitor PFAS in river systems, knowledge gaps remain regarding sources and emissions via different pathways. This study investigates PFAS contamination across multiple environmental compartments in the Upper Danube Basin, including surface water, groundwater, wastewater, landfill leachate, surface runoff, and atmospheric deposition. The primary objectives are to assess the extent of PFAS contamination, identify key emission sources and transport pathways, and evaluate associated risks in terms of the potential exceedance of current and proposed environmental regulatory thresholds in the European Union.</p>                                   Results             <p>The findings reveal a widespread presence of PFAS, with PFOA, PFOS and short-chain compounds being predominant. The Alz River and Gendorf chemical park emerge as hotspots with far-reaching effects downstream, contributing significantly to diffuse legacy contamination of PFOA and being a significant source of two industrial PFOA substitutes, ADONA and GenX. Wastewater treatment plants, old municipal landfills, and sites with a history of fire-fighting foam application are identified as key pathways or sources of legacy pollution, exhibiting higher concentrations compared to the other matrices. Notably, no significant removal is observed when comparing influent and effluent samples from conventional WWTPs. The study further demonstrates that groundwater is vulnerable to contamination from point sources and to infiltration from rivers, with bank filtration proving largely ineffective in preventing PFAS contamination.</p>                                   Conclusions             <p>The study underscores the necessity for source and pathway control measures to mitigate PFAS pollution, the implementation of advanced treatment technologies to safeguard drinking water and surface water quality, and targeted remediation for legacy soil and groundwater contamination. Additionally, strong use regulations should be explored to minimize ongoing emissions. The multi-compartment monitoring proves to be a crucial approach to understand the complexity of PFAS distribution at the catchment scale. Comparative analysis and risk assessment highlight challenging situations for water management, offering an indispensable basis for emission modeling as a next step for quantitative assessment of the relevance of different sources and pathways for surface water pollution.</p>", "keywords": ["Emerging contaminants", "Emerging Pollutants", "PFAS", "Source identification", "Watershed management", "Environmental sciences", "Emission", "Water Framework Directive", "Environmental law", "Water pollution", "GE1-350", "K3581-3598", "Catchment monitoring", "Environmental Monitoring"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1186/s12302-025-01141-6.pdf"}, {"href": "https://doi.org/10.5281/zenodo.15680931"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Sciences%20Europe", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15680931", "name": "item", "description": "10.5281/zenodo.15680931", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15680931"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-06-15T00:00:00Z"}}, {"id": "10.5281/zenodo.8089699", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:37Z", "type": "Journal Article", "created": "2019-11-28", "title": "High-resolution and three-dimensional mapping of soil texture of China", "description": "The lack of detailed three-dimensional soil texture information largely restricts many applications in agriculture, hydrology, climate, ecology and environment. This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8089699"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8089699", "name": "item", "description": "10.5281/zenodo.8089699", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8089699"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10773/25427", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:26Z", "type": "Journal Article", "created": "2018-01-07", "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/10773/25427"}, {"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": "10773/25427", "name": "item", "description": "10773/25427", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10773/25427"}, {"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": "10.7910/DVN/HXAH87", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Arbuscular and ectomycorrhizal fungi diversity in the Indian subcontinent", "description": "Mycorrhizal fungi (MF) are below-ground organisms playing a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Arbuscular and ectomycorrhizal fungi are the two mycorrhizal types most relevant to worldwide ecosystems, but areas like the Indian sub-continent remain under-represented in global maps. The dataset presented here reports the available information regarding arbuscular and ectomycorrhizal fungi diversity in cultivated and natural ecosystems of the Indian subcontinent. We have selected studies published in English in ISI Web of Science during the years 2005 - 2020 that provided a taxonomic classification of MF and their associated abundance in terms of percentage of root colonization or number of spores per quantity of soil. From the screening of 74 studies, we have recorded: i. the scientific or common name of the plant or the generic habitat sampled for MF identification; ii the MF genus and species; iii. the location of the study with associated altitude and geographic coordinates; iv. main soil physico-chemical properties (soil pH, texture, organic Carbon, Total Nitrogen, available Phosphorus); climatic variables such as mean annual precipitation and temperature.&lt;br&gt;&lt;br&gt;", "keywords": ["ecosystem management", "Asia", "Agricultural Sciences", "CGIAR Research Program on Water", " Land and Ecosystems", "Multifunctional Landscapes", "gesti\u00f3n de ecosistemas", "soil biology", "MYCORRHIZAE", "CGIAR Research Program", "Earth and Environmental Sciences", "SOIL BIOLOGY", "BIODIVERSITY", "mycorrhizae", "biolog\u00eda del suelo"], "contacts": [{"organization": "Beggi, Francesca, Dasgupta, Debarshi,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/HXAH87"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/HXAH87", "name": "item", "description": "10.7910/DVN/HXAH87", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/HXAH87"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/LNPSGP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "Forest greenhouse gas gross emissions", "description": "Displays the gross greenhouse gas emissions from stand-replacing forest disturbance globally from 2001 onwards. Geospatial data are in 10x10 degree geotifs.  <p><p> The northwest corner of each geotif is noted in the file name, e.g., 50N_030E has its northwest corner at (50 deg N, 30 deg E) and has its southeast corner at (40 deg N, 40 deg E). Use the shapefile in GFW_Hansen_tile_footprints.zip to determine which 10x10 degree geotifs cover your area(s) of interest.  <p> <b>Description (adapted from GFW Open Data Portal, <a>https://data.globalforestwatch.org/datasets/gfw::forest-greenhouse-gas-emissions/about</a>):</b> <p> This emissions layer is part of the forest carbon flux model described in\u202fHarris et al. (2021). This paper introduces a geospatial monitoring framework for estimating global forest carbon fluxes which can assist a variety of actors and organizations with tracking greenhouse gas fluxes from forests and in decreasing emissions or increasing removals by forests. Forest carbon emissions represent the greenhouse gas emissions arising from stand-replacing forest disturbances that occurred in each modeled year (megagrams CO2 emissions/ha, between 2001 and 2023). Emissions include all relevant ecosystem carbon pools (aboveground biomass, belowground biomass, dead wood, litter, soil organic carbon) and greenhouse gases (CO2, CH4, N2O). Emissions estimates for each pixel are calculated following IPCC Guidelines for\u202fnational greenhouse gas inventories\u202fwhere stand-replacing disturbance occurred, as mapped in the Global Forest Change annual tree cover loss data of\u202fHansen et al. (2013). The carbon emitted from each pixel is based on carbon densities in 2000, with adjustment for carbon accumulated between 2000 and the year of disturbance.  <p> Emissions reflect a gross estimate, i.e., carbon removals from subsequent regrowth are not included. Instead, gross carbon removals resulting from subsequent regrowth after clearing are accounted for\u202fin the companion forest carbon removals layer. The fraction of carbon emitted from each pixel upon disturbance (emission factor) is affected by several factors, including the direct driver of disturbance, whether fire was observed in the year of or preceding the observed disturbance event,\u202fwhether the disturbance occurred on peat, and more. All emissions are assumed to occur in the year of disturbance. Emissions can be assigned to a specific year using the Hansen tree cover loss data; separate rasters for emissions for each year are not available from GFW. All input layers were resampled to a common resolution of 0.00025 x 0.00025 degrees each to match Hansen et al. (2013). Emissions are available for download in megagrams of CO2e/ha from 2001 onwards. It is appropriate for visualizing (mapping) emissions because it represents the density of emissions per hectare from 2001 onwards. <p> Each year, the tree cover loss, drivers of tree cover loss, and burned area are updated. In 2023 and 2024, a few model input data sets and constants were changed as well, as described below. Please refer to <a>https://www.globalforestwatch.org/blog/data/whats-new-carbon-flux-monitoring/</a> for more information.  <p> 1. The source of the ratio between belowground carbon and aboveground carbon. Previously used one global constant; now uses map from Huang et al. 2021. <p> 2. The years of tree cover gain. Previously used 2000-2012; now uses 2000-2020 from Potapov et al. 2022. <p> 3. The source of fire data. Previously used MODIS burned area; now uses tree cover loss from fires from Tyukavina et al. 2022. <p> 4. The source of peat maps. New tropical data sets have been included and the data set above 40 degrees north has been changed. <p> 5. Global warming potential (GWP) constants for CH4 and N2O. Previously used GWPs from IPCC Fifth Assessment Report; now uses GWPs from IPCC Sixth Assessment Report. <p> 6. Removal factors for older (>20 years) secondary temperate forests and their associated uncertainties. Previously used removal factors published in Table 4.9 of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories; now uses corrected removal factors and uncertainties from the 4th Corrigenda to the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. <p> 7. Planted tree extent and removal factors. Previously used Spatial Database of Planted Trees (SDPT) Version 1.0; now uses SDPT Version 2.0 and associated removal factors. <p>  <b>Cautions:</b><p>  1. Data are the product of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use.\u202f <p> 2. Values are applicable to forest areas only (canopy cover >30 percent and >5 m height or areas with tree cover gain). See\u202fHarris et al. (2021)\u202ffor further information on the forest definition used in the analysis. <p> 3. Although emissions in each pixel are associated with a specific year of disturbance, emissions over an area of interest reflect the total over the model period of 2001-2023. Thus, values must be divided by 23 to calculate average annual removals. <p> 4. Emissions reflect stand-replacing disturbances as observed in Landsat satellite imagery and do not include emissions from unobserved forest degradation. <p> 5. Emissions reflect a gross estimate, i.e., carbon removals from any regrowth that occurs after disturbance are not included. Instead, gross carbon removals are accounted for in the companion forest carbon removals layer. <p> 6. Emissions data contain temporal inconsistencies. Improvements in the detection of tree cover loss due to the incorporation of new satellite data and methodology changes between 2011 and 2015 may result in higher estimates of emissions in recent years compared to earlier years. Refer to https://www.globalforestwatch.org/blog/data-and-research/tree-cover-loss-satellite-data-trend-analysis/ for additional information. <p> 7. Forest carbon emissions do not reflect carbon transfers from ecosystem carbon pools to the harvested wood products (HWP) pool. <p> 8. This dataset has been updated since its original publication. See Overview for more information.", "keywords": ["Greenhouse gases", "Carbon dioxide", "Emissions", "Earth and Environmental Sciences", "Source", "Forests", "Deforestation"], "contacts": [{"organization": "Gibbs, David, Rose, Melissa, Harris, Nancy,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/LNPSGP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/LNPSGP", "name": "item", "description": "10.7910/DVN/LNPSGP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/LNPSGP"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/M4ZGXP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory", "description": "&lt;b&gt;MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory&lt;/b&gt; &lt;br&gt;&lt;br&gt; -------------------------------------------------------------------------------------- &lt;br&gt; MSZSI is a data extraction tool for Google Earth Engine that aggregates time-series remote sensing information to multiple administrative levels using the FAO GAUL data layers. The code at the bottom of this page (metadata) can be pasted into the Google Earth Engine JavaScript code editor and ran at https://code.earthengine.google.com/.  &lt;br&gt;&lt;br&gt; &lt;i&gt;Please refer to the associated publication&lt;/i&gt;:  &lt;br&gt; Peter, B.G., Messina, J.P., Breeze, V., Fung, C.Y., Kapoor, A. and Fan, P., 2024. Perspectives on modifiable spatiotemporal unit problems in remote sensing of agriculture: evaluating rice production in Vietnam and tools for analysis. &lt;i&gt;Frontiers in Remote Sensing&lt;/i&gt;, 5, p.1042624. &lt;br&gt; &lt;a href='https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624'&gt;https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624&lt;/a&gt; &lt;br&gt;&lt;br&gt; &lt;i&gt;Input options:&lt;/i&gt; &lt;br&gt; [1] Country of interest &lt;br&gt; [2] Start and end year &lt;br&gt; [3] Start and end month &lt;br&gt; [4] Option to mask data to a specific land-use/land-cover type &lt;br&gt; [5] Land-use/land-cover type code from CGLS LULC &lt;br&gt; [6] Image collection for data aggregation &lt;br&gt; [7] Desired band from the image collection &lt;br&gt; [8] Statistics type for the zonal aggregations &lt;br&gt; [9] Statistic to use for annual aggregation &lt;br&gt; [10] Scaling options &lt;br&gt; [11] Export folder and label suffix &lt;br&gt;&lt;br&gt; &lt;i&gt;Output:&lt;/i&gt; Two CSVs containing zonal statistics for each of the FAO GAUL administrative level boundaries &lt;br&gt; &lt;i&gt;Output fields:&lt;/i&gt; system:index, 0-ADM0_CODE, 0-ADM0_NAME, 0-ADM1_CODE, 0-ADM1_NAME, 0-ADMN_CODE, 0-ADMN_NAME, 1-AREA_PERCENT_LULC, 1-AREA_SQM_LULC, 1-AREA_SQM_ZONE, 2-X_2001, 2-X_2002, 2-X_2003, ..., 2-X_2020, .geo &lt;br&gt;&lt;br&gt; &lt;img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_input_v5.PNG?raw=true' width='1000' height='auto'&lt;/img&gt; &lt;br&gt;&lt;br&gt; &lt;b&gt;PREPROCESSED DATA DOWNLOAD&lt;/b&gt; &lt;br&gt;&lt;br&gt; The datasets available for download contain zonal statistics at 2 administrative levels (FAO GAUL levels 1 and 2). Select countries from Southeast Asia and Sub-Saharan Africa &lt;b&gt;(Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Thailand, Vietnam, Burundi, Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe)&lt;/b&gt; are included in the current version, with plans to extend the dataset to contain global metrics. Each zip file is described below and two example NDVI tables are available for preview. &lt;br&gt;&lt;br&gt; &lt;b&gt;Key&lt;/b&gt;: [source, data, units, temporal range, aggregation, masking, zonal statistic, notes]  &lt;br&gt;&lt;br&gt; Currently available: &lt;br&gt;&lt;b&gt;MSZSI-V2_V-NDVI-MEAN.tar&lt;/b&gt;: [NASA-MODIS, NDVI, index, 2001\u20132020, annual mean, agriculture, mean, n/a]  &lt;br&gt;&lt;b&gt;MSZSI-V2_T-LST-DAY-MEAN.tar&lt;/b&gt;: [NASA-MODIS, LST Day, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a]  &lt;br&gt;&lt;b&gt;MSZSI-V2_T-LST-NIGHT-MEAN.tar&lt;/b&gt;: [NASA-MODIS, LST Night, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a]  &lt;br&gt;&lt;b&gt;MSZSI-V2_R-PRECIP-SUM.tar&lt;/b&gt;: [UCSB-CHG-CHIRPS, Precipitation, mm, 2001\u20132020, annual sum, agriculture, mean, n/a]  &lt;br&gt;&lt;b&gt;MSZSI-V2_S-BDENS-MEAN.tar&lt;/b&gt;: [OpenLandMap, Bulk density, g/cm3, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-ORGC-MEAN.tar&lt;/b&gt;: [OpenLandMap, Organic carbon, g/kg, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-PH-MEAN.tar&lt;/b&gt;: [OpenLandMap, pH in H2O, pH, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-WATER-MEAN.tar&lt;/b&gt;: [OpenLandMap, Soil water, % at 33kPa, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-SAND-MEAN.tar&lt;/b&gt;: [OpenLandMap, Sand, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-SILT-MEAN.tar&lt;/b&gt;: [OpenLandMap, Silt, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_S-CLAY-MEAN.tar&lt;/b&gt;: [OpenLandMap, Clay, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] &lt;br&gt;&lt;b&gt;MSZSI-V2_E-ELEV-MEAN.tar&lt;/b&gt;: [MERIT, [elevation, slope, flowacc, HAND], [m, degrees, km&lt;sup&gt;2&lt;/sup&gt;, m], static, n/a, agriculture, mean, n/a] &lt;br&gt;&lt;br&gt;&lt;i&gt;Coming soon&lt;/i&gt; &lt;br&gt;&lt;b&gt;MSZSI-V2_C-STAX-MEAN.tar&lt;/b&gt;: [OpenLandMap, Soil taxonomy, category, static, n/a, agriculture, area sum, n/a] &lt;br&gt;&lt;b&gt;MSZSI-V2_C-LULC-MEAN.tar&lt;/b&gt;: [CGLS-LC100-V3, LULC, category, 2015\u20132019, mode, none, area sum, n/a] &lt;br&gt;&lt;br&gt;&lt;br&gt; &lt;img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_diagram_v2.png?raw=true' width='1000' height='auto'&lt;/img&gt; &lt;br&gt;&lt;br&gt; &lt;b&gt;Data sources:&lt;/b&gt;  &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1'&gt;https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2'&gt;https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD'&gt;https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01'&gt;https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global'&gt;https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1'&gt;https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0'&gt;https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1'&gt;https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1&lt;/a&gt; &lt;br&gt;&lt;li&gt;&lt;a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2'&gt;https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2&lt;/a&gt;&lt;/li&gt; &lt;br&gt; &lt;b&gt;Project information:&lt;/b&gt; &lt;br&gt; SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes &lt;br&gt; &lt;a href='http://seagul.info/'&gt;http://seagul.info/&lt;/a&gt;; &lt;a href='https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental'&gt;https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental&lt;/a&gt; &lt;br&gt; This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) &lt;br&gt;&lt;br&gt; For an additional interactive visualization, visit: &lt;a href='https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi'&gt;https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi&lt;/a&gt; &lt;br&gt;&lt;br&gt; &lt;img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_app.png?raw=true' width='1000' height='auto'&lt;/img&gt; &lt;br&gt;&lt;br&gt;&lt;br&gt; &lt;i&gt; Google Earth Engine code&lt;/i&gt; &lt;pre&gt; /*/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// MSZSI: Multi-Scale Zonal Statistics Inventory Authors: Brad G. Peter, Department of Geography, University of Alabama  Joseph Messina, Department of Geography, University of Alabama  Austin Raney, Department of Geography, University of Alabama  Rodrigo E. Principe, AgriCircle AG  Peilei Fan, Department of Geography, Environment, and Spatial Sciences, Michigan State University  Citation: Peter, Brad; Messina, Joseph; Raney, Austin; Principe, Rodrigo; Fan, Peilei, 2021,  'MSZSI: Multi-Scale Zonal Statistics Inventory', https://doi.org/10.7910/DVN/YCUBXS, Harvard Dataverse, V#  SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes http://seagul.info/ https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740)   ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////*/  /*----------------------------------------------------------------------------------------------------------------------------------- Description: MSZSI is a data extraction tool for aggregating time-series remote sensing information to multiple administrative levels  using the FAO GAUL data layers.  Input parameterization: [1] Enter the country code for the desired country [2] Select a start and end year. Be sure to check for data availability in the collection selected in input 6. [3] Select a start month and end month to specify a temporal range within each year.  [4] Select an image collection for data aggregation. [5] Select the desired band from the image collection. [6] Option to mask data to a specific land-use/land-cover type. Enter 'TRUE' or 'FALSE'. [7] Enter a land-use/land-cover type code from CGLS LULC. Ignore this option if no masking is desired and set input 4 to 'FALSE'. [8] Select a statistics type for the zonal aggregations (defaults to mean) [9] Select a statistic for temporal aggregation (see available options in the parameterization below) [10] Scaling options [11] Export folder output file label suffix  Check tasks tab for CSV exports. Select a point on the map to view timeseries statistics.  Hover over the layers panel to turn layers on/off and set visualization parameters.   For an additional interactive visualization, visit: https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi  Boundary data Layers: https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2 -----------------------------------------------------------------------------------------------------------------------------------*/  // \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022 USER PARAMETERIZATION \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022  /*[1]*/ var countryCode = 264  // Refer to http://www.fao.org/in-action/countrystat/news-and-events/events/training-material/gaul-codes2014/en/  /*[2]*/ var startYear = 2001 // Check data availability for the collection selected in input 4  var endYear = 2020 /*[3]*/ var startMonth = 1  var endMonth = 12  /*[4]*/ var ic = ee.ImageCollection('MODIS/006/MOD13Q1') /*[5]*/ var band = 'NDVI'  /*[6]*/ var maskToLULC = 'TRUE' // Set to 'TRUE' or 'FALSE'  /*[7]*/ var lcType = 40   // Refer to https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global  /*[8]*/ var zonalStatType = ee.Reducer.mean() // examples: ee.Reducer.mean(), ee.Reducer.median(), ee.Reducer.stdDev(),   // ee.Reducer.min(), ee.Reducer.max(), ee.Reducer.sum() /*[9]*/ var temporalAggregateType = 'mean' // available options: 'mean', 'median', 'stddev', 'min', 'max', 'sum'  /*[10]*/ var nativeScale = 'TRUE' // Set to 'TRUE' or 'FALSE'  var scale = 1000 // option to increase the scale to avoid memory crashes  /*[11]*/ var exportFolder = 'GEE_Exports'  var labelSuffix = 'NDVI-MEAN_VIETNAM'  // sample export name: MSZSI-V2_2001-2020_1-12_LC40_GAUL-152-L1_NDVI-MEAN_VIETNAM, but can be changed during download prompt  // note that some country names will need to be adjusted in the download prompt if they contain special characters  ///////////////////////////////////////////////////// NO USER INPUT NEEDED BELOW ////////////////////////////////////////////////////  // Administrative zones and preprocessing ------------------------------------------------------------------------------------------- ic = ic.select(band) var years = ee.List.sequence(startYear,endYear)  var fc_L0 = ee.FeatureCollection('FAO/GAUL/2015/level0').filterMetadata('ADM0_CODE','equals',countryCode) var fc_L1 = ee.FeatureCollection('FAO/GAUL/2015/level1').filterMetadata('ADM0_CODE','equals',countryCode)  .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME'],  ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME']) fc_L1 = fc_L1.map(function(f) {  return f.set('0-ADM2_CODE','NULL').set('0-ADM2_NAME','NULL')  })   var fc_L2 = ee.FeatureCollection('FAO/GAUL/2015/level2').filterMetadata('ADM0_CODE','equals',countryCode)  .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME','ADM2_CODE','ADM2_NAME'],  ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME','0-ADM2_CODE','0-ADM2_NAME'])  // LULC preprocessing --------------------------------------------------------------------------------------------------------------- var lulc = ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global').select('discrete_classification') var lulcMode = lulc.mode().eq(lcType) var lcLabel = '_LC'+lcType var lulcClip = lulcMode.clip(fc_L0) var lulcZone = lulcClip.remap([0,1],[1,1]).rename('zoneArea') var mask = lulcClip.updateMask(lulcClip.eq(1)).rename('mask')  if(maskToLULC == 'FALSE') {  lcLabel = ''  mask = lulcZone }  if(nativeScale == 'TRUE') {  scale = lulc.first().projection().nominalScale() }  // Add area fields ------------------------------------------------------------------------------------------------------------------ var temporal = ee.ImageCollection(years.map(function(y) {  var filterYear = ic.filter(ee.Filter.calendarRange(y,y,'year'))  .filter(ee.Filter.calendarRange(startMonth, endMonth, 'month'))   var aggregate // the temporal aggregation type is set in input 9  if (temporalAggregateType == 'mean') {  aggregate = filterYear.mean()  }  if (temporalAggregateType == 'median') {  aggregate = filterYear.median()  }  if (temporalAggregateType == 'stddev') {  aggregate = filterYear.stdDev()  }  if (temporalAggregateType == 'min') {  aggregate = filterYear.min()  }  if (temporalAggregateType == 'max') {  aggregate = filterYear.max()  }  if (temporalAggregateType == 'sum') {  aggregate = filterYear.sum()  }    return aggregate.where(aggregate.eq(0),1e-10) // True zeroes are currently set to 1e-10 to avoid false no data flags  .updateMask(mask)  .set('extract',ee.String('2-'+labelSuffix+'_').cat(ee.Number(y).toInt()))  .set('year',ee.Number(y).toInt())  .rename('band') }))  // Run functions for each administrative level -------------------------------------------------------------------------------------- var zonal_L1 = zonalStat(fc_L1) var zonal_L2 = zonalStat(fc_L2) var merge = zonal_L1.combine(zonal_L2)  var fcAreas_L1 = getAreas(fc_L1) var fcAreas_L2 = getAreas(fc_L2)  var samples_L1 = createSamples(fc_L1) var samples_L2 = createSamples(fc_L2)  var added_L1 = addFields(samples_L1,fcAreas_L1.select('zoneAreas'),fcAreas_L1.select('lulcAreas')) var added_L2 = addFields(samples_L2,fcAreas_L2.select('zoneAreas'),fcAreas_L2.select('lulcAreas'))  exporter(added_L1,zonal_L1,1) exporter(added_L2,zonal_L2,2)  // Calculate zonal statistics ------------------------------------------------------------------------------------------------------- function zonalStat(fc) {  return temporal.map(function(i) {  var year = i.get('year')  return i.reduceRegions({  collection: fc,  reducer: ee.Reducer.mean().setOutputs(['zStat']),   scale: scale  }).reduceToImage({  properties: ['zStat'],  reducer: ee.Reducer.first()  }).set('extract',i.get('extract')).set('year',year).rename('band')  }) }  // Calculate areas ------------------------------------------------------------------------------------------------------------------ function getAreas(fc) {  var zoneAreas = ee.Image.pixelArea().updateMask(lulcZone).reduceRegions({  collection: fc,  reducer: ee.Reducer.sum(),   scale: scale  }).reduceToImage({  properties: ['sum'],  reducer: ee.Reducer.first()  }).rename('zoneAreas')  var lulcAreas = ee.Image.pixelArea().updateMask(mask).reduceRegions({  collection: fc,  reducer: ee.Reducer.sum(),   scale: scale  }).reduceToImage({  properties: ['sum'],  reducer: ee.Reducer.first()  }).rename('lulcAreas')  return zoneAreas.addBands(lulcAreas) }  // Feature to points ---------------------------------------------------------------------------------------------------------------- function createSamples(fc) {  return fc.map(function(g) {  return ee.Feature(ee.FeatureCollection.randomPoints({  region: g.geometry(),   points: 1,   seed: 0  }).geometry()).copyProperties(g)  })  }  // Add area fields ------------------------------------------------------------------------------------------------------------------ function addFields(samples, areaGridZone, areaGridLULC) {  return samples.map(function(p) {  var point = p.geometry()  var zoneArea = areaGridZone.rename('area').reduceRegion({  reducer: ee.Reducer.first(),   geometry: point,   scale: 1,   maxPixels: 1e13  }).get('area')  var lulcArea = areaGridLULC.rename('area').reduceRegion({  reducer: ee.Reducer.first(),  geometry: point,  scale: 1  }).get('area')  var percLULC = ee.Number(lulcArea).divide(zoneArea).multiply(100)  return ee.Feature(p).set('1-AREA_SQM_LULC',0)  .set('1-AREA_SQM_ZONE',zoneArea).set('1-AREA_SQM_LULC',ee.Algorithms.If(lulcArea,lulcArea,0))  .set('1-AREA_PERCENT_LULC',ee.Algorithms.If(lulcArea,percLULC,0))  }) }  // Export function ------------------------------------------------------------------------------------------------------------------ function exporter(e,zones,n) {  var extracted = e.map(extractToPoints)  function extractToPoints(feature) {  var geom = feature.geometry()  var addField = function(image, f) {  var newFeature = ee.Feature(f)  var getName = image.get('extract')  var setValue = image.reduceRegion({  reducer: ee.Reducer.first(),   geometry: geom,   scale: 1,   maxPixels: 1e13  }).get('band')  return ee.Feature(ee.Algorithms.If(setValue,  newFeature.set(getName, ee.String(setValue)),  newFeature.set(getName, ee.String('No data'))))  }  var newFeature = ee.Feature(zones.iterate(addField, feature))  return newFeature  }    Export.table.toDrive({  collection: extracted,  description: 'MSZSI-V2_'+startYear+'-'+endYear+'_'+startMonth+'-'+endMonth  +lcLabel+'_GAUL-'+countryCode+'-L'+n+'_'+labelSuffix,  folder: exportFolder  }) }  // Map display settings ------------------------------------------------------------------------------------------------------------- var leftMap = ui.Map() var rightMap = ui.Map() ui.Map.Linker([leftMap, rightMap]) ui.root.widgets().reset([leftMap,rightMap]) leftMap.centerObject(fc_L0) leftMap.setOptions('HYBRID').style().set('cursor', 'crosshair') rightMap.setOptions('HYBRID').style().set('cursor', 'crosshair')  // Adds each image to the map displays var len = years.length().getInfo() for (var i = 0; i &lt; len; i++) {  var year = i+startYear  var namer = 'ZSTATS_'+year  var image_L1 = ee.Image(zonal_L1.toList(zonal_L1.size()).get(i)).rename(band)  var image_L2 = ee.Image(zonal_L2.toList(zonal_L2.size()).get(i)).rename(band)  leftMap.addLayer(image_L1,{},namer,false)  rightMap.addLayer(image_L2,{},namer,false) }  var hollow = {color: 'white', width: 0.3, fillColor: '00000000'} leftMap.addLayer(fc_L1.style(hollow),{},'FAO-GAUL-L1') rightMap.addLayer(fc_L2.style(hollow),{},'FAO-GAUL-L2')  // Chart display settings ----------------------------------------------------------------------------------------------------------- var chartOptions = {  fontSize: 11,  width: '100px',  curveType: 'function',  format: 'short',  margin: '0 0 0 0',  hAxis: {format: '0000', textStyle: {fontSize: 10, color: '303030'}, gridlines: {color: 'transparent'}},  vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}},  trendlines: {0: {color: '303030', lineWidth: 0.5, visibleInLegend: false}},  series: {0: {color: '303030', lineWidth: 0.8}},  legend: {textStyle: {color: '303030'}}, }  var panelStyle = {  width: '235px',  position: 'bottom-left',  margin: '0 0 0 0',  border: '1px solid #303030' } var leftChart = ui.Panel({  widgets: ui.Label('Select a point to chart regional time-series',{margin: '0 0 0 0', color:'303030'}),  style: panelStyle }) leftMap.add(leftChart)  // onClick function to query time-series --------------------------------------------------------------------------------------------  function pickLocation(location) {  leftChart.widgets().set(0,ui.Label('Time-series',{fontSize: '14px', fontWeight: 'bold', color: '303030', margin: '7px 0 7px 10px'}))  var chartOptions = {  fontSize: 10,  height: '200px',  curveType: 'function',  format: 'short',  margin: '0 0 0 0',  hAxis: {format: '0000', textStyle: {fontSize: 11, color: '303030'}, gridlines: {color: 'transparent'}},  vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}},  trendlines: {0: {color: 'blue', lineWidth: 0.5, visibleInLegend: false},  1: {color: 'red', lineWidth: 0.5, visibleInLegend: false}  },  series: {0: {color: 'blue', lineWidth: 0.8},  1: {color: 'red', lineWidth: 0.8}  },  legend: {position:'none'}  }    leftChart.widgets().set(1,ui.Label('Loading...',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'}))  leftChart.widgets().set(2,ui.Label('',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'}))    var pLat = location.lat  var pLon = location.lon  var point = ee.Geometry.Point([pLon,pLat])  var selection_L1 = fc_L1.filterBounds(point)  var selection_L2 = fc_L2.filterBounds(point)  var zone_L1_name = ee.Feature(selection_L1.first()).get('0-ADM1_NAME')  var zone_L2_name = ee.Feature(selection_L2.first()).get('0-ADM2_NAME')    leftChart.widgets().set(3,ui.Chart.image.series({  imageCollection: merge,  region: point,  scale: scale,  xProperty: 'year'  }).setOptions(chartOptions))    zone_L1_name.evaluate(function(result_L1) {  zone_L2_name.evaluate(function(result_L2) {  leftChart.widgets().set(1,ui.Label(result_L1+' (L1)',{fontSize: '13px', color: 'blue', margin: '0 0 7px 10px'}))  leftChart.widgets().set(2,ui.Label(result_L2+' (L2)',{fontSize: '13px', color: 'red', margin: '0 0 0 10px'}))  })  })    leftMap.layers().set(len+1, ui.Map.Layer(point,{color: 'blue', opacity: 0.6},'Selected point'))  rightMap.layers().set(len+1, ui.Map.Layer(point,{color: 'red', opacity: 0.6},'Selected point')) }  leftMap.onClick(pickLocation) rightMap.onClick(pickLocation) &lt;/pre&gt;", "keywords": ["Computer and Information Science", "Agricultural Sciences", "Earth and Environmental Sciences", "Social Sciences"], "contacts": [{"organization": "Peter, Brad, Messina, Joseph, Raney, Austin, Principe, Rodrigo, Fan, Peilei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/M4ZGXP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/M4ZGXP", "name": "item", "description": "10.7910/DVN/M4ZGXP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/M4ZGXP"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/T8CMAT", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "created": "2016-02-28", "title": "GMCSD-2. Global Mangrove Carbon, 2000 to 2012, 1 Arc-second, 1 m soil.", "description": "Open AccessGlobal Mangrove Carbon, 2000 to 2012, 1 Arc-Second, 1 m Soil, mid, EQ5.  <p> Annual stocks.  <p> Each of these 13 years is 3TB when extracted. So that is 39 TB as a tif. <p> We needed to use file geodatabase format to compress enough to post on the Dataverse. Hence no TIffs.", "keywords": ["Earth and Environmental Sciences", "Raster", "ArcGIS file Geodatabase rasters", "Global Mangrove Carbon"], "contacts": [{"organization": "Hamilton, Stuart", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/T8CMAT"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/T8CMAT", "name": "item", "description": "10.7910/DVN/T8CMAT", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/T8CMAT"}, {"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": "11586/524923", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:34Z", "type": "Journal Article", "created": "2024-12-03", "title": "Addressing the environmental sustainability of plastics used in agriculture: a multi-actor perspective", "description": "Abstract                   <p>Plastics used in agriculture, commonly known as agriplastics (AP), offer numerous advantages in terrestrial agriculture, forestry, fisheries and aquaculture, but the diffusion of AP-intensive practices has led to extensive pollution. This review aims to synthesise scientific and policy discussions surrounding AP, examining evidence of their benefits and detrimental environmental and agricultural impacts. Following the proposal of a preliminary general taxonomy of AP, this paper presents the findings from a survey conducted among international experts from the plastic industry, farmer organisations, NGOs and environmental research institutes. This analysis highlights knowledge gaps, demands and perspectives for the sustainable future use of AP. Stakeholder positions vary on the options of \uffe2\uff80\uff98rejection\uffe2\uff80\uff99 or \uffe2\uff80\uff98reduction\uffe2\uff80\uff99 of AP, as well as the role of alternative materials such as (bio)degradable and compostable plastics. However, there is consensus on critical issues such as redesign, labelling, traceability, environmental safety standards, deployment and retrieval standards, as well as innovative waste management approaches. All stakeholders express concern for the environment. A \uffe2\uff80\uff98best practice\uffe2\uff80\uff99-based circular model was elaborated capturing these perspectives. In the context of global food systems increasingly reliant on AP, scientists emphasise the need to simultaneously preserve nature-based and traditional knowledge-based sustainable agricultural practices to enhance food system resilience.</p", "keywords": ["multi-actor approach", "330", "Multi-actor approach", "Agriculture", "Environmental technology. Sanitary engineering", "630", "Environmental sciences", "plastic pollution", "plastic waste", "Agriplastics", "Plastic pollution", "Plastic waste", "agriplastics", "GE1-350", "TD1-1066", "agriculture"]}, "links": [{"href": "https://doi.org/11586/524923"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Cambridge%20Prisms%3A%20Plastics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "11586/524923", "name": "item", "description": "11586/524923", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/11586/524923"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-12-04T00:00:00Z"}}, {"id": "1854/LU-8732814", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:40Z", "type": "Journal Article", "created": "2021-11-09", "title": "Litter quality, mycorrhizal association, and soil properties regulate effects of tree species on the soil fauna community", "description": "Abstract   Forest management, including selection of appropriate tree species to mitigate climate change and sustain biodiversity, requires a better understanding of factors that affect the composition of soil fauna communities. These communities are an integral part of the soil ecosystem and play an essential role in forest ecosystem functioning related to carbon and nitrogen cycling. Here, by performing a field study across six common gardens in Denmark, we evaluated the effects of tree species identity and mycorrhizal association (i.e., arbuscular mycorrhiza (AM) and ectomycorrhiza (ECM)) on soil fauna (meso- and macrofauna) taxonomic and functional community composition by using diversity, abundance, and biomass as proxies. We found that (1) tree species identity and mycorrhizal association both showed significant effects on soil fauna communities, but the separation between community characteristics in AM and ECM tree species was not entirely consistent; (2) total soil fauna abundance, biomass, as well as taxonomic and functional diversity were generally significantly higher under AM tree species, as well as lime, with higher litter quality (high N and base cation and low lignin:N ratio); (3) tree species significantly influenced the properties of litter, forest floor, and soil, among which litter and/or forest floor N, P, Ca, and Mg concentrations, soil pH, and soil moisture predominantly affected soil fauna abundance, biomass, and taxonomic and functional diversity. Our results from this multisite common garden experiment provide strong and consistent evidence of positive effects of tree species with higher litter quality on soil fauna communities in general, which helps to better understand the effects of tree species selection on soil biodiversity and its functions related to forest soil carbon sequestration.", "keywords": ["DECOMPOSITION", "EARTHWORMS", "Diversity", "PH", "FOREST FLOOR", "Common garden experiment", "Soil meso- and macrofauna", "DIVERSITY", "Biology and Life Sciences", "04 agricultural and veterinary sciences", "15. Life on land", "NITROGEN", "CARBON", "Taxonomic group", "FUNCTIONAL TRAITS", "Abundance", "13. Climate action", "Earth and Environmental Sciences", "Functional group", "0401 agriculture", " forestry", " and fisheries", "BIODIVERSITY", "ABUNDANCE", "Biomass"]}, "links": [{"href": "https://doi.org/1854/LU-8732814"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1854/LU-8732814", "name": "item", "description": "1854/LU-8732814", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1854/LU-8732814"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-02-01T00:00:00Z"}}, {"id": "1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:41Z", "type": "Journal Article", "created": "2022-11-21", "title": "Global biomass burning fuel consumption and emissions at 500\u2009m spatial resolution based on the Global Fire Emissions Database (GFED)", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. In fire emission models, the spatial resolution of both the modelling framework and the satellite data used to quantify burned area can have considerable impact on emission estimates. Consideration of this sensitivity is especially important in areas with heterogeneous land cover and fire regimes and when constraining model output with field measurements. We developed a global fire emissions model with a spatial resolution of 500\u2009m using MODerate resolution Imaging Spectroradiometer (MODIS) data. To accommodate this spatial resolution, our model is based on a simplified version of the Global Fire Emissions Database (GFED) modelling framework. Tree mortality as a result of fire, i.e.\u00a0fire-related forest loss, was modelled based on the overlap between 30\u2009m forest loss data and MODIS burned area and active fire detections. Using this new 500\u2009m model, we calculated global average carbon emissions from fire of 2.1\u00b10.2 (\u00b11\u03c3 interannual variability, IAV)\u2009Pg\u2009C\u2009yr\u22121 during 2002\u20132020. Fire-related forest loss accounted for 2.6\u00b10.7\u2009% (uncertainty range =1.9\u2009%\u20133.3\u2009%) of global burned area and 24\u00b16\u2009% (uncertainty range =16\u2009%\u201331\u2009%) of emissions, indicating that fuel consumption in forest fires is an order of magnitude higher than the global average. Emissions from the combustion of soil organic carbon (SOC) in the boreal region and tropical peatlands accounted for 13\u00b14\u2009% of global emissions. Our global fire emissions estimate was higher than the 1.5\u2009Pg\u2009C\u2009yr\u22121 from GFED4 and similar to 2.1\u2009Pg\u2009C\u2009yr\u22121 from GFED4s. Even though GFED4s included more burned area by accounting for small fires undetected by the MODIS burned area mapping algorithm, our emissions were similar to GFED4s due to higher average fuel consumption. The global difference in fuel consumption could mainly be explained by higher SOC emissions from the boreal region as constrained by additional measurements. The higher resolution of the 500\u2009m model also contributed to the difference by improving the simulation of landscape heterogeneity and reducing the scale mismatch in comparing field measurements to model grid cell averages during model calibration. Furthermore, the fire-related forest loss algorithm introduced in our model led to more accurate and widespread estimation of high-fuel-consumption burned area. Recent advances in burned area detection at resolutions of 30\u2009m and finer show a substantial amount of burned area that remains undetected with 500\u2009m sensors, suggesting that global carbon emissions from fire are likely higher than our 500\u2009m estimates. The ability to model fire emissions at 500\u2009m resolution provides a framework for further improvements with the development of new satellite-based estimates of fuels, burned area, and fire behaviour, for use in the next generation of GFED.</p></article>", "keywords": ["QE1-996.5", "13. Climate action", "11. Sustainability", "Geology", "15. Life on land", "7. Clean energy", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2", "name": "item", "description": "1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1871.1/bbc7e25d-d1b9-4c7d-baa4-1a09012f06b2"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-30T00:00:00Z"}}, {"id": "10.1002/jgrg.20063", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:31Z", "type": "Journal Article", "created": "2013-04-25", "title": "Effect Of Continued Nitrogen Enrichment On Greenhouse Gas Emissions From A Wetland Ecosystem In The Sanjiang Plain, Northeast China: A 5 Year Nitrogen Addition Experiment", "description": "Abstract<p>Mounting evidence supports that wetland ecosystems, one of the largest carbon pools on the earth, are exposed to ample nitrogen (N) additions due to atmospheric deposition or N loading from upstream agricultural fertilizer application. However, our understanding of how N enrichment affects the fluxes of greenhouse gases (GHGs) in wetlands is weak. A 5\uffe2\uff80\uff89year N addition experiment was conducted to examine the responses of CH4 and N2O fluxes as well as ecosystem respiration from wetlands in the Sanjiang Plain, Northeast China, through 2005 to 2009. Four levels of N addition (control, 0\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921\uffe2\uff80\uff89yr\uffe2\uff88\uff921; low\uffe2\uff80\uff90level, 60\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921\uffe2\uff80\uff89yr\uffe2\uff88\uff921; medium\uffe2\uff80\uff90level, 120\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921\uffe2\uff80\uff89yr\uffe2\uff88\uff921; high\uffe2\uff80\uff90level, 240\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921\uffe2\uff80\uff89yr\uffe2\uff88\uff921) were designed in this study. Overall, our results show that medium and high levels of N addition increased ecosystem respiration by 28% and 69% (P\uffe2\uff80\uff89&lt;\uffe2\uff80\uff890.05), respectively, while low\uffe2\uff80\uff90level N addition has no effect on ecosystem respiration (P\uffe2\uff80\uff89&gt;\uffe2\uff80\uff890.05). High\uffe2\uff80\uff90level N fertilization exerted stronger effects on ecosystem respiration in the initial year than the following years. It indicated that the effects of high\uffe2\uff80\uff90level N fertilization on CO2 might be overestimated by short\uffe2\uff80\uff90term observations. High\uffe2\uff80\uff90level N fertilization increased N2O emissions by 396% over the 5\uffe2\uff80\uff89years (P\uffe2\uff80\uff89&lt;\uffe2\uff80\uff890.05), but the low\uffe2\uff80\uff90 and medium\uffe2\uff80\uff90level\uffe2\uff80\uff90N addition did not exert any apparent effect on N2O emissions (P\uffe2\uff80\uff89&gt;\uffe2\uff80\uff890.05). N2O emission under high\uffe2\uff80\uff90level N addition in the first and fifth years showed stronger pronounced responses to N addition compared with that from the third and fourth years, indicating the importance of long\uffe2\uff80\uff90term field observation. Over the 5\uffe2\uff80\uff89years, however, the low and medium\uffe2\uff80\uff90level N addition showed no effect on N2O emissions. The four levels of N addition exerted no effect on CH4 emissions (P\uffe2\uff80\uff89&gt;\uffe2\uff80\uff890.05). Furthermore, the relationship between GHGs and soil temperature or water table depth varied among different plots and experimental time. Our findings highlighted the importance of gas species, experimental time, and the amount of fertilizer N with regard to the responses of GHG emissions to N fertilization.</p>", "keywords": ["2. Zero hunger", "13. Climate action", "11. Sustainability", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1002/jgrg.20063"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Geophysical%20Research%3A%20Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/jgrg.20063", "name": "item", "description": "10.1002/jgrg.20063", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/jgrg.20063"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-05-21T00:00:00Z"}}, {"id": "10.1002/jpln.200700317", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:32Z", "type": "Journal Article", "created": "2008-09-30", "title": "Fluxes Of Climate-Relevant Trace Gases Between A Norway Spruce Forest Soil And Atmosphere During Repeated Freeze-Thaw Cycles In Mesocosms", "description": "Abstract<p>For this century, an increasing frequency of extreme meteorological boundary conditions is expected, presumably resulting in a changing frequency of freezing and thawing of soils in higher\uffe2\uff80\uff90elevation areas. Our current knowledge about the effects of these events on trace\uffe2\uff80\uff90gas emissions from soils is scarce. In this study, the effects of freeze\uffe2\uff80\uff93thaw events on the fluxes of the trace gases CO2, N2O, and NO between soil and atmosphere were investigated in a laboratory experiment. Undisturbed soil columns were collected from a mature Norway spruce forest in the \uffe2\uff80\uff9cFichtelgebirge\uffe2\uff80\uff9d, SE Germany. The influence of freezing temperatures (\uffe2\uff80\uff933\uffc2\uffb0C, \uffe2\uff80\uff938\uffc2\uffb0C, \uffe2\uff80\uff9313\uffc2\uffb0C) on gas fluxes was studied during the thawing periods (+5\uffc2\uffb0C) in three freeze\uffe2\uff80\uff93thaw cycles (FTCs) and compared to unfrozen controls (+5\uffc2\uffb0C).</p><p>Two different types of soil columns were examined in parallel\uffe2\uff80\uff94one consisting of O layer only (O columns) and one composed of O layer and mineral soil horizons (O+M columns)\uffe2\uff80\uff94to quantify the contribution of the organic layer and the top mineral soil to the production or consumption of these trace gases.</p><p>During the thawing period, we observed increasing emissions of CO2, N2O, and NO from the spruce forest soil, but the cumulative emissions of these gases did mostly not exceed the level of the controls. The results show that the O layers were mainly involved in the gas production. Severe soil frost increased CO2 fluxes during soil thawing, whereas repetition of the freeze\uffe2\uff80\uff93thaw events decreased CO2 fluxes from the thawing soil. Fluxes of N2O and NO were neither influenced by freezing temperature nor by freeze\uffe2\uff80\uff93thaw repetition.</p><p>Stable\uffe2\uff80\uff90isotope analysis indicated that denitrification was mostly responsible for the N2O production in the FTC columns. Furthermore, isotope data demonstrated a consumption of N2O through microbial denitrification to N2. It was further shown, that production of N2O also occurred in the mineral horizons. The NO emissions were mainly driven by increasing soil temperature during thawing. In this freeze\uffe2\uff80\uff93thaw experiment up to 20 times higher NO than N2O fluxes were recorded. Our results suggest that topsoil thawing has little potential to increase the emissions of CO2, N2O, and NO in spruce forest soils.</p>", "keywords": ["13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1002/jpln.200700317"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Plant%20Nutrition%20and%20Soil%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/jpln.200700317", "name": "item", "description": "10.1002/jpln.200700317", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/jpln.200700317"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-09-30T00:00:00Z"}}, {"id": "10.1007/s00442-008-1116-9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:51Z", "type": "Journal Article", "created": "2008-07-31", "title": "Increasing Precipitation Event Size Increases Aboveground Net Primary Productivity In A Semi-Arid Grassland", "description": "Water availability is the primary constraint to aboveground net primary productivity (ANPP) in many terrestrial biomes, and it is an ecosystem driver that will be strongly altered by future climate change. Global circulation models predict a shift in precipitation patterns to growing season rainfall events that are larger in size but fewer in number. This 'repackaging' of rainfall into large events with long intervening dry intervals could be particularly important in semi-arid grasslands because it is in marked contrast to the frequent but small events that have historically defined this ecosystem. We investigated the effect of more extreme rainfall patterns on ANPP via the use of rainout shelters and paired this experimental manipulation with an investigation of long-term data for ANPP and precipitation. Experimental plots (n = 15) received the long-term (30-year) mean growing season precipitation quantity; however, this amount was distributed as 12, six, or four events applied manually according to seasonal patterns for May-September. The long-term mean (1940-2005) number of rain events in this shortgrass steppe was 14 events, with a minimum of nine events in years of average precipitation. Thus, our experimental treatments pushed this system beyond its recent historical range of variability. Plots receiving fewer, but larger rain events had the highest rates of ANPP (184 +/- 38 g m(-2)), compared to plots receiving more frequent rainfall (105 +/- 24 g m(-2)). ANPP in all experimental plots was greater than long-term mean ANPP for this system (97 g m(-2)), which may be explained in part by the more even distribution of applied rain events. Soil moisture data indicated that larger events led to greater soil water content and likely permitted moisture penetration to deeper in the soil profile. These results indicate that semi-arid grasslands are capable of responding immediately and substantially to forecast shifts to more extreme precipitation patterns.", "keywords": ["0106 biological sciences", "2. Zero hunger", "Colorado", "Time Factors", "Rain", "Water", "Carbon Dioxide", "15. Life on land", "Poaceae", "01 natural sciences", "Soil", "13. Climate action", "Seasons", "Ecosystem", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Eugene F. Kelly, Jana L. Heisler-White, Jana L. Heisler-White, Alan K. Knapp,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s00442-008-1116-9"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Oecologia", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00442-008-1116-9", "name": "item", "description": "10.1007/s00442-008-1116-9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00442-008-1116-9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2008-08-01T00:00:00Z"}}, {"id": "10.1007/s00376-006-0726-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:50Z", "type": "Journal Article", "created": "2006-09-14", "title": "Comparison Of Co2 Effluxes And Their Driving Factors Between Two Temperate Steppes In Inner Mongolia, China", "description": "Soil respiration is a key component of the global terrestrial ecosystem carbon cycle. The static opaque chamber method was used to measure the CO2 effluxes from soil of a semiarid Aneurolepidium chinense steppe and a Stipa krylovii steppe in the Xilin River Basin of Inner Mongolia, China from March 2002 to December 2004. The results indicated that the soil respiration rates of the semiarid Aneurolepidium chinense steppe and the Stipa krylovii steppe were both relatively high from mid-May to mid-September of each year and remained low during the rest of the year. The minimum value of soil respiration occurred in December or January and negative effluxes of CO2 appeared for several days during the non-growing season of individual years at the two sampling sites. A high annual variation was found in the two steppes with the coefficients of variance (CV) being over 94%, even high to 131%. The annual sums of soil CO2 efflux of the Aneurolepidium chinense steppe varied between 356.4 gC m\u22122 yr\u22121 and 408.8 gC m\u22122 yr\u22121, while those of the Stipa krylovii steppe in the three years were in the range of 110.6 gC m\u22122 yr\u22121 to 148.6 gC m\u22122 yr\u22121. The mean respiration rates of the Aneurolepidium chinense steppe were significantly higher than those of the Stipa krylovii steppe in different statistical periods with the exception of the non-growing season. About 59.9% and 80.6% of the soil respiration variations in both steppes for the whole sampling period were caused by the changes of temperature and soil water content. In the Aneurolepidium chinense steppe, the soil respiration rate has significant or extremely significant positive correlation (r = 0.58\u20130.85, p < 0.05 or p < 0.01) with air temperature and ground temperature of the topsoil except in 2002; the unique contributions of temperature change to the soil respiration variation of the three years were 53.3%, 81.0% and 58.6%, respectively. But, for the Stipa krylovii steppe in the same time interval, the soil water content (especially that of the 10\u201320 cm layer) has a greater effect on the change of soil respiration, and the unique contributions of the change of the 10\u201320 cm soil water content to the variations of soil respiration in 2002 and 2003 were 60.0% and 54.3%, respectively. In 2004, in spite of the higher contribution of temperature than soil water content, the contribution of ground temperature at a depth of 10 cm was only 46.2%, much weaker than that of any single year in the Aneurolepidium chinense steppe.", "keywords": ["13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Manfred Domroes, Xing-Ren Liu, Li-xin Liu, Yuanbo Geng, Yuchun Qi, Yunshe Dong,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s00376-006-0726-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Advances%20in%20Atmospheric%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00376-006-0726-6", "name": "item", "description": "10.1007/s00376-006-0726-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00376-006-0726-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-10-01T00:00:00Z"}}, {"id": "10.1007/s00382-016-3308-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:50Z", "type": "Journal Article", "created": "2016-08-23", "title": "Assessing mid-latitude dynamics in extreme event attribution systems", "description": "Open AccessISSN:1432-0894", "keywords": ["Atmospheric Science", "550", "0207 environmental engineering", "02 engineering and technology", "551", "01 natural sciences", "Dynamics", "[SDU] Sciences of the Universe [physics]", "[SDU.STU.CL] Sciences of the Universe [physics]/Earth Sciences/Climatology", "[SDU]Sciences of the Universe [physics]", "[SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology", "13. Climate action", "Mid-latitudes", "Event attribution; Dynamics; Mid-latitudes; Extreme", "Event attribution", "Extreme", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://centaur.reading.ac.uk/66579/7/art%253A10.1007%252Fs00382-016-3308-z.pdf"}, {"href": "https://doi.org/10.1007/s00382-016-3308-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Climate%20Dynamics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00382-016-3308-z", "name": "item", "description": "10.1007/s00382-016-3308-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00382-016-3308-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-08-23T00:00:00Z"}}, {"id": "10.1016/j.agee.2006.01.008", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:25Z", "type": "Journal Article", "created": "2006-03-14", "title": "Promising Indicators For Assessment Of Agroecosystems Alteration Among Natural, Reforested And Agricultural Land Use In Southern Brazil", "description": "Microbiological soil-quality indicators, especially related to C and N cycles, and microbial diversity may be useful tools to determine whether a particular environment responds to an imposed management or reclamation strategy. External influences such as forest clearance and soil management affect biological indicators making them useful to point out whether the land use strategy is sustainable. Accordingly, the aim of this work was to assess the utility of some soil chemical and microbiological properties and 16S rDNA diversity in bacteria domain and their significance as soil-quality indicators in different land use systems in southern Brazil, Parana State. Nine sites with soil originated from basalt (Rhodic Ferralsol), previously covered with the Atlantic native forest were evaluated: a native forest tract as reference; three sites artificially reforested with native species, but with understory differently managed; secondary forest naturally regenerated from abandoned pasture; artificially reforested with eucalyptus; two wheat-cropped sites at differing vegetative stages; one site in fallow. Twenty-four chemical and microbiological properties and their derivatives were assessed, in addition to molecular diversity of bacteria domain based on denaturating gradient gel electrophoresis (DGGE) analysis. Amongst all variables, the most dissimilar along the sites were total organic C, microbial biomass C and N, and ammonification rate. Total organic C was highest in the native forest, followed by secondary forest, eucalyptus and the artificially reforested sites; the wheat-cropped and fallow sites produced the lowest values. This trend was also observed for ammonification rate, which was closely correlated to organic C. Microbial biomass C and N were also higher in the reforested sites, whereas for microbial N biomass, the eucalyptus site resembled to the wheat-cropped and fallow sites. The DGGE analysis revealed that the fallow, eucalyptus and wheat-cropped sites had less bacterial diversity. All the sites reforested with native species grouped with the native forest, while the eucalyptus, fallow and wheat-cropped sites formed separate clusters. A similar clustering pattern was observed when all chemical and microbiological properties were considered in a grouping analysis. The results for reforestation employing native species tended to be similar to those of the stable native forest, while the use of an exotic species (eucalyptus) tended to be similar to those of the cropped sites. In addition, the fallow site showed general unfavorable trends in microbiological indicators and less bacterial diversity, suggesting that such soil management is not sustainable at least in subtropical areas. In this case, would be preferable provide the soil with vegetal covering that increase the organic C inputs and consequently microbial diversity and activity.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2006.01.008"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2006.01.008", "name": "item", "description": "10.1016/j.agee.2006.01.008", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2006.01.008"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-07-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2006.02.006", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:25Z", "type": "Journal Article", "created": "2006-04-18", "title": "The Practical Use Of Water Management Based On Soil Redox Potential For Decreasing Methane Emission From A Paddy Field In Japan", "description": "Abstract   Water management is one of the most effective options in decreasing methane (CH4) emission from a paddy field. We have proposed the water management based on soil redox potential (Eh) named \u2018Eh control\u2019, and demonstrated the effectiveness of Eh control in decreasing CH4 emission in pot experiments. The objective of the present study was to consider the practicability of Eh control under field conditions.  Two-year experiments were carried out in a paddy field at the Agricultural and Forestry Research Center, University of Tsukuba, Japan in 2003 and 2004. Experimental factors were water management and rice (Oryza sativa L., cultivar: Koshihikari) straw treatment. Two methods of water management during rice growing period were continuous flooding and Eh control. For Eh control, drainage was carried out whenever the soil Eh decreased to \u2212150\u00a0mV, and flooding was carried out whenever the soil Eh increased to 0\u00a0mV in 2003 and 100\u00a0mV in 2004. Two methods of rice straw treatment were application and removal in the preceding winters of all straw harvested. The CH4 flux was measured by a closed chamber method and the total emission during the growing period was estimated. Rice grain and straw yields were examined by a quadrat sampling method. The yield component was analyzed only in 2004.  The total CH4 emission was decreased by Eh control to 36% of continuous flooding on the 2-year average. Although straw application hastened the decrease in soil Eh when compared with straw removal, it did not affect the total CH4 emission. Rice grain and straw yields were not affected by the experimental factors. However, yield component analysis showed that Eh control increased the number of panicles per hill and resulted in increased brown rice yield. Straw application also increased the number of panicles per hill, but did not affect brown rice yield.  Consequently, the present study demonstrates the practicability of Eh control under the field conditions on an experimental level. Two important suggestions were obtained from the above results. One is that Eh control decreases CH4 emission to a minimum level according to the range of soil Eh determined. Another is that it may be possible to change the range of soil Eh to a more positive value that will decrease CH4 emission more and increase rice grain yield.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2006.02.006"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2006.02.006", "name": "item", "description": "10.1016/j.agee.2006.02.006", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2006.02.006"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-09-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2018.12.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:19Z", "type": "Journal Article", "created": "2018-12-19", "title": "Organic carbon content controls the severity of water repellency and the critical moisture level across New Zealand pasture soils", "description": "<p>Organic matter can render soil hydrophobic and cause soil water repellency (SWR) which has large implications for agriculture. Consequences such as fingered flow, uneven wetting patterns, and increased overland flow reduce irrigation efficiency and plant nutrient availability. The phenomenon of SWR is a transient soil property depending, inter alia, on soil water content (w). Soil can exhibit SWR from oven-dry w until the critical w where it again becomes fully wettable (w<sub>NON</sub>). The total SWR can be obtained from the nonlinear SWR-w relationship as the integrated trapezoidal area under the SWR-w curve (SWR<sub>AREA</sub>). We analyzed 78 soil samples, representing five dominant soil orders in the South Island of New Zealand. The soils had a large range in clay (0.000\u20130.520 kg kg<sup>\u22121</sup>) and organic carbon (OC) content (0.021\u20130.217 kg kg<sup>\u22121</sup>). The degree of SWR was measured on soils at air-dry conditions (SWR<sub>AD</sub>) and after heat-pretreatment at 60 (SWR<sub>60</sub>) and 105\u00b0C (SWR<sub>105</sub>). Further, SWR was measured in small w increments above air-dry w until w<sub>NON</sub> was reached. The SWR-w curves were either unimodal or bimodal, or no SWR occurred. SWR<sub>AREA</sub> ranged from 0.16 to 26.82 mN m<sup>\u22121</sup> kg kg<sup>\u22121</sup>. Among the five soil orders tested, the Podzols exhibited the highest severity in SWR, whereas the Semiarid soils were the least hydrophobic soils. In conclusion, OC was the main factor for controlling the severity of SWR. Though, pH also had minor effects on SWR. Further, an upper limit critical water content was derived from the simple relationship between the w<sub>NON</sub> and OC, which could be applied to improve irrigation practices of pastoral soils. However, there is a need for further testing on different soils and land uses.</p>", "keywords": ["2. Zero hunger", "07 Agricultural and Veterinary Sciences", "05 Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "06 Biological Sciences", "910", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2018.12.007"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2018.12.007", "name": "item", "description": "10.1016/j.geoderma.2018.12.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2018.12.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-03-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2013.03.014", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:29Z", "type": "Journal Article", "created": "2013-04-30", "title": "Effects Of Long-Term Tillage And Drainage Treatments On Greenhouse Gas Fluxes From A Corn Field During The Fallow Period", "description": "Abstract   Advance tillage research suggests that tillage decreases soil fertility and adversely affects the environment. The objective of this research was to estimate the greenhouse gas (GHG) flux vis-a-vis GHG production potential at different soil depths (0\u2013100\u00a0cm) from tillage and drainage management treatments during the fallow period (October 2009 to April 2010) in a continuous (since 1994) corn ( Zea mays ) growing field at the Waterman farm in central Ohio. The Crosby silt loam ( Aeric ochraqualf ) soil of the experimental farm has been managed with the same practice since 1994 with two tillage sub-factors: no till (NT) and chisel tillage (T) and two drainage sub-factors: tile drainage (D) and no-drainage (ND). The fallow period was from the middle of October to the middle of April. The field was under snow cover during the middle of December to the first week of March. GHG fluxes (CO 2 , CH 4  and N 2 O) were significantly lower during the snow cover period. This study suggests that the CO 2  flux was significantly higher from T and D plots compared to NT and ND plots. Neither CH 4  nor N 2 O fluxes were influenced by tillage or drainage. The CO 2  flux from T\u00a0+\u00a0D treatments was significantly higher (25.98\u2013398.65\u00a0mg\u00a0m \u22122 \u00a0h \u22121 ) throughout the fallow period. Significantly higher N 2 O flux (87.07\u2013125.76\u00a0\u03bcg\u00a0m \u22122 \u00a0h \u22121 ) was recorded from all treatments during the thawing period in the first week of March. Considering that the total C flux involves only the loss from the SOC stock, as much as 3.05% of the total SOC stock (1.23\u00a0Mg\u00a0C\u00a0ha \u22121 ) was lost during the fallow period from T\u2013D plots as CO 2  and CH 4 . Analysis of soil from different soil depths suggests that the CO 2  and N 2 O emissions from soil were mostly dependent on production potential at 0\u201310\u00a0cm and 0\u201330\u00a0cm of soil depths, respectively. However, there was no such trend for CH 4  emissions from soil.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences", "12. Responsible consumption"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2013.03.014"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2013.03.014", "name": "item", "description": "10.1016/j.agee.2013.03.014", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2013.03.014"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-05-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2018.01.015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:33Z", "type": "Journal Article", "created": "2018-01-30", "title": "Runoff, sediment and nutrient exports from a Mediterranean vineyard under integrated production: An experiment at plot scale", "description": "Abstract   Conventional management of Mediterranean vineyards strongly contributes to land degradation. In Portugal, the use of integrated production has been encouraged by governmental subsidies because it is assumed to be a farm management system that protects the environment and favours agriculture sustainability. The purpose of this study is to assess the impact of minimum tillage and regulated fertilization practices, driven by integrated production, on runoff and associated sediment and nutrient exports (total phosphorous \u2013 TP, total nitrogen \u2013 TN and nitrates \u2013 NO3). A vineyard in the Bairrada wine region was instrumented with six runoff plots (80\u2013122\u202fm2). Plots were monitored on a weekly to bi-weekly basis (depending on the rainfall pattern), over two hydrological years (from October 2012 to September 2014). Results indicated that annual runoff coefficients ranged from 10% to 20%, sediment losses from 1.1 to 29.0\u202fMg\u202fha\u22121\u202fyr\u22121, TP exports from 0.4 to 6.5\u202fkg\u202fha\u22121\u202fyr\u22121, TN exports from 0.2 to 20.0\u202fkg\u202fha\u22121\u202fyr\u22121 and NO3 exports from 0.1 to 0.8\u202fkg\u202fha\u22121\u202fyr\u22121. These results highlight the susceptibility of vineyards to land degradation and their role as a diffuse source of pollution. Rainfall strongly influenced runoff as well as sediment and nutrient concentrations, leading to relevant inter-annual and seasonal differences. Over the study period, about 60% of runoff and >85% of sediments and nutrients exported by runoff were recorded during winter. Management practices, namely inter-row tillage deeply influenced sediment exports, whereas fertilization, had a strong effect on nitrate exports. Although integrated production lead to lower runoff and nutrient exports than conventional viticulture, additional measures are needed to effectively prevent soil erosion and nutrient losses in Mediterranean vineyards.", "keywords": ["2. Zero hunger", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2018.01.015"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2018.01.015", "name": "item", "description": "10.1016/j.agee.2018.01.015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2018.01.015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2006.09.012", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:25Z", "type": "Journal Article", "created": "2006-11-14", "title": "Influence Of No-Tillage On The Distribution And Lability Of Phosphorus In Finnish Clay Soils", "description": "Abstract   No-tillage (NT) is a method adopted to reduce erosion and particulate phosphorus (P) load from arable land to watercourses. However, it has been found to increase the loss of dissolved P with surface runoff, but the reasons for that have rarely been examined in detail. The objective of the present study was to determine the chemical factors explaining this response by investigating the impact of NT on the type and distribution of P reserves as well as on organic carbon (C) in the 0\u201335\u00a0cm topsoil layer of clay soil profiles (Vertic Cambisols). Soil samples were taken from two experimental fields (Jokioinen and Aurajoki) at 0\u20135, 5\u201320 and 20\u201335\u00a0cm depths in conventionally tilled (CT) and non-tilled (for 4\u20135 years) plots. The plots had been cultivated and fertilized according to the common field practices in Finland (15\u201318\u00a0kg\u00a0P and 100\u2013128\u00a0kg\u00a0N\u00a0ha \u22121 \u00a0year \u22121 ).  Inorganic and organic P reserves characterized by a modified Chang and Jackson fractionation procedure were not significantly affected by the cultivation methods. However, in the uppermost soil layer (0\u20135\u00a0cm) in NT of the Jokioinen field, the labile P determined by water extraction (P w ) increased significantly, whereas the increase in P extracted with acid ammonium acetate (P AAC ) remained statistically insignificant. The increase in labile P coincided with a significant increase in organic carbon (C), which supports the theory that competition between organic anions and phosphate for the same sorption sites on oxide surfaces will enhance the lability of soil P. In the Aurajoki field with distinct soil cracking, P w  and P AAC  were not affected by NT in the uppermost soil layer, but they increased in the deepest soil layer (20\u201335\u00a0cm) concomitantly with an increase in Al-bound P and organic C. However, the increases were not statistically significant. In both fields, soil acidification due to the repeated application of N fertilizers at a shallow soil depth as well as the accumulation of organic C lowered pH of the uppermost soil layer in NT compared to the deeper soil layers. The results indicated that even short-term NT can increase the labile P in clay soil. However, further studies are needed to assess the long-term changes in lability of surface soil P and, consequently, the possible need for readjustment of the fertilization level in NT.", "keywords": ["suorakylv\u00f6", "2. Zero hunger", "330", "no-tillage", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "puskurikyky", "6. Clean water", "ploughing", "inorganic phosphorus", "kynt\u00f6", "Suomi", "clay soils", "0401 agriculture", " forestry", " and fisheries", "Ka", "savimaat", "water-soluble phosphorus", "phosphorus", "fosfori", "P buffering capacit", "vesiliukoinen fosfori", "Finland", "ep\u00e4orgaaninen fosfori", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2006.09.012"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2006.09.012", "name": "item", "description": "10.1016/j.agee.2006.09.012", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2006.09.012"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-05-01T00:00:00Z"}}, {"id": "10.1007/s00248-007-9308-0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:44Z", "type": "Journal Article", "created": "2007-09-01", "title": "Long-Term Effect Of Municipal Solid Waste Amendment On Microbial Abundance And Humus-Associated Enzyme Activities Under Semiarid Conditions", "description": "Microbial ecology is the key to understanding the function of soil biota for organic matter cycling after a single amendment of organic waste in semiarid soils. Therefore, in this paper, the long-term effect (17 years) of adding different doses of a solid municipal waste to an arid soil on humus-enzyme complexes, a very stable and long-lasting fraction of soil enzymes, as well as on microbial and plant abundance, was studied. Humic substances were extracted by 0.1 M pH 7 sodium pyrophosphate from soil samples collected in experimental plots amended with different doses of a solid municipal waste (0, 65, 130, 195, and 260 t/ha) 17 years before. The activity of different hydrolases related with the C (beta-glucosidase), N (urease), and P (alkaline phosphatase) cycles and with the formation of humic substances (o-diphenol oxidase) were determined in this extract. The density and diversity of plant cover in the plots, as well as the fungal and bacterial biomass (by analyzing phopholipid fatty acids) were also determined. In general, the amended plots showed greater humic substance-related enzymatic activity than the unamended plots. This activity increased with the dose but only up to a certain level, above which it leveled off or even diminished. Plant diversity and cover density followed the same trend. Fungal and bacterial biomass also benefited in a dose-dependent manner. Different signature molecules representing gram+ and gram- bacteria, and those corresponding to monounsaturated and saturated fatty acids showed a similar behavior. The results demonstrate that organic amendment had a noticeable long-term effect on the vegetal development, humic substances-related enzyme activity and on the development of bacteria and fungi in semiarid conditions.", "keywords": ["2. Zero hunger", "Analysis of Variance", "Time Factors", "Bacteria", "Fatty Acids", "Fungi", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Enzymes", "Refuse Disposal", "12. Responsible consumption", "Soil", "Ergosterol", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "Biomass", "Humic Substances", "Phospholipids", "Soil Microbiology", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s00248-007-9308-0"}, {"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/s00248-007-9308-0", "name": "item", "description": "10.1007/s00248-007-9308-0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00248-007-9308-0"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2007-09-02T00:00:00Z"}}, {"id": "10.1007/bf01098474", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:42Z", "type": "Journal Article", "created": "2005-02-05", "title": "Integrated Land-Use Systems: Assessment Of Promising Agroforest And Alternative Land-Use Practices To Enhance Carbon Conservation And Sequestration", "description": "Degraded or sub-standard soils and marginal lands occupy a significant proportion of boreal, temperate and tropical biomes. Management of these lands with a wide range of existing, site-specific, integrated, agroforest systems represents a significant global opportunity to reduce the accumulation of greenhouse gases in the atmosphere. Establishment of extensive agricultural, agroforest, and alternative land-use systems on marginal or degraded lands could sequester 0.82\u20132.2 Pg carbon (C) per year, globally, over a 50-year time-frame. Moreover, slowing soil degradation by alternative grassland management and by impeding desertification could conserve up to 0.5\u20131.5 Pg C annually. A global analysis of biologic and economic data from 94 nations representing diverse climatic and edaphic conditions reveals a range of integrated land-use systems which could be used to establish and manage vegetation on marginal or degraded lands. Promising land-use systems and practices identified to conserve and temporarily store C include agroforestry systems, fuelwood and fiber plantations, bioreserves, intercropping systems, and shelterbelts/windbreaks. For example, successful establishment of low-intensity agroforestry systems can store up to 70 Mg C/ha in boreal, temperate and tropical ecoregions. The mean initial cost of soil rehabilitation and revegetation ranges from $500\u20133,000/ha for the 94 nations surveyed. Natural regeneration of woody vegetation or agro-afforestation establishment costs were less than $1000/ha in temperate and tropical regions. The costs of C sequestration in soil and vegetation systems range from $1-69/Mg C, which compares favorably with other options to reduce greenhouse gas emissions to the atmosphere. Although agroforestry system projects were recently established to conserve and sequester C in Guatemala and Malaysia, constraints to wide-spread implementation include social conditions (demographic factors, land tenure issues, market conditions, lack of infrastructure), economic obstacles (difficulty of demonstrating benefits of alternative systems, capital requirements, lack of financial incentives) and, ecologic considerations (limited knowledge of impacts and sustainability of some systems).", "keywords": ["2. Zero hunger", "13. Climate action", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Robert K. Dixon, Jack K. Winjum, Paul E. Schroeder, Kenneth Andrasko, Jeffrey J. Lee,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/bf01098474"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Climatic%20Change", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/bf01098474", "name": "item", "description": "10.1007/bf01098474", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/bf01098474"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1994-01-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2018.11.092", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:36Z", "type": "Journal Article", "created": "2018-11-10", "title": "Hydroperiod, Soil Moisture And Bioturbation Are Critical Drivers Of Greenhouse Gas Fluxes And Vary As A Function Of Landuse Change In Mangroves Of Sulawesi, Indonesia", "description": "The loss and degradation of mangroves can result in potentially significant sources of atmospheric greenhouse gas (GHG) emissions. For mangrove rehabilitation carbon projects, quantifying GHG emissions as forests regenerate is a key accounting requirement. The current study is one of the first attempts to systematically quantify emissions of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4) from: 1) aquaculture ponds, 2) rehabilitating mangroves, and 3) intact mangrove sites and frame GHG flux within the context of landuse change. In-situ static chamber measurements were made at three contrasting locations in Sulawesi, Indonesia. The influence of key biophysical variables known to affect GHG flux was also assessed. Peak GHG flux was observed at rehabilitating (32.8\u202f\u00b1\u202f2.1\u202fMg\u202fCO2e\u202fha-1\u202fy-1) and intact, mature reference sites (43.8\u202f\u00b1\u202f4.5\u202fMg\u202fCO2e\u202fha-1\u202fy-1) and a dry, exposed disused aquaculture pond (30.6\u202f\u00b1\u202f1.9\u202fMg\u202fCO2e\u202fha-1\u202fy-1). Emissions were negligible at low productivity rehabilitating sites with high hydroperiod (mean 1.0\u202f\u00b1\u202f0.1\u202fMg\u202fCO2e\u202fha-1\u202fy-1) and an impounded, operational aquaculture pond (1.1\u202f\u00b1\u202f0.2\u202fMg\u202fCO2e\u202fha-1\u202fy-1). Heterogeneity in biophysical conditions and geomorphic position exerted a strong influence on GHG flux, with the longer hydroperiod and higher soil moisture content of seaward fringing mangroves correlated with decreased fluxes. A greater abundance of Mud lobster mounds and root structures in landward mangroves correlated to higher flux. When viewed across a landuse change continuum, our results suggest that the initial conversion of mangroves to aquaculture ponds releases extremely high rates of GHGs. Furthermore, the re-institution of hydrological regimes in dry, disused aquaculture ponds to facilitate tidal flushing is instrumental in rapidly mediating GHG flux, leading to a significant reduction in baseline emissions. This is an important consideration for forest carbon project proponents seeking to maximise creditable GHG emissions reductions and removals.", "keywords": ["Nitrous Oxide", "Aquaculture", "Carbon Dioxide", "Forests", "15. Life on land", "01 natural sciences", "12. Responsible consumption", "Greenhouse Gases", "Soil", "Indonesia", "13. Climate action", "11. Sustainability", "Water Movements", "Seasons", "14. Life underwater", "Ponds", "Methane", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2018.11.092"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2018.11.092", "name": "item", "description": "10.1016/j.scitotenv.2018.11.092", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2018.11.092"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-03-01T00:00:00Z"}}, {"id": "10.1007/s11027-017-9764-x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:05Z", "type": "Journal Article", "created": "2017-10-25", "title": "Artificial lakes as a climate change adaptation strategy in drylands: evaluating the trade-off on non-target ecosystem services", "description": "Drylands are very susceptible to the effects of climate change due to water stress. One possible climate change adaptation measure is the construction of lakes to increase water availability for drinking and irrigation (food production) and decrease fire risk. These lakes can also increase local biodiversity and human well-being. However, other non-target services such as carbon (C) storage, water purification, and sediment retention might also change. Our main aim was to evaluate the trade-offs on non-targeted ecosystem services due to lakes construction in drylands. This was done using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling tools, comparing a Mediterranean area located in southwest (SW) Europe, with and without artificial lakes. Results showed that the construction of artificial lakes caused an increase of 9.4% in C storage. However, the consequent increase in agricultural area decreased water purification and sediment retention services. This could diminish the life span of the lakes changing the initial beneficial cost-benefit analysis on lakes as adaptation measures to climate change. As a global measure for mitigation and adaptation to climate change strategy, we consider lake construction in drylands to be positive since it can store C in sediments and reduces the vulnerability to water scarcity. However, as a general recommendation and when built to support or increase agriculture in semi-arid landscapes, we consider that lakes should be complemented with additional measures to reduce soil erosion and nutrient leaching such as (i) locate agricultural areas outside the lakes water basin, (ii) afforestation surrounding the lakes, and (iii) adopt the best local agriculture practices to prevent and control soil erosion and nutrient leaching.", "keywords": ["2. Zero hunger", "13. Climate action", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences", "12. Responsible consumption"]}, "links": [{"href": "http://link.springer.com/content/pdf/10.1007/s11027-017-9764-x.pdf"}, {"href": "https://doi.org/10.1007/s11027-017-9764-x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Mitigation%20and%20Adaptation%20Strategies%20for%20Global%20Change", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11027-017-9764-x", "name": "item", "description": "10.1007/s11027-017-9764-x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11027-017-9764-x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-25T00:00:00Z"}}, {"id": "10.1002/2017JD027346", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:28Z", "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": "10.1002/2017gb005693", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:28Z", "type": "Journal Article", "created": "2017-10-02", "title": "Release of Black Carbon From Thawing Permafrost Estimated by Sequestration Fluxes in the East Siberian Arctic Shelf Recipient", "description": "Abstract<p>Black carbon (BC) plays an important role in carbon burial in marine sediments globally. Yet the sequestration of BC in the Arctic Ocean is poorly understood. Here we assess the concentrations, fluxes, and sources of soot BC (SBC)\uffe2\uff80\uff94the most refractory component of BC\uffe2\uff80\uff94in sediments from the East Siberian Arctic Shelf (ESAS), the World's largest shelf sea system. SBC concentrations in the contemporary shelf sediments range from 0.1 to 2.1\uffc2\uffa0mg\uffc2\uffa0g\uffe2\uff88\uff921\uffc2\uffa0dw, corresponding to 2\uffe2\uff80\uff9312% of total organic carbon. The 210Pb\uffe2\uff80\uff90derived fluxes of SBC (0.42\uffe2\uff80\uff9311\uffc2\uffa0g\uffc2\uffa0m\uffe2\uff88\uff922\uffc2\uffa0yr\uffe2\uff88\uff921) are higher or in the same range as fluxes reported for marine surface sediments closer to anthropogenic emissions. The total burial flux of SBC in the ESAS (~4,000\uffc2\uffa0Gg\uffc2\uffa0yr\uffe2\uff88\uff921) illustrates the great importance of this Arctic shelf in marine sequestration of SBC. The radiocarbon signal of the SBC shows more depleted yet also more uniform signatures (\uffe2\uff88\uff92721 to \uffe2\uff88\uff92896\uffe2\uff80\uffb0; average of \uffe2\uff88\uff92774\uffc2\uffa0\uffc2\uffb1\uffc2\uffa062\uffe2\uff80\uffb0) than of the non\uffe2\uff80\uff90SBC pool (\uffe2\uff88\uff92304 to \uffe2\uff88\uff92728\uffe2\uff80\uffb0; average of \uffe2\uff88\uff92491\uffc2\uffa0\uffc2\uffb1\uffc2\uffa0163\uffe2\uff80\uffb0), suggesting that SBC is coming from an, on average, 5,900\uffc2\uffa0\uffc2\uffb1\uffc2\uffa0300\uffc2\uffa0years older and more specific source than the non\uffe2\uff80\uff90SBC pool. We estimate that the atmospheric BC input to the ESAS is negligible (~0.6% of the SBC burial flux). Statistical source apportionment modeling suggests that the ESAS sedimentary SBC is remobilized by thawing of two permafrost carbon (PF/C) systems: surface soil permafrost (topsoil/PF; 25\uffc2\uffa0\uffc2\uffb1\uffc2\uffa08%) and Pleistocene ice complex deposits (ICD/PF; 75\uffc2\uffa0\uffc2\uffb1\uffc2\uffa08%). The SBC contribution to the total mobilized permafrost carbon (PF/C) increases with increasing distance from the coast (from 5 to 14%), indicating that the SBC is more recalcitrant than other forms of translocated PF/C. These results elucidate for the first time the key role of permafrost thaw in the transport of SBC to the Arctic Ocean. With ongoing global warming, these findings have implications for the biogeochemical carbon cycle, increasing the size of this refractory carbon pool in the Arctic Ocean.</p", "keywords": ["13. Climate action", "Arctic Ocean", "SDG 14 - Life Below Water", "14. Life underwater", "black carbon", "01 natural sciences", "permafrost", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017GB005693"}, {"href": "https://doi.org/10.1002/2017gb005693"}, {"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": "10.1002/2017gb005693", "name": "item", "description": "10.1002/2017gb005693", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/2017gb005693"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-10-01T00:00:00Z"}}, {"id": "10.1007/s11367-012-0488-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:16Z", "type": "Journal Article", "created": "2012-09-10", "title": "Baseline Time Accounting: Considering Global Land Use Dynamics When Estimating The Climate Impact Of Indirect Land Use Change Caused By Biofuels", "description": "Abstract                        Purpose             <p>Current estimations of the climate impact from indirect land use change (ILUC) caused by biofuels are heavily influenced by assumptions regarding the biofuel production period. The purpose of this paper is to propose a new method (baseline time accounting) that takes global land use dynamics into account that is consistent with the global warming potential, that is applicable to any phenomenon causing land use change, and that is independent of production period assumptions.</p>                                   Methods             <p>We consider ILUC in two forms. The first is called \uffe2\uff80\uff9caccelerated expansion\uffe2\uff80\uff9d and concerns ILUC in regions with an expanding agricultural area. The second is called \uffe2\uff80\uff9cdelayed reversion\uffe2\uff80\uff9d and concerns ILUC in regions with a decreasing agricultural area. We use recent trends in international land use and projections of future land use change to assess how ILUC from biofuels will alter the development in global agricultural land use dynamics compared to the existing trend (i.e., the baseline development). We then use the definition of the global warming potential to determine the CO2 equivalence of the change in land use dynamics.</p>                                   Results and discussion             <p>We apply baseline time accounting to two existing ILUC studies in the literature. With current trends in global agricultural land use, the method significantly reduces the estimated climate impact in the previous ILUC studies (by more than half). Sensitivity analyses show that results are somewhat sensitive to assumptions regarding carbon sequestration and assumptions regarding postreversion ecosystems.</p>                                   Conclusions             <p>The global dynamic development in land use has important implications for the time accounting step when estimating the climate impact of ILUC caused by biofuel production or other issues affecting land use. Ignoring this may lead to erroneous conclusions about the actual climate impact of ILUC. Several land use projections indicate that the global agricultural area will keep expanding up to and beyond 2050. We therefore recommend to apply the baseline time accounting concept as an integrated part of future ILUC studies and to update the results on a regular basis.</p>", "keywords": ["2. Zero hunger", "Environmental Science(all)", "13. Climate action", "0202 electrical engineering", " electronic engineering", " information engineering", "02 engineering and technology", "15. Life on land", "01 natural sciences", "7. Clean energy", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Steffen Mueller, Jesper Hedal Kl\u00f8verpris,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1007/s11367-012-0488-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20International%20Journal%20of%20Life%20Cycle%20Assessment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11367-012-0488-6", "name": "item", "description": "10.1007/s11367-012-0488-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11367-012-0488-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-09-11T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Environmental+Sciences&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=Environmental+Sciences&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=Environmental+Sciences&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Environmental+Sciences&offset=50", "hreflang": "en-US"}], "numberMatched": 4742, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-10-22T20:49:34.915818Z"}