{"type": "FeatureCollection", "features": [{"id": "10.5061/dryad.bvq83bkbg", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:05Z", "type": "Dataset", "title": "Recent photosynthates are the primary carbon source for soil microbial respiration in subtropical forests", "description": "unspecifiedTropical and subtropical forests represent the largest terrestrial carbon pool. Elucidating the carbon sources for soil microbial respiration (Rm) in tropical and subtropical forests is of fundamental importance to the global carbon cycle in a warming world. Based on hourly measurements, we quantified Rm of\u00a0in situ\u00a0forest soil and soil cores from a subtropical forest. We found recent photosynthates, not soil organic carbon (SOC), contributed 88% \u00b1 12% of the carbon source fueling Rm. The control of recent photosynthates on Rm is also supported by the close relationship between Rm and photosynthetically active radiation as well as literature data synthesis results. These results challenge conventional models based on the tenet that Rm is mainly regulated by soil temperature in all forest ecosystems. The results imply that the widely observed warming-induced Rm increases are largely explained by the enhanced input of recent photosynthates in tropical forests, not SOC consumption.", "keywords": ["recent photosynthates", "microbial respiration", "13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land", "subtropical forest"], "contacts": [{"organization": "Yang, zhijie, Lin, Teng-Chiu, Wang, Lixin, Yang, Yusheng,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.bvq83bkbg"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.bvq83bkbg", "name": "item", "description": "10.5061/dryad.bvq83bkbg", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.bvq83bkbg"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-10-25T00:00:00Z"}}, {"id": "10.5061/dryad.c59zw3rbg", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:05Z", "type": "Dataset", "title": "Soil carbon is mostly grass-derived in tropical savannas, even under woody encroachment", "description": "unspecifiedTropical savannas have been increasingly targeted for carbon (C) sequestration from afforestation, assuming large gains in soil organic C (SOC) with increasing tree cover. Because savanna SOC is also derived from grasses, this assumption may not reflect real changes in SOC under afforestation, but grass contributions to SOC and changes in SOC with increasing tree cover remain poorly synthesized. Here, we combine a case study from Kruger National Park, South Africa, with data synthesized from tropical savannas globally to show that grass-derived C constitutes more than half of total SOC to a soil depth of 1-meter, even in soils directly under trees. The largest SOC concentrations were associated with the largest grass contributions (> 70% of total SOC). Regionally and across the tropics, SOC concentration was not explained by tree cover. Both SOC gain and loss were observed following increasing tree cover, and on average SOC storage within 1-meter profile only increased by a negligible and non-significant 6% (SE = 4%, n = 44). These results underscore the substantial contribution of grasses to SOC and the considerable uncertainty in SOC responses to increasing tree cover, challenging the widespread assumption that afforestation universally and substantially enhances SOC storage across tropical savannas.", "keywords": ["2. Zero hunger", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Zhou, Yong, Staver, Carla,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.c59zw3rbg"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.c59zw3rbg", "name": "item", "description": "10.5061/dryad.c59zw3rbg", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.c59zw3rbg"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-28T00:00:00Z"}}, {"id": "10.5061/dryad.cc2fqz6d9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:05Z", "type": "Dataset", "created": "2023-12-20", "title": "Data from: Do Tasmanian devil declines impact ecosystem function?", "description": "unspecifiedTasmanian eucalypt forests are among the most carbon-dense in the world, but projected changes in climate could destabilize this critical carbon sink. While the impact of abiotic factors on forest ecosystem carbon dynamics have received considerable attention, biotic factors, such as the input of animal scat, are less understood. Tasmanian devils (Sarcophilus harrisii)\u2014an osteophageous scavenger that can ingest and solubilize nutrients locked in bone material\u2014may subsidize plant and microbial productivity by concentrating bioavailable nutrients (e.g., nitrogen and phosphorus) in scat latrines. Dramatic declines in devil population densities are driven by the spread of a transmissible cancer and may have underappreciated consequences for soil organic carbon (SOC) storage and forest productivity by altering nutrient cycling. Here, we fuse experimental data and modeling to quantify and predict future changes to forest productivity and SOC under various climate and scat-quality futures. We find that devil scat significantly increases concentrations of nitrogen, ammonium, phosphorus, and phosphate in the soil, and shifts soil microbial communities towards those dominated by r-selected (e.g., fast-growing) phyla. Further, under simulated increases in temperature and precipitation, devil scat inputs are projected to increase above- and belowground net primary productivity and microbial biomass carbon through 2100. In contrast, when devil scat is replaced by lower-quality scat (e.g., from non-osteophageous scavengers and herbivores), forest carbon pools either increase more slowly or decline. Together, our results suggest biotic factors will interact with climate change to drive current and future carbon pool dynamics in Tasmanian forests.", "keywords": ["forest productivity", "Tasmanian devils", "soil microbiome", "Climate change", "nutrient cycling", "FOS: Earth and related environmental sciences", "scat inputs", "Soil carbon"], "contacts": [{"organization": "Stephenson, Torrey", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.cc2fqz6d9"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.cc2fqz6d9", "name": "item", "description": "10.5061/dryad.cc2fqz6d9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.cc2fqz6d9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-09T00:00:00Z"}}, {"id": "10.5061/dryad.djh9w0w67", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:06Z", "type": "Dataset", "created": "2023-11-08", "title": "Data for: Stabilisation of soil organic matter with rock dust partially counteracted by plants", "description": "unspecifiedIn this study, the effect of rock dust addition on both soil inorganic and organic carbon contents was investigated. Soil chemical changes were measured, including soil organic carbon (totals and fractions), soil inorganic carbon, pH, electric conductivity, and water-extractable and ammonium acetate-extractable ion levels (Ca, Mg, Al, Fe, Mn, Fe, Zn, Si). In addition, the effect of plants on soil chemistry and rocks on plant growth (biomass) and plant ion uptake was studied. The results demonstrated rock weathering during the 6 months incubation period and a stabilisation of organic carbon. Plants partially counteracted the stabilisation of soil organic carbon. This was attributed to interactions between soil chemical changes induced by rock dust, plant exudation, and subsequent soil organic carbon stabilisation mechanisms.", "keywords": ["2. Zero hunger", "soil organic carbon", "soil carbon sequestration", "13. Climate action", "Particulate organic matter", "aggregate carbon", "FOS: Earth and related environmental sciences", "15. Life on land", "enhanced rock weathering", "Basalt", "mineral associated organic matter", "6. Clean water", "inorganic carbon"], "contacts": [{"organization": "Buss, Wolfram, Hasemer, Heath, Ferguson, Scott, Borevitz, Justin,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.djh9w0w67"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.djh9w0w67", "name": "item", "description": "10.5061/dryad.djh9w0w67", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.djh9w0w67"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-27T00:00:00Z"}}, {"id": "10.5061/dryad.fj6q573x9", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:06Z", "type": "Dataset", "title": "A synthesis of nitric oxide emissions across global fertilized croplands from crop-specific emission factors", "description": "Nitrogen (N)-fertilizer application to agricultural soils results in substantial emissions of nitric oxide (NO), a key substance in tropospheric chemistry involved in climate forcing and air pollution. However, estimates of global cropland NO emissions remain uncertain due to a lack of information on direct NO emission factors (EFds) of applied N for variours cropping systems at seasonal or annual scales. Here we quantified the crop-specific seasonal and annual-scale NO EFds through synthesizing 1094 measurements from 125 field-based studies worldwide. The global mean crop-specific seasonal EFd was 0.53%, with the highest for vegetables (0.75%). Among cereal crops, the EFd of maize (0.45%) or wheat (0.47%) was about three-times higher than for rice (0.12%). At annual scale, the mean EFd across all cropping systems was 0.58%, with tea plantations having the highest (1.54%). For other cropping systems, the annual-scale EFds ranged from 0.02% to 1.07%. Besides crop type, also soil organic carbon, total N and pH as well as N fertilizer type were the main factors explaining the variations of NO EFds. Based on obtained specific EFds for each crop type, we estimated that NO emissions due to the use of synthetic fertilizers from global croplands are about 0.42\u20130.62 Tg N yr\u22121. Our budgets are relatively lower if compared to estimates derived by the use of IPCC defaults for NO emissions (0.72\u20131.66 Tg N yr\u22121) or reported elsewhere (0.67\u20131.04 Tg N yr\u22121). In our estimates, cash crops (vegetable, tea and orchard), which cover only 9% of the world cropland area, contributed about 31% to total NO emissions from global fertilized croplands. Overall, our meta-analysis provides improved crop-specific NO EFds reflecting current stage of knowledge. The work also highlights the relative importance of cash crop production as sources for atmospheric NO, i.e., agricultural systems on which mitigation efforts may focus.", "keywords": ["2. Zero hunger", "cropland NO emission", "13. Climate action", "Nitric oxide", "FOS: Earth and related environmental sciences", "15. Life on land", "7. Clean energy"], "contacts": [{"organization": "Wang, Yan, Yao, Zhisheng, Zheng, Xunhua, Subramaniam, Logapragasan, Butterbach-Bahl, Klaus,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.fj6q573x9"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.fj6q573x9", "name": "item", "description": "10.5061/dryad.fj6q573x9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.fj6q573x9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-04-07T00:00:00Z"}}, {"id": "10.5061/dryad.g1jwstqx5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:07Z", "type": "Dataset", "created": "2023-09-27", "title": "Microbial traits dictate soil neromass accumulation coefficient: A global synthesis", "description": "unspecified# Readme **Title** Microbial necromass carbon accumulation coefficients (NAC) dataset **Author** Bingbing Han, Yanzhong Yao, Yini Wang, Xiaoxuan Su, Lihua Ma, Xinping Chen, Zhaolei Li * **Corresponding author:** Zhaolei Li, Professor E-mail: lizhaolei@swu.edu.cn **Correspondence address:** College of Resources and Environment, and Academy of Agricultural Sciences, Southwest University, Chongqing 400715, China **Data abstract** The accumulation of microbial necromass carbon has drawn mounting attention due to the slow decomposition. However, it remains unclear what determines the microbial necromass carbon accumulation via reiterated community turnover on large spatial scales. This study aimed to explore the characteristics of soil necromass carbon accumulation in terrestrial ecosystems. A dataset was compiled with 993 observations on the coefficient of microbial carbon accumulation in the equilibrium from 82 peer-reviewed papers. The linear mixed-effect models and structural equation models were used to ascertain the controlling factors of NAC on a global scale. The average NAC was higher in croplands (28.2) and forests (26.8) than that in grasslands (21.1). Although the edaphic factors seemingly affect the NAC whereby the NAC lowered in soils with high levels of pH and clay content on a global scale, the biotic factors, particularly for the living microorganism abundance and microbial biomass nitrogen content, were the pivotal drivers of NAC that accounted for approximately 42.5% of the geographic variances in NAC. More organic carbon was likely to be preserved in soil with a higher NAC regardless of ecosystem types. Novel findings on the overriding controls from the living microorganism abundance and microbial biomass nitrogen in driving NAC raise an urgent need for viable strategies in manipulating microbial characteristics for carbon sequestrations. **Data collect** The NACs dataset was compiled from peer-reviewed papers. These peer-reviewed papers were obtained by means of two platforms: the Web of Science ([http://apps.webofkonwledge.com](http://apps.webofkonwledge.com)) and the China National Knowledge Infrastructure Database ([http://www.cnki.net](http://www.cnki.net)). At the same time, the papers were supplemented by Google Scholar. The keywords used to search papers are soil microbial biomass AND microbial necromass AND microbial residue * AND amino sugar * AND PLFAs. The publishing date for the peer-reviewed paper was up to January 20, 2023. The eligible peer-reviewed papers matched the following criteria: (1) Soil microbial necromass was measured using amino sugars as markers; (2) The living microorganisms were determined by phospholipid fatty acid (PLFAs). Finally, the NAC dataset was constructed based on the 82 peer-reviewed papers. The details of the experimental site were also extracted from papers, including the geographic information of the experiment site (i.e., latitude and longitude), climate conditions (i.e., mean annual temperature and mean annual precipitation), and ecosystem types (i.e., grasslands, forests, and croplands). Additionally, soil physicochemical properties [soil pH, the ratio of carbon to nitrogen (soil C: N), total nitrogen (TN), bulk density (BD), clay content, and ammonium content (NH4+)] and the number of replicates were also extracted from the articles. Additionally, in the NAC dataset, the empty cells are representing the data scarcity (i.e., NA values). You should know that not every article will contain all the metrics. **Data analysis** The content of fungal and bacterial necromass carbon was calculated based on the concentrations of amino sugar in microbial cell walls: glucosamine and muramic acid. The bacterial necromass carbon and fungal necromass carbon were calculated using equations (1) and (2). where, MurA is muramic acid and GlcN is glucosamine. In equation (1), 45 is the conversion factor from MurA to bacterial necromass carbon; in equation (2), 9 is the conversion factor from GlcN to fungal necromass carbon; while 179.17 and 251.23 are the molecule weights of GlcN and MurA, respectively. Total microbial necromass carbon was the sum of fungal necromass carbon and bacterial necromass carbon. For the absence of microbial biomass carbon (MBC) in some experimental sites. The NAC functions as the ratio of the microbial necromass carbon to microbial biomass carbon: where MBC is soil microbial biomass carbon. The linear mixed-effect models were used to test the bivariate relationship between the NAC and environmental factor by means of *lme4* packages in R (version 4.2.2., R Core Team). The equation (4) was: where NAC refers to the microbial necromass carbon accumulation coefficient, lnX is the logarithm of each edaphic and climatic factor (except for soil pH and fungi: bacteria ratio), refers to the intercept of this model, refers to the slope value, refers to the random effect of study, refers to the sampling error. **Document Type** We will upload it in data _NAC _2023.csv format to the Dryad database. The main variables collected in the data form were muramic acid (MurA) and glucosamine (GlcN). We perform the calculation of NAC based on equations 1, 2, and 3 above. Total biomass represents the abundance of living microorganisms. Fungal biomass represents the abundance of fungi. Bacterial biomass represents the abundance of bacteria. MBC is microbial biomass nitrogen. SOC is soil organic carbon. **Data processing software** We processed the entire set of data by utilizing the R language, version 4.2.2., R Core Team. **Contact Information** **Corresponding author:** Zhaolei Li, Professor **E-mail:** [lizhaolei@swu.edu.cn](mailto:lizhaolei@swu.edu.cn) **ORCID:** [https://orcid.org/0000-0001-8767-1277](https://orcid.org/0000-0001-8767-1277)", "keywords": ["2. Zero hunger", "microbial abundance", "soil carbon sequestration", "microbial necromass carbon", "living microbes", "FOS: Earth and related environmental sciences", "15. Life on land", "microbial carbon pump", "ecosystem type"], "contacts": [{"organization": "Han, Bingbing, Yao, Yan Zhong, Wang, Yini, Su, Xiaoxuan, Ma, Lihua, Chen, Xinping, Li, Zhaolei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.g1jwstqx5"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.g1jwstqx5", "name": "item", "description": "10.5061/dryad.g1jwstqx5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.g1jwstqx5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-10-05T00:00:00Z"}}, {"id": "10.5061/dryad.h70rxwdqs", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:07Z", "type": "Dataset", "created": "2023-11-13", "title": "Data from: Microbial carbon use efficiency and soil organic carbon stocks across an elevational gradient in the Peruvian Andes", "description": "unspecifiedSoils of mountain ecosystems are one of the most vulnerable ecosystems to climate change, while the ecosystem services they produce are significant and currently at risk. High altitude soils contain high C stocks, but due to difficult access to sites these areas are understudied. Moreover, how the C and N cycling is changing in response to climate change in these ecosystems, is still unclear. Microbial carbon use efficiency (CUE) and its dependency on the environmental constraints along the altitudinal gradients is one important unknown factor. Here we present results from an altitudinal gradient study (3500 to 4500 m a.s.l.) from a Polylepis forest in the Peruvian Andes. We measured the soil organic carbon (SOC) stocks and microbial metabolic CUE by\u00a013C glucose tracing and microbial resource use efficiency (CUEC:N) based on enzyme activity measurements. We expected to find an increase in SOC stock, microbial nutrient limitations, and lower CUE with elevation. SOC stocks depended on soil development and followed a unimodal curve that peaks at 4000 m in two of the three studied valleys. Neither 13CUE nor CUEC:N changed significantly with altitude. Soil C:N ratio, \u03b2-glucosidase, chitinase, and phosphatase enzyme activities increased with elevation, but peroxidase activity decreased with elevation. We suggest that more labile organic matter left at high elevation could compensate for the increasing nutrient limitation at high elevation, resulting in no noticeable change in CUE with elevation.", "keywords": ["soil organic carbon", "Exoenzyme", "Carbon use efficiency", "FOS: Earth and related environmental sciences", "Stoichiometric modelling", "Elevational gradient"], "contacts": [{"organization": "Martin Vivanco, Angela Katherine, Sieti\u00f6, Outi-Maaria, Meyer, Nele, Mganga, Kevin, Kalu, Subin, Adamczyk, Sylwia, Celis, Susan, Alegre, Julio, Karhu, Kristiina,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.h70rxwdqs"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.h70rxwdqs", "name": "item", "description": "10.5061/dryad.h70rxwdqs", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.h70rxwdqs"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-18T00:00:00Z"}}, {"id": "10.5061/dryad.h70rxwdsm", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:07Z", "type": "Dataset", "created": "2024-06-01", "title": "Data from: Impacts of organic matter amendments on urban soil carbon and soil quality: A meta-analysis", "description": "unspecified# Organic Matter Impacts on Urban Soil Meta-Analysis [https://doi.org/10.5061/dryad.h70rxwdsm](https://doi.org/10.5061/dryad.h70rxwdsm) ## Description of the data and file structure This dataset (all the excel files) has information from almost 50 papers that research the use of organic matter amendments (compost, biochar, and biosolids) on urban soils until July of 2023. The focus data collected is soil carbon, nitrogen, phosphorus, potassium, bulk density, and pH. Other data includes sample size, sampling depth, years of application, application rate, type of urban environment, plant types, and publication information for each included study. The file 'Urban Amendments (Y or N) sheet' is the main data file. The has an extra column with a 'Yes' or 'No' depending on if organic matter amendment application occurred. A 'No'' indicates the control samples within studies. This includes data for all the soil properties included in the meta-analysis as well. The main data in included in the first tab titled 'General Info (C,N,BD) Sheet'. Comments are present to give context if unit conversions were made or data pulled from a paper was unclear. The second tab 'Heavy Metals Sheet'\u00a0 contains information on the impacts of organic matter amendments on heavy metals in soils. Data in this second tab was not used in the associated paper. The file 'Application Amount Mg per ha (1 or 0)' has all application rates given as %'s converted to Mg/ha of application (if the information needed for the conversion was available. The 1 indicates organic matter application occurred while a 0 indicates a control (no amending) sample. Data from the first excel file above in included in this data set as well. The file 'Spreadsheet Long and Lat for Urban Amendments' has the latitude and longitude values converted for use in GIS software for mapping. Most data from the first two excel files above in included in this data set as well, however, this file contains no comments for context on data. Missing data code: NA I welcome any inquiries at my email [zmalone@ucmerced.edu\u00a0.](mailto:zmalone@ucmerc.e) ## Sharing/Access information Data was derived from the following sources: * Papers found via searches on Google Scholar and Web of Science.\u00a0African Journals Online and Dialnet were also used for searching.", "keywords": ["Urban Soil", "meta-analysis", "compost", "Organic Matter Amendments", "FOS: Earth and related environmental sciences"], "contacts": [{"organization": "Malone, Zachary, Berhe, Asmeret, Ryals, Rebecca,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.h70rxwdsm"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.h70rxwdsm", "name": "item", "description": "10.5061/dryad.h70rxwdsm", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.h70rxwdsm"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-05T00:00:00Z"}}, {"id": "10.5061/dryad.ht76hdrnm", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-26T16:24:08Z", "type": "Dataset", "created": "2023-10-19", "title": "Data from: Abiotic legacies mediate plant-soil feedback during early vegetation succession on rare earth element mine tailings", "description": "Open AccessAn increasing number of studies have shown how feedback interactions between plants and soil can influence primary and secondary succession. However, very little is known about the patterns and mechanisms of such plant-soil feedbacks on stressed mine tailings ecosystem, which can be severely contaminated by a range of toxic elements.\u00a0 In a two-phase plant-soil feedback experiment based on the rare earth element (REE) mine tailing soil, we investigated biotic (changes in bacterial and fungal community) and abiotic legacies (changes in chemical properties) of three pioneer grass species, and examined feedback effects of three grasses, two legumes and two woody plants with different root traits. Positive plant-soil feedback was found in Miscanthus sinensis, Paspalum thunbergii and Tephrosia candida, and neutral feedback was observed in other four plants. These effects corresponded with an increase of nutrients and total organic carbon, as well as a decrease of acidity and extractable aluminum and REEs. There were less signs of biotic changes in the conditioned tailings.\u00a0 The correlation analysis suggested a relationship between responses to soil legacies and root traits, as well as root economics spectrum. On the mine tailings, acquisitive species with higher specific root length appeared to have greater potential for positive feedback.\u00a0 Synthesis and application: Our study shows that early succession on contaminated REE mine tailings may lead to more positive plant-soil feedback than predicted based on results of non-contaminated soils, mainly due to the alleviation of abiotic stress in tailings. Therefore, the improvement of specific abiotic soil stress and the trait-based selection of acquisitive plants should be preferentially considered to promote the primary restoration of degraded land.", "keywords": ["plant-soil feedback", "primary succession", "rare earth mine waste soil", "Trait-based approach", "root functional traits", "FOS: Earth and related environmental sciences", "soil legacies", "Ecological restoration"], "contacts": [{"organization": "Zhu, Shi Chen, Liu, Wen Shen, Chen, Zi Wu, Liu, Xiao Rui, Zheng, Hong Xiang, Chen, Bo Yu, Zhi, Xin Yu, Chao, Yuanqing, Qiu, Rong Liang, Chu, Chengjin, Liu, Chong, Morel, Jean Louis, van der Ent, Antony, Tang, Ye Tao,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.ht76hdrnm"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.ht76hdrnm", "name": "item", "description": "10.5061/dryad.ht76hdrnm", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.ht76hdrnm"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10.5061/dryad.j3tx95xk8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:08Z", "type": "Dataset", "title": "Patterns and determinants of plant-derived lignin phenols in coastal wetlands: implications for organic C accumulation", "description": "unspecifiedPlease see the README document\u00a0\u00a0('Lignin_content_and_monomer_composition.csv', 'Site_location.csv', 'Soil_organic_carbon_content.csv', 'Soil_properties.csv', 'Vegetation_and_climate.csv') and the accompanying published article: Shaopan Xia, Zhaoliang Song, Weiqi Wang, Yaran Fan, Laodong Guo, Lukas Van Zwieten, Iain P. Hartley, Yin Fang, Yidong Wang, Zhenqing Zhang, Cong-Qiang Liu, and Hailong Wang. 2023. Patterns and determinants of plant-derived lignin phenols in coastal wetlands: implications for organic C accumulation. Functional Ecology. Accepted. DOI: 10.5061/dryad.j3tx95xk8", "keywords": ["lignin biomarker", "salt marsh and mangrove", "13. Climate action", "plant-soil Interactions", "blue carbon", "organic C source apportionment", "14. Life underwater", "FOS: Earth and related environmental sciences", "15. Life on land", "6. Clean water"], "contacts": [{"organization": "Song, Zhaoliang, Xia, Shaopan, Wang, Weiqi, Fan, Yaran, Guo, Laodong, Van Zwieten, Lukas, Hartley, Iain P., Fang, Yin, Wang, Yidong, Zhang, Zhenqing, Liu, Cong-Qiang, Wang, Hailong,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.j3tx95xk8"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.j3tx95xk8", "name": "item", "description": "10.5061/dryad.j3tx95xk8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.j3tx95xk8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-02-02T00:00:00Z"}}, {"id": "10.5061/dryad.jm63xsj8p", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:08Z", "type": "Dataset", "title": "Meta-analysis of glucose tracing studies", "description": "unspecifiedA longstanding assumption of glucose tracing experiments is that all glucose is microbially utilized during short incubations of \u22642\u00a0days to become microbial biomass or carbon dioxide. Carbon use efficiency (CUE) estimates have consequently ignored the formation of residues (non-living microbial products) although such materials could represent an important sink of glucose that is prone to stabilization as soil organic matter. We examined the dynamics of microbial residue formation from a short tracer experiment with frequent samplings over 72\u00a0h, and conducted a meta-analysis of previously published glucose tracing studies to assess the generality of these experimental results. Both our experiment and meta-analysis indicated 30\u201334% of amended glucose-C (13C or\u00a014C) was in the form of residues within the first 6\u00a0h of substrate addition. We expand the conventional efficiency calculation to include residues in both the numerator and denominator of efficiency, thereby deriving a novel metric of the potential persistence of glucose-C in soil as living microbial biomass plus residues (\u2018carbon stabilization efficiency\u2019). This new metric indicates nearly 40% of amended glucose-C persists in soil 180\u00a0days after amendment, the majority as non-biomass residues. Starting microbial biomass and clay content emerge as critical factors that positively promote such long term stabilization of labile C. Rapid residue production supports the conclusion that non-growth maintenance activity can illicit high demands for C in soil, perhaps equaling that directed towards growth, and that residues may have an underestimated role in the cycling and sequestration potential of C in soil.", "keywords": ["2. Zero hunger", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Geyer, Kevin, Schnecker, Joerg, Grandy, Stuart, Richter, Andreas, Frey, Serita,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.jm63xsj8p"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.jm63xsj8p", "name": "item", "description": "10.5061/dryad.jm63xsj8p", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.jm63xsj8p"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-17T00:00:00Z"}}, {"id": "10.5061/dryad.ksn02v75n", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-06-26T16:24:09Z", "type": "Dataset", "title": "Tree identity and diversity directly affect soil moisture and temperature but not soil carbon ten years after planting", "description": "1. Soil C is the largest C pool in forest ecosystems that contributes to C sequestration and mitigates climate change. Tree diversity enhances forest productivity, so diversifying the tree species composition, notably in managed forests, could increase the quantity of organic matter being transferred to soils, and alter other soil properties relevant to the C cycle. 2. A ten-year-old tree diversity experiment was used to study the effects of tree identity and diversity (functional and taxonomic) on soils. Surface (0-10 cm) mineral soil was repeatedly measured for soil C concentration, C:N ratio, pH, moisture and temperature in twenty-four tree species mixtures and twelve corresponding monocultures (replicated in four blocks). 3. Soil pH, moisture and temperature responded to tree diversity and identity. Greater productivity in above- and below-ground tree components did not increase soil C concentration. Soil pH increased and soil moisture decreased with functional diversity, more specifically, when species had different growth strategies and shade tolerances. Functional identity affected soil moisture and temperature, such that tree communities with more slow-growing and shade-tolerant species had greater soil moisture and temperature. Higher temperature was measured in communities with broadleaf-deciduous species compared to communities with coniferous-evergreen species. 4. We conclude that long-term soil C cycling in forest plantations will likely respond to changes in soil pH, moisture and temperature that is mediated by tree species composition, since tree species affect these soil properties through their litter quality, water uptake and physical control of soil microclimates.", "keywords": ["FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Martin-Guay, Marc-Olivier, Belluau, Micha\u00ebl, C\u00f4t\u00e9, Beno\u00eet, Handa, Ira Tanya, Jewell, Mark, Khlifa, Rim, Munson, Alison, Rivest, Maxime, Whalen, Joann, Rivest, David,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.ksn02v75n"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.ksn02v75n", "name": "item", "description": "10.5061/dryad.ksn02v75n", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.ksn02v75n"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-08T00:00:00Z"}}, {"id": "10.5061/dryad.jwstqjqbs", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:08Z", "type": "Dataset", "title": "Data from: Positron-emitting radiotracers spatially resolve unexpected biogeochemical relationships linked with methane oxidation in Arctic soils", "description": "Arctic soils are marked by cryoturbic features, which impact soil-atmosphere methane (CH4) dynamics vital to global climate regulation. Cryoturbic diapirism alters C/N chemistry within frost boils by introducing soluble organic carbon and nutrients, potentially influencing microbial CH4\u00a0oxidation. CH4\u00a0oxidation in soils, however, requires a spatio-temporal convergence of ecological factors to occur. Spatial delineation of microbial activity with respect to these key microbial and biogeochemical factors at relevant scales is experimentally challenging in inherently complex and heterogeneous natural soil matrices. This work aims to overcome this barrier by spatially linking microbial CH4\u00a0oxidation with C/N chemistry and metagenomic characteristics. This is achieved by using positron-emitting radiotracers to visualize millimeter-scale active CH4\u00a0uptake areas in Arctic soils with and without diapirism. X-ray absorption spectroscopic speciation of active and inactive areas shows CH4\u00a0uptake spatially associates with greater proportions of inorganic N in diapiric frost boils. Metagenomic analyses reveal\u00a0Ralstonia pickettii\u00a0associates with CH4\u00a0uptake across soils along with pertinent CH4\u00a0and inorganic N metabolism associated genes. This study highlights the critical relationship between CH4 and N cycles in Arctic soils, with potential implications for better understanding future climate. Furthermore, our experimental framework presents a novel, widely applicable strategy for unraveling ecological relationships underlying greenhouse gas dynamics under global change.", "keywords": ["13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Schmidt, Michael, Mamet, Steven, Senger, Curtis, Schebel, Alixandra, Ota, Mitsuaki, Tian, Tony, Aziz, Umair, Stein, Lisa, Regier, Tom, Stanley, Kevin, Peak, Derek, Siciliano, Steven,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.jwstqjqbs"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.jwstqjqbs", "name": "item", "description": "10.5061/dryad.jwstqjqbs", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.jwstqjqbs"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-12T00:00:00Z"}}, {"id": "10.5061/dryad.k6djh9wdx", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:08Z", "type": "Dataset", "created": "2024-01-30", "title": "Fluxes and concentrations of dissolved organic carbon in soils", "description": "unspecifiedThe data were compiled from data in our study and those from published sources by searching for \u201cdissolved organic carbon\u201d, \u201csolute\u201d, \u201cflux\u201d, \u201cleaching\u201d, and \u201csoil\u201d in Google Scholar. We compiled the data of DOC fluxes in throughfall and soil profiles from 91 sites, of which the DOC flux data at 18 sites have been published by our group. The climate was classified into four groups [polar climate (MAT < 0 \u00baC), boreal climate (0 \u00baC < MAT < 6 \u00baC), temperate climate (6 \u00baC < MAT < 20 \u00baC), tropical climate (20 \u00baC < MAT)], based on mean annual air temperature. The other parameters include climatic properties [mean annual precipitation and mean annual air temperature], plant litter properties [litterfall C input, C/N ratio, Klason-lignin (residue after digestion with sulfuric acid; Allen et al., 1974), lignin/N ratio, root litter production] and soil properties [soil C stocks (O horizon and mineral soil (0-30 cm depth)), pH (water extraction), clay content, short-range-order (amorphous) aluminum (Al), iron (Fe) (acid ammonium oxalate extractable Al and Fe; McKeague and Day, 1966)]. The sampling and analytical methods are concisely summarized as follows: Throughfall (canopy leaching) samples were collected by precipitation collector, while soil solution samples were collected using tension-free lysimeters for downward flux of water percolating in the soil profiles. Sample solutions were filtered through a 0.45 \u00b5m filter (e.g., PTFE syringe filter) and stored at 1\u00b0C in the dark prior to analyses. The concentrations of DOC were determined using a total organic carbon and nitrogen analyzer (TOC-VCSH, Shimadzu, Japan). The dissolved organic nitrogen (DON) concentrations were calculated by subtracting dissolved inorganic nitrogen (sum of NH4+ and NO3-) from TDN concentrations (DON = TDN - NH4+ - NO3-) to obtain DOC/DON ratios in soil solution. The DOC flux at the depth of 0 cm (the bottom of organic layers) and the bottom of B horizon (the bottom of rooting zone) was estimated by multiplying DOC concentrations in soil solution and water fluxes at each depth. Soil water fluxes were estimated by hydrological models or precipitation-evapotranspiration water budgets. Annual root production was measured by ingrowth core method, net sheet method, or sequential sampling method and estimated to be equal to annual root litter inputs. Proportion of DOC flux from the O horizon relative to C input via both throughfall and litterfall was calculated by dividing DOC flux from the O horizon by C input via both throughfall and litterfall. DOC retention in the mineral soil was calculated as the percentage of net decrease in DOC flux between O and B horizons relative to DOC flux from the O horizon. The apparent turnover time (yr) of soil C was estimated by dividing soil C stocks (Mg C ha\u20131) by C inputs (net DOC inputs and root litter inputs into the mineral soil) (Mg C ha\u20131 yr\u20131).", "keywords": ["tropical forest", "FOS: Earth and related environmental sciences", "Soil pH", "dissolved organic carbon", "dissolved organic nitrogen"], "contacts": [{"organization": "Fujii, Kazumichi", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.k6djh9wdx"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.k6djh9wdx", "name": "item", "description": "10.5061/dryad.k6djh9wdx", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.k6djh9wdx"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-19T00:00:00Z"}}, {"id": "10.5061/dryad.m0cfxpp9w", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:09Z", "type": "Dataset", "created": "2024-01-03", "title": "Organo-organic interactions dominantly drive soil organic carbon accrual", "description": "unspecifiedOrgano-mineral interactions have been regarded as the primary mechanism for the stabilization of soil organic carbon (SOC) over decadal to millennial timescales, and the capacity for soil carbon (C) storage has commonly been assessed based on soil mineralogical attributes, particularly mineral surface availability. However, it remains contentious whether soil C sequestration is exclusively governed by mineral vacancies, making it challenging to accurately predict SOC dynamics. Here, through a 400-day incubation experiment using 13C-labeled organic materials in two contrasting soils (i.e., Mollisol and Ultisol), we show that despite the unsaturation of mineral surfaces in both soils, the newly incorporated C predominantly adheres to 'dirty' mineral surfaces coated with native organic matter (OM), demonstrating the crucial role of organo-organic interactions in exogenous C sequestration. Such interactions lead to multilayered C accumulation that is not constrained by mineral vacancies, a process distinct from direct organo-mineral contacts. The coverage of native OM by new C, representing the degree of organo-organic interactions, is noticeably larger in Ultisol (~14.2%) than in Mollisol (~5.8%), amounting to the net retention of exogenous C in Ultisol by 0.2\u20131.3 g kg\u22121 and in Mollisol by 0.1\u20131.0 g kg\u22121. Additionally, organo-organic interactions are primarily mediated by polysaccharide-rich microbial necromass. Further evidence indicates that iron oxides can selectively preserve polysaccharide compounds, thereby promoting the organo-organic interactions. Overall, our findings provide direct empirical evidence for an overlooked but critically important pathway of C accumulation, challenging the prevailing \u201cC saturation\u201d concept that emphasizes the overriding role of mineral vacancies. It is estimated that, through organo-organic interactions, global Mollisols and Ultisols might sequester ~0.1\u20131.0 Pg C and ~0.3\u20131.7 Pg C per year, respectively, corresponding to the neutralization of ca. 0.5%\u20133.0% of soil C emissions or 5%\u201330% of fossil fuel combustion globally.", "keywords": ["organo-organic interactions", "mineral-associated organic carbon", "SR-FTIR", "SOC accrual", "NanoSIMS", "FOS: Earth and related environmental sciences", "microbial necromass", "stable C isotope"], "contacts": [{"organization": "Kang, Jie, Qu, Chenchen, Chen, Wenli, Cai, Peng, Chen, Chengrong, Huang, Qiaoyun,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.m0cfxpp9w"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.m0cfxpp9w", "name": "item", "description": "10.5061/dryad.m0cfxpp9w", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.m0cfxpp9w"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-15T00:00:00Z"}}, {"id": "10.5061/dryad.m63xsj45g", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:09Z", "type": "Dataset", "title": "Plant litter chemistry controls coarse-textured soil carbon dynamics", "description": "unspecifiedThe data are archieved as a .csv text file.", "keywords": ["2. Zero hunger", "Decomposition", "Ecosystem function and services", "plant litter", "13. Climate action", "soil organic matter", "soil carbon storage", "Carbon cycle", "FOS: Earth and related environmental sciences", "15. Life on land", "Priming effect"], "contacts": [{"organization": "Huys, Raoul, Poirier, Vincent, Bourget, Malo, Roumet, Catherine, Hattenschwiler, Stephan, Fromin, Nathalie, Munson, Alison, Freschet, Gr\u00e9goire,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.m63xsj45g"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.m63xsj45g", "name": "item", "description": "10.5061/dryad.m63xsj45g", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.m63xsj45g"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-09-15T00:00:00Z"}}, {"id": "10.5061/dryad.mgqnk991r", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:09Z", "type": "Dataset", "title": "Increased precipitation and nitrogen addition accelerate the temporal increase of soil respiration during eight-year old-field grassland succession", "description": "Ecological succession after disturbance plays a vital role in influencing ecosystem structure and functioning. However, how global change factors regulate ecosystem carbon (C) cycling in successional plant communities remains largely elusive. As part of an eight-year (2012-2019) manipulative experiment, this study was designed to examine the responses of soil respiration and its heterotrophic component to simulated increases in precipitation and atmospheric nitrogen (N) deposition in an old-field grassland undergoing secondary succession. Over the eight-year experimental period, increased precipitation stimulated soil respiration by 11.6%, but did not affect soil heterotrophic respiration. Nitrogen addition increased both soil respiration (5.1%) and heterotrophic respiration (6.2%). Soil respiration and heterotrophic respiration linearly increased with time in the control plots, resulting from changes in soil moisture and shifts of plant community composition from grass-forb codominance to grass dominance in this old-field grassland. Compared to the control, increased precipitation significantly strengthened the temporal increase of soil respiration through stimulating belowground net primary productivity. By contrast, N addition accelerated temporal increases of both soil respiration and its heterotrophic component by driving plant community shifts and thus stimulating soil organic C. Our findings indicate that increases in water and N availabilities may accelerate soil C release during old-field grassland succession and reduce their potential positive impacts on soil C accumulation under future climate change scenarios.", "keywords": ["2. Zero hunger", "13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Zhang, Jiajia, Ru, Jingyi, Song, Jian, Li, Heng, Li, Xiaoming, Ma, Yafei, Li, Zheng, Hao, Yuanfang, Chi, Zhensheng, Hui, Dafeng, Wan, Shiqiang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.mgqnk991r"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.mgqnk991r", "name": "item", "description": "10.5061/dryad.mgqnk991r", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.mgqnk991r"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-29T00:00:00Z"}}, {"id": "10.5061/dryad.np5hqc016", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:09Z", "type": "Dataset", "created": "2023-12-08", "title": "Protists regulate microbially-mediated organic carbon turnover in soil aggregates", "description": "unspecifiedSoil protists, the major predator of bacteria and fungi, shape the taxonomic and functional structure of soil microbiome via trophic regulation. However, how trophic interactions between protists and their prey influence microbially mediated soil organic carbon turnover remains largely unknown. Here, we investigated the protistan communities and microbial trophic interactions across different aggregates-size fractions in agricultural soil with long-term fertilization regimes. Our results showed that aggregate sizes significantly influenced the protistan community and microbial hierarchical interactions. Bacterivores were the predominant protistan functional group and were more abundant in macroaggregates and silt + clay than in microaggregates, while omnivores showed an opposite distribution pattern. Furthermore, partial least square path modeling revealed positive impacts of omnivores on the C-decomposition genes and soil organic matter (SOM) contents, while bacterivores displayed negative impacts. Microbial trophic interactions were intensive in macroaggregates and silt + clay but were restricted in microaggregates, as indicated by the intensity of protistan-bacterial associations and network complexity and connectivity. Cercozoan taxa were consistently identified as the keystone species in SOM degradation-related ecological clusters in macroaggregates and silt + clay, indicating the critical roles of protists in SOM degradation by regulating bacterial and fungal taxa. Chemical fertilization had a positive effect on soil C sequestration through suppressing SOM degradation-related ecological clusters in macroaggregate and silt + clay. Conversely, the associations between the trophic interactions and SOM contents were decoupled in microaggregates, suggesting limited microbial contributions to SOM turnovers. Our study demonstrates the importance of protists-driven trophic interactions on soil C cycling in agricultural ecosystems.", "keywords": ["soil aggregates", "Soil protists", "FOS: Earth and related environmental sciences", "carbon cycling", "Trophic interactions"], "contacts": [{"organization": "Liao, Hao, Hao, Xiuli, Li, Yiting, Ma, Silin, Gao, Shenghan, Cai, Peng, Chen, Wenli, Huang, Qiaoyun,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.np5hqc016"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.np5hqc016", "name": "item", "description": "10.5061/dryad.np5hqc016", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.np5hqc016"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-22T00:00:00Z"}}, {"id": "10.5061/dryad.ns1rn8prv", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:09Z", "type": "Dataset", "title": "Root and chemical traits", "description": "Many studies have quantified the functional variation of fine root traits to understand the overarching trade-off between maximizing resource acquisition or conservation (root economics spectrum -RES-). However, we know remarkably less on how plant strategies along the RES are actually constrained by the amount of photosynthates required to construct roots (i.e. construction costs, CC) or how belowground interactions with symbiotic organisms modify root trait patterns and their relationships with CC. Our main aim was to quantify CC of fine roots (<2 mm) and their underlying components (carbon, minerals and organic nitrogen concentrations) in 60 Mediterranean woody species with contrasting symbiotic association types (ectomycorrhizas, arbuscular and ericoid mycorrhizas and N-fixing bacteria). We examined (1) if the covariation among fine root traits along the RES was related to the intrinsic cost of producing roots and if this relationship was dependent on the type of root symbiosis; (2) if the relationship of each CC component with the RES was dependent on the type of root symbiosis; and (3) whether soil water and nutrient availability determined differences in CC across sites. According to the RES hypothesis, fine root traits showed a main covariation trend (acquisition vs. conservation), defined by the first PCA axis, which also segregated species by their two main contrasting symbiotic types (arbuscular and ectomycorrhizal). We found a positive relationship between root CC and the RES (i.e. PCA axis 1) and, interestingly, slopes differed among symbiotic types, in response to the different role of each specific CC component. In addition, independently of symbiotic type, root CC decreased linearly with soil nutrient availability and quadratically with plant water availability. Synthesis. Our study demonstrates that woody plants display different functional strategies in their root CC, related with their position on the RES, and that CC differ among symbiotic groups. The influence of the root CC components across species varied among symbiotic associations, pointing to a trade-off between structural and metabolic compounds. Root CC were also strongly modulated by soil resource availability (nutrients and water). This study highlights that root CC are fundamental to better understand belowground resource use strategies.", "keywords": ["2. Zero hunger", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "G. de la Riva, Enrique", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.ns1rn8prv"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.ns1rn8prv", "name": "item", "description": "10.5061/dryad.ns1rn8prv", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.ns1rn8prv"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-09T00:00:00Z"}}, {"id": "10.5061/dryad.qjq2bvqkn", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:10Z", "type": "Dataset", "title": "The contribution of Fe(III) reduction to soil carbon mineralization in montane meadows depends on soil chemistry, not parent material or microbial community", "description": "The long-term stability of soil carbon (C) is strongly influenced by organo-mineral interactions.\u00a0Iron (Fe)-oxides can both inhibit microbial decomposition by providing physicochemical protection for organic molecules and enhance rates of C mineralization by serving as a terminal electron acceptor, depending on redox conditions. Restoration of floodplain hydrology in montane meadows has been proposed as a method of sequestering C for climate change mitigation. However, dissimilatory microbial reduction of Fe(III) could lead to C losses under increased reducing conditions. In this study, we explored variations in Fe-C interactions over a range of redox conditions and in soils derived from two distinct parent materials to elucidate biochemical and microbial controls on soil C cycling in Sierra Nevada montane meadows. Differences in parent material were associated with different rates of Fe(III) reduction at increasing soil moisture levels, but not with differences in soil C mineralization. Known Fe(III)-reducing taxa were present in all samples but neither the relative abundance nor richness of Fe(III) reducers corresponded with measured rates of Fe(III) reduction. Under reducing conditions, our results suggest that Fe(III) reduction contributes to C mineralization only when Fe-bound C is present. However, Fe-bound C was not present in all of our soils and was below theoretical limits for C sorption onto Fe-oxides where it was found. Overall, our results suggest that meadow-specific soil chemistry drives Fe-C interactions and that the impact of Fe on C cycling in montane meadows may be smaller than in other ecosystems.", "keywords": ["montane meadows", "13. Climate action", "Wetlands", "meadow restoration", "Iron reduction", "FOS: Earth and related environmental sciences", "biogeochemical cycles", "Carbon cycle", "15. Life on land"], "contacts": [{"organization": "Reed, Cody C., Dunham\u2010Cheatham, Sarrah M., Castle, Sarah C., Vuono, David C., Sullivan, Benjamin W.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.qjq2bvqkn"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.qjq2bvqkn", "name": "item", "description": "10.5061/dryad.qjq2bvqkn", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.qjq2bvqkn"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-05-11T00:00:00Z"}}, {"id": "10.5061/dryad.qz612jmnx", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:10Z", "type": "Dataset", "created": "2023-10-30", "title": "Hot spots and hot moments of greenhouse gas emissions in agricultural peatlands", "description": "unspecified# Hot spots and hot moments of greenhouse gas emissions in agricultural peatlands [https://doi.org/10.5061/dryad.qz612jmnx](https://doi.org/10.5061/dryad.qz612jmnx)
2017-2021 Automated chamber (Eosense eosAC) and Picarro G2508 GHG analyzer flux data for CO2, CH4, and N2O from corn, pasture, and alfalfa, and 2018-2021 continuous soil sensing data (oxygen, moisture, and temperature) from corn and alfalfa ## Description of the data and file structure Alfalfa _Chamber, Corn _chamber, and Pasture _chamber flux data tab: Alfalfa: Continuous soil flux measurements from January 2017-February 2021 Corn: Continuous soil flux measurements from July 2017-October 2021 Pasture: Continuous soil flux measurements from April 2019-July 2022 * Chamber * ChamberPressure (kPa) * ChamberTemperature (K) * CO2 flux: CO2 _umol/m2/s * CH4 flux: CH4 _nmol/m2/s * N2O flux: N2O _nmol/m2/s * Site Year Alfalfa, Corn, Soil Sensor Data tab: Measurements at 10, 30, and 50 cm soil depths from October 2018-February 2021 * Temp = Temperature in Celsius * VWC= volumetric water content in m3/m3 * O2 = Oxygen concentration in % * TIMESTAMP: Date and Time * Temp _10cm (C) * Temp _30cm (C) * Temp _50cm (C) * VWC _10cm (m3/m3) * VWC _30cm (m3/m3) * VWC _50cm (m3/m3) * O2 _10cm (%) * O2 _30cm (%) * O2 _50cm (%) NEE: Net Ecosystem Exchange (\u00b5molCO2 m-2 s-1) data can be found in Ameriflux datasets available at URLs below ## Sharing/Access information Links to other publicly accessible locations of the data: Was data derived from another source? All Eddy covariance data (Net Ecosystem Exchange (NEE)) from Ameriflux tower sites. If yes, list source(s): https://ameriflux.lbl.gov/sites/siteinfo/US-Bi1 https://ameriflux.lbl.gov/sites/siteinfo/US-Bi1 https://ameriflux.lbl.gov/sites/siteinfo/US-Snf", "keywords": ["2. Zero hunger", "nitrous oxide", "hot moments", "greenhouse gas fluxes", "FOS: Earth and related environmental sciences", "15. Life on land", "12. Responsible consumption", "hot spots", "agricultural peatlands", "Carbon dioxide", "13. Climate action", "11. Sustainability", "soil fluxes", "Methane", "peatlands"], "contacts": [{"organization": "Anthony, Tyler", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.qz612jmnx"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.qz612jmnx", "name": "item", "description": "10.5061/dryad.qz612jmnx", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.qz612jmnx"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-11-06T00:00:00Z"}}, {"id": "10.5061/dryad.rn8pk0p73", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:11Z", "type": "Dataset", "title": "Effects of plant functional group removal on CO2 fluxes and belowground C stocks across contrasting ecosystems", "description": "Changes in plant communities can have large effects on ecosystem carbon (C) dynamics and long-term C stocks. However, how these effects are mediated by environmental context or vary among ecosystems is not well understood. To study this, we used a long-term plant removal experiment set up across 30 forested lake islands in northern Sweden which collectively represent a strong gradient of soil fertility and ecosystem productivity. We measured forest floor CO2 exchange and aboveground and belowground C stocks for a 22-year experiment involving factorial removal of the two dominant functional groups of the boreal forest understory, namely ericaceous dwarf shrubs and feather mosses, on each of the 30 islands. We found that long-term shrub and moss removal increased forest floor net CO2 loss and decreased belowground C stocks consistently across the islands irrespective of their productivity or soil fertility. However, we did see context-dependent responses of respiration to shrub removals because removals only increased respiration on islands of intermediate productivity. Both CO2 exchange and C stocks responded more strongly to shrub removal than to moss removal. Shrub removal reduced gross primary productivity of the forest floor consistently across the island gradient, but it had no effect on respiration, which suggests that loss of belowground C caused by the removals was driven by reduced litter inputs. Across the island gradient, shrub removal consistently depleted C stocks in the soil organic horizon by 0.8 kg C m-2. Our results show that the effect of plant functional group diversity on C dynamics can be relatively consistent across contrasting ecosystems that vary greatly in productivity and soil fertility. These findings underline the key role of understory vegetation in forest C cycling, and suggest that global change leading to changes in the relative abundance of both shrubs and mosses could impact on the capacity of boreal forests to store C.", "keywords": ["2. Zero hunger", "13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5061/dryad.rn8pk0p73"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.rn8pk0p73", "name": "item", "description": "10.5061/dryad.rn8pk0p73", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.rn8pk0p73"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-05T00:00:00Z"}}, {"id": "10.5061/dryad.t3k2t2j", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:11Z", "type": "Dataset", "created": "2023-08-17", "title": "Data from: Fate of atmospherically deposited NH4+ and NO3- in two temperate forests in China: temporal pattern and redistribution", "description": "The impacts of anthropogenic nitrogen (N) deposition on forest ecosystems depend in large part on its fate. However, our understanding of the fates of different forms of deposited N as well as the redistribution over time within different ecosystems is limited. In this study, we used the 15N-tracer method to investigate both the short-term (1 week to 3 months) and long-term (1 to 3 years) fates of deposited NH4+ or NO3- by following the recovery of the 15N in different ecosystem compartments in a larch plantation forest and a mixed forest located in northeastern China. The results showed similar total ecosystem retention for deposited NH4+ and NO3-, but their distribution within the ecosystems (plants vs soil) differed distinctly particularly in the short-term, with higher 5NO3- recoveries in plants (while lower recoveries in organic layer) than found for 15NH4+. The different short-term fate was likely related to the higher mobility of 15NO3- than 15NH4+ in soils instead of plant uptake preferences for NO3- over NH4+. In the long-term, differences between N forms became less prevalent but higher recoveries in trees (particularly in the larch forest) of\u00a015NO3- than 15NH4+ tracer persisted, suggesting that incoming NO3- may contribute more to plant biomass increment and forest carbon sequestration than incoming NH4+. Differences between the two forests in recoveries were largely driven by a higher 15N recovery in the organic layer (both N forms) and in trees (for 5NO3-) in the larch forest compared to the mixed forest. This was due to a more abundant organic layer and possibly higher tree N demand in the larch forest than in the mixed forest. Leachate 15N loss was minor (<1% of the added 15N) for both N forms and in both forests. Total 15N recovery averaged 78% in the short-term and decreased to 55% in the long-term but with increasing amount of 15N label (re)-redistributed into slow turn-over pools (e.g., trees and mineral soil). The different retention dynamics of deposited NH4+ and NO3- may have implications in environmental policy related to the anthropogenic emissions of the two N forms.", "keywords": ["15N tracer", "N retention and redistribution", "FOS: Earth and related environmental sciences", "15. Life on land"]}, "links": [{"href": "https://doi.org/10.5061/dryad.t3k2t2j"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.t3k2t2j", "name": "item", "description": "10.5061/dryad.t3k2t2j", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.t3k2t2j"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-26T00:00:00Z"}}, {"id": "10.5061/dryad.t4b8gtj2p", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:11Z", "type": "Dataset", "title": "Soil respiration in a successional tropical forest in Thailand", "description": "unspecifiedWe made the measurements in the wet season (June and September 2020) and in the dry season measurements (February and March 2021); hereafter described as \u2018wet season\u2019 and \u2018dry season\u2019, respectively. In each forest stage, we established a 1-ha plot and divided it into 20\u00d720 m subplots as shown in Figure A2. Then, we randomly selected six sampling points within the 1-ha plot and measured all study variables concurrently at each point during 1000\u20131500 h on sunny days. For SR, we used a portable photosynthesis system (TARGAS-1, PP Systems, Amesbury, MA, USA) connected to a soil respiration chamber (SRC-2 Soil Respiration Chamber, PP Systems, Amesbury, MA, USA). In this process, the SR rate, measured in g CO2 m\u22122 h\u22121, was calculated by measuring the rate of increase of CO2 concentration in the chamber over a period which was set to 60 seconds. Before taking measurements, we installed a soil collar, whose cross-sectional area was 78 cm2, on each selected sampling point at 5-cm depth in the soil, leaving it for at least one hour prior to the SR measurement. Before putting the soil respiration chamber on the soil collar, we removed small living plants and coarse litter from the soil surface within the collar to avoid measuring their respiration (Zhou et al., 2007; Peng et al., 2014). Simultaneously, ST was measured using a probe (STP-2 Soil Temperature Probe, PP Systems, Amesbury, MA, USA) at 10-cm depth near the soil collar. Soil moisture was measured at 5-cm depth from the soil surface using a probe (SM150T, DeltaT Devices, London, UK). For each sampling point, all measurements of SR, ST and SM were repeated three times and then averaged to represent each sampling point. For the soil analyses, we collected three 3.2-cm diameter soil core samples from each study plot at 10-cm soil depth in the wet season (September 2020) and the dry season (February 2021). We used a total organic carbon analyzer (Multi N/C 3100, Analytik Jena) to obtain OM values.", "keywords": ["13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Tor-ngern, Pantana, Rodtassana, Chadtip, Unawong, Weerapong, Yaemphum, Siriphong, Chanthorn, Wirong, Chawchai, Sakonvan, Nathalang, Anuttara, Brockelman, Warren,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.t4b8gtj2p"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.t4b8gtj2p", "name": "item", "description": "10.5061/dryad.t4b8gtj2p", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.t4b8gtj2p"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-08-03T00:00:00Z"}}, {"id": "10.5061/dryad.t4b8gtj8d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:11Z", "type": "Dataset", "created": "2024-02-07", "title": "Data for: Male, female and mixed-sex poplar plantations support divergent soil microbial communities", "description": "unspecifiedMixed-species forests are often more productive than monocultures because of a lower niche overlap and higher taxonomic and functional diversity of soil microbial communities. Males and females of dioecious plants have sex-specific adaptations to diverse habitats. The potential of using sexual differences in establishing more diverse poplar plantations has not been explored in degraded areas. We conducted a series of greenhouse and field experiments to investigate how belowground competition, soil microbial communities and seasonal variation nitrogen content differ among female, male and mixed-sex Populus cathayana plantations. In the greenhouse experiment, female neighbors suppressed the growth of males under optimal nitrogen conditions. However, male neighbors enhanced \u03b415N of females under inter-sexual competition. In the field, the root length density, root area density and biomass of fine roots were lower in female plantations than in male or mixed-sex plantations. Bacterial networks of female, male and mixed-sex plantations were characterized by different composition of hub nodes, including connectors, module and network hubs. The sex composition of plantations altered bacterial and fungal community structures according to Bray-Curtis distances, with 44% and 65% of variance explained by the root biomass, respectively. The total soil nitrogen content of mixed-sex plantation was higher than that in female plantation in spring and summer. The mixed-sex plantation also had a higher \u03b2-1,4-N-acetyl-glucosaminidase activity in summer and a higher nitrification rate in autumn than the other two plantations. The seasonal soil N content, nitrification rate and root distribution traits demonstrated spatiotemporal niche separation in the mixed-sex plantation. We argue that a strong female-female competition and limited nitrogen content could strongly impede plant growth and reduce the resistance of monosex plantations to climate change and the mixed-sex plantations constitutes a promising way to restore degraded land.", "keywords": ["belowground competition", "plant-microbe interactions", "neighbor sexual identity", "FOS: Earth and related environmental sciences", "microbiota assembly", "dioecious species"], "contacts": [{"organization": "Guo, Qingxue", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.t4b8gtj8d"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.t4b8gtj8d", "name": "item", "description": "10.5061/dryad.t4b8gtj8d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.t4b8gtj8d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-02-23T00:00:00Z"}}, {"id": "10.5061/dryad.v6wwpzh2j", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:12Z", "type": "Dataset", "created": "2023-09-07", "title": "Data from: Unravelling large-scale patterns and drivers of biodiversity in dry rivers", "description": "unspecified# Data from: Unravelling large-scale patterns and drivers of biodiversity in dry rivers [https://doi.org/10.5061/dryad.v6wwpzh2j](https://doi.org/10.5061/dryad.v6wwpzh2j) Sediment samples were collected by an international consortium ([http://1000_intermittent_rivers_project.irstea.fr](http://1000_intermittent_rivers_project.irstea.fr)) following a standardized protocol during dry phases in the years 2015-2016. We conducted a metabarcoding approach on environmental DNA targeting multiple taxa (i.e. Archaea, Bacteria, Fungi, Algae, Protozoa, Nematoda, Arthropoda and Streptophyta). ## Description of the data and file structure * DRIME_bact02.filtered.uniq.fasta : de-replicated and de-multiplexed sequencing data for the barcode Bact02 targetting Bacteria and Archaea * Metabarcoding DRIME workflow Bact02.Rmd : R markdown file describing the bioinformatic processing and the statistical analyses conducted on the Bact02 barcode * bact_OTU_097_DRIME_agg_ORDER.txt : curated OTU table obtained for the Bact02 barcode * CLASSIFICATION_clean_trimmed.txt : taxonomic assignation of Bact02 OTUs * environment_DRIME_ORDER_Bact02_NC.txt : environmental data used in statistical analyses for the Bact02 barcode Euka02 : folder for the barcode Euka02 targetting Eukaryotes * DRIME_euka2.filtered.uniq.fasta : de-replicated and de-multiplexed sequencing data for the barcode Euka02 targetting Eukaryotes * Metabarcoding DRIME workflow Euka02.Rmd : R markdown file describing the bioinformatic processing and the statistical analyses conducted on the Euka02 barcode * euka_OTU_097_DRIME_agg_ORDER.txt : curated OTU table obtained for the Euka02 barcode * CLASSIFICATION_clean_curated.txt : taxonomic assignation of Euka02 OTUs * environment_DRIME_ORDER_Euka02_NC.txt : environmental data used in statistical analyses for the Euka02 barcode * environmental_variables_description.xlsx: environmental data name, description and units ## Code/Software Code can be run using the OBITools software package and R.", "keywords": ["metabarcoding", "FOS: Earth and related environmental sciences", "Biodiversity", "eDNA", "intermittent rivers"], "contacts": [{"organization": "Foulquier, Arnaud", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.v6wwpzh2j"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.v6wwpzh2j", "name": "item", "description": "10.5061/dryad.v6wwpzh2j", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.v6wwpzh2j"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-05T00:00:00Z"}}, {"id": "10.5061/dryad.wpzgmsbq8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:12Z", "type": "Dataset", "title": "Data from: Global warming intensity of biofuel derived from switchgrass grown on marginal land in Michigan", "description": "Energy crops for biofuel production, especially switchgrass (Panicum virgatum), are of interest from a climate change perspective. Here, we use outputs from a crop growth model and life cycle assessment (LCA) to examine the global warming intensity (GWI; g CO2 MJ-1) and greenhouse gas (GHG) mitigation potential (Mg CO2 year-1) of biofuel systems based on a spatially explicit analysis of switchgrass grown on marginal land (abandoned former cropland) in Michigan, USA. We find that marginal lands in Michigan can annually produce over 0.57 hm3 of liquid biofuel derived from nitrogen-fertilized switchgrass, mitigating 1.2-1.5 Tg of CO2 per year.\u00a0 About 96% of these biofuels can meet the Renewable Fuel Standard (60% reduction in lifecycle GHG emissions compared with conventional gasoline; GWI \u2264 37.2 g CO2 MJ-1). Furthermore, 73-75% of these biofuels are carbon-negative (GWI less than zero) due to enhanced soil organic carbon (SOC) sequestration. However, simulations indicate that SOC levels would fail to increase and even decrease on the 11% of lands where SOC stocks >> 200 Mg C ha-1, leading to carbon intensities greater than gasoline. Results highlight the strong climate mitigation potential of switchgrass grown on marginal lands as well as the needs to avoid carbon rich soils such as histosols and wetlands and to ensure that productivity will be sufficient to provide net mitigation.", "keywords": ["2. Zero hunger", "13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land", "7. Clean energy"], "contacts": [{"organization": "Kim, Seungdo, Dale, Bruce, Martinez-Feria, Rafael, Basso, Bruno, Thelen, Kurt, Maravelias, Christos, Landis, Douglas, Lark, Tyler, Robertson, G. Philip,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.wpzgmsbq8"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.wpzgmsbq8", "name": "item", "description": "10.5061/dryad.wpzgmsbq8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.wpzgmsbq8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-04T00:00:00Z"}}, {"id": "10.5061/dryad.wpzgmsbtq", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:12Z", "type": "Dataset", "created": "2023-10-05", "title": "Data from: Integrating variation in bacterial-fungal co-occurrence network with soil carbon dynamics", "description": "unspecifiedThe experimental site is located in the state-owned Daguishan Forest Farm in Hezhou City, Guangxi Zhuang Autonomous Region, China (111\u00b020\u20195\u2019\u2019E, 23\u00b058\u201933\u2019\u2019N). The mean annual temperature in this area is 19.3\u2103, with mean annual precipitation and evaporation of 2,056 mm and 1,200 mm, respectively. The soil type is classified as red soil (i.e., ferralsols). A total of 12 plots (20 m wide \u00d7 30 m long) were established to collect soil samples in\u00a0triplicate representing four generations of Eucalyptus plantation. In each treatment, the Eucalyptus trees were at the same stage of development (i.e., 4 years after planting). The treatments included the first generation (PrG) of Eucalyptus reforestation, the second generation (SeG) regenerating after the PrG was cut, the third generation (ThG) regenerating after the SeG, and the fourth generation (FoG) regenerating after the ThG. An evergreen broadleaf forest with three adjacent plots was selected as the control (CK), which was a\u00a0precursor to the Eucalyptus plantation. All the plots were located within a 5 km2 area. The Eucalyptus species planted in these plots was a hybrid of Eucalyptus urophylla S.T. Blake \u00d7 Eucalyptus grandis Hill ex Maiden (Eucalyptus urograndis).", "keywords": ["total bacterial diversity", "soil enzymatic activities", "bacterial-fungal associations", "13. Climate action", "carbon mineralization", "SparCC network", "FOS: Earth and related environmental sciences", "15. Life on land", "Successive planting of Eucalyptus", "keystone bacterial diversity"], "contacts": [{"organization": "Chen, Lijun, Dini-Andreote, Francisco, Liu, Hongqiang, Wang, Huaxiang, Dumbrell, Alex, Wang, Zhengye, Chen, Xingyu, Chen, Fangfang, Chen, Xiaolong, Wu, Lichao, Jiang, Yuji,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.wpzgmsbtq"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.wpzgmsbtq", "name": "item", "description": "10.5061/dryad.wpzgmsbtq", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.wpzgmsbtq"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-10-11T00:00:00Z"}}, {"id": "10.5061/dryad.x95x69psf", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:12Z", "type": "Dataset", "created": "2024-03-11", "title": "Effects of biochar soil amendments on soil properties and plant recruitment in coastal climate change adaptation projects", "description": "unspecified# Effects of biochar soil amendments on soil properties and restoration success in coastal climate change adaptation projects [https://doi.org/10.5061/dryad.x95x69psf](https://doi.org/10.5061/dryad.x95x69psf) ### There are five files uploaded as part of this data release: 1. landscape_vegetation.csv - this file details the plant cover derived from drone imagery analysis in 2018-2023 in the landscape scale plots constructed at the Elkhorn Slough National Estuarine Research Reserve. 2. landscape_soil.csv - this file details soil analysis for soils collected in summer 2022 from landscape scale plots. 3. plot_vegetation.csv - this file details the plant cover derived from point-intercept field surveys conducted at Elkhorn Slough National Estuarine Research Reserve, Waquoit Bay National Estuarine Research Reserve, and Prudence Island National Estuarine Research Reserve in November of 2017, September of 2018, March of 2019, August of 2019, and August of 2020. 4. plot_soil.csv - this file details soil analysis for soils collected in March 2019 from small (0.7m x 0.7m) sediment addition plots. 5. particle_size.csv - this file details outputs of grain size analysis for the biochar amended plots for the landscape scale experiment. ## Description of the data and file structure **landscape_vegetation.csv** - This file contains seven fields: site, code, soil, treatment, amendment, date, plant_cover_fraction. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field soil refers to one of four soil types: hester_soil, which refers to the type of the sediment used in the whole 50-ha restoration, 50_50_mix, a 50:50 mix of granite fines with the restoration sediment, capped_fines a mixture of granite fines capped with restoration soil, or granite_fines alone, which is just granite fines. The field treatment refers to one of four treatments: reference, biochar, fines, or mix, where reference is the same sediment as the rest of the restoration, biochar refers to restoration soil mixed with biochar, fines refers to one of types of granite fine amended soils (see field soil), and mix refers to a mix of granite fine amended soils and biochar. The field amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. The date refers to the date of the drone flight in YYYY-MM-DD format. The plant_cover_fraction refers to the area of the drone image that had plant cover. **landscape_soil.csv** - This file contains 24 fields, including analysis, site, code, replicate, old-Bag-code, new-Bag-code, plant, amendment, plant_cover, LOI, bulk_density, water_fraction, salinity, pH, redox, KCl_NH4, KCl_NO3, D50, sand_frct, mud_frct, silt_frct, clay_frct, sand_fines, CH4_flux_s, CH4_flux_h, CO2_flux. The field analysis refers to one of two codes: GHG or soil, where GHG refers to greenhouse gas flux measures, and soil refers to soil analysis measures. These measures were not taken at the same exact locations and had different numbers of replicates per plot. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field replicate refers to, where multiple measures are taken in one plot, the replicate number (1 or 2). The field old-Bag-code refers to the code written on the bag. The field new-Bag-code refers to the code which should have been written on the bag. The field plant, may be of two values, 0 or 1, where the value is 1 if the soil was collected beneath a plant or bare soil. The field amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. The field plant_cover refers to field estimated plant cover in the plot, with values from 0-100. The field LOI refers to the organic content of the sediment, as a fraction (0-1). The field bulk_density refers to the bulk density of the soil sample, in g/cc. The field water_fraction is the fraction of the field moist sample that is water. The field salinity is the salinity of the sample, in ppt. The field ORP is redox of the soil sample in mV. The field pH is the pH of the sample on a 1:1 soil to water mix. The field KCl_NH4 is ammonium concentration of KCL extraction (uM / g dry sed). The field KCl_NO3 refers to nitrate concentrations of KCL extraction (uM / g dry sed). The field D50 refers to the median particle size diameter of the sample in micrometers. The field sand_frct refers to the fraction of the sample that is sand (0-1). The field mud_frct refers to the fraction of the sample that is mud (silt and clay) (0-1). The field silt_frct refers to the fraction of the sample that is silt (0-1). The field clay_frct refers to the fraction of the sample that is clay (0-1). The field sand_fines refers to the ratio of sand to mud (silt and clay). The field CH4_flux_s refers to methane emissions (CH4 flux) (in dark flux chambers) in uM/m^2/second. The field CH4_flux_h refers to methane emissions (CH4 flux) (in dark flux chambers) in uM/m2/hour. The field CO2 is soil respiration (CO2 flux) (in dark flux chambers) in uM/m^2/s. Missing data is coded -999. **plot_vegetation.csv** - This file contains eight fields: NERR_code, elevation, plot, treatment, name, cover, date, and time stamp. The NERR_code refers to which site the data was collected at: one of three codes, ELK for Elkhorn Slough, NAR, for Prudence Island, and WQB for Sage Lot Pond, Waquoit Bay. The field elevation is either high or low, as there were five high elevation plots per treatment and five low elevation plots per treatment. The field plot refers to the code of the plot (A, B, C, D, E), or which replicate it is. The field treatment lists one of four treatments: control (a paired plot that received no sediment), reference (a paired plot with high plant cover; the restoration target), 14 (14cm of sediment added) and biochar (14cm of sediment added with 10% biochar admixture). The field name is the plot name that includes the plot, elevation and treatment, H or L for high or low, A, B, C, D, or E for plot, and a code for treatment: 14 cm (14), 14 cm of sediment with biochar (b) reference (R), control (C). The field cover is the percent of the plot that had vegetation cover, with values 0-100. The field date is the date the measure was taken in MM/DD/YEAR. The field timestamp refers to when the measure was taken, before the sediment was added (pre_sediment), during the first year (year1_fall), in the second year during spring (year2_spring), during the second year during fall (year2_fall), and during the third year during fall (year3_fall). Missing data for reference plots is coded -999. **plot_soil.csv** - This file contains 14 fields: NERR_code, date,\u00a0 elevation, \u00a0plot, treatment, name, bulk_density, water_fraction, salinity, ORP, pH, NH4, CO2, vegetation_cover. The NERR_code refers to which site the data was collected at: one of three codes, ELK for Elkhorn Slough, NAR, for Prudence Island, and WQB for Sage Lot Pond, Waquoit Bay. The field date is the date the measure was taken in MM/DD/YEAR. The field elevation is either high or low, as there were five high elevation plots per treatment and five low elevation plots per treatment. The field plot refers to the code of the plot (A, B, C, D, E), or which replicate it is. The field treatment lists one of four treatments: control (a paired plot that received no sediment), reference (a paired plot with high plant cover; the restoration target), 14 (14cm of sediment added) and biochar (14cm of sediment added with 10% biochar admixture). The field name is the plot name that includes the plot, elevation and treatment, H or L for high or low, A, B, C, D, or E for plot, and a code for treatment: 14 cm (14), 14 cm of sediment with biochar (b) reference (R), control (C). The field bulk_density is the bulk density of the soil sample, in g/cc. The field water_fraction is the fraction of the field moist sample that is water. The field salinity is the salinity of the sample, in ppt. The field ORP is redox of the soil sample in mV. The field pH is the pH of the sample on a 1:1 soil to water mix. The field NH4 is ammonium concentration of KCL extraction (uM / g dry sed). The field CO2 is soil respiration (CO2 flux) (in dark flux chambers) in uM/m^2/s. The field vegetation_cover is the year 3 vegetation cover on plots, on a scale of 0-100. The missing or uncollected data is coded -999. **particle_size.csv** - This file has 125 fields, including project, site, code, replicate, old-Bag-code, new-Bag-code, amendment, and 117 codes that reflect particle size bins. The field project has two potential values, landscape or plot. The field site refers to which plot was sampled, 1, 2, or 3, where 1 refers to the northernmost series of plots, 2 refers to the middle series of plots, and 3 is the southernmost series of plots. The field code refers to A, B, or C, where A is the series of plots on the left facing south, B refers to the center series of plot facing south, and C is the right series plot facing south. The field replicate refers to, where multiple measures are taken in one plot, the replicate number (1 or 2). The field old-Bag-code refers to the code written on the bag. The field new-Bag-code refers to the code which should have been written on the bag. The field soil amendment refers one of two values, biochar or none, representing biochar amendments or no amendments. These bins include the following: 0.040\u00a0 0.044\u00a0\u00a0 0.048\u00a0\u00a0 0.053\u00a0\u00a0 0.058\u00a0\u00a0 0.064\u00a0\u00a0 0.070\u00a0\u00a0 0.077\u00a0\u00a0 0.084\u00a0\u00a0 0.093\u00a0\u00a0 0.102\u00a0\u00a0 0.112\u00a0\u00a0 0.122\u00a0\u00a0 0.134\u00a0\u00a0 0.148\u00a0\u00a0 0.162\u00a0\u00a0 0.178\u00a0\u00a0 0.195\u00a0\u00a0 0.214 0.235\u00a0\u00a0 0.258\u00a0\u00a0 0.284\u00a0\u00a0 0.311\u00a0\u00a0 0.342\u00a0\u00a0 0.375\u00a0\u00a0 0.412\u00a0\u00a0 0.452\u00a0\u00a0 0.496\u00a0\u00a0 0.545\u00a0\u00a0 0.598\u00a0\u00a0 0.657\u00a0\u00a0 0.721\u00a0\u00a0 0.791\u00a0\u00a0 0.869\u00a0\u00a0 0.953\u00a0\u00a0 1.047\u00a0\u00a0 1.149\u00a0\u00a01.261\u00a0\u00a0 1.385\u00a0\u00a0 1.520\u00a0\u00a0 1.669\u00a0\u00a0 1.832\u00a0\u00a0 2.010\u00a0\u00a0 2.207\u00a0\u00a0 2.423\u00a0\u00a0 2.660\u00a0\u00a0 2.920\u00a0\u00a0 3.206\u00a0\u00a0 3.519\u00a0\u00a0 3.862\u00a0\u00a0 4.241\u00a0\u00a0 4.656\u00a0\u00a0 5.111\u00a0\u00a0 5.611\u00a0\u00a0 6.158\u00a0\u00a0\u00a0\u00a0 6.761\u00a0\u00a0 7.421\u00a0\u00a0 8.147\u00a0\u00a0 8.944\u00a0\u00a0 9.819\u00a0\u00a0 10.78\u00a0\u00a0 11.83\u00a0\u00a0 12.99\u00a0\u00a0 14.26\u00a0\u00a0 15.65\u00a0\u00a0 17.17\u00a0\u00a0 18.86\u00a0\u00a0 20.70\u00a0\u00a0 22.73\u00a0\u00a0 24.95\u00a0\u00a0 27.38\u00a0\u00a0 30.07\u00a0\u00a0 33.00\u00a0\u00a036.24\u00a0\u00a0 39.77\u00a0\u00a0 43.66\u00a0\u00a0 47.93\u00a0\u00a0 52.63\u00a0\u00a0 57.77\u00a0\u00a0 63.41\u00a0\u00a0 69.62\u00a0\u00a0 76.43\u00a0\u00a0 83.90\u00a0\u00a0 92.09\u00a0\u00a0 101.1\u00a0\u00a0 111.0\u00a0\u00a0 121.8\u00a0\u00a0 133.7\u00a0\u00a0 146.8\u00a0\u00a0 161.2\u00a0\u00a0 176.8\u00a0\u00a0194.2\u00a0\u00a0 213.2\u00a0\u00a0 234.1\u00a0\u00a0 256.8\u00a0\u00a0 282.1\u00a0\u00a0 309.6\u00a0\u00a0 339.8\u00a0\u00a0 373.1\u00a0\u00a0 409.6\u00a0\u00a0 449.7\u00a0\u00a0 493.6\u00a0\u00a0 541.9\u00a0\u00a0 594.9\u00a0\u00a0 653.0\u00a0\u00a0 716.9\u00a0\u00a0 786.9\u00a0\u00a0 863.9\u00a0\u00a0 948.2\u00a0\u00a0 1041\u00a01143\u00a0\u00a0\u00a0 1255\u00a0\u00a0\u00a0 1377\u00a0\u00a0\u00a0 1512\u00a0\u00a0\u00a0 1660\u00a0\u00a0\u00a0 1822\u00a0\u00a0\u00a0 2000. Each of these particle size bins is the percent weight of sediment that falls between the bin labeled (e.g., 2000uM diameter), and the next lowest bin (e.g., 1822 uM). The sum of all the rows of data in the bins equals 100. ## Sharing/Access information There are no other publicly accessible data locations. ## Code/Software No code or software are provided.", "keywords": ["restoration", "Wetlands", "biochar", "FOS: Earth and related environmental sciences"], "contacts": [{"organization": "Barufaldi, Joshua, Fountain, Monique, Raposa, Kenneth, Tyrell, Megan, Ikeh, Rupert, Gray, Andrew, Watson, Elizabeth,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.x95x69psf"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.x95x69psf", "name": "item", "description": "10.5061/dryad.x95x69psf", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.x95x69psf"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-03-19T00:00:00Z"}}, {"id": "10.5061/dryad.xd2547dhk", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:12Z", "type": "Dataset", "title": "Global patterns and drivers of soil microbial biomass C, N, and P in terrestrial ecosystems", "description": "Soil microbes play key roles in driving and regulating nutrient cycling in terrestrial ecosystems. However, a lack of global-scale information regarding the distribution of soil microbial biomass C (SMB C), N (SMB N), and P (SMB P) in terrestrial ecosystems has limited our ability to incorporate the broad-scale soil microbial nutritional properties and the associated processes into biogeochemical models. Here, we synthesized a global dataset including 3,801 observations for SMB C, 3,154 observations of SMB N, and 2,429 observations of SMB P in the top 0\u201330 cm soil depth. Based on this comprehensive global dataset, we generated quantitative and spatially explicit maps of SMB C, N, and P across terrestrial ecosystems using a random forest approach. In general, the global mean values of SMB C, N, and P concentrations were 693.0 mg kg-1, 89.5 mg kg-1, and 35.5 mg kg-1, respectively. These mean values belie a significantly spatial heterogeneity of these concentrations across biomes and a clear latitudinal trend (wherein SMB C, N, and P increase in cold and high latitude environments along with the large soil organic carbon, SOC). SOC was the most important factor regulating SMB C, N, and P at a global scale. At the global scale, the storage of SMB C, N, and P was estimated to be 23.13 Pg C, 3.93 Pg N, and 2.16 Pg P in the top 0\u201330 cm soil surface, respectively. Our global maps of SMB C, N, and P presented here can be used to constraint Earth system models, and provide the first step forward to predict the roles of soil microbial nutrients in terrestrial nutrient cycling.", "keywords": ["2. Zero hunger", "13. Climate action", "FOS: Earth and related environmental sciences", "15. Life on land"], "contacts": [{"organization": "Wang, Zhiqiang", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.xd2547dhk"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.xd2547dhk", "name": "item", "description": "10.5061/dryad.xd2547dhk", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.xd2547dhk"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-08-26T00:00:00Z"}}, {"id": "10.5061/dryad.xsj3tx9nx", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:13Z", "type": "Dataset", "created": "2023-12-26", "title": "Data from: Promoting success in thin layer sediment placement: effects of sediment grain size and amendments on salt marsh plant growth and greenhouse gas exchange", "description": "unspecifiedThin layer sediment placement (TLP) is a method to mitigate factors resulting in loss of elevation and severe alteration of hydrology, such as sea level rise and anthropogenic modifications, and prolong the lifespan of drowning salt marshes. However, TLP success may vary due to plant stress associated with reductions in nutrient availability and hydrologic flushing or through the creation of acid sulfate soils. This study examined the influence of sediment grain size and soil amendments on plant growth, soil and porewater characteristics, and greenhouse gas exchange for three key US salt marsh plants: Spartina alterniflora, Spartina patens, and Salicornia pacifica. We found that bioavailable nitrogen concentrations (measured as extractable NH4+-N) and porewater pH and salinity were found to have an inverse relationship with grain size, while soil redox was more reducing in finer sediments. This suggests that utilizing finer sediments in TLP projects will result in a more reduced environment with higher nutrient availability, while larger grain-sized sediments will be better flushed and oxidized. We further found that grain size had a significant effect on vegetation biomass allocation and rates of gas exchange, although these effects were species-specific. We found that soil amendments (biochar and compost) did not subsidize plant growth but were associated with increases in soil respiration and methane emissions. Biochar amendments were additionally ineffective in ameliorating acid sulfate conditions. This study uncovers complex interactions between sediment type and vegetation, emphasizing limitations of soil amendments. The findings aid restoration project managers in making informed decisions regarding sediment type, target vegetation, and soil amendments for successful TLP projects.", "keywords": ["Salt marsh", "Greenhouse gases", "restoration", "soil amendment", "biochar", "FOS: Earth and related environmental sciences", "Particle size distribution", "Sea level rise", "Ecosystems"]}, "links": [{"href": "https://doi.org/10.5061/dryad.xsj3tx9nx"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.xsj3tx9nx", "name": "item", "description": "10.5061/dryad.xsj3tx9nx", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.xsj3tx9nx"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-09T00:00:00Z"}}, {"id": "10.5194/bg-10-2671-2013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:17Z", "type": "Journal Article", "created": "2012-07-28", "title": "Nitrous Oxide Emissions From European Agriculture - An Analysis Of Variability And Drivers Of Emissions From Field Experiments", "description": "

Abstract. Nitrous oxide emissions from a network of agricultural experiments in Europe and Zimbabwe were used to explore the relative importance of site and management controls of emissions. At each site, a selection of management interventions were compared within replicated experimental designs in plot based experiments. Arable experiments were conducted at Beano in Italy, El Encin in Spain, Foulum in Denmark, Log\uffc3\uffa5rden in Sweden, Maulde in Belgium, Paulinenaue in Germany, Harare in Zimbabwe and Tulloch in the UK. Grassland experiments were conducted at Crichton, Nafferton and Peaknaze in the UK, G\uffc3\uffb6d\uffc3\uffb6ll\uffc3\uffb6 in Hungary, Rzecin in Poland, Zarnekow in Germany and Theix in France. Nitrous oxide emissions were measured at each site over a period of at least two years using static chambers. Emissions varied widely between sites and as a result of manipulation treatments. Average site emissions (throughout the study period) varied between 0.04 and 21.21 kg N2O-N ha\uffe2\uff88\uff921 yr\uffe2\uff88\uff921, with the largest fluxes and variability associated with the grassland sites. Total nitrogen addition was found to be the single most important determinant of emissions, accounting for 15% of the variance (using linear regression) in the data from the arable sites (p < 0.0001), and 77% in the grassland sites. The annual emissions from arable sites were significantly greater than those that would be predicted by IPCC default emission factors. Variability in N2O within sites that occurred as a result of manipulation treatments was greater than that resulting from site to site and year to year variation, highlighting the importance of management interventions in contributing to greenhouse gas mitigation.

", "keywords": ["Technology", "Atmospheric sciences", "550", "FILLED PORE-SPACE;N2O EMISSIONS;GRASSLAND SYSTEMS;CO2 EMISSIONS;SOILS;MANAGEMENT;FLUXES;FERTILIZATION;CROP;NO", "Economics", "[SDV]Life Sciences [q-bio]", "Environmental protection", "630", "Agricultural and Biological Sciences", "Engineering", "Life", "QH501-531", "FERTILIZATION", "Arable land", "QH540-549.5", "2. Zero hunger", "QE1-996.5", "GRASSLAND SYSTEMS", "Nitrous oxide", "Ecology", "Agricultura", "Life Sciences", "Agriculture", "Hydrology (agriculture)", "Geology", "Agriculture-Farming", "Qu\u00edmica", "04 agricultural and veterinary sciences", "Chemical Engineering", "Grassland", "[SDV] Life Sciences [q-bio]", "Physical Sciences", "FLUXES", "Biogeochemical Cycling of Nutrients in Aquatic Ecosystems", "571", "Soil Science", "N2O EMISSIONS", "Greenhouse gas", "Environmental science", "NO", "MANAGEMENT", "Environmental Chemistry", "Chemical and Biological Technologies for Odor Control", "Biology", "FOS: Chemical engineering", "Process Chemistry and Technology", "Nitrogen Dynamics", "Production", "CROP", "FOS: Earth and related environmental sciences", "15. Life on land", "FILLED PORE-SPACE", "Agronomy", "SOILS", "Geotechnical engineering", "CO2 EMISSIONS", "13. Climate action", "Earth and Environmental Sciences", "FOS: Biological sciences", "Environmental Science", "0401 agriculture", " forestry", " and fisheries", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Fertilizer Applications"]}, "links": [{"href": "https://air.uniud.it/bitstream/11390/876174/1/Rees_et_al_2013.pdf"}, {"href": "https://univ-lyon1.hal.science/hal-02522217/file/2013_Rees_Biogeosciences_1.pdf"}, {"href": "https://doi.org/10.5194/bg-10-2671-2013"}, {"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-10-2671-2013", "name": "item", "description": "10.5194/bg-10-2671-2013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-10-2671-2013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-07-27T00:00:00Z"}}, {"id": "10.5194/hess-19-4201-2015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:34Z", "type": "Journal Article", "created": "2015-10-20", "title": "Multidecadal Change In Streamflow Associated With Anthropogenic Disturbances In The Tropical Andes", "description": "

Abstract. Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974\uffe2\uff80\uff932008) and land cover reconstructions (1963\uffe2\uff80\uff932009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963\uffe2\uff80\uff932009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or \uffe2\uff88\uff9231 km2) corresponding to a mean rate of 67 ha yr\uffe2\uff88\uff921, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963\uffe2\uff80\uff932009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Ni\uffc3\uffb1o\uffe2\uff80\uff93Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.

", "keywords": ["Technology", "Period (music)", "0208 environmental biotechnology", "Urban Flooding", "Precipitation", "02 engineering and technology", "Oceanography", "Environmental technology. Sanitary engineering", "land-use change", "Geography. Anthropology. Recreation", "Climate change", "GE1-350", "TD1-1066", "Water Science and Technology", "Climatology", "2. Zero hunger", "Global and Planetary Change", "Geography", "Ecology", "T", "Physics", "Hydrology (agriculture)", "Geology", "Programming language", "Hydrological Modeling and Water Resource Management", "Physical Sciences", "Cartography", "Land cover", "1443", "Hydrometeorology", "Drainage basin", "0207 environmental engineering", "Streamflow", "Environmental science", "G", "Global Flood Risk Assessment and Management", "Meteorology", "Afforestation", "Agroforestry", "Biology", "Land use", " land-use change and forestry", "FOS: Earth and related environmental sciences", "Acoustics", "15. Life on land", "Computer science", "Environmental sciences", "Geotechnical engineering", "Deforestation (computer science)", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Global Drought Monitoring and Assessment", "Land use"]}, "links": [{"href": "https://doi.org/10.5194/hess-19-4201-2015"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-19-4201-2015", "name": "item", "description": "10.5194/hess-19-4201-2015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-19-4201-2015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-10-20T00:00:00Z"}}, {"id": "10.5194/essd-13-3707-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:30Z", "type": "Journal Article", "created": "2021-01-07", "title": "C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)", "description": "

Abstract. A better understanding of the hydrological functioning of irrigated crops using remote sensing observations is of prime importance in the semi-arid areas where the water resources are limited. Radar observations, available at high resolution and revisit time since the launch of Sentinel-1 in 2014, have shown great potential for the monitoring of the water content of the upper soil and of the canopy. In this paper, a complete set of data for radar signal analysis is shared to the scientific community for the first time to our knowledge. The data set is composed of Sentinel-1 products and in situ measurements of soil and vegetation variables collected during three agricultural seasons over drip-irrigated winter wheat in the Haouz plain in Morocco. The in situ data gathers soil measurements (time series of half-hourly surface soil moisture, surface roughness and agricultural practices) and vegetation measurements collected every week/two weeks including above-ground fresh and dry biomasses, vegetation water content based on destructive measurements, cover fraction, leaf area index and plant height. Radar data are the backscattering coefficient and the interferometric coherence derived from Sentinel-1 GRDH (Ground Range Detected High resolution) and SLC (Single Look Complex) products, respectively. The normalized difference vegetation index derived from Sentinel-2 data based on Level-2A (surface reflectance and cloud mask) atmospheric effects-corrected products is also provided. This database, which is the first of its kind made available in open access, is described here comprehensively in order to help the scientific community to evaluate and to develop new or existing remote sensing algorithms for monitoring wheat canopy under semi-arid conditions. The data set is particularly relevant for the development of radar applications including surface soil moisture and vegetation parameters retrieval using either physically based or empirical approaches such as machine and deep learning algorithms. The database is archived in the DataSuds repository and is freely-accessible via the DOI: https://doi.org/10.23708/8D6WQC (Ouaadi et al., 2020a).

", "keywords": ["550", "Arid", "Soil Moisture", "0211 other engineering and technologies", "FOS: Mechanical engineering", "02 engineering and technology", "Digital Soil Mapping Techniques", "Normalized Difference Vegetation Index", "630", "Agricultural and Biological Sciences", "Engineering", "Pathology", "GE1-350", "2. Zero hunger", "QE1-996.5", "Vegetation Monitoring", "Water content", "Ecology", "Geography", "Statistics", "Life Sciences", "Hydrology (agriculture)", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Soil Erosion and Agricultural Sustainability", "6. Clean water", "Satellite Observations", "Archaeology", "Physical Sciences", "Leaf area index", "Telecommunications", "Medicine", "Vegetation (pathology)", "Environmental Engineering", "Data set", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Aerospace Engineering", "Soil Science", "Environmental science", "Digital Soil Mapping", "[SDU] Sciences of the Universe [physics]", "Global Soil Information", "FOS: Mathematics", "Biology", "Radar", "Synthetic Aperture Radar Interferometry", "Canopy", "FOS: Environmental engineering", "Soil Properties", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Agronomy", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "Mathematics"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/3707/2021/essd-13-3707-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-3707-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-13-3707-2021", "name": "item", "description": "10.5194/essd-13-3707-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-3707-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-07T00:00:00Z"}}, {"id": "10.5194/hess-24-3789-2020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:35Z", "type": "Journal Article", "created": "2020-07-27", "title": "Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)", "description": "

Abstract. The main objective of this work is to question the representation of the energy budget in soil\u2013vegetation\u2013atmosphere transfer\u00a0(SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere\u00a0(ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one\u00a0patch), is compared to the new multiple energy balance\u00a0(MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two\u00a0patches) is also considered for the olive orchard. Continuous observations of evapotranspiration\u00a0(ET), with an eddy covariance system and plant transpiration\u00a0(Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA\u2013MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil\u2013vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA\u2013MEB did not exceed 10\u2009W\u2009m\u22122 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P\u00a0(ISBA\u2013MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled\u00a0(ISBA-2P) and the coupled\u00a0(ISBA\u2013MEB) representations, outperformed the single-source version\u00a0(ISBA-1P), with slightly better results for ISBA\u2013MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA\u2013MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of\u00a01.60, 0.90, and 0.70\u2009mm\u2009d\u22121 and R2\u00a0of\u00a00.43, 0.69, and\u00a00.70\u00a0for ISBA-1P, ISBA-2P and ISBA\u2013MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalis\u00e9e (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA\u2013MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA\u2013MEB model.

", "keywords": ["Technology", "Atmospheric Science", "Atmospheric sciences", "550", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "02 engineering and technology", "Energy balance", "Eddy covariance", "Environmental technology. Sanitary engineering", "01 natural sciences", "Environmental science", "G", "Meteorology", "Geography. Anthropology. Recreation", "GE1-350", "Biology", "TD1-1066", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Evapotranspiration", "Ecology", "Global Forest Drought Response and Climate Change", "T", "Causes and Impacts of Climate Change Over Millennia", "Physics", "Hydrology (agriculture)", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "[SDV] Life Sciences [q-bio]", "Environmental sciences", "Earth and Planetary Sciences", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Global Drought Monitoring and Assessment", "Leaf area index", "Thermodynamics", "Global Vegetation Models"]}, "links": [{"href": "https://doi.org/10.5194/hess-24-3789-2020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-24-3789-2020", "name": "item", "description": "10.5194/hess-24-3789-2020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-24-3789-2020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-15T00:00:00Z"}}, {"id": "10.5194/gmd-11-3903-2018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:32Z", "type": "Journal Article", "created": "2018-09-27", "title": "GOLUM-CNP v1.0: a data-driven modeling of carbon, nitrogen and phosphorus cycles in major terrestrial biomes", "description": "

Abstract. Global terrestrial nitrogen (N) and phosphorus (P) cycles are coupled to the global carbon (C) cycle for net primary production (NPP), plant C allocation, and decomposition of soil organic matter, but N and P have distinct pathways of inputs and losses. Current C-nutrient models exhibit large uncertainties in their estimates of pool sizes, fluxes, and turnover rates of nutrients, due to a lack of consistent global data for evaluating the models. In this study, we present a new model\uffe2\uff80\uff93data fusion framework called the Global Observation-based Land-ecosystems Utilization Model of Carbon, Nitrogen and Phosphorus (GOLUM-CNP) that combines the CARbon DAta MOdel fraMework (CARDAMOM) data-constrained C-cycle analysis with spatially explicit data-driven estimates of N and P inputs and losses and with observed stoichiometric ratios. We calculated the steady-state N- and P-pool sizes and fluxes globally for large biomes. Our study showed that new N inputs from biological fixation and deposition supplied >20\uffe2\uff80\uff89% of total plant uptake in most forest ecosystems but accounted for smaller fractions in boreal forests and grasslands. New P inputs from atmospheric deposition and rock weathering supplied a much smaller fraction of total plant uptake than new N inputs, indicating the importance of internal P recycling within ecosystems to support plant growth. Nutrient-use efficiency, defined as the ratio of gross primary production (GPP) to plant nutrient uptake, were diagnosed from our model results and compared between biomes. Tropical forests had the lowest N-use efficiency and the highest P-use efficiency of the forest biomes. An analysis of sensitivity and uncertainty indicated that the NPP-allocation fractions to leaves, roots, and wood contributed the most to the uncertainties in the estimates of nutrient-use efficiencies. Correcting for biases in NPP-allocation fractions produced more plausible gradients of N- and P-use efficiencies from tropical to boreal ecosystems and highlighted the critical role of accurate measurements of C allocation for understanding the N and P cycles.

", "keywords": ["Atmospheric sciences", "550", "Organic chemistry", "Carbon Dynamics in Peatland Ecosystems", "Deposition (geology)", "01 natural sciences", "Nutrient cycle", "Agricultural and Biological Sciences", "Terrestrial ecosystem", "Biome", "Taiga", "2. Zero hunger", "QE1-996.5", "Ecology", "Primary production", "Nutrient Cycling", "Life Sciences", "Phosphorus", "Geology", "Carbon cycle", "Nitrogen Cycle", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "Chemistry", "Physical Sciences", "environment", "Ecosystem Functioning", "Biogeochemical Cycling of Nutrients in Aquatic Ecosystems", "Nitrogen", "Soil Science", "Environmental science", "Environmental Chemistry", "New production", "Soil Carbon Sequestration", "Biology", "Ecosystem", "0105 earth and related environmental sciences", "[SDU.OCEAN]Sciences of the Universe [physics]/Ocean", "Atmosphere", "[SDU.OCEAN] Sciences of the Universe [physics]/Ocean", " Atmosphere", "ddc:550", "Nitrogen Dynamics", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Phytoplankton", "Sediment", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "Soil Carbon Dynamics and Nutrient Cycling in Ecosystems", "Nutrient"]}, "links": [{"href": "https://gmd.copernicus.org/articles/11/3903/2018/gmd-11-3903-2018.pdf"}, {"href": "https://doi.org/10.5194/gmd-11-3903-2018"}, {"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-11-3903-2018", "name": "item", "description": "10.5194/gmd-11-3903-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-11-3903-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-22T00:00:00Z"}}, {"id": "10.5194/hess-2019-105", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:34Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-2019-105"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-2019-105", "name": "item", "description": "10.5194/hess-2019-105", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-2019-105"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10.5194/hess-24-1781-2020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:35Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\uffe2\uff80\uff89km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\uffe2\uff80\uff89km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\uffe2\uff80\uff932018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\uffe2\uff80\uff932018). The field was seeded for the 2014\uffe2\uff80\uff932015 (S1), 2016\uffe2\uff80\uff932017 (S2) and 2017\uffe2\uff80\uff932018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\uffe2\uff80\uff932016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \uffce\uffb1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \uffce\uffb1PT remains at a mostly constant value (\uffe2\uff88\uffbc\uffe2\uff80\uff890.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\uffe2\uff80\uff89W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.5194/hess-24-1781-2020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/hess-24-1781-2020", "name": "item", "description": "10.5194/hess-24-1781-2020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-24-1781-2020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10.5194/isprs-archives-xlii-3-w6-9-2019", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:24:35Z", "type": "Journal Article", "created": "2019-07-29", "title": "EVAPOTRANSPIRATION AND EVAPORATION/TRANSPIRATION RETRIEVAL USING DUAL-SOURCE SURFACE ENERGY BALANCE MODELS INTEGRATING VIS/NIR/TIR DATA WITH SATELLITE SURFACE SOIL MOISTURE INFORMATION", "description": "

Abstract. Evapotranspiration is an important component of the water cycle. For the agronomic management and ecosystem health monitoring, it is also important to provide an estimate of evapotranspiration components, i.e. transpiration and soil evaporation. To do so, Thermal InfraRed data can be used with dual-source surface energy balance models, because they solve separate energy budgets for the soil and the vegetation. But those models rely on specific assumptions on raw levels of plant water stress to get both components (evaporation and transpiration) out of a single source of information, namely the surface temperature. Additional information from remote sensing data are thus required. This works evaluates the ability of the SPARSE dual-source energy balance model to compute not only total evapotranspiration, but also water stress and transpiration/evaporation components, using either the sole surface temperature as a remote sensing driver, or a combination of surface temperature and soil moisture level derived from microwave data. Flux data at an experimental plot in semi-arid Morocco is used to assess this potentiality and shows the increased robustness of both the total evapotranspiration and partitioning retrieval performances. This work is realized within the frame of the Phase A activities for the TRISHNA CNES/ISRO Thermal Infra-Red satellite mission.

", "keywords": ["Technology", "Environmental Engineering", "550", "Ecosystem Resilience", "Soil Moisture", "Evaporation", "Energy balance", "Biochemistry", "Environmental science", "Transpiration", "Meteorology", "Artificial Intelligence", "Soil water", "Thermal Infrared", "Applied optics. Photonics", "Machine Learning Methods for Solar Radiation Forecasting", "Photosynthesis", "TRISHNA", "Water balance", "Biology", "Soil science", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "Global Forest Drought Response and Climate Change", "T", "FOS: Environmental engineering", "Geology", "FOS: Earth and related environmental sciences", "Remote sensing", "15. Life on land", "Engineering (General). Civil engineering (General)", "Remote Sensing of Soil Moisture", "6. Clean water", "TA1501-1820", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Computer Science", "TA1-2040", "Water cycle"]}, "links": [{"href": "https://doi.org/10.5194/isprs-archives-xlii-3-w6-9-2019"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20International%20Archives%20of%20the%20Photogrammetry%2C%20Remote%20Sensing%20and%20Spatial%20Information%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/isprs-archives-xlii-3-w6-9-2019", "name": "item", "description": "10.5194/isprs-archives-xlii-3-w6-9-2019", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/isprs-archives-xlii-3-w6-9-2019"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-07-26T00:00:00Z"}}, {"id": "10.6084/m9.figshare.11925045", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:45Z", "type": "Dataset", "created": "2020-03-03", "title": "Additional file 4 of Impact of process temperature and organic loading rate on cellulolytic / hydrolytic biofilm microbiomes during biomethanation of ryegrass silage revealed by genome-centered metagenomics and metatranscriptomics", "description": "Additional file 4. Taxonomic affiliations of metagenome-assembled genomes (MAGs) of this study originating from HR biofilms.", "keywords": ["Ecology", "FOS: Biological sciences", "110309 Infectious Diseases", "Marine Biology", "FOS: Earth and related environmental sciences", "FOS: Health sciences", "Microbiology", "59999 Environmental Sciences not elsewhere classified", "69999 Biological Sciences not elsewhere classified"], "contacts": [{"organization": "Maus, Irena, Klocke, Michael, Derenk\u00f3, Jaqueline, Stolze, Yvonne, Beckstette, Michael, Jost, Carsten, Wibberg, Daniel, Blom, Jochen, Henke, Christian, Willenb\u00fccher, Katharina, Rumming, Madis, Rademacher, Antje, P\u00fchler, Alfred, Sczyrba, Alexander, Schl\u00fcter, Andreas,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.6084/m9.figshare.11925045"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.11925045", "name": "item", "description": "10.6084/m9.figshare.11925045", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.11925045"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.13236749", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:25:08Z", "type": "Dataset", "title": "Gridded spatial information on soil organic carbon content, density and stock in Hungary for 1992 and 2000", "description": "Predictive soil organic carbon (SOC) content, density, and stock maps, along with the associated prediction uncertainty, are provided for the years 1992 and 2000, for the entire territory of Hungary. The maps refer to the topsoils (0\u201330 cm) with a spatial resolution of 100\u2a2f100 m. The uncertainty associated with the SOC property maps is expressed by the lower and upper limits of the 90% prediction interval (PI), the range of values within which the true value is expected to occur 9 times out of 10. This means that there are two maps to each SOC property map, quantifying its prediction uncertainty. It should be added that all maps have been masked with open water bodies, as these areas are not relevant for soils. For more details / to cite this dataset please use: Szatm\u00e1ri, G., Laborczi, A., M\u00e9sz\u00e1ros, J., Tak\u00e1cs, K., Ben\u0151, A., Ko\u00f3s, S., Bakacsi, Z., & P\u00e1sztor, L. (2024). Gridded, temporally referenced spatial information on soil organic carbon for Hungary. Scientific Data 11, 1312. Custom code used for digital soil mapping and validation is available on GitHub: https://github.com/GaborSzatmari/HU-SOC-mapping Description of the files: The resulting maps are shared as GeoTIFF files. The coordinate reference system is the Hungarian Unified National Projection System (HD72/EOV; EPSG: 23700) (https://epsg.io/23700). The table below provides further information on the published maps. Note that the first file (00_Overview.jpg) gives an overview of the SOC property maps. SOC property maps Unit Year Filename SOC content map [g \u2219 kg-1] 1992 SOCc_0_30cm_1992_pred.tif SOC content, lower limit of the 90% PI [g \u2219 kg-1] 1992 SOCc_0_30cm_1992_q05.tif SOC content, upper limit of the 90% PI [g \u2219 kg-1] 1992 SOCc_0_30cm_1992_q95.tif SOC density map [kg \u2219 m-3] 1992 SOCd_0_30cm_1992_pred.tif SOC density, lower limit of the 90% PI [kg \u2219 m-3] 1992 SOCd_0_30cm_1992_q05.tif SOC density, upper limit of the 90% PI [kg \u2219 m-3] 1992 SOCd_0_30cm_1992_q95.tif SOC stock map [tons \u2219 ha-1] 1992 SOCs_0_30cm_1992_pred.tif SOC stock, lower limit of the 90% PI [tons \u2219 ha-1] 1992 SOCs_0_30cm_1992_q05.tif SOC stock, upper limit of the 90% PI [tons \u2219 ha-1] 1992 SOCs_0_30cm_1992_q95.tif SOC content map [g \u2219 kg-1] 2000 SOCc_0_30cm_2000_pred.tif SOC content, lower limit of the 90% PI [g \u2219 kg-1] 2000 SOCc_0_30cm_2000_q05.tif SOC content, upper limit of the 90% PI [g \u2219 kg-1] 2000 SOCc_0_30cm_2000_q95.tif SOC density map [kg \u2219 m-3] 2000 SOCd_0_30cm_2000_pred.tif SOC density, lower limit of the 90% PI [kg \u2219 m-3] 2000 SOCd_0_30cm_2000_q05.tif SOC density, upper limit of the 90% PI [kg \u2219 m-3] 2000 SOCd_0_30cm_2000_q95.tif SOC stock map [tons \u2219 ha-1] 2000 SOCs_0_30cm_2000_pred.tif SOC stock, lower limit of the 90% PI [tons \u2219 ha-1] 2000 SOCs_0_30cm_2000_q05.tif SOC stock, upper limit of the 90% PI [tons \u2219 ha-1] 2000 SOCs_0_30cm_2000_q95.tif", "keywords": ["Soil sciences", "Digital soil mapping", "Soil organic carbon", "Soil health", "Earth and related environmental sciences", "Soil monitoring", "FOS: Earth and related environmental sciences"], "contacts": [{"organization": "Szatm\u00e1ri, G\u00e1bor, Laborczi, Annam\u00e1ria, M\u00e9sz\u00e1ros, J\u00e1nos, Tak\u00e1cs, Katalin, Ben\u0151, Andr\u00e1s, Ko\u00f3s, S\u00e1ndor, Bakacsi, Zs\u00f3fia, P\u00e1sztor, L\u00e1szl\u00f3,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.13236749"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.13236749", "name": "item", "description": "10.5281/zenodo.13236749", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.13236749"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-08-14T00:00:00Z"}}, {"id": "10.6084/m9.figshare.11925045.v1", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:45Z", "type": "Dataset", "created": "2020-03-03", "title": "Additional file 4 of Impact of process temperature and organic loading rate on cellulolytic / hydrolytic biofilm microbiomes during biomethanation of ryegrass silage revealed by genome-centered metagenomics and metatranscriptomics", "description": "Additional file 4. Taxonomic affiliations of metagenome-assembled genomes (MAGs) of this study originating from HR biofilms.", "keywords": ["Ecology", "FOS: Biological sciences", "110309 Infectious Diseases", "Marine Biology", "FOS: Earth and related environmental sciences", "FOS: Health sciences", "Microbiology", "59999 Environmental Sciences not elsewhere classified", "69999 Biological Sciences not elsewhere classified"], "contacts": [{"organization": "Maus, Irena, Klocke, Michael, Derenk\u00f3, Jaqueline, Stolze, Yvonne, Beckstette, Michael, Jost, Carsten, Wibberg, Daniel, Blom, Jochen, Henke, Christian, Willenb\u00fccher, Katharina, Rumming, Madis, Rademacher, Antje, P\u00fchler, Alfred, Sczyrba, Alexander, Schl\u00fcter, Andreas,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.6084/m9.figshare.11925045.v1"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.11925045.v1", "name": "item", "description": "10.6084/m9.figshare.11925045.v1", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.11925045.v1"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.5281/zenodo.14863825", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:25:43Z", "type": "Dataset", "created": "2024-09-22", "title": "Global mycorrhizal status drives leaf \u03b415N patterns", "description": "Open AccessFoliar \u03b415N values were obtained from a recent version of the global dataset described by Craine et al. (2018) that was updated with newly published data for Meta-analyses. \u00a0Multi-year average MAT, MAP, and PET maps with a spatial resolution of 4 km \u00d7 4 km for 1982 through 2018 were extracted from the TerraClimate dataset (Abatzoglou et al., 2018). AI values (defined as the ratio of precipitation to PET) were calculated from MAP and PET values. A digital elevation model (DEM) map with a spatial resolution of 1 km \u00d7 1 km was extracted from the Global Land One km Base Elevation (GLOBE) Project (https://www.ngdc.noaa.gov/mgg/topo/globe.html). A slope map was generated from the DEM map. Soil clay, silt, sand, soil organic carbon (SOC), and TN contents with a spatial resolution of 250 m \u00d7 250 m were obtained from the SoilGrids dataset (Hengl et al., 2017). Multi-year (1982\u20132018) GPP values were calculated using data from the Global Land Surface Satellite (GLASS) project (Liang et al., 2021). Multi-year (1982\u20132015) average normalized difference vegetation index (NDVI) values were calculated from the GIMMS3g dataset (Tucker et al., 2005). The mycorrhizal plant type map (showing the distribution of AM, ECM, ERM, and NM plants) was generated from maps showing the proportional aboveground plant biomass of AM, ECM, ERM, and NM plants (Soudzilovskaia et al., 2019) for Random Forest.", "keywords": ["Isotopes", "15N", "Ecosystem ecology", "global pattern", "nitrogen dynamics", "Plant\u2013soil interactions", "ecosystem ecology", "FOS: Earth and related environmental sciences", "plant\u2013soil interactions", "mycorrhizae", "isotopes", "\u03b415N"], "contacts": [{"organization": "Chen, Qiong, Li, Huiwen, Yu, Fei, Lyu, Ruobing, Li, Zhenxin, Hao, Zhanqing, Yuan, Zuoqiang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14863825"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14863825", "name": "item", "description": "10.5281/zenodo.14863825", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14863825"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-13T00:00:00Z"}}, {"id": "10.5281/zenodo.14863826", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:25:43Z", "type": "Dataset", "created": "2024-09-22", "title": "Global mycorrhizal status drives leaf \u03b415N patterns", "description": "unspecifiedFoliar \u03b415N values were obtained from a recent version of the global dataset described by Craine et al. (2018) that was updated with newly published data for Meta-analyses. \u00a0Multi-year average MAT, MAP, and PET maps with a spatial resolution of 4 km \u00d7 4 km for 1982 through 2018 were extracted from the TerraClimate dataset (Abatzoglou et al., 2018). AI values (defined as the ratio of precipitation to PET) were calculated from MAP and PET values. A digital elevation model (DEM) map with a spatial resolution of 1 km \u00d7 1 km was extracted from the Global Land One km Base Elevation (GLOBE) Project (https://www.ngdc.noaa.gov/mgg/topo/globe.html). A slope map was generated from the DEM map. Soil clay, silt, sand, soil organic carbon (SOC), and TN contents with a spatial resolution of 250 m \u00d7 250 m were obtained from the SoilGrids dataset (Hengl et al., 2017). Multi-year (1982\u20132018) GPP values were calculated using data from the Global Land Surface Satellite (GLASS) project (Liang et al., 2021). Multi-year (1982\u20132015) average normalized difference vegetation index (NDVI) values were calculated from the GIMMS3g dataset (Tucker et al., 2005). The mycorrhizal plant type map (showing the distribution of AM, ECM, ERM, and NM plants) was generated from maps showing the proportional aboveground plant biomass of AM, ECM, ERM, and NM plants (Soudzilovskaia et al., 2019) for Random Forest.", "keywords": ["Isotopes", "15N", "Ecosystem ecology", "global pattern", "nitrogen dynamics", "Plant\u2013soil interactions", "ecosystem ecology", "FOS: Earth and related environmental sciences", "plant\u2013soil interactions", "mycorrhizae", "isotopes", "\u03b415N"], "contacts": [{"organization": "Chen, Qiong, Li, Huiwen, Yu, Fei, Lyu, Ruobing, Li, Zhenxin, Hao, Zhanqing, Yuan, Zuoqiang,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14863826"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14863826", "name": "item", "description": "10.5281/zenodo.14863826", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14863826"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-13T00:00:00Z"}}, {"id": "10.5281/zenodo.16926945", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:26:17Z", "type": "Dataset", "title": "Adjusted bulk density data in the Hungarian Soil Information and Monitoring System", "description": "This dataset provides corrected bulk density (BD) values and their associated uncertainty estimates for 4,340 soil genetic horizons across 1,236 monitoring sites of the Hungarian Soil Information and Monitoring System. The correction was achieved by developing a pedotransfer function (PTF) based on the Hungarian Detailed Soil Hydro-physical Database (Hungarian acronym: MARTHA) and advanced machine learning algorithms. Soil properties (i.e., soil organic carbon, pH in water, and sand, silt, and clay content) together with environmental covariates, used as proxies for the soil forming factors, were integrated into the PTF development to improve predictive performance. Uncertainty of the BD predictions is provided in two forms: (1) the 90% prediction interval (defined by its lower and upper limits, within which the true value is expected to occur nine times out of ten), and (2) the standard error of the corrected BD values. To ensure transparency, reproducibility, and open access, the corrected BD values, their corresponding uncertainty estimates, and the developed code are publicly available. For more details / to cite this dataset please use: Sohrab, S., Szab\u00f3, B., P\u00e1sztor, L., Mak\u00f3, A., Szatm\u00e1ri, G. (2025). Adjusting bulk density observations in the Hungarian Soil Information and Monitoring System using advanced pedotransfer functions. European Journal of Soil Science (submitted manuscript) Codes are available on GitHub: https://github.com/Mehrsoh/Soil-BD-Correction Description of the files: Two versions of the same dataset are provided, differing only in file format: (1) 'HUN-SIMS_BD_corrected.csv' \u2013 CSV format (separated by semicolon), and (2) 'HUN-SIMS_BD_corrected.xlsx' \u2013 Microsoft Excel format. The table below summarizes the column names, units, and data formats, and also provides a description for each column. Note that the coordinate reference system is the Hungarian Unified National Projection System (HD72/EOV; EPSG: 23700). For more details, see https://epsg.io/23700. Column name Format Unit Description PROFILE_ID string - Identifier of monitoring sites in the Hungarian Soil Information and Monitoring System LAYER_ID string - Identifier of soil genetic horizons at a monitoring site X numeric [m] X coordinate Y numeric [m] Y coordinate TOP numeric [cm] Upper depth boundary of soil genetic horizons BOTTOM numeric [cm] Lower depth boundary of soil genetic horizons BD_CORRECTED numeric [g\u00b7cm-3] Bias-corrected bulk density value Q_05 numeric [g\u00b7cm-3] 5th quantile; lower limit of the 90% prediction interval Q_95 numeric [g\u00b7cm-3] 95th quantile; upper limit of the 90% prediction interval SE numeric [g\u00b7cm-3] Standard error of the bias-corrected bulk density value", "keywords": ["Soil sciences", "Soil health", "Earth and related environmental sciences", "Soil physics", "Soil monitoring", "FOS: Earth and related environmental sciences", "Pedotransfer function"], "contacts": [{"organization": "Sohrab, Seyedehmehrmanzar, Szab\u00f3, Brigitta, P\u00e1sztor, L\u00e1szl\u00f3, Mak\u00f3, Andr\u00e1s, Szatm\u00e1ri, G\u00e1bor,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16926945"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16926945", "name": "item", "description": "10.5281/zenodo.16926945", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16926945"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-09-04T00:00:00Z"}}, {"id": "10.5281/zenodo.16927293", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:26:17Z", "type": "Dataset", "title": "Soil gas analyses and geochemistry in B\u0103ile L\u0103z\u0103re\u0219ti, Harghita, Romania, August 2022", "description": "For given locations, results of soil gas analyses, TOC, CaCO3, Na2O, MgO, SiO2, P2O5, K2O, CaO, Ti, V, Cr, MnO, Fa2O3, Ni, Cu, Zn, As, Sr, Zr, Sn, Hg, Pb, water content, dry matter, total organic carbon, carbonates, siliciclastic.", "keywords": ["Geochemistry", "Metals", " Heavy", "Soil gas flux", "Oxides", "FOS: Earth and related environmental sciences", "TOC"], "contacts": [{"organization": "Dudu, Alexandra, Naliana, Lupascu, GeoEcoMar,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.16927293"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.16927293", "name": "item", "description": "10.5281/zenodo.16927293", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.16927293"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-08-22T00:00:00Z"}}, {"id": "10.60692/khb9k-9s285", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:42Z", "type": "Journal Article", "created": "2020-07-27", "title": "Evapotranspiration partition using the multiple energy balance version of the ISBA-A-gs land surface model over two irrigated crops in a semi-arid Mediterranean region (Marrakech, Morocco)", "description": "

Abstract. The main objective of this work is to question the representation of the energy budget in soil\u2013vegetation\u2013atmosphere transfer\u00a0(SVAT) models for the prediction of the turbulent fluxes in the case of irrigated crops with a complex structure (row) and under strong transient hydric regimes due to irrigation. To this end, the Interaction between Soil, Biosphere, and Atmosphere\u00a0(ISBA-A-gs) is evaluated at a complex open olive orchard and, for the purposes of comparison, on a winter wheat field taken as an example of a homogeneous canopy. The initial version of ISBA-A-gs, based on a composite energy budget (hereafter ISBA-1P for one\u00a0patch), is compared to the new multiple energy balance\u00a0(MEB) version of ISBA that represents a double source arising from the vegetation located above the soil layer. In addition, a patch representation corresponding to two adjacent, uncoupled source schemes (hereafter ISBA-2P for two\u00a0patches) is also considered for the olive orchard. Continuous observations of evapotranspiration\u00a0(ET), with an eddy covariance system and plant transpiration\u00a0(Tr) with sap flow and isotopic methods were used to evaluate the three representations. A preliminary sensitivity analyses showed a strong sensitivity to the parameters related to turbulence in the canopy introduced in the new ISBA\u2013MEB version. For wheat, the ability of the single- and dual-source configuration to reproduce the composite soil\u2013vegetation heat fluxes was very similar; the root mean square error (RMSE) differences between ISBA-1P, ISBA-2P and ISBA\u2013MEB did not exceed 10\u2009W\u2009m\u22122 for the latent heat flux. These results showed that a composite energy balance in homogeneous covers is sufficient to reproduce the total convective fluxes. The two configurations are also fairly close to the isotopic observations of transpiration in spite of a light underestimation (overestimation) of ISBA-1P\u00a0(ISBA\u2013MEB). At the olive orchard, contrasting results are obtained. The dual-source configurations, including both the uncoupled\u00a0(ISBA-2P) and the coupled\u00a0(ISBA\u2013MEB) representations, outperformed the single-source version\u00a0(ISBA-1P), with slightly better results for ISBA\u2013MEB in predicting both total heat fluxes and evapotranspiration partition. Concerning plant transpiration in particular, the coupled approach ISBA\u2013MEB provides better results than ISBA-1P and, to a lesser extent, ISBA-2P with RMSEs of\u00a01.60, 0.90, and 0.70\u2009mm\u2009d\u22121 and R2\u00a0of\u00a00.43, 0.69, and\u00a00.70\u00a0for ISBA-1P, ISBA-2P and ISBA\u2013MEB, respectively. In addition, it is shown that the acceptable predictions of composite convective fluxes by ISBA-2P for the olive orchard are obtained for the wrong reasons as neither of the two patches is in agreement with the observations because of a bad spatial distribution of the roots and a lack of incoming radiation screening for the bare soil patch. This work shows that composite convection fluxes predicted by the SURFace EXternalis\u00e9e (SURFEX) platform and the partition of evapotranspiration in a highly transient regime due to irrigation is improved for moderately open tree canopies by the new coupled dual-source ISBA\u2013MEB model. It also points out the need for further local-scale evaluations on different crops of various geometry (more open rainfed agriculture or a denser, intensive olive orchard) to provide adequate parameterisation to global database, such as ECOCLIMAP-II, in the view of a global application of the ISBA\u2013MEB model.

", "keywords": ["Technology", "Atmospheric Science", "Atmospheric sciences", "550", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "02 engineering and technology", "Energy balance", "Eddy covariance", "Environmental technology. Sanitary engineering", "01 natural sciences", "Environmental science", "G", "Meteorology", "Geography. Anthropology. Recreation", "GE1-350", "Biology", "TD1-1066", "Ecosystem", "0105 earth and related environmental sciences", "Soil science", "2. Zero hunger", "Global and Planetary Change", "Evapotranspiration", "Ecology", "Global Forest Drought Response and Climate Change", "T", "Causes and Impacts of Climate Change Over Millennia", "Physics", "Hydrology (agriculture)", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Agronomy", "[SDV] Life Sciences [q-bio]", "Environmental sciences", "Earth and Planetary Sciences", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Global Drought Monitoring and Assessment", "Leaf area index", "Thermodynamics", "Global Vegetation Models"]}, "links": [{"href": "https://doi.org/10.60692/khb9k-9s285"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/khb9k-9s285", "name": "item", "description": "10.60692/khb9k-9s285", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/khb9k-9s285"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-15T00:00:00Z"}}, {"id": "10.60692/7hann-x9205", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:42Z", "type": "Journal Article", "created": "2020-12-08", "title": "Linkages between Rainfed Cereal Production and Agricultural Drought through Remote Sensing Indices and a Land Data Assimilation System: A Case Study in Morocco", "description": "

In Morocco, cereal production shows high interannual variability due to uncertain rainfall and recurrent drought periods. Considering the socioeconomic importance of cereal for the country, there is a serious need to characterize the impact of drought on cereal yields. In this study, drought is assessed through (1) indices derived from remote sensing data (the vegetation condition index (VCI), temperature condition index (TCI), vegetation health ind ex (VHI), soil moisture condition index (SMCI) and soil water index for different soil layers (SWI)) and (2) key land surface variables (Land Area Index (LAI), soil moisture (SM) at different depths, soil evaporation and plant transpiration) from a Land Data Assimilation System (LDAS) over 2000\u20132017. A lagged correlation analysis was conducted to assess the relationships between the drought indices and cereal yield at monthly time scales. The VCI and LAI around the heading stage (March-April) are highly linked to yield for all provinces (R = 0.94 for the Khemisset province), while a high link for TCI occurs during the development stage in January-February (R = 0.83 for the Beni Mellal province). Interestingly, indices related to soil moisture in the superficial soil layer are correlated with yield earlier in the season around the emergence stage (December). The results demonstrate the clear added value of using an LDAS compared with using a remote sensing product alone, particularly concerning the soil moisture in the root-zone, considered a key variable for yield production, that is not directly observable from space. The time scale of integration is also discussed. By integrating the indices on the main phenological stages of wheat using a dynamic threshold approach instead of the monthly time scale, the correlation between indices and yield increased by up to 14%. In addition, the contributions of VCI and TCI to VHI were optimized by using yield anomalies as proxies for drought. This study opens perspectives for the development of drought early warning systems in Morocco and over North Africa, as well as for seasonal crop yield forecasting.

", "keywords": ["[SDE] Environmental Sciences", "550", "Science", "0207 environmental engineering", "Agricultural drought", "02 engineering and technology", "01 natural sciences", "630", "Environmental science", "remote sensing", "Land data assimilation systems", "Pathology", "assimilation systems", "Biology", "land data assimilation systems", "0105 earth and related environmental sciences", "2. Zero hunger", "Global and Planetary Change", "Vegetation Monitoring", "Water content", "Ecology", "Drought", "Global Forest Drought Response and Climate Change", "Q", "Hydrology (agriculture)", "Geology", "cereal yield", "Remote Sensing in Vegetation Monitoring and Phenology", "FOS: Earth and related environmental sciences", "Remote sensing", "semiarid region", "15. Life on land", "agricultural drought", "Agronomy", "6. Clean water", "Cereal yield", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "[SDE]Environmental Sciences", "Global Drought Monitoring and Assessment", "Environmental Science", "Physical Sciences", "Leaf area index", "Medicine", "Semiarid region", "land data", "Vegetation (pathology)"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://www.mdpi.com/2072-4292/12/24/4018/pdf"}, {"href": "https://doi.org/10.60692/7hann-x9205"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/7hann-x9205", "name": "item", "description": "10.60692/7hann-x9205", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/7hann-x9205"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-08T00:00:00Z"}}, {"id": "10.60692/g4rcv-eqz54", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:42Z", "type": "Journal Article", "created": "2019-04-23", "title": "An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data", "description": "

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1\u2009km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1\u2009km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014\u20132018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014\u20132018). The field was seeded for the 2014\u20132015 (S1), 2016\u20132017 (S2) and 2017\u20132018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015\u20132016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated \u03b1PT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved \u03b1PT remains at a mostly constant value (\u223c\u20090.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181\u2009W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62\u2009W/m2 for S1, S2, S3 and B1 respectively.

", "keywords": ["Technology", "Atmospheric sciences", "550", "Soil Moisture", "0208 environmental biotechnology", "02 engineering and technology", "Environmental technology. Sanitary engineering", "01 natural sciences", "Engineering", "Geography. Anthropology. Recreation", "Pathology", "GE1-350", "TD1-1066", "2. Zero hunger", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "T", "Soil Water Retention", "Moderate-resolution imaging spectroradiometer", "Hydrology (agriculture)", "Geology", "[SDU.ENVI] Sciences of the Universe [physics]/Continental interfaces", " environment", "6. Clean water", "Aerospace engineering", "Physical Sciences", "Medicine", "environment", "Vegetation (pathology)", "Latent heat", "Mechanics and Transport in Unsaturated Soils", "Land cover", "Environmental Engineering", "0207 environmental engineering", "Energy balance", "Thermal Effects on Soil", "Environmental science", "[SDU] Sciences of the Universe [physics]", "G", "Meteorology", "Civil engineering", "14. Life underwater", "[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology", "Biology", "Civil and Structural Engineering", "0105 earth and related environmental sciences", "Global Forest Drought Response and Climate Change", "FOS: Environmental engineering", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "Satellite", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Land use", "[SDU.STU.HY] Sciences of the Universe [physics]/Earth Sciences/Hydrology", "[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces", "FOS: Civil engineering"]}, "links": [{"href": "https://hess.copernicus.org/articles/24/1781/2020/hess-24-1781-2020.pdf"}, {"href": "https://doi.org/10.60692/g4rcv-eqz54"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/g4rcv-eqz54", "name": "item", "description": "10.60692/g4rcv-eqz54", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/g4rcv-eqz54"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-23T00:00:00Z"}}, {"id": "10.60692/t1jsz-vm842", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:27:43Z", "type": "Journal Article", "created": "2019-07-29", "title": "EVAPOTRANSPIRATION AND EVAPORATION/TRANSPIRATION RETRIEVAL USING DUAL-SOURCE SURFACE ENERGY BALANCE MODELS INTEGRATING VIS/NIR/TIR DATA WITH SATELLITE SURFACE SOIL MOISTURE INFORMATION", "description": "

Abstract. Evapotranspiration is an important component of the water cycle. For the agronomic management and ecosystem health monitoring, it is also important to provide an estimate of evapotranspiration components, i.e. transpiration and soil evaporation. To do so, Thermal InfraRed data can be used with dual-source surface energy balance models, because they solve separate energy budgets for the soil and the vegetation. But those models rely on specific assumptions on raw levels of plant water stress to get both components (evaporation and transpiration) out of a single source of information, namely the surface temperature. Additional information from remote sensing data are thus required. This works evaluates the ability of the SPARSE dual-source energy balance model to compute not only total evapotranspiration, but also water stress and transpiration/evaporation components, using either the sole surface temperature as a remote sensing driver, or a combination of surface temperature and soil moisture level derived from microwave data. Flux data at an experimental plot in semi-arid Morocco is used to assess this potentiality and shows the increased robustness of both the total evapotranspiration and partitioning retrieval performances. This work is realized within the frame of the Phase A activities for the TRISHNA CNES/ISRO Thermal Infra-Red satellite mission.

", "keywords": ["Technology", "Environmental Engineering", "550", "Ecosystem Resilience", "Soil Moisture", "Evaporation", "Energy balance", "Biochemistry", "Environmental science", "Transpiration", "Meteorology", "Artificial Intelligence", "Soil water", "Thermal Infrared", "Applied optics. Photonics", "Machine Learning Methods for Solar Radiation Forecasting", "Photosynthesis", "TRISHNA", "Water balance", "Biology", "Soil science", "Global and Planetary Change", "Water content", "Evapotranspiration", "Geography", "Ecology", "Global Forest Drought Response and Climate Change", "T", "FOS: Environmental engineering", "Geology", "FOS: Earth and related environmental sciences", "Remote sensing", "15. Life on land", "Engineering (General). Civil engineering (General)", "Remote Sensing of Soil Moisture", "6. Clean water", "TA1501-1820", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "Geotechnical engineering", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Computer Science", "TA1-2040", "Water cycle"]}, "links": [{"href": "https://doi.org/10.60692/t1jsz-vm842"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20International%20Archives%20of%20the%20Photogrammetry%2C%20Remote%20Sensing%20and%20Spatial%20Information%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.60692/t1jsz-vm842", "name": "item", "description": "10.60692/t1jsz-vm842", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.60692/t1jsz-vm842"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-07-26T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=FOS%3A+Earth+and+related+environmental+sciences&offset=50&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=FOS%3A+Earth+and+related+environmental+sciences&offset=50&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "prev", "title": "items (prev)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=FOS%3A+Earth+and+related+environmental+sciences&offset=0", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=FOS%3A+Earth+and+related+environmental+sciences&offset=100", "hreflang": "en-US"}], "numberMatched": 132, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-06-27T05:22:56.140524Z"}