{"type": "FeatureCollection", "features": [{"id": "10.1016/j.foreco.2010.07.002", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:38Z", "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.geoderma.2019.114061", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:44Z", "type": "Journal Article", "created": "2019-11-28", "title": "High-resolution and three-dimensional mapping of soil texture of China", "description": "The lack of detailed three-dimensional soil texture information largely restricts many applications in agriculture, hydrology, climate, ecology and environment. This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2019.114061"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2019.114061", "name": "item", "description": "10.1016/j.geoderma.2019.114061", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2019.114061"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.1016/j.jenvman.2024.121882", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:50Z", "type": "Journal Article", "created": "2024-07-17", "title": "A systematic benchmarking framework for future assessments of soil health: An example from Denmark", "description": "Based on current evidence and established critical thresholds for soil degradation indicators, it is concerning that over 60-70% of European soils are unhealthy due to unsustainable management and the impact of climate change. Despite European and national efforts to improve soil health, significant gaps remain. The proposal for a Soil Monitoring and Resilience Law, to be implemented by the European Union, seeks to establish a framework for soil monitoring and promote sustainable management practices to achieve healthy soils by 2050. This requires extensive data collection and soil monitoring systems to accurately estimate soil health across Europe, considering the diversity of soil types, climates, and land uses. To establish a framework for soil monitoring, we must understand the site-specific status of soil and the ranges of soil health indicators across specific pedoclimatic regions. In our study, we evaluated the soil status in agricultural areas in Denmark using soil health indicators and a site-specific benchmarking approach. We compiled nationally representative datasets, combining point and model-informed data of soil parameters such as organic carbon content, bulk density, pH, electrical conductivity, clay-to-soil organiccarbon ratio, water erosion, and nitrogen leaching. By categorizing Danish agricultural soils into monitoring units based on textural classes, landscape elements, and wetland types, we calculated benchmarks for these indicators, considering different cropping systems. Our approach provided detailed point-based results and a spatially explicit overview of the status of soil health indicators in Denmark. We identified areas where soil deviates from the benchmarks of different indicators. Such deviations might indicate soil functions operating outside the normal range, posing potential threats to soil health. This proposed framework could support the establishment of a baseline for assessing the directionality of future changes in soil health. Moreover, it is adaptable for implementation by other countries to support assessments of soil health.", "keywords": ["2. Zero hunger", "Conservation of Natural Resources", "European soil monitoring and resilience law", "Soil monitoring units", "Denmark", "Climate Change", "Agriculture", "15. Life on land", "6. Clean water", "12. Responsible consumption", "Soil districts", "Soil", "13. Climate action", "11. Sustainability", "Soil health indicators", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1016/j.jenvman.2024.121882"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jenvman.2024.121882", "name": "item", "description": "10.1016/j.jenvman.2024.121882", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jenvman.2024.121882"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-01T00:00:00Z"}}, {"id": "10.1016/j.jhazmat.2021.125292", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:51Z", "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.jhydrol.2021.126551", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:51Z", "type": "Journal Article", "created": "2021-06-08", "title": "Smartphone-based tension disc infiltrometer for soil hydraulic characterisation", "description": "31 Pags.- 18 Figs.- 1 Tabl. The definitive version is available at: https://www.sciencedirect.com/science/journal/00221694 The tension disc infiltrometer has become a widespread method to measure soil hydraulic properties under unsaturated conditions. Although several automated devices have been developed, most designs include an elongated water reservoir and a pressure transducer with electronic components to register the water level, increasing its cost and limiting its application. The objective of this work is to present a new tension disc infiltrometer with a compact design of 10 cm diameter and height, where the water level is monitored by a smartphone camera. The infiltration curve is determined from the automated analysis of the images recorded by the smartphone without additional electronic components. The device was first validated in the laboratory by comparing visual measurements (V), the camera imagery (Ca) and a pressure transducer (PT). Next, it was tested on field infiltration experiments. Robust fits (R2 = 0.99) were found between the water level measured with Ca in the laboratory and those obtained with V and PT procedures. The Ca method is accurate, robust and independent of the relative camera position. Good fits were also observed between Ca water level and those obtained with PT in the field experiments. Similar hydraulic conductivity and sorptivity values were obtained with both sensors using the numerical solution of the Haverkamp (NSH) equation. The compact infiltrometer, in conjunction with the smartphone camera, is an accurate, accessible, portable and easy-to-use field-based device for soil hydraulic characterisation. This research was supported by the MINECO project ASBIO (PGC2018-094332-B-100) and the European Union\u2019s Horizon 2020 research and innovation program under grant agreement No [H2020-MSCA-RISE-777803]. Peer reviewed", "keywords": ["Automated single-ring infiltrometer", "Compact design", "0207 environmental engineering", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "02 engineering and technology", "Soil hydraulic properties", "Infiltration rate measurements", "NSH", "6. Clean water"]}, "links": [{"href": "https://doi.org/10.1016/j.jhydrol.2021.126551"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hydrology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhydrol.2021.126551", "name": "item", "description": "10.1016/j.jhydrol.2021.126551", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhydrol.2021.126551"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2014.02.009", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:16:07Z", "type": "Journal Article", "created": "2014-02-26", "title": "Pyrogenic Carbon Additions To Soil Counteract Positive Priming Of Soil Carbon Mineralization By Plants", "description": "Abstract Important due to both its role in fire-affected ecosystems, and also its proposed intentional production and application for carbon (C) management, pyrogenic organic matter (PyOM) is thought to contain very stable forms of C. However, the mechanisms behind its interactions with non-PyOM soil organic C (SOC) remain speculative, with studies often showing short-term positive and then long-term negative \u201cpriming effects\u201d on SOC decomposition after PyOM applications. Furthermore, studies of these interactions to date have been limited to systems that do not include plants. This study describes results from a 12-week greenhouse experiment where PyOM-SOC priming effects with and without plants were investigated using stable isotope partitioning. In addition, we investigated the optimal \u03b413C proxies for sources of SOC, PyOM, and plant-derived CO2 emissions. The two-factorial experiment included the presence or absence of corn plants and of 13C-labelled PyOM. In order to control for pH and nutrient addition effects from PyOM, its pH was adjusted to that of the soil and optimal nutrient and water conditions were provided to the plants. The \u03b413C of PyOM sub-components were significantly different. Significant losses of 0.4% of the applied PyOM-C occurred in the first week. We find evidence for a \u201cnegative priming\u201d effect of PyOM on SOC in the system (SOC losses are 48% lower with PyOM present), which occurred primarily during the first week, indicating it may be due to transient effects driven by easily mineralizable PyOM. Additionally, while the presence of corn plants resulted in significantly increased SOC losses (\u201cpositive priming\u201d), PyOM additions counteract this effect, almost completely eliminating net C losses either by decreasing SOC decomposition or increasing corn C additions to soil. This highlights the importance of including plants in studies of PyOM-SOC interactions.", "keywords": ["2. Zero hunger", "13. Climate action", "8. Economic growth", "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": "Thea Whitman, Akio Enders, Johannes Lehmann,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.soilbio.2014.02.009"}, {"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.2014.02.009", "name": "item", "description": "10.1016/j.soilbio.2014.02.009", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.soilbio.2014.02.009"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-06-01T00:00:00Z"}}, {"id": "10.1023/a:1013072519889", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:16:28Z", "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": "10.1038/s41561-021-00714-3", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:16:37Z", "type": "Journal Article", "created": "2021-04-07", "title": "Co-variation of silicate, carbonate and sulfide weathering drives CO2 release with erosion", "description": "Abstract

Global climate is thought to be modulated by the supply of minerals to Earth\uffe2\uff80\uff99s surface. Whereas silicate weathering removes carbon dioxide (CO2) from the atmosphere, weathering of accessory carbonate and sulfide minerals is a geologically relevant source of CO2. Although these weathering pathways commonly operate side by side, we lack quantitative constraints on their co-variation across erosion rate gradients. Here we use stream-water chemistry across an erosion rate gradient of three orders of magnitude in shales and sandstones of southern Taiwan, and find that sulfide and carbonate weathering rates rise with increasing erosion, while silicate weathering rates remain steady. As a result, on timescales shorter than marine sulfide compensation (approximately 106\uffe2\uff80\uff93107 years), weathering in rapidly eroding terrain leads to net CO2 emission rates that are about twice as fast as CO2 sequestration rates in slow-eroding terrain. We propose that these weathering reactions are linked and that sulfuric acid generated from sulfide oxidation boosts carbonate solubility, whereas silicate weathering kinetics remain unaffected, possibly due to efficient buffering of the pH. We expect that these patterns are broadly applicable to many Cenozoic mountain ranges that expose marine metasediments.

", "keywords": ["[SDU] Sciences of the Universe [physics]", "13. Climate action", "[SDU.STU.GC] Sciences of the Universe [physics]/Earth Sciences/Geochemistry", "15. Life on land", "01 natural sciences", "333", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.nature.com/articles/s41561-021-00714-3.pdf"}, {"href": "https://doi.org/10.1038/s41561-021-00714-3"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Geoscience", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41561-021-00714-3", "name": "item", "description": "10.1038/s41561-021-00714-3", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41561-021-00714-3"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-04-01T00:00:00Z"}}, {"id": "10.1111/gcbb.12255", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:19Z", "type": "Journal Article", "created": "2015-02-19", "title": "Bioenergy Harvest, Climate Change, And Forest Carbon In The Oregon Coast Range", "description": "Abstract

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.

", "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.1365-2486.2008.01809.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:23Z", "type": "Journal Article", "created": "2008-11-04", "title": "Soil Organic Carbon Contents In Long-Term Experimental Grassland Plots In The Uk (Palace Leas And Park Grass) Have Not Changed Consistently In Recent Decades", "description": "Abstract

A recent report of widespread declines in soil organic C (SOC) in the UK over the 10\uffe2\uff80\uff9325 years until the early 2000s has focussed attention on the importance of resampling previously characterized sites to assess long\uffe2\uff80\uff90term trends in SOC contents and the importance of soils as a potentially volatile and globally significant reservoir of terrestrial C. We have used two sets of long\uffe2\uff80\uff90term experimental plots which have been under constant and known management for over a century and for which historical data exist that allow comparison over recent decades to determine what, if any, changes in SOC content have occurred. The plots used are the Palace Leas (PL) Meadow Hay Plots in north\uffe2\uff80\uff90east England (UK) established in 1897, and from the Park Grass (PG) Continuous Hay experiment established in 1856 at Rothamsted in south\uffe2\uff80\uff90east England. Collectively, these plots represent the only grassland sites in the UK under long\uffe2\uff80\uff90term management where changes in SOC over several decades can be assessed, and are probably unique in the world. The plots have received different manure and fertilizer treatment and have been under known management for at least 100 years. In 1982, total SOC contents were determined for the 0\uffe2\uff80\uff9327\uffe2\uff80\uff83cm layer of six of the PL plots using measurements of SOC concentrations, bulk density and soil depth. In 2006, the same six PL plots were resampled and SOC contents determined again. Four of the plots showed no net change in SOC content, but two plots showed net loss of SOC of 15% and 17% (amounting to decreases of 18 and 15\uffe2\uff80\uff83t\uffe2\uff80\uff83C\uffe2\uff80\uff83ha\uffe2\uff88\uff921) since 1982. However, these differences in total SOC content were in a similar range to the variations in bulk density (6\uffe2\uff80\uff9331%) with changing soil water content. In 1959, the soil masses and SOC concentrations to 23\uffe2\uff80\uff83cm depth were measured on six PG plots with fertilizer and manure treatments corresponding closely with those measured on PL. In 2002, the SOC concentrations on the same plots were measured again. On three of the PG plots, SOC concentrations had declined by 2\uffe2\uff80\uff9310%, but in the other three it had increased by 4\uffe2\uff80\uff938% between 1959 and 2002. If it is assumed that the soil bulk density had not changed over this period, the losses of SOC from the top soils ranged range from 10 to 3\uffe2\uff80\uff83t\uffe2\uff80\uff83C\uffe2\uff80\uff83ha\uffe2\uff88\uff921, while the gains ranged from 4 to 7\uffe2\uff80\uff83t\uffe2\uff80\uff83C\uffe2\uff80\uff83ha\uffe2\uff88\uff921. When the differences with time in SOC contents for the six PL and the six PG plots were examined using paired t\uffe2\uff80\uff90tests, that is, regarding the plots as two sets of six replicate permanent grasslands, there were no significant differences between 1982 and 2006 for the PL plots or between 1959 and 2002 for the PG plots. Thus, these independent observations on similar plots at PL and PG indicate there has been no consistent decrease in SOC stocks in surface soils under old, permanent grassland in England in recent decades, even though meteorological records for both sites indicate significant warming of the soil and air between 1980 and 2000. Because the potential influences of changes in management or land use have been definitively excluded, and measured rather than derived bulk densities have been used to convert from SOC concentrations to SOC amounts, our observations question whether for permanent grassland in England, losses in SOC in recent decades reported elsewhere can be attributed to widespread environmental change.

", "keywords": ["2. Zero hunger", "Ecology", "0401 agriculture", " forestry", " and fisheries", "biodiversity conservation", "04 agricultural and veterinary sciences", "15. Life on land", "Environmental Sciences"]}, "links": [{"href": "https://doi.org/10.1111/j.1365-2486.2008.01809.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.1365-2486.2008.01809.x", "name": "item", "description": "10.1111/j.1365-2486.2008.01809.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/j.1365-2486.2008.01809.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-06-05T00:00:00Z"}}, {"id": "10.1111/j.1365-2486.2009.02121.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:23Z", "type": "Journal Article", "created": "2009-12-22", "title": "Functional Changes In The Control Of Carbon Fluxes After 3 Years Of Increased Drought In A Mediterranean Evergreen Forest?", "description": "Abstract

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.

", "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": "2026-09-19T16:17:41Z", "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": "10.1175/bams-d-17-0212.1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:41Z", "type": "Journal Article", "created": "2018-01-09", "title": "The Global N 2 O Model Intercomparison Project", "description": "Abstract

Nitrous oxide (N2O) is an important greenhouse gas and also an ozone-depleting substance that has both natural and anthropogenic sources. Large estimation uncertainty remains on the magnitude and spatiotemporal patterns of N2O fluxes and the key drivers of N2O production in the terrestrial biosphere. Some terrestrial biosphere models have been evolved to account for nitrogen processes and to show the capability to simulate N2O emissions from land ecosystems at the global scale, but large discrepancies exist among their estimates primarily because of inconsistent input datasets, simulation protocol, and model structure and parameterization schemes. Based on the consistent model input data and simulation protocol, the global N2O Model Intercomparison Project (NMIP) was initialized with 10 state-of-the-art terrestrial biosphere models that include nitrogen (N) cycling. Specific objectives of NMIP are to 1) unravel the major N cycling processes controlling N2O fluxes in each model and identify the uncertainty sources from model structure, input data, and parameters; 2) quantify the magnitude and spatial and temporal patterns of global and regional N2O fluxes from the preindustrial period (1860) to present and attribute the relative contributions of multiple environmental factors to N2O dynamics; and 3) provide a benchmarking estimate of N2O fluxes through synthesizing the multimodel simulation results and existing estimates from ground-based observations, inventories, and statistical and empirical extrapolations. This study provides detailed descriptions for the NMIP protocol, input data, model structure, and key parameters, along with preliminary simulation results. The global and regional N2O estimation derived from the NMIP is a key component of the global N2O budget synthesis activity jointly led by the Global Carbon Project and the International Nitrogen Initiative.

", "keywords": ["[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "13. Climate action", "11. Sustainability", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "15. Life on land", "environment", "01 natural sciences", "7. Clean energy", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://journals.ametsoc.org/downloadpdf/journals/bams/99/6/bams-d-17-0212.1.xml"}, {"href": "https://doi.org/10.1175/bams-d-17-0212.1"}, {"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-17-0212.1", "name": "item", "description": "10.1175/bams-d-17-0212.1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1175/bams-d-17-0212.1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-01T00:00:00Z"}}, {"id": "10.1186/s12302-025-01141-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:41Z", "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

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.

Results

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.

Conclusions

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.

", "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": "10.15454/SVDTOU", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:17:53Z", "type": "Dataset", "title": "Statistiques spatio-temporelles sur les propri\u00e9t\u00e9s agronomiques des sols agricoles en France issues de la Base de Donn\u00e9es d'Analyses de Terre (BDAT)", "description": "In France, farmers commission about 250,000 soil-testing analyses per year to assist them managing soil fertility. The number and diversity of origin of the samples make these analyses an interesting and original information source regarding cultivated topsoil variability. Moreover, these analyses relate to several parameters strongly influenced by human activity (macronutrient contents, pH...), for which existing cartographic information is not very relevant. Compiling the results of these analyses into a database makes it possible to re-use these data within both a national and temporal framework. A database compilation relating to data collected over the period 1990-2014 has been recently achieved. So far, commercial soil-testing laboratories approved by the Ministry of Agriculture have provided analytical results from more than 3,600,000 samples. After the initial quality control stage, analytical results from more than 1,900,000 samples were available in the database. The anonymity of the landholders seeking soil analyses is perfectly preserved, as the only identifying information stored is the location of the nearest administrative city to the sample site. We present in this dataset a set of statistical parameters of the spatial distributions for several agronomic soil properties. These statistical parameters are calculated for 4 different nested spatial entities (administrative areas: e.g. regions, departments, counties and agricultural areas) and for 5 time periods (1990-1994, 1995-1999, 2000-2004, 2005-2009, 2010-2014). Two kinds of agronomic soil properties are available: the first one correspond to the quantitative variables like the organic carbon content, and the second one corresponds to the qualitative variables like the texture class. For each spatial unit and temporal period, we calculated the following statistics sets: the first set is calculated for the quantitative variables and corresponds to the number of samples, the mean, the standard deviation and, the 2-,4-,10-quantiles; the second set is calculated for the qualitative variables and corresponds to the number of samples, the value of the dominant class, the number of samples of the dominant class, the second dominant class, the number of samples of the second dominant class.", "keywords": ["2. Zero hunger", "Earth and Environmental Science", "Soils and soil sciences", "Earth and Environmental Sciences", "Soil Sciences", "soil texture", "15. Life on land", "soil analysis", "Environmental Research", "Natural Sciences", "Geosciences"], "contacts": [{"organization": "Saby, Nicolas P.A., Lemercier, Blandine, Arrouays, Dominique, Walter, Christian, Gouny, Laetitia, Swidersky, Chlo\u00e9, Toutain, Beno\u00eet, Bispo, Antonio,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.15454/SVDTOU"}, {"rel": "self", "type": "application/geo+json", "title": "10.15454/SVDTOU", "name": "item", "description": "10.15454/SVDTOU", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.15454/SVDTOU"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.2111/08-106.1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:18:08Z", "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": "2026-09-19T16:21:08Z", "type": "Journal Article", "created": "2018-07-19", "title": "Molecular Fingerprinting of14C Dated Soil Organic Matter Fractions from Archaeological Settings in NW Spain", "description": "Abstract

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.

Abstract. The boreal forest landscape covers approximately 10\u2009% of the earth's land area and accounts for almost 30\u2009% of the global annual terrestrial sink of carbon\u00a0(C). Increased emissions due to climate-change-amplified fire frequency, size, and intensity threaten to remove elements such as C and nitrogen\u00a0(N) from forest soil and vegetation at rates faster than they accumulate. This may result in large areas within the region becoming a net source of greenhouse gases, creating a positive feedback loop with a changing climate. Meter-scale estimates of area-normalized fire emissions are limited in Eurasian boreal forests, and knowledge of their relation to climate and ecosystem properties is sparse. This study sampled 50 separate Swedish wildfires, which occurred during an extreme fire season in 2018, providing quantitative estimates of C and N loss due to fire along a climate gradient. Mean annual precipitation had strong positive effects on total fuel, which was the strongest driver for increasing C and N losses. Mean annual temperature\u00a0(MAT) influenced both pre- and postfire organic layer soil bulk density and C\u2009:\u2009N ratio, which had mixed effects on C and N losses. Significant fire-induced loss of C estimated in the 50 plots was comparable to estimates in similar Eurasian forests but approximately a quarter of those found in typically more intense North American boreal wildfires. N loss was insignificant, though a large amount of fire-affected fuel was converted to a low C\u2009:\u2009N surface layer of char in proportion to increased MAT. These results reveal large quantitative differences in C and N losses between global regions and their linkage to the broad range of climate conditions within Fennoscandia. A need exists to better incorporate these factors into models to improve estimates of global emissions of C and N due to fire in future climate scenarios. Additionally, this study demonstrated a linkage between climate and the extent of charring of soil fuel and discusses its potential for altering C and N dynamics in postfire recovery.

", "keywords": ["QE1-996.5", "Ecology", "Life", "13. Climate action", "QH501-531", "Geology", "15. Life on land", "01 natural sciences", "QH540-549.5", "Climate Science", "Klimatvetenskap", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/bg-19-2487-2022"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-19-2487-2022", "name": "item", "description": "10.5194/bg-19-2487-2022", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-19-2487-2022"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-13T00:00:00Z"}}, {"id": "10.5194/bg-21-109-2024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:16Z", "type": "Journal Article", "created": "2024-01-05", "title": "Geographically divergent trends in snow disappearance timing and fire ignitions across boreal North America", "description": "

Abstract. The snow cover extent across the Northern Hemisphere has diminished, while the number of lightning ignitions and amount of burned area have increased over the last 5\u00a0decades with accelerated warming. However, the effects of earlier snow disappearance on fire are largely unknown. Here, we assessed the influence of snow disappearance timing on fire ignitions across 16 ecoregions of boreal North America. We found spatially divergent trends in earlier (later) snow disappearance, which led to an increasing (decreasing) number of ignitions for the northwestern (southeastern) ecoregions between 1980 and 2019. Similar northwest\u2013southeast divergent trends were observed in the changing length of the snow-free season and correspondingly the fire season length. We observed increases (decreases) over northwestern (southeastern) boreal North America which coincided with a continental dipole in air temperature changes between 2001 and 2019. Earlier snow disappearance induced earlier ignitions of between 0.22 and 1.43\u2009d earlier per day of earlier snow disappearance in all ecoregions between 2001 and 2019. Early-season ignitions (defined by the 20\u2009% earliest fire ignitions per year) developed into significantly larger fires in 8 out of 16 ecoregions, being on average 77\u2009% larger across the whole domain. Using a piecewise structural equation model, we found that earlier snow disappearance is a good direct proxy for earlier ignitions but may also result in a cascade of effects from earlier desiccation of fuels and favorable weather conditions that lead to earlier ignitions. This indicates that snow disappearance timing is an important trigger of land\u2013atmosphere dynamics. Future warming and consequent changes in snow disappearance timing may contribute to further increases in western boreal fires, while it remains unclear how the number and timing of fire ignitions in eastern boreal North America may change with climate change.

", "keywords": ["0301 basic medicine", "QE1-996.5", "03 medical and health sciences", "Ecology", "Life", "13. Climate action", "QH501-531", "Geology", "15. Life on land", "01 natural sciences", "QH540-549.5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://bg.copernicus.org/articles/21/109/2024/bg-21-109-2024.pdf"}, {"href": "https://doi.org/10.5194/bg-21-109-2024"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-21-109-2024", "name": "item", "description": "10.5194/bg-21-109-2024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-21-109-2024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-05T00:00:00Z"}}, {"id": "10.5194/bg-7-315-2010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:16Z", "type": "Journal Article", "created": "2010-04-29", "description": "

Abstract. Global climate change in the real world always exhibits simultaneous changes in multiple factors. Prediction of ecosystem responses to multi-factor global changes in a future world strongly relies on our understanding of their interactions. However, it is still unclear how nitrogen (N) deposition and elevated atmospheric carbon dioxide concentration [CO2] would interactively influence forest floor soil respiration in subtropical China. We assessed the main and interactive effects of elevated [CO2] and N addition on soil respiration by growing tree seedlings in ten large open-top chambers under CO2 (ambient CO2 and 700 \uffce\uffbcmol mol\uffe2\uff88\uff921) and nitrogen (ambient and 100 kg N ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921) treatments. Soil respiration, soil temperature and soil moisture were measured for 30 months, as well as above-ground biomass, root biomass and soil organic matter (SOM). Results showed that soil respiration displayed strong seasonal patterns with higher values observed in the wet season (April\uffe2\uff80\uff93September) and lower values in the dry season (October\uffe2\uff80\uff93March) in all treatments. Significant exponential relationships between soil respiration rates and soil temperatures, as well as significant linear relationships between soil respiration rates and soil moistures (below 15%) were found. Both CO2 and N treatments significantly affected soil respiration, and there was significant interaction between elevated [CO2] and N addition (p<0.001, p=0.003, and p=0.006, respectively). We also observed that the stimulatory effect of individual elevated [CO2] (about 29% increased) was maintained throughout the experimental period. The positive effect of N addition was found only in 2006 (8.17% increased), and then had been weakened over time. Their combined effect on soil respiration (about 50% increased) was greater than the impact of either one alone. Mean value of annual soil respiration was 5.32 \uffc2\uffb1 0.08, 4.54 \uffc2\uffb1 0.10, 3.56 \uffc2\uffb1 0.03 and 3.53 \uffc2\uffb1 0.03 kg CO2 m\uffe2\uff88\uff922 yr\uffe2\uff88\uff921 in the chambers exposed to elevated [CO2] and high N deposition (CN), elevated [CO2] and ambient N deposition (CC), ambient [CO2] and high N deposition (NN), and ambient [CO2] and ambient N deposition (CK as a control), respectively. Greater above-ground biomass and root biomass was obtained in the CN, CC and NN treatments, and higher soil organic matter was observed only in the CN treatment. In conclusion, the combined effect of elevated [CO2] and N addition on soil respiration was apparent interaction. They should be evaluated in combination in subtropical forest ecosystems in China where the atmospheric CO2 and N deposition have been increasing simultaneously and remarkably.

", "keywords": ["0106 biological sciences", "2. Zero hunger", "QE1-996.5", "Ecology", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "Life", "13. Climate action", "QH501-531", "0401 agriculture", " forestry", " and fisheries", "QH540-549.5", "0105 earth and related environmental sciences"], "contacts": [{"organization": "Qi Deng, Shuangquan Liu, Honglang Duan, Guoyi Zhou, Juxiu Liu, Dainan Zhang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5194/bg-7-315-2010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-7-315-2010", "name": "item", "description": "10.5194/bg-7-315-2010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-7-315-2010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-08-24T00:00:00Z"}}, {"id": "10.5194/gmd-17-5349-2024", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:21Z", "type": "Journal Article", "created": "2024-07-11", "title": "Modelling boreal forest's mineral soil and peat C dynamics with the Yasso07 model coupled with the Ricker moisture modifier", "description": "

Abstract. As soil microbial respiration is the major component of land CO2 emissions, differences in the functional dependence of respiration on soil moisture among Earth system models (ESMs) contributes significantly to the uncertainties in their projections. Using soil organic C (SOC) stocks and CO2 data from a boreal forest\u2013mire ecotone in Finland and Bayesian data assimilation, we revised the original precipitation-based monotonic saturation dependency of the Yasso07 soil carbon model using the non-monotonic Ricker function based on soil volumetric water content. We fit the revised functional dependency of moisture to the observed microbial respiration and SOC stocks and compared its performance against the original Yasso07 model and the version used in the JSBACH land surface model with a reduction constant for decomposition rates in wetlands. The Yasso07 soil\u00a0C model coupled with the calibrated unimodal Ricker moisture function with an optimum in well-drained soils accurately reconstructed observed SOC stocks and soil CO2 emissions and clearly outperformed previous model versions on paludified organo-mineral soils in forested peatlands and water-saturated organic soils in mires. The best estimate of the posterior moisture response of decomposition used both measurements of SOC stocks and CO2 data from the full range of moisture conditions (from dry and xeric to wet and water-saturated soils). We observed unbiased residuals of SOC and CO2 data modelled with the moisture optimum in well-drained soils, suggesting that this modified function accounts more precisely for the long-term SOC change dependency according to ecosystem properties as well as the contribution of short-term CO2 responses including extreme events. The optimum moisture for decomposition in boreal forests was found in well-drained soils instead of the mid-range between dry and water-saturated conditions as is commonly assumed among soil\u00a0C and ESMs. Although the unimodal moisture modifier with an optimum in well-drained soils implicitly incorporates robust biogeochemical mechanisms of SOC accumulation and CO2 emissions, it needs further evaluation with large-scale data to determine if its use in land surface models will decrease the uncertainty in projections.

", "keywords": ["[SDE] Environmental Sciences", "QE1-996.5", "550", "Forestry", "Geology", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "630", "12. Responsible consumption", "Environmental sciences", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5194/gmd-17-5349-2024"}, {"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-17-5349-2024", "name": "item", "description": "10.5194/gmd-17-5349-2024", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-17-5349-2024"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-11T00:00:00Z"}}, {"id": "10.5194/soil-2020-96", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:23Z", "type": "Report", "created": "2021-02-06", "title": "Controls on heterotrophic soil respiration and carbon cycling in geochemically distinct African tropical forest soils", "description": "

Abstract. Heterotrophic soil respiration is an important component of the global terrestrial carbon (C) cycle, driven by environmental factors acting from local to continental scales. For tropical Africa, these factors and their interactions remain largely unknown. Here, using samples collected along strong topographic and geochemical gradients in the East African Rift Valley, we study how soil chemistry and soil fertility, derived from the geochemical composition of soil parent material, can drive soil respiration even after many millennia of weathering and soil development. To address the drivers of soil respiration, we incubated soils from three regions with contrasting geochemistry (mafic, felsic, and mixed sedimentary) sampled along slope gradients. For three soil depths, we measured the potential maximum heterotrophic respiration under stable environmental conditions as well as the radiocarbon content (\u039414C) of the bulk soil and respired CO2. We found that soil microbial communities were able to mineralize C from fossil as well as other poor quality C sources under laboratory conditions representative of tropical topsoils. Furthermore, despite similarities in terms of climate, vegetation, and the size of soil C stocks, soil respiration showed distinct patterns with soil depth and parent material geochemistry. The topographic origin of our samples was not a main determinant of the observed respiration rates and \u039414C. In situ, however, soil hydrological conditions likely influence soil C stability by inhibiting decomposition in valley subsoils. Our study shows that soil fertility conditions are the main determinant of C stability in tropical forest soils. Further, in the presence of organic carbon sources of poor quality or the presence of strong mineral related C stabilization, microorganisms tend to discriminate against these sources in favor of more accessible forms of soil organic matter as energy sources, resulting in a slower rate of C cycling. Our results demonstrate that even in deeply weathered tropical soils, parent material has a long-lasting effect on soil chemistry that can influence and control microbial activity, the size of subsoil C stocks, and the turnover of C in soil. Soil parent material and its lasting control on soil chemistry need to be taken into account to understand and predict C stabilization and rates of C cycling in tropical forest soils.

", "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/soil-2020-96"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/soil-2020-96", "name": "item", "description": "10.5194/soil-2020-96", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/soil-2020-96"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-04T00:00:00Z"}}, {"id": "10.5281/zenodo.14027088", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:19:46Z", "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": "2026-09-19T16:19:58Z", "type": "Dataset", "title": "Precision Liming Soil Datasets (LimeSoDa) Zenodo Repository", "description": "Overview Precision Liming Soil Datasets (LimeSoDa) is a collection of 31 datasets from a field- and farm-scale soil mapping context. These datasets are 'ready-to-use' for modeling purposes, as they include target soil properties and features in a tidy tabular format. Three target soil properties are present in every dataset: (1) soil organic matter (SOM) or soil organic carbon (SOC), (2) pH, and (3) clay content, while the features for modeling are dataset-specific. The primary goal of `LimeSoDa` is to enable more reliable benchmarking of machine learning methods in digital soil mapping and pedometrics. All the associated materials and data from LimeSoDa can be downloaded in this data repository. However, for a more in-depth analysis, we refer to the published paper 'LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping' by Schmidinger et al. (2025). You may also use our R\u00a0and Python package likewise called LimeSoDa. \u00a0 Citation Upon usage of datasets from LimeSoDa, please cite our associated paper: Schmidinger, J., Vogel, S., Barkov, V., Pham, A.-D., Gebbers, R., Tavakoli, H., Correa, J., Tavares, T.R., Filippi, P., Jones, E. J., Lukas, V., Boenecke, E., Ruehlmann, J., Schroeter, I., Kramer, E., Paetzold, S., Kodaira, M., Wadoux, A.M.J.-C., Bragazza, L., Metzger, K., Huang, J., Valente, D.S.M., Safanelli, J.L., Bottega, E.L., Dalmolin, R.S.D., Farkas, C., Steiger, A., Horst, T. Z., Ramirez-Lopez, L., Scholten, T., Stumpf, F., Rosso, P., Costa, M.M., Zandonadi, R.S., Wetterlind, J. & Atzmueller, M. (2025). LimeSoDa: A Dataset Collection for Benchmarking of Machine Learning Regressors in Digital Soil Mapping.", "keywords": ["Environmental sciences", "Soil Organic Carbon", "Pedometrics", "pH", "Soil Organic Matter", "Clay", "Remote sensing", "Digital Soil Mapping"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14936177"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14936177", "name": "item", "description": "10.5281/zenodo.14936177", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14936177"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.15680931", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:09Z", "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

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.

Results

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.

Conclusions

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.

", "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.17206462", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:13Z", "type": "Dataset", "title": "Polyaromatic Hydrocarbon (PAHs) Concentration and Peak intensities Data", "description": "This data set is published as Wildfire, ecosystem, and climate interactions in the Early Triassic in Communication Earth and Enivronment (https://doi.org/10.1038/s43247-025-02789-x). Wildfires are an important component of Earth system dynamics particularly with respect to nutrient- and carbon cycling. The\u00a0 occurrence of wildfires is linked to complex feedbacks between climate, vegetation and landscape structure. It is therefore crucial to understand wildfire activity in the context of (paleo-)climatic and environmental change. In this study, we explore wildfire activity during the Early Triassic (Smithian and Spathian substages, ca. 250 million years ago) \u2013 a time interval characterized by large global carbon cycle perturbation, climatic oscillations, prominent terrestrial vegetation succession, along with radiation and extinction pulses \u2013 using polyaromatic hydrocarbon (PAH) biomarkers, which serve as a robust indicator of fire in sedimentary geologic archives. PAH abundances in shales from Spitsbergen show a prominent increase after the Smithian-Spathian boundary. Further, diagnostic ratios of PAHs suggest that these compounds were derived from relatively unaltered biomass as opposed to soil erosion and petrogenic carbon inputs or coal combustion vis-\u00e0-vis a coincidental Siberian Trap volcanism. Instead, our data indicates that as sea surface temperatures decline during the late Smithian, the hydrological cycle becomes less intense and large-scale changing vegetation successions become amenable to wildfire activity. From our results, we hypothesize that the change in regional wildfire regime would have exerted influence on other regional biogeochemical cycles, especially pyrogenic carbon, which in turn may have impacted long-term carbon sequestration dynamics. The coupled behavior of this water-vegetation-wildfire system amid key perturbations in Earth\u2019s history provides new insights into imminent future consequences of human activities and the related impacts on climate.", "keywords": ["Environmental sciences", "Earth Sciences", "Organic geochemistry"], "contacts": [{"organization": "Blattmann, Franziska, Ragon, Charline, Vennemann, Torsten W., Schneebeli-Hermann, Elke, V\u00e9rard, Christian, Kasparian, J\u00e9r\u00f4me, Brunetti, Maura, Bucher, Hugo F.R., Adatte, Thierry, Magill, Clayton,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17206462"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17206462", "name": "item", "description": "10.5281/zenodo.17206462", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17206462"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-26T00:00:00Z"}}, {"id": "10.5281/zenodo.17878641", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:15Z", "type": "Report", "title": "Learning Environment development strategy (update 2). Deliverable D7.4 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D7.4 (update 1) of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). D7.4 presents the overall strategy and method used to develop the OPTAIN Learning Environment. The first version was prepared at month 12, reviewed and validated by the European Commission at month 18. The first update was delivered in month 36. This document is the second update (month 48). The first version and the updates\u00a0respectively correspond to the 2 parts of the deliverable. Summary Deliverable D7.4 OPTAIN Learning Environment development strategy is related to task 7.2 'Learning Environment and website' of OPTAINs WP7 'Communication, dissemination and Learning Environment'. The Learning Environment (LE) is an online platform that is being developed to help building capacity and disseminate OPTAIN\u00a0methodologies and results and to convey the knowledge co-created by OPTAIN consortium towards NSWRM stakeholders and beyond.\u00a0 The strategy development for the LE is an iterative process that has started at the beginning of the project (September 2020). Two updates of the strategy are planned over the course of the project. The first version of deliverable D7.4 was released at month 12 (August 2021). It corresponds to PART 1 of the deliverable. Among other things on the method, targeted audiences, planning, etc., it presents the consolidated vision of the LE. The vision was based on the foreseen LE described in the 'Description of Activities' and the expectations of the partners gathered via interviews. As a result, the frame of the LE was designed.\u00a0 The first update of the deliverable D7.4 was submitted in October 2023. It corresponds to PART 2 of this document. The starting point of the first update is the LE frame (Figure a), which guided the development of the first mock-up (Figure b) and then the development the first online version. The overall development benefited from regular exchanges with the partners, case studies stakeholders through the MARG as well as with external stakeholders through interviews made for deliverable D7.5 to set OPTAIN training analysis.\u00a0 PART 2 first highlights the conceptual development of the LE, which took place from August 2021 to October 2023. It then focusses on the technical development, which ended up on the first online version, presented during the OPTAIN Summer School (Prague, Czech Republic, July 2023) and the OPTAIN General Assembly (Iseo, Italy, September 2023). PART 2 also recalls the key discussions on the indicators used by the CS leaders to describe their NSWRMs.\u00a0 The second update of the deliverable D7.4 was submitted in February 2025 (this report). It contains key refinements to enhance usability, navigation, and partner feedback. Structured progress updates have been introduced under each section of PART 2 to track specific improvements and milestones: Interactive mapping and visualisation tools, improving user interaction. Structured knowledge pathways, tailoring content for different stakeholders. Enhanced case study integration, ensuring that case studies are incorporated. Optimised menu navigation, refining content access and usability. Expanded language features, enabling multilingual accessibility.\u00a0 Advanced filtering and search functionalities, facilitating content discovery.\u00a0 The LE is now available with its final URL (https://le.optain.eu/). Although the content is not yet available for the public, all partners have been given a login and password so they can provide feedback. Each section now includes dedicated progress update boxes so that progress can be tracked in a structured format. The final version of the LE is on track for completion by the end of 2025, with improvements continuing based on user feedback and testing. This continuous improvement process supports the long-term usability and sustainability of the platform and ensures its relevance beyond the project duration.", "keywords": ["Learning Environment", "communication", "NSWRM", "H2020", "OPTAIN", "dissemination"], "contacts": [{"organization": "Amorsi, Natacha, Lanceleur, Philippe, Bernard, Sadika,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.17878641"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.17878641", "name": "item", "description": "10.5281/zenodo.17878641", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.17878641"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-28T00:00:00Z"}}, {"id": "10.5281/zenodo.8089699", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:32Z", "type": "Journal Article", "created": "2019-11-28", "title": "High-resolution and three-dimensional mapping of soil texture of China", "description": "The lack of detailed three-dimensional soil texture information largely restricts many applications in agriculture, hydrology, climate, ecology and environment. This study predicted 90 m resolution spatial variations of sand, silt and clay contents at a national extent across China and at multiple depths 0\u20135, 5\u201315, 15\u201330, 30\u201360, 60\u2013100 and 100\u2013200 cm. We used 4579 soil profiles collected from a national soil series inventory conducted recently and currently available environmental covariates. The covariates characterized environmental factors including climate, parent materials, terrain, vegetation and soil conditions. We constructed random forest models and employed a parallel computing strategy for the predictions of soil texture fractions based on its relationship with the environmental factors. Quantile regression forest was used to estimate the uncertainty of the predictions. Results showed that the predicted maps were much more accurate and detailed than the conventional linkage maps and the SoilGrids250m product, and could well represent spatial variation of soil texture across China. The relative accuracy improvement was around 245\u2013370% relative to the linkage maps and 83\u2013112% relative to the SoilGrids250m product with regard to the R2, and it was around 24\u201326% and 14\u201319% respectively with regard to the RMSE. The wide range between 5% lower and 95% upper prediction limits may suggest that there was a substantial room to improve current predictions. Besides, we found that climate and terrain factors are major controllers for spatial patterns of soil texture in China. The heat and water-driven physical and chemical weathering and wind-driven erosion processes primarily shape the pattern of clay content. The terrain, wind and water-driven deposition, erosion and transportation sorting processes of soil particles primarily shape the pattern of silt. The findings provide clues for modeling future soil evolution and for national soil security management under the background of global and regional environmental changes.", "keywords": ["2. Zero hunger", "Digital soil mapping", "13. Climate action", "Large extent", "Machine learning", "Environmental factors", "Uncertainty", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8089699"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8089699", "name": "item", "description": "10.5281/zenodo.8089699", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8089699"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-01T00:00:00Z"}}, {"id": "10.5846/stxb201107151055", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:52Z", "type": "Journal Article", "created": "2012-04-25", "title": "Effect Of Fertilization On Ammonia Volatilization From Paddy Fields In Chao Lake Basin", "description": "Ammonia(NH3) is formed constantly in soils because of the biological degradation of organic compounds and NH+4 yielding mineral and organic fertilizers.NH3 volatilization is one of the major losses of applied nitrogen fertilizers,which is affected by the local climate conditions(e.g.,temperature,sun illumination,and wind speed),soil moisture content,urease activity,fertilization time,and ammonium concentration in surface water of the paddy fields.In this study,A situ experiment combined with venting method was conducted to study the effects of different fertilization patterns on NH3 volatilization in Chao Lake Basin during the rice season in 2010.In the experiment,there were six treatments with the control,the conventional fertilization,the optimization fertilization(according to local test of fertilization recipe),the reduction by 30% of nitrogen fertilizer,the reduction by 50% of phosphorus fertilizer and the straw return.The results showed that the NH3 volatilization loss from paddy fields was affected by fertilization and ammonium nitrogen(NH+4-N)concentration in surface water of the paddy fields.The NH3 volatilization among different treatments lasted for one week and the volatilization peak occurred within one to three days after fertilization,then declined quickly.When the rate of phosphorus fertilizer remained the same(e.g.,he treatments of the optimization fertilization and the reduction by 30% of nitrogen fertilizer),The concentration of NH3 volatilization loss enhanced as the nitrogen application rate increased with the same rate of phosphorus fertilizer.The amount of NH3 volatilization ranged from 7.22 to 14.20 kg/hm2,Which accounted for 4.59% to 6.64% of the total applied N for the whole period of rice growth.Compared with the conventional fertilization,the NH3 volatilization loss was reduced by 1% to 2% respectively with the treatments of the reduction by 30% of nitrogen fertilizer\u3001by 50% of phosphorus fertilizer and the optimization fertilization,while the NH3 volatilization loss was reduced by 6.98 kg/hm2 with the treatment of the straw return,which total ammonia volatilize quantity was 54% of the conventional fertilization.The highest NH3 volatilization loss occurred at basal dressing,which amount for 60% of the total NH3 loss,while the lowest loss did at panicle stage.The concentration of NH+4-N in surface water reached the highest within one to two days after fertilization.The positive correlation was observed between NH3 loss and NH+4-N concentration in the surface water of the basal dressing and the first top-dressing.From the point of the water improvement of Chao Lake basin,the period within a week after the fertilizer application was a critical time to control N loss and leaching from flooded paddy fields.NH3 loss would be decreased when N and P ferlization was rational.It is necessary to apply rational and balanced fertilization for N and P.Combined with economic benefit and environmental risk,the straw return is recommended for rice production in Chao Lake basin.", "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"], "contacts": [{"organization": "\u6731\u5c0f\u7ea2 Zhu Xiaohong, \u8096\u5723\u8f89 Xiao Shenghui, \u5f90\u5b8f\u519b Xu Hongjun, \u9a6c\u53cb\u534e Ma Youhua, \u9a6c\u4e2d\u6587 Ma Zhongwen, \u6c6a\u4e3d\u5a77 Wang Liting, \u5f20\u4e3d\u5a1f Zhang Lijuan,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5846/stxb201107151055"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Acta%20Ecologica%20Sinica", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5846/stxb201107151055", "name": "item", "description": "10.5846/stxb201107151055", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5846/stxb201107151055"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.7910/DVN/M4ZGXP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:03Z", "type": "Dataset", "title": "MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory", "description": "<b>MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory</b> <br><br> -------------------------------------------------------------------------------------- <br> 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/. <br><br> <i>Please refer to the associated publication</i>: <br> 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. <i>Frontiers in Remote Sensing</i>, 5, p.1042624. <br> <a href='https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624'>https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624</a> <br><br> <i>Input options:</i> <br> [1] Country of interest <br> [2] Start and end year <br> [3] Start and end month <br> [4] Option to mask data to a specific land-use/land-cover type <br> [5] Land-use/land-cover type code from CGLS LULC <br> [6] Image collection for data aggregation <br> [7] Desired band from the image collection <br> [8] Statistics type for the zonal aggregations <br> [9] Statistic to use for annual aggregation <br> [10] Scaling options <br> [11] Export folder and label suffix <br><br> <i>Output:</i> Two CSVs containing zonal statistics for each of the FAO GAUL administrative level boundaries <br> <i>Output fields:</i> 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 <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_input_v5.PNG?raw=true' width='1000' height='auto'</img> <br><br> <b>PREPROCESSED DATA DOWNLOAD</b> <br><br> 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 <b>(Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Thailand, Vietnam, Burundi, Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe)</b> 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. <br><br> <b>Key</b>: [source, data, units, temporal range, aggregation, masking, zonal statistic, notes] <br><br> Currently available: <br><b>MSZSI-V2_V-NDVI-MEAN.tar</b>: [NASA-MODIS, NDVI, index, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-DAY-MEAN.tar</b>: [NASA-MODIS, LST Day, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-NIGHT-MEAN.tar</b>: [NASA-MODIS, LST Night, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_R-PRECIP-SUM.tar</b>: [UCSB-CHG-CHIRPS, Precipitation, mm, 2001\u20132020, annual sum, agriculture, mean, n/a] <br><b>MSZSI-V2_S-BDENS-MEAN.tar</b>: [OpenLandMap, Bulk density, g/cm3, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-ORGC-MEAN.tar</b>: [OpenLandMap, Organic carbon, g/kg, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-PH-MEAN.tar</b>: [OpenLandMap, pH in H2O, pH, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-WATER-MEAN.tar</b>: [OpenLandMap, Soil water, % at 33kPa, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SAND-MEAN.tar</b>: [OpenLandMap, Sand, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SILT-MEAN.tar</b>: [OpenLandMap, Silt, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-CLAY-MEAN.tar</b>: [OpenLandMap, Clay, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_E-ELEV-MEAN.tar</b>: [MERIT, [elevation, slope, flowacc, HAND], [m, degrees, km<sup>2</sup>, m], static, n/a, agriculture, mean, n/a] <br><br><i>Coming soon</i> <br><b>MSZSI-V2_C-STAX-MEAN.tar</b>: [OpenLandMap, Soil taxonomy, category, static, n/a, agriculture, area sum, n/a] <br><b>MSZSI-V2_C-LULC-MEAN.tar</b>: [CGLS-LC100-V3, LULC, category, 2015\u20132019, mode, none, area sum, n/a] <br><br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_diagram_v2.png?raw=true' width='1000' height='auto'</img> <br><br> <b>Data sources:</b> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD'>https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global'>https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1'>https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2</a></li> <br> <b>Project information:</b> <br> SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes <br> <a href='http://seagul.info/'>http://seagul.info/</a>; <a href='https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental'>https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental</a> <br> This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) <br><br> For an additional interactive visualization, visit: <a href='https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi'>https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi</a> <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_app.png?raw=true' width='1000' height='auto'</img> <br><br><br> <i> Google Earth Engine code</i> <pre> /*/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// 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 < 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) </pre>", "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": "2026-09-19T16:21:03Z", "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.

Annual stocks.

Each of these 13 years is 3TB when extracted. So that is 39 TB as a tif.

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": "2026-09-19T16:21:26Z", "type": "Journal Article", "created": "2024-12-03", "title": "Addressing the environmental sustainability of plastics used in agriculture: a multi-actor perspective", "description": "Abstract

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.

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.

", "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": "1887/4246123", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:21:33Z", "type": "Journal Article", "created": "2023-08-30", "title": "Inland Waters Increasingly Produce and Emit Nitrous Oxide", "description": "Nitrous oxide (N2O) is a long-lived greenhouse gas and currently contributes \u223c10% to global greenhouse warming. Studies have suggested that inland waters are a large and growing global N2O source, but whether, how, where, when, and why inland-water N2O emissions changed in the Anthropocene remains unclear. Here, we quantify global N2O formation, transport, and emission along the aquatic continuum and their changes using a spatially explicit, mechanistic, coupled biogeochemistry-hydrology model. The global inland-water N2O emission increased from 0.4 to 1.3 Tg N yr-1 during 1900-2010 due to (1) growing N2O inputs mainly from groundwater and (2) increased inland-water N2O production, largely in reservoirs. Inland waters currently contribute 7 (5-10)% to global total N2O emissions. The highest inland-water N2O emissions are typically in and downstream of reservoirs and areas with high population density and intensive agricultural activities in eastern and southern Asia, southeastern North America, and Europe. The expected continuing excessive use of nutrients, dam construction, and development of suboxic conditions in aging reservoirs imply persisting high inland-water N2O emissions.", "keywords": ["Inland waters", "N2O cycling", " long-term temporal changes", "long-term temporal changes", "Nitrous oxide", "Asia", " Southern", "Nitrous Oxide", "Integrated process-based modeling", "Water", "Agriculture", "General Chemistry", "15. Life on land", "N2O cycling", "6. Clean water", "Greenhouse gas emission", "13. Climate action", "Environmental Chemistry", "14. Life underwater", "Spatial distributions", "closed N2O budget"]}, "links": [{"href": "https://doi.org/1887/4246123"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "1887/4246123", "name": "item", "description": "1887/4246123", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/1887/4246123"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-08-30T00:00:00Z"}}, {"id": "10.1007/s11104-010-0544-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:50Z", "type": "Journal Article", "created": "2010-09-01", "title": "Biochar Impact On Development And Productivity Of Pepper And Tomato Grown In Fertigated Soilless Media", "description": "The impact of additions (1\u20135% by weight) of a nutrient-poor, wood-derived biochar on pepper (Capsicum annuum L.) and tomato (Lycopersicum esculentum Mill.) plant development and productivity in a coconut fiber:tuff growing mix under optimal fertigation conditions was examined. Pepper plant development in the biochar-treated pots was significantly enhanced as compared with the unamended controls. This was reflected by a system-wide increase in most measured plant parameters: leaf area, canopy dry weight, number of nodes, and yields of buds, flowers and fruit. In addition to the observed increases in plant growth and productivity, the rhizosphere of biochar-amended pepper plants had significantly greater abundances of culturable microbes belonging to prominent soil-associated groups. Phylogenetic characterization of unique bacterial isolates based on 16S rRNA gene analysis demonstrated that of the 20 unique identified isolates from roots and bulk soil from the char-amended growing mix, 16 were affiliated with previously described plant growth promoting and/or biocontrol agents. In tomato, biochar treatments positively enhanced plant height and leaf size, but had no effect on flower and fruit yield. The positive impacts of biochar on plant response were not due to direct or indirect effects on plant nutrition, as there were no differences between control and treatments in leaf nutrient content. Nor did biochar affect the field capacity of the soilless mixture. A number of organic compounds belonging to various chemical classes, including n-alkanoic acids, hydroxy and acetoxy acids, benzoic acids, diols, triols, and phenols were identified in organic solvent extracts of the biochar. We conjecture two related alternatives to explain the improved plant performance under biochar treatment: (i) the biochar stimulated shifts in microbial populations towards beneficial plant growth promoting rhizobacteria or fungi, due to either chemical or physical attributes of the biochar; or (ii) low doses of biochar chemicals, many of which are phytotoxic or biocidal at high concentrations, stimulated plant growth at low doses (hormesis).", "keywords": ["2. Zero hunger", "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/10.1007/s11104-010-0544-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20and%20Soil", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11104-010-0544-6", "name": "item", "description": "10.1007/s11104-010-0544-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11104-010-0544-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-09-02T00:00:00Z"}}, {"id": "10.1016/j.agrformet.2018.01.017", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:15:10Z", "type": "Journal Article", "created": "2018-02-19", "title": "Potential of solar-induced chlorophyll fluorescence to estimate transpiration in a temperate forest", "description": "Abstract By utilizing continuous measurements of water fluxes and solar-induced chlorophyll fluorescence (SIF) over the entire growing season, we exploit the potential of broadband SIF in predicting plant transpiration (T) in a temperate forest. After reconstructing the full SIF spectrum from the selected absorption lines and simulations from the SCOPE (Soil Canopy Observation Photochemistry and Energy fluxes) model, linear regression (LR) and Gaussian processes regression (GPR) models are used to analyze the relation between T and combinations of different SIF bands. We find that SIF emissions in the near-infrared spectrum (at 720\u202fnm, 740\u202fnm and 760\u202fnm) are more sensitive to T than SIF emissions in the red spectrum (at 685\u202fnm and 687\u202fnm). While conditions such as light and heat stress decouple the relationship between single-band SIF and T, the combination of different SIF bands allows the retrieval of reliable T estimates even in these conditions. Overall, we find that the use of SIF as a proxy for T yields estimates that are at least as accurate as those from traditional transpiration models such as the Penman-Monteith equation, which are input demanding and complex to apply to in situ and satellite data. Specifically, we find that (1) the SIF-T relationship deteriorates when Photosynthetically Active Radiation (PAR), vapor pressure deficit and air temperature exceed biological optimal thresholds; (2) a high leaf area index exerts a negative impact on the SIF-T correlation due to increasing scattering and (re)absorption of the SIF signal; (3) the SIF-T relationship does not change depending on the observation time during the day; and (4) temporal aggregation to days further enhanced the SIF-T correlations. Altogether, our results provide the first ground-based evidence that SIF emission has potential to be a close predictor of plant transpiration, especially when a combination of different SIF bands is considered.", "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/10.1016/j.agrformet.2018.01.017"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20and%20Forest%20Meteorology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agrformet.2018.01.017", "name": "item", "description": "10.1016/j.agrformet.2018.01.017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agrformet.2018.01.017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-01T00:00:00Z"}}, {"id": "10.1007/s11258-005-9031-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:54Z", "type": "Journal Article", "created": "2006-02-27", "title": "Plant Performance In A Warmer World: General Responses Of Plants From Cold, Northern Biomes And The Importance Of Winter And Spring Events", "description": "During the past three decades the Earth has warmed with a rate unprecedented during the past 1000 years. There is already ample evidence that this fast climate warming has affected a broad range of organisms, including plants. Plants from high-latitude and high-altitude sites ('cold biomes') are especially sensitive to climate warming. In this paper we (1) review the response in the phenology of plants, changes in their range and distribution, soil nutrient availability, and the effects on the structure and dynamics of plant communities for cold, northern biomes; and (2) we show, by using data from an ongoing snow and temperature manipulation experiment in northern Sweden, that also winter and spring events have a profound influence on plant performance. Both long-term phenological data sets, experimental warming studies (performed in summer or year-round), natural gradient studies and satellite images show that key phenological events are responsive to temperature increases and that recent climate warming does indeed lead to changes in plant phenology. However, data from a warming and snow manipulation study that we are conducting in northern Sweden show that plants respond differently to the various climatic scenarios that we had imposed on these species and that especially winter and spring events have a profound impact. This indicates that it is necessary to include several scenarios of both summer and winter climate change in experimental climate change studies, and that we need detailed projections of future climate at a regional scale to be able to assess their impacts on natural ecosystems. There is also ample evidence that the range shift of herbs and shrubs to more northern regions is for the vast majority of species mainly caused by changes in the climate. This is in line with the observed 'up-greening' of northern tundra sites. These rapid northern shifts in distribution of plants as a result of climate warming may have substantial consequences for the structure and dynamics of high-latitude ecosystems. An analysis of warming studies at 9 tundra sites shows that heating during at least 3 years increased net N-mineralization from 0.32\u00b10.31 (SE) g N m", "keywords": ["0106 biological sciences", "2. Zero hunger", "13. Climate action", "SDG 13 - Climate Action", "15. Life on land", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s11258-005-9031-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%20Ecology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11258-005-9031-1", "name": "item", "description": "10.1007/s11258-005-9031-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11258-005-9031-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2006-01-01T00:00:00Z"}}, {"id": "10.1002/jgrg.20063", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:15Z", "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

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<\uffe2\uff80\uff890.05), respectively, while low\uffe2\uff80\uff90level N addition has no effect on ecosystem respiration (P\uffe2\uff80\uff89>\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<\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>\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>\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.

", "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/ece3.9322", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:14Z", "type": "Journal Article", "created": "2022-09-22", "title": "Impacts of insect frass and cadavers on soil surface litter decomposition along a tropical forest temperature gradient", "description": "Abstract

Insect herbivores play important roles in shaping many ecosystem processes, but how climate change will alter the effects of insect herbivory are poorly understood. To address this knowledge gap, we quantified for the first time how insect frass and cadavers affected leaf litter decomposition rates and nutrient release along a highly constrained 4.3\uffc2\uffb0C mean annual temperature (MAT) gradient in a Hawaiian montane tropical wet forest. We constructed litterbags of standardized locally sourced leaf litter, with some amended with insect frass + cadavers to produce treatments designed to simulate ambient (Control\uffc2\uffa0=\uffc2\uffa0no amendment), moderate (Amended\uffe2\uff80\uff90Low\uffc2\uffa0=\uffc2\uffa02\uffe2\uff80\uff89\uffc3\uff97\uffe2\uff80\uff89Control level), or severe (Amended\uffe2\uff80\uff90High\uffc2\uffa0=\uffc2\uffa011\uffe2\uff80\uff89\uffc3\uff97\uffe2\uff80\uff89Control level) insect outbreak events. Multiple sets of these litterbags were deployed across the MAT gradient, with individual litterbags collected periodically over one\uffe2\uff80\uff89year to assess how rising MAT altered the effects of insect deposits on litter decomposition rates and nitrogen (N) release. Increased MAT and insect inputs additively increased litter decomposition rates and N immobilization rates, with effects being stronger for Amended\uffe2\uff80\uff90High litterbags. However, the apparent temperature sensitivity (Q10) of litter decomposition was not clearly affected by amendments. The effects of adding insect deposits in this study operated differently than the slower litter decomposition and greater N mobilization rates often observed in experiments which use chemical fertilizers (e.g., urea, ammonium nitrate). Further research is required to understand mechanistic differences between amendment types. Potential increases in outbreak\uffe2\uff80\uff90related herbivore deposits coupled with climate warming will accelerate litter decomposition and nutrient cycling rates with short\uffe2\uff80\uff90term consequences for nutrient cycling and carbon storage in tropical montane wet forests.Deliverable report D2.2 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). List of tailored and case-specific performance indicators (environmental and socio-economical) that help to evaluate the effectiveness of NSWRM monitored (existing measures) and modelled (potential future measures) in the OPTAIN case studies as well as used to establish a common language across project members and activities and to facilitate the knowledge sharing with stakeholders and the wider dissemination of project results. Summary: The content of this deliverable addresses the activities of the task 2.2 \u201cIdentification of performance indicators for the selected NSWRM\u201d within the H2020 project OPTAIN. The core purpose of the task is to develop a customized set of indicators that allow assessing the effectiveness of selected (either existing or potential future) Natural/Small Water Retention Measures (NSWRMs) in and across the OPTAIN case studies (CS). The relevance of specific NSWRMs to face local challenges, their multifunctional nature and the manifold impacts they may have in the territory require identifying key elements that easily resume such features, while being flexible and adaptable enough to be used in different contexts. Therefore, task 2.2 elaborated a pathway to produce a list of Performance Indicators (PI), to set the focus for model parametrisation at different scales as well as to ensure an appropriate model setup and utilisation of modelling outcomes (WP4, WP5). For this reason, the screening, selection and tailoring of the most relevant indicators, to be used as PI, have been conducted from both the environmental (EPIs) and socio-economic (SPIs) points of view. The selection process was built at the interface between science and society, in a fruitful process of knowledge co-creation and sharing. As such, agreed lists of indicators can be used to support the harmonized approach of OPTAIN by establishing a common language across project members and activities, favour the understanding and the comparison of modelling results across CS, facilitating the dialogue with stakeholders and the wider dissemination of project results. The methodology followed to outline the customized list of indicators, to be used as PIs, was based upon the initial contribution of scientific / academic partners\u2019 expertise to compile all the potential or candidate indicators and preselect the most relevant ones for the selected NSWRMs. As a result, we ended up with short lists of both environmental (25) and socio-economic (17) indicators that cover the most relevant issues of the OPTAIN case studies. In the second instance a participative approach involved local research teams and stakeholders in the valuation, adjustment and prioritisation of the most important indicators, also owing to the intensive consultation with OPTAINs Multi-Actor-Reference Groups (MARG). Based on the feedback obtained, the task 2.2 partners conducted an analysis of the commonalities and differences between CSs and scales. This allowed drawing the conclusion that, despite CS are experiencing diverse challenges, the most important issues covered by the selected indicators, and priorities given are very similar. Finally, for comparison purposes across CSs, a common set of PIs is proposed, including first discussions on the best way to represent selected PIs based on monitoring and/or modelling results to be available in CS.", "keywords": ["environmental performance", "Multi-Actor-Reference Groups (MARG)", "13. Climate action", "NSWRM", "11. Sustainability", "socio-economic performance", "H2020", "OPTAIN", "indicators", "12. Responsible consumption"], "contacts": [{"organization": "Krzeminska, Dominika, Monaco, Federica,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7050653"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7050653", "name": "item", "description": "10.5281/zenodo.7050653", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7050653"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-31T00:00:00Z"}}, {"id": "10.1002/2017gb005693", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:12Z", "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

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.\u00a00.05) while optimizing the crop yield. The analysis identified the nutrient N rates in combination with specific crops and rotation systems that can be used to manage [Formula: see text] leaching while balancing impacts on crop yields within the watershed.", "keywords": ["2. Zero hunger", "Analysis of Variance", "Conservation of Natural Resources", "Geologic Sediments", "Nitrates", "Agriculture", "04 agricultural and veterinary sciences", "Models", " Theoretical", "15. Life on land", "01 natural sciences", "6. Clean water", "Environmental Policy", "Nova Scotia", "13. Climate action", "Water Quality", "Humans", "0401 agriculture", " forestry", " and fisheries", "Fertilizers", "Groundwater", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s00267-013-0148-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00267-013-0148-z", "name": "item", "description": "10.1007/s00267-013-0148-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00267-013-0148-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-08-13T00:00:00Z"}}, {"id": "10.1046/j.1469-8137.2000.00665.x", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:16:44Z", "type": "Journal Article", "created": "2003-03-12", "title": "Growth Responses Of Quercus Petraea, Fraxinus Excelsior And Pinus Sylvestris To Elevated Carbon Dioxide, Ozone And Water Supply", "description": "

Seedlings of Quercus petraea (oak), Fraxinus excelsior (ash) and Pinus sylvestris (Scots pine) were grown at two CO2 concentrations with two O3 and two water supply treatments for 3 yr in a factorial experiment. Oak was the most responsive species to all three treatments; elevated CO2 and irrigation increased biomass by an average of 79% and 41%, respectively, whereas the ozone treatment resulted in a 30% reduction in growth. Significant treatment interactions in this species demonstrated that CO2 ameliorated and irrigation exacerbated the effects of ozone. For Scots pine and ash, irrigation and elevated CO2 increased growth by approx. 60% and 20%, respectively, whereas ozone had no detectable effect on ash and resulted in a 15% reduction in growth of Scots pine. Carbon partitioning to the shoot was enhanced by both the CO2 and H2O treatments in oak, while branching was also increased in this species in response to elevated O3, resulting in changes to the allometric relationships. CO2 enhanced leaf production in oak and Scots pine, and together with the promotion of shoot allocation, this indicates an increased susceptibility to windthrow. Biomass accumulation expressed as relative growth rate, suggested three different time\uffe2\uff80\uff90dependent growth responses to elevated CO2; the CO2 fertilization effect was maintained through the third year of growth in oak, had disappeared in Scots pine and a negative effect was evident in ash. Foliar nitrogen and chlorophyll concentrations indicated a CO2\uffe2\uff80\uff90induced nitrogen deficiency in oak and ash, but not in Scots pine. Chlorophyll degradation in response to ozone was observed in oak, an effect that was enhanced by irrigation and reduced by CO2, presumably through stomatal mediated changes in effective ozone dose. These results therefore suggest that elevated atmospheric CO2 concentrations will enhance growth of some UK forest tree species, although this might only be apparent during the juvenile phase. However, nitrogen deficiencies might limit this enhancement on some sites while changes in allocation and leaf area might promote susceptibility to windthrow. Elevated CO2 also provides some protection against ozone pollution, especially in combination with limited soil moisture availability. These interactions between CO2, ozone and water supply should be taken into account when predicting the effects of environmental change on tree growth and forest productivity.

", "keywords": ["0106 biological sciences", "15. Life on land", "01 natural sciences", "6. Clean water", "0105 earth and related environmental sciences"], "contacts": [{"organization": "S. B. Jackson, M. S. J. Broadmeadow,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1046/j.1469-8137.2000.00665.x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/New%20Phytologist", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1046/j.1469-8137.2000.00665.x", "name": "item", "description": "10.1046/j.1469-8137.2000.00665.x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1046/j.1469-8137.2000.00665.x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2000-06-01T00:00:00Z"}}, {"id": "10.5281/zenodo.7057381", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:20:27Z", "type": "Report", "title": "Training analysis - Identifying the needs and capacity of relevant target groups for tailoring the OPTAIN Learning Environment to their potential users' requirements. Deliverable D7.5 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D7.5 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). The report aims at identifying the needs and capacity of potential users of the OPTAIN Learning Environment. Summary: The \u2018training analysis\u2019 aims at identifying the needs and capacity of relevant target groups for tailoring the OPTAIN Learning Environment to their potential users\u2019 requirements. The training analysis is an on-going process next to the development of the Learning Environment. This report presents a first state of the art that will be constantly updated until the second version is produced in February 2025. At that stage, one challenge is to engage with potential users while the Learning Environment is under development. OPTAINs first training analysis focused on farmers, NGOs/associations, scientists, advisors/farmers\u2019 unions. Their profile was described in individual persona based on the information gathered in interviews and desk analysis. A preliminary illustration of the key relation (i.e. trust, co-creation/transfer or communication) among persona was illustrated on a stakeholder mapping highlighting three sectors (training, dissemination and raising awareness). These information was then used to elaborate a training matrix bringing together the core needs of each persona, their related sector and potential materials to be used for trainings. The recommendations to set the trainings were drawn based on a 360\u00b0 framework detailing 11 criteria to be taken into account and synthetic views for the targets, content, format, and transversal tips. Advisors/Farmers\u2019 unions and NGOs/associations are the primary targets of OPTAIN training. As knowledge broker, they work at the interface with other stakeholders such as farmers. Scientists are the secondary target of the training. They are knowledge providers facing the huge challenge of co-creating the knowledge while providing demonstration of the multiple benefits of NSWRM and related themes. This leads to a change of the usual content and format of training. Indeed, the content should be scientific and community based (with experience sharing) and embedded in a trans-disciplinary approach. The format should offer the opportunities for learning experience through networking. The next steps will consist in enlarging the stakeholder mapping by adding persona related to the European Commission, regional authorities, decision makers and managers, students and representatives of the civil society. Each format (on-site, on-line, and continuous) will be further detailed in the respect of the balance between training ambitions and OPTAIN budget and resources.", "keywords": ["Learning Environment", "target groups", "H2020", "OPTAIN", "training analysis"], "contacts": [{"organization": "Amorsi, Natacha, Jacquin, Natacha, Pronost, Joseph, Fribourg-Blanc, Beno\u00eet, Semko, Jergus,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7057381"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7057381", "name": "item", "description": "10.5281/zenodo.7057381", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7057381"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-31T00:00:00Z"}}, {"id": "10.1007/s10533-009-9381-1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:42Z", "type": "Journal Article", "created": "2009-10-13", "title": "Plant-Soil Interactions And Acclimation To Temperature Of Microbial-Mediated Soil Respiration May Affect Predictions Of Soil Co2 Efflux", "description": "Open AccessPeer reviewed", "keywords": ["Life Sciences", " general", "Carbon cycle modeling", "2. Zero hunger", "Ecosystem ecology", "Life Sciences", "Soil respiration", "04 agricultural and veterinary sciences", "15. Life on land", "Biogeosciences", "Ecosystems", "6. Clean water", "general", "13. Climate action", "Earth Sciences", "Environmental Chemistry", "Climate change", "0401 agriculture", " forestry", " and fisheries", "Earth-Surface Processes", "Water Science and Technology"]}, "links": [{"href": "https://escholarship.org/content/qt74h8k7gh/qt74h8k7gh.pdf"}, {"href": "https://doi.org/10.1007/s10533-009-9381-1"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeochemistry", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10533-009-9381-1", "name": "item", "description": "10.1007/s10533-009-9381-1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10533-009-9381-1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-10-14T00:00:00Z"}}, {"id": "10.1007/s10646-009-0329-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:43Z", "type": "Journal Article", "created": "2009-06-06", "title": "Trace Elements And Activity Of Antioxidative Enzymes In Cistus Ladanifer L. Growing On An Abandoned Mine Area", "description": "The Mediterranean shrub Cistus ladanifer grows naturally in S\u00e3o Domingos (Portugal), an abandoned copper mine. High levels of trace elements in plants can generate oxidative stress increasing the activity of antioxidant enzymes. The aim of this work was to evaluate and compare As, Cu, Pb and Zn concentrations and the activity of the soluble and cell wall ionically bounded forms of the enzymes catalase, peroxidase and superoxide dismutase in leaves of C. ladanifer, collected in spring and summer, growing on S\u00e3o Domingos mine and on a non-contaminated area (Pomar\u00e3o). S\u00e3o Domingos soils showed high total concentrations of As (2.6 g kg(-1)) and Pb (7.3 g kg(-1)) however the available fraction represented less than 1.5% of the total. C. ladanifer population from mine showed tolerance to Pb and Zn, which attain in leaves concentrations considered toxic for plants. The enzymatic activity of catalase, peroxidise and superoxide dismutase varied with plant populations and seasons, although with no particular trend, being specific to each trace element and enzyme cell localization. Catalase activity was evenly distributed between the soluble and ionically bounded forms, whereas the ionically bounded form of peroxidase predominated relatively to total activity, and the opposite was observed for superoxide dismutase. Spring and summer leaves from the two areas presented enzymatic activities in both fractions except to peroxidase soluble activities in leaves collected in summer. C. ladanifer enzymatic activity seems to be related with the co-existence of different stress factors (trace elements concentration, temperature, UV radiation and drought). The survival and growth of this species on contaminated mining soils is due to the presence of effective antioxidant enzyme-based defence systems.", "keywords": ["0106 biological sciences", "trace elements", "Industrial Waste", "antioxidative enzymes", "Antioxidative enzymes", "01 natural sciences", "Mining", "Soil", "Cell Wall", "Soil Pollutants", "adaptative capacity", "0105 earth and related environmental sciences", "Trace elements", "Portugal", "Cistus", "Adaptative capacity", "15. Life on land", "Sulphide abandoned mine", "cistus ladanifer L.", "Trace Elements", "Plant Leaves", "Oxidative Stress", "sulphide abandoned mine", "Cistus ladanifer L.", "Oxidoreductases", "Copper"]}, "links": [{"href": "https://doi.org/10.1007/s10646-009-0329-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecotoxicology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10646-009-0329-y", "name": "item", "description": "10.1007/s10646-009-0329-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10646-009-0329-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-06-05T00:00:00Z"}}, {"id": "10.1002/ece3.71670", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-19T16:14:14Z", "type": "Journal Article", "created": "2025-07-17", "title": "Ground\u2010Dwelling Spider Community Responses to Forest Management in a Mediterranean Oak Forest", "description": "ABSTRACT

Timber production is one of the most important ecosystem services provided by hardwood forests, but clear\uffe2\uff80\uff90cutting causes severe soil disturbance. There is a current need to develop alternative forest management practices to clear\uffe2\uff80\uff90cutting in order to simultaneously promote timber production, preserve biodiversity and enhance forest health and economic value. Here, we experimentally manipulated a Quercus pubescens forest to evaluate the effects of a thinning gradient (i.e., partial tree removal) ranging from 25% to 75% basal area reduction and a logging residue retention (i.e., slash management) on ground\uffe2\uff80\uff90dwelling spider abundance and species richness. These two alternative management practices were compared with clear\uffe2\uff80\uff90cutting (100% basal area reduction) and logging residue exportation methods. In each treatment, we recorded soil temperature and moisture, understorey vegetation cover, richness and functional traits and mesologic factors describing habitat characteristics. We found clear\uffe2\uff80\uff90cutting had a stronger effect than thinning on the microclimatic conditions, i.e., higher temperatures, drier soils and reduced forest buffering capacity. The 25% thinning intensity was sufficient to drastically reduce both spider abundance and richness, but we did not find a more significant reduction when more intensive cutting was applied. This result suggests a threshold effect in the response of spiders to cutting. Significant changes in the functional diversity of understory plant communities in response to basal area were observed, along with strong effects on spider communities. Unexpectedly, slash retention appeared to have little or no effect on the forest microclimate, spider abundance and species richness. This work is intended for forest managers and policymakers and aims to contribute to the development of relevant practices that address current environmental and economic challenges. While our findings provide valuable insights into understudied forest management practices in Mediterranean climates, additional research is required, particularly through multi\uffe2\uff80\uff90seasonal and long\uffe2\uff80\uff90term spider sampling.