{"type": "FeatureCollection", "features": [{"id": "10.5281/zenodo.8057232", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:24:48Z", "type": "Dataset", "title": "Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning", "description": "Data Description: To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used the MGC approach to segment the United States at 30 arc second resolution based on principal component information from environmental covariates (gNATSGO soil properties, WorldClim bioclimatic variables, MODIS biological variables, and physiographic variables) to 20 SOC regions. We then trained separate random forest model ensembles for each of the SOC regions identified using environmental covariates and soil profile measurements from the International Soil Carbon Network (ISCN) and an Alaska soil profile data. We estimated United States SOC for 0-30 cm and 0-100 cm depths were 52.6 + 3.2 and 108.3 + 8.2 Pg C, respectively. Files in collection (32): Collection contains 22 soil properties geospatial rasters, 4 soil SOC geospatial rasters, 2 ISCN site SOC observations csv files, and 4 R scripts gNATSGO TIF files: \u251c\u2500\u2500 available_water_storage_30arc_30cm_us.tif [30 cm depth soil available water storage]
\u251c\u2500\u2500 available_water_storage_30arc_100cm_us.tif [100 cm depth soil available water storage]
\u251c\u2500\u2500 caco3_30arc_30cm_us.tif [30 cm depth soil CaCO3 content]
\u251c\u2500\u2500 caco3_30arc_100cm_us.tif [100 cm depth soil CaCO3 content]
\u251c\u2500\u2500 cec_30arc_30cm_us.tif [30 cm depth soil cation exchange capacity]
\u251c\u2500\u2500 cec_30arc_100cm_us.tif [100 cm depth soil cation exchange capacity]
\u251c\u2500\u2500 clay_30arc_30cm_us.tif [30 cm depth soil clay content]
\u251c\u2500\u2500 clay_30arc_100cm_us.tif [100 cm depth soil clay content]
\u251c\u2500\u2500 depthWT_30arc_us.tif [depth to water table]
\u251c\u2500\u2500 kfactor_30arc_30cm_us.tif [30 cm depth soil erosion factor]
\u251c\u2500\u2500 kfactor_30arc_100cm_us.tif [100 cm depth soil erosion factor]
\u251c\u2500\u2500 ph_30arc_100cm_us.tif [100 cm depth soil pH]
\u251c\u2500\u2500 ph_30arc_100cm_us.tif [30 cm depth soil pH]
\u251c\u2500\u2500 pondingFre_30arc_us.tif [ponding frequency]
\u251c\u2500\u2500 sand_30arc_30cm_us.tif [30 cm depth soil sand content]
\u251c\u2500\u2500 sand_30arc_100cm_us.tif [100 cm depth soil sand content]
\u251c\u2500\u2500 silt_30arc_30cm_us.tif [30 cm depth soil silt content]
\u251c\u2500\u2500 silt_30arc_100cm_us.tif [100 cm depth soil silt content]
\u251c\u2500\u2500 water_content_30arc_30cm_us.tif [30 cm depth soil water content]
\u2514\u2500\u2500 water_content_30arc_100cm_us.tif [100 cm depth soil water content] SOC TIF files: \u251c\u2500\u250030cm SOC mean.tif [30 cm depth soil SOC]
\u251c\u2500\u2500100cm SOC mean.tif [100 cm depth soil SOC]
\u251c\u2500\u250030cm SOC CV.tif [30 cm depth soil SOC coefficient of variation]
\u2514\u2500\u2500100cm SOC CV.tif [100 cm depth soil SOC coefficient of variation] site observations csv files: ISCN_rmNRCS_addNCSS_30cm.csv 30cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data ISCN_rmNRCS_addNCSS_100cm.csv 100cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data
Data format: Geospatial files are provided in Geotiff format in Lat/Lon WGS84 EPSG: 4326 projection at 30 arc second resolution. Geospatial projection: 
GEOGCS['GCS_WGS_1984', DATUM['D_WGS_1984', SPHEROID['WGS_1984',6378137,298.257223563]], PRIMEM['Greenwich',0], UNIT['Degree',0.017453292519943295]] (base) [jbk@theseus ltar_regionalization]$ g.proj -w GEOGCS['wgs84', DATUM['WGS_1984', SPHEROID['WGS_1984',6378137,298.257223563]], PRIMEM['Greenwich',0], UNIT['degree',0.0174532925199433]]
", "keywords": ["gNATSGO", "the United States SOC", "US soil properties", "15. Life on land", "Gridded National Soil Survey Geographic Database", "International Soil Carbon Network (ISCN)"]}, "links": [{"href": "https://doi.org/10.5281/zenodo.8057232"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8057232", "name": "item", "description": "10.5281/zenodo.8057232", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8057232"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-25T00:00:00Z"}}, {"id": "ONF_Habitats_Limonade", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:30:16Z", "type": "Dataset", "language": "en", "title": "Habitats Limonade: transects to sample the local environmental variability in August 2013.", "description": "The site Limonade is composed of three 3km-transects (20m wide). 3354 trees with dbh>=20cm have been recorded by Office national des for\u00eats (ONF). Fauna inventories have been made by Office national de la chasse et de la faune sauvage (ONCFS) few days after. No under-storey plots on this site. Soils have been described using 16 samples (1.20m depth max.). No laboratory analysis available for soils.", "keywords": ["diameter-measurements", "dispositifs-forestiers-habitats", "forest-composition", "forest-structure", "fr", "labex-ceba", "limonade", "local-coverage", "mesoscale-plot-network", "sampling-plots", "soil", "tree-community", "tree-flora", "tropical-forest-types"]}, "links": [{"href": "http://data.europa.eu/88u/dataset/d24c3a12-7a27-4d7f-8f74-2a3d0ba36e63"}, {"rel": "self", "type": "application/geo+json", "title": "ONF_Habitats_Limonade", "name": "item", "description": "ONF_Habitats_Limonade", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ONF_Habitats_Limonade"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.1002/2016rg000543", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:14:16Z", "type": "Journal Article", "created": "2017-03-23", "title": "A review of spatial downscaling of satellite remotely sensed soil moisture", "description": "Abstract

Satellite remote sensing technology has been widely used to estimate surface soil moisture. Numerous efforts have been devoted to develop global soil moisture products. However, these global soil moisture products, normally retrieved from microwave remote sensing data, are typically not suitable for regional hydrological and agricultural applications such as irrigation management and flood predictions, due to their coarse spatial resolution. Therefore, various downscaling methods have been proposed to improve the coarse resolution soil moisture products. The purpose of this paper is to review existing methods for downscaling satellite remotely sensed soil moisture. These methods are assessed and compared in terms of their advantages and limitations. This review also provides the accuracy level of these methods based on published validation studies. In the final part, problems and future trends associated with these methods are analyzed.Bionanohybrids of carbon nanotubes and fluorescent proteins (FPs) are a promising class of materials for optoelectronic applications. Understanding and controlling the charge transport mechanism between FPs and carbon nanotubes are critical to achieving functional reproducibility and exploring novel synergetic effects. This work demonstrates a novel phenomenon of photocurrent generation in field\uffe2\uff80\uff90effect transistors based on the conjugation of an individual single\uffe2\uff80\uff90walled carbon nanotube (SWCNT) and FPs. When studying the effect of gate voltage on the photoresponse, reversible switching from fast positive to a slow negative photoresponse in bionanohybrids associated with depletion and accumulation modes, respectively is observed. The latter demonstrates a stable memory effect after the light is turned off. It is revealed that in depletion mode, the charge carriers from the protein are not trapped at the interface due to effective screening by the gate potential. It is suggested that the main mechanism in photoresponse switching is a competitive effect between photogating and effective photodoping of the SWCNT by charges trapped at the nanotube interface. The noticeable effect of water molecules can support proton transfer as the main mechanism of charge transfer. This result illustrates that SWCNT/FP bionanohybrids bear great potential for the realization of novel optoelectronic devices.Growing sustainability demands on land have a high knowledge requirement across multiple scientific domains. Exploring networks can expose opportunities for targeting. Using mixed-methods combining social network analysis (SNA) and surveys, networks for key soil functions in case studies in Germany, Ireland and the Netherlands are explored. We find a diversity of contrasting networks that reflect local conditions, sustainability challenges and governance structure. Farmers were found to occupy a central role in the agri-environmental governance network. A comparison of the SNA and survey results indicate low acceptance of messages from many central actors indicating scope to better harness the network for sustainable land management. The source of the messages was important when it came to the implementation of farm management actions. Two pathways for enhanced farmer uptake of multi-functionality are proposed that have wider application are; to increase trust between farmers and actors that are agents of multi-functional messages and/or to increase the bundling or multi-functionality of messages (mandate) of actors trusted by farmers.2 of 0.71 and 0.65 for 2019 and 2020, respectively. The proposed new framework provides an effective method to estimate the salt content in the soil profile for precision agriculture in arid and semi-arid regions.", "keywords": ["2. Zero hunger", "Soil salinity", "Random Forest", "13. Climate action", "Time-series images", "Soil profile", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "Temporal Convolution Network"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2021.115656"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2021.115656", "name": "item", "description": "10.1016/j.geoderma.2021.115656", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2021.115656"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-03-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2022.116072", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:16:48Z", "type": "Journal Article", "created": "2022-08-10", "title": "Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis", "description": "

Soil biopore genesis is a dynamic and context-dependent process. Yet integrative investigations of biopore genesis under varying soil type, tillage and vegetation history are rare. Recent advances in Machine Learning (ML) made faster and more accurate image analysis possible. We validated a model trained on Convolutional Neural Network (CNN) using a multisite dataset from varying soil types (Luvisol, Cambisol and Kandosol), tillage (deep ploughing and without deep ploughing) and vegetation history (taprooted and fibrous-rooted crops) to automatically predict biopore formation. The model trained on the multisite dataset outperformed individually trained single-site models, especially when the dataset contained images with noise and/or fewer biopores. Our model successfully replicated previously established treatment effects but provided new insights at more detailed scales and for different pore-size classes. These insights demonstrated that effects of deep ploughing on soil biopores can persist for more than 50 years and are more pronounced on the Luvisol rather than the Cambisol soil type. The effects of perennial fodder crops with high biopore generating capacity were also shown to persist for at least a decade. re-growing the same fodder crops or a mixture with grass had no further impact on biopore density but generated a shift in pore-size classes from large to smaller biopores. We suspect this is likely to have resulted from three possible scenarios; (1) newly created fine pores (1\u20134 mm); (2) blockage of large-sized pores by earthworm faeces; (3) decrease in pore diameter. In summary, by using a single robust model trained on the multisite dataset, we were able to generate new insights on pore-size distribution as affected by site, vegetation, and deep ploughing. We have demonstrated that Deep Learning-based image analysis can provide easier biopore quantification and can generate models that provide novel insights across different research settings consistently and accurately.

", "keywords": ["2. Zero hunger", "AI", "RootPainter", "0401 agriculture", " forestry", " and fisheries", "Convolutional neural network", "Perennial crops", "04 agricultural and veterinary sciences", "15. Life on land", "Deep tillage", "Subsoil"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2022.116072"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2022.116072", "name": "item", "description": "10.1016/j.geoderma.2022.116072", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2022.116072"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-11-01T00:00:00Z"}}, {"id": "10.1016/j.geodrs.2023.e00716", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:16:49Z", "type": "Journal Article", "created": "2023-09-27", "title": "Stakeholders' point of view on access to soil knowledge in France. What are the opportunities for further improvement?", "description": "Life on earth depends on soil health. However, soils are threatened across the world. To respond to the challenges posed by climate change and soil degradation, there is a need to better integrate scientific soil knowledge into the practice. The aim of this paper is to better understand the access to soil knowledge in France and identify opportunities for further improvement, with a particular focus on the difference of point of view between six categories of stakeholders. This study is based on 1951 responses from a participatory stakeholders\u2019 consultation we conducted in France. Our results showed that most stakeholders considered the knowledge they have access to as not adapted to their needs. They also expressed that knowledge sharing between stakeholders was not sufficient. To improve access to soil knowledge, stakeholders suggested adapting at the territorial level the content of soil knowledge shared and transferred, as well as improving ways of sharing and transfer soil knowledge. Additionally, stakeholders valued different exchange networks based on their type of knowledge. Stakeholders with more theoretical soil knowledge (public authorities, NGOs, researchers) stated being more interested in networks between policy, science and society. However, networks with farmers and advisors were more favored by stakeholders with empirical soil knowledge. Considering our findings, in order to strengthen knowledge transfer and sharing, we encourage the promotion of the profession of scientific mediator, as well as the implementation of Living Labs and Lighthouse farms to bring together various stakeholders at a local level towards innovation, training and education. This will ensure a transition towards a more sustainable soil management in Europe.", "keywords": ["multi-actor consultation", "partage des connaissances", "[SDE] Environmental Sciences", "vision des acteurs", "Knowledge sharing", "consultation multi-acteurs", "visi\u00f3n de los actores", "Exchange networks", "consulta multiactor", "Knowledge transfer", "stakeholder perspective.", "333", "12. Responsible consumption", "intercambio de conocimientos", "transfert de connaissances", "sant\u00e9 des sols", "EJPSOIL", "Soil health", "11. Sustainability", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "transferencia de conocimientos", "2. Zero hunger", "salud de los suelos", "soil health", "9. Industry and infrastructure", "4. Education", "15. Life on land", "knowledge transfer", "16. Peace & justice", "exchange networks", "r\u00e9seaux d'\u00e9changes", "Multi-actor consultation", "6. Clean water", "13. Climate action", "[SDE]Environmental Sciences", "8. Economic growth", "redes de intercambio", "Stakeholder perspective", "knowledge sharing"], "contacts": [{"organization": "Mason, Elo\u00efse, Cornu, Sophie, Chenu, Claire,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.geodrs.2023.e00716"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma%20Regional", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geodrs.2023.e00716", "name": "item", "description": "10.1016/j.geodrs.2023.e00716", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geodrs.2023.e00716"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-12-01T00:00:00Z"}}, {"id": "10.1016/j.geoderma.2017.10.020", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:16:47Z", "type": "Journal Article", "created": "2017-11-06", "title": "Characterising and linking X-ray CT derived macroporosity parameters to infiltration in soils with contrasting structures", "description": "

Soils deliver the regulating ecosystem services of water infiltration and distribution, which can be controlled by macropores. Parameterizing macropore hydraulic properties is challenging due to the lack of direct measurement methods. With tension-disc infiltrometry hydraulic properties near saturation can be measured. Differentiating between hydrologically active and non-active pores, at a given water potential, indirectly assesses macropore continuity. Water flow through macropores is controlled by macropore size distribution, tortuosity, and connectivity, which can be directly derived by X-ray computed tomography (CT). Our objective was to parameterize macropore hydraulic properties based on the imaged macropore network of three horizons of an Andosol and a Gleysol. Hydraulic conductivity K unsat was derived from infiltration measurements. Soil cores from the infiltration areas were scanned with X-ray CT. K unsat was significantly higher in the Andosol than in the Gleysol at all water potentials, and decreased significantly with depth in both soils. The in situ measurements guided the definition of new macroporosity parameters from the X-ray CT reconstructions. For the Andosol, K unsat was best predicted using the imaged-limited macroporosity. A low total macroporosity, coupled with a high macropore density, indicated the abundance of smaller macropores, leading to homogeneous matrix flux. Imaged macropores were not well connected. In contrast, the Gleysol had a bi-modal macropore system with few very large, but well-connected macropores. K unsat was best predicted using the imaged macroporosity consisting only of macropores with diameters between 0.75 and 3 mm. Our research demonstrates that linking traditional soil physical measurements with soil-visualization techniques has a huge potential to improve parameterizing macropore hydraulic properties. The relevance of the relationships found in this study for larger scales and other soil types still needs to be tested, for example by a multi-scale investigation including a much wider range of different soils.

", "keywords": ["[SDE] Environmental Sciences", "Hydraulic parameters", "0207 environmental engineering", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "6. Clean water", "Image analysis", "Tension disc in\ufb01ltrometr", "Tension disc infiltrometry", "Pore network", "13. Climate action", "Soil structure", "[SDE.ES] Environmental Sciences/Environment and Society", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://doi.org/10.1016/j.geoderma.2017.10.020"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoderma", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.geoderma.2017.10.020", "name": "item", "description": "10.1016/j.geoderma.2017.10.020", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.geoderma.2017.10.020"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-03-01T00:00:00Z"}}, {"id": "10.1016/j.jhazmat.2024.134231", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:16:59Z", "type": "Journal Article", "created": "2024-04-06", "title": "Soil microbial community fragmentation reveals indirect effects of fungicide exposure mediated by biotic interactions between microorganisms", "description": "Fungicides are used worldwide to improve crop yields, but they can affect non-target soil microorganisms which are essential for ecosystem functioning. Microorganisms form complex communities characterized by a myriad of interspecies interactions, yet it remains unclear to what extent non-target microorganisms are indirectly affected by fungicides through biotic interactions with sensitive taxa. To quantify such indirect effects, we fragmented a soil microbial community by filtration to alter biotic interactions and compared the effect of the fungicide hymexazol between fractions in soil microcosms. We postulated that OTUs which are indirectly affected would exhibit a different response to the fungicide across the fragmented communities. We found that hymexazol primarily affected bacterial and fungal communities through indirect effects, which were responsible for more than 75% of the shifts in relative abundance of the dominant microbial OTUs after exposure to an agronomic dose of hymexazol. However, these indirect effects decreased for the bacterial community when hymexazol doses increased. Our results also suggest that N-cycling processes such as ammonia oxidation can be impacted indirectly by fungicide application. This work sheds light on the indirect impact of fungicide exposure on soil microorganisms through biotic interactions, which underscores the need for higher-tier risk assessment. ENVIRONMENTAL IMPLICATION: In this study, we used a novel approach based on the fragmentation of the soil microbial community to determine to which extent fungicide application could indirectly affect fungi and bacteria through biotic interactions. To assess off-target effects of fungicide on soil microorganisms, we selected hymexazol, which is used worldwide to control a variety of fungal plant pathogens, and exposed arable soil to the recommended field rate, as well as to higher rates. Our findings show that at least 75% of hymexazol-impacted microbial OTUs were indirectly affected, therefore emphasizing the importance of tiered risk assessment.", "keywords": ["2. Zero hunger", "570", "Bacteria", "hymexazol", "[SDV]Life Sciences [q-bio]", "Microbiota", "Fungi", "500", "[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study", "15. Life on land", "Fungicides", " Industrial", "[SDV] Life Sciences [q-bio]", "nitrogen cycling", "13. Climate action", "network", "ammonia-oxidizing microorganism", "Soil Pollutants", "Microbial Interactions", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "pesticide", "Soil Microbiology"]}, "links": [{"href": "https://doi.org/10.1016/j.jhazmat.2024.134231"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hazardous%20Materials", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhazmat.2024.134231", "name": "item", "description": "10.1016/j.jhazmat.2024.134231", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhazmat.2024.134231"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-01T00:00:00Z"}}, {"id": "10.1016/j.physrep.2020.09.005", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:17:05Z", "type": "Journal Article", "created": "2020-10-03", "title": "Statistical physics approaches to the complex Earth system", "description": "Global climate change, extreme climate events, earthquakes and their accompanying natural disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, strategic interactions and complex structure of the Earth system, the understanding and in particular the predicting of such disruptive events represent formidable challenges for both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge for a better understanding of the Earth system, including climate extreme events, earthquakes and Earth geometric relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as, critical phenomena, network theory, percolation, tipping points analysis, as well as entropy can be applied to complex Earth systems (climate, earthquakes, etc.). Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics approaches can be useful in the field of Earth system science.", "keywords": ["0301 basic medicine", "Physics - Physics and Society", "Earthquake", "550", "Climate Change", "Complex Network", "FOS: Physical sciences", "Physics and Society (physics.soc-ph)", "Complex Earth Systems", "Article", "Physics - Geophysics", "03 medical and health sciences", "S\u00edndrome respiratorio agudo grave", "11. Sustainability", "Condensed Matter - Statistical Mechanics", "0303 health sciences", "Statistical Mechanics (cond-mat.stat-mech)", "SARS-CoV-2", "Statistical Physics", "COVID-19", "500", "Geophysics (physics.geo-ph)", "Coronavirus", "13. Climate action", "Physics - Data Analysis", " Statistics and Probability", "Data Analysis", " Statistics and Probability (physics.data-an)"]}, "links": [{"href": "https://doi.org/10.1016/j.physrep.2020.09.005"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Physics%20Reports", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.physrep.2020.09.005", "name": "item", "description": "10.1016/j.physrep.2020.09.005", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.physrep.2020.09.005"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2020.137065", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:17:13Z", "type": "Journal Article", "created": "2020-02-01", "title": "A new circular business model typology for creating value from agro-waste", "description": "Shifting from a linear to a circular economy in the agrifood domain requires innovative business models, including reverse logistics, new visions on customer-supplier relationships, and new forms of organization and marketing strategies at the crossroads of various value chains. This research aims to identify and characterise different types of business models that create value from agricultural waste and by-products via cascading or closing loops. Conceptual and management insights into circular business models are still sparse. In total, 39 cases have been studied that convert agro-waste and by-products into valuable products via a circular economy approach. Semi-structured interviews and on-site visits of six representative cases have been done, and secondary data been collected. Data has been treated with content analysis. Cases are presented according to the type of organisational structure, resources, transformation processes, value propositions, key partners, customers, strategic approaches and innovation. Six types of circular business models are identified and discussed: biogas plant, upcycling entrepreneurship, environmental biorefinery, agricultural cooperative, agropark and support structure. They differ in their way of value creation and organisational form, but strongly depend on partnerships and their capacity to respond to changing external conditions. This study offers the first circular business model typology within the agricultural domain, revealing the interconnectedness of the six different business model types. It provides options for managers in positioning and adapting their business strategies. It highlights the potential of using biomass first for higher added-value products before exploiting it as energy source. Cascading biomass valorisation at a territorial level will increasingly be important for locally cooperating actors within a circular bioeconomy approach.", "keywords": ["2. Zero hunger", "Circular economy", "[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering", "05 social sciences", "[SDV.IDA] Life Sciences [q-bio]/Food engineering", "650", "Bioeconomy", "Business models", "01 natural sciences", "7. Clean energy", "12. Responsible consumption", "[SDV.IDA]Life Sciences [q-bio]/Food engineering", "0502 economics and business", "8. Economic growth", "Agro-waste valorisation", "[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering", "Networks", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://hal.inrae.fr/hal-02624927/file/2020_Donner_Gohier_Science_Total_Environment_1.pdf"}, {"href": "https://doi.org/10.1016/j.scitotenv.2020.137065"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2020.137065", "name": "item", "description": "10.1016/j.scitotenv.2020.137065", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2020.137065"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-05-01T00:00:00Z"}}, {"id": "10.1016/j.soilbio.2022.108604", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:17:30Z", "type": "Journal Article", "created": "2022-03-18", "title": "From diversity to complexity: Microbial networks in soils", "description": "ABSTRACT

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research.This study assesses the potential of regional microwave backscatter data assimilation (DA) in AquaCrop for the first time, using NASA's Land Information System. The objective is to assess whether the assimilation setup can improve surface soil moisture (SSM) and crop biomass estimates. SSM and crop biomass simulations from AquaCrop were updated using Sentinel\uffe2\uff80\uff901 synthetic aperture radar observations, over three regions in Europe in two separate DA experiments. The first experiment concerned updating SSM using VV\uffe2\uff80\uff90polarized backscatter and the corrections were propagated via the model to the biomass. In the second experiment, the DA setup was extended by also updating the biomass with VH\uffe2\uff80\uff90polarized backscatter. SSM was evaluated with local in situ data and with downscaled Soil Moisture Active Passive (SMAP) retrievals for all cropland grid cells, whereas crop biomass was compared to SMAP vegetation optical depth and the Copernicus dry matter productivity. The assimilation showed mixed results for root mean square error and Pearson's correlation, with slight overall improvements in the (anomaly) correlations of updated SSM relative to independent in situ and satellite data. By contrast, the biomass estimates obtained with backscatter DA did not agree better with reference data sets. Overall, the SSM evaluation showed that there is potential in using Sentinel\uffe2\uff80\uff901 backscatter for assimilation in AquaCrop, but the present setup was not able to improve crop biomass estimates. Our study reveals how the complex interaction between SSM, crop biomass and backscatter affect the impact and performance of DA, offering insight into ways to optimize DA for crop growth estimation. of alginate via 5-dehydro-4-deoxy-D-glucuronate (DDG) and 3-deoxy-D-glycerol-2,5-hexdiulosonate (DGH) as the intermediates to 2-keto-3-deoxy-gluconate (KDG) was constructed based on the metagenomic and metaproteomic analysis. In summary, this work documented the core enzymes and metabolic pathway for alginate degradation, which provides a good paradigm when analyzing the degrading mechanism of unacquainted substrates. The outcome will further contribute to the application of Bacteroides-dominated ADC on WAS methanogenesis in the future.", "keywords": ["DDG and DGH", "alginate-degrading consortia", "Bacteria", "Sewage", "Alginates", "two chemostats in series", "0211 other engineering and technologies", "02 engineering and technology", "01 natural sciences", "6. Clean water", "Glucuronic Acid", "extracellular alginate lyase (EC 4.2.2.3)", "Bacteroides", "new Entner\u2212Doudoroff pathway", "Metabolic Networks and Pathways", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1021/acs.est.1c05289"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/acs.est.1c05289", "name": "item", "description": "10.1021/acs.est.1c05289", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/acs.est.1c05289"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-12-03T00:00:00Z"}}, {"id": "10.1021/acs.est.4c12247", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:17:58Z", "type": "Journal Article", "created": "2025-02-27", "title": "Predicting Toxicity toward Nitrifiers by Attention-Enhanced Graph Neural Networks and Transfer Learning from Baseline Toxicity", "description": "Assessing chemical environmental impacts is critical but challenging due to the time-consuming nature of experimental testing. Graph neural networks (GNNs) support superior prediction performance and mechanistic interpretation of (eco-)toxicity data, but face the risk of overfitting on the typically small experimental data sets. In contrast to purely data-driven approaches, we propose a mechanism-guided transfer learning strategy that is highly efficient and provides key insights into the underlying drivers of (eco-)toxicity. By leveraging the mechanistic link between baseline toxicity and toxicity toward nitrifiers, we pretrained a GNN on lipophilicity data (log P) and subsequently fine-tuned it on the limited data set of toxicity toward nitrifiers, achieving prediction performance comparable with pretraining on much larger but mechanistically less relevant data sets. Additionally, we enhanced GNN interpretability by adjusting multihead attentions after convolutional layers to identify key substructures, and quantified their contributions using a Shapley Value method adapted for graph-structured data with improved computational efficiency. The highlighted substructures aligned well with and effectively distinguished known structural alerts for baseline toxicity and specific modes of toxic action in nitrifiers. The proposed strategy will allow uncovering new structural alerts in other (eco)toxicity data, and thus foster new mechanistic insights to support chemical risk assessment and safe-by-design principles.", "keywords": ["Neural Networks", " Computer", "Nitrification"]}, "links": [{"href": "https://doi.org/10.1021/acs.est.4c12247"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1021/acs.est.4c12247", "name": "item", "description": "10.1021/acs.est.4c12247", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1021/acs.est.4c12247"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-27T00:00:00Z"}}, {"id": "10.1088/1748-9326/aa9c5c", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:01Z", "type": "Journal Article", "created": "2017-11-22", "title": "Gap assessment in current soil monitoring networks across Europe for measuring soil functions", "description": "Soil is the most important natural resource for life on Earth after water. Given its fundamental role in sustaining the human population, both the availability and quality of soil must be managed sustainably and protected. To ensure sustainable management we need to understand the intrinsic functional capacity of different soils across Europe and how it changes over time. Soil monitoring is needed to support evidence-based policies to incentivise sustainable soil management. To this aim, we assessed which soil attributes can be used as potential indicators of five soil functions; (1) primary production, (2) water purification and regulation, (3) carbon sequestration and climate regulation, (4) soil biodiversity and habitat provisioning and (5) recycling of nutrients. We compared this list of attributes to existing national (regional) and EU-wide soil monitoring networks. The overall picture highlighted a clearly unbalanced dataset, in which predominantly chemical soil parameters were included, and soil biological and physical attributes were severely under represented. Methods applied across countries for indicators also varied. At a European scale, the LUCAS-soil survey was evaluated and again confirmed a lack of important soil biological parameters, such as C mineralisation rate, microbial biomass and earthworm community, and soil physical measures such as bulk density. In summary, no current national or European monitoring system exists which has the capacity to quantify the five soil functions and therefore evaluate multi-functional capacity of a soil and in many countries no data exists at all. This paper calls for the addition of soil biological and some physical parameters within the LUCAS-soil survey at European scale and for further development of national soil monitoring schemes.", "keywords": ["[SDE] Environmental Sciences", "570", "[SDV]Life Sciences [q-bio]", "Science", "QC1-999", "soil functions;soil monitoring networks;soil attributes;Europe", "Environmental technology. Sanitary engineering", "630", "12. Responsible consumption", "GE1-350", "TD1-1066", "2. Zero hunger", "Physics", "Q", "04 agricultural and veterinary sciences", "soil functions", "15. Life on land", "S590 Soill / Talajtan", "soil monitoring networks", "6. Clean water", "[SDV] Life Sciences [q-bio]", "Europe", "Environmental sciences", "soil attributes", "13. Climate action", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://hal.inrae.fr/hal-02622332/file/2017_Leeuwen_Environmental%20Research%20Letters_1.pdf"}, {"href": "https://doi.org/10.1088/1748-9326/aa9c5c"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Research%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1088/1748-9326/aa9c5c", "name": "item", "description": "10.1088/1748-9326/aa9c5c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1088/1748-9326/aa9c5c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-01T00:00:00Z"}}, {"id": "10.1038/s41467-021-25665-6", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:18:21Z", "type": "Journal Article", "created": "2021-09-06", "title": "Growth-coupled selection of synthetic modules to accelerate cell factory development.", "description": "Synthetic biology has brought about a conceptual shift in our ability to redesign microbial metabolic networks. Combining metabolic pathway-modularization with growth-coupled selection schemes is a powerful tool that enables deep rewiring of the cell factories\u2019 biochemistry for rational bioproduction.", "keywords": ["0301 basic medicine", "0303 health sciences", "Science", "Q", "Comment", "Recombinant Proteins", "Biological Factors", "03 medical and health sciences", "Metabolic Engineering", "Saccharomycetales", "Escherichia coli", "Life Science", "Humans", "Synthetic Biology", "Metabolic Networks and Pathways"]}, "links": [{"href": "https://www.nature.com/articles/s41467-021-25665-6.pdf"}, {"href": "https://doi.org/10.1038/s41467-021-25665-6"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Communications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41467-021-25665-6", "name": "item", "description": "10.1038/s41467-021-25665-6", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41467-021-25665-6"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-06T00:00:00Z"}}, {"id": "10.1038/s41559-019-1084-y", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:18:23Z", "type": "Journal Article", "created": "2020-02-03", "title": "Multiple elements of soil biodiversity drive ecosystem functions across biomes", "description": "The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Here, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.", "keywords": ["0301 basic medicine", "NETWORK ANALYSIS", "Life on Land", "STERILIZATION METHODS", "biotic communities", "CARBON", "Soil", "03 medical and health sciences", "XXXXXX - Unknown", "Humans", "soils", "Ecosystem", "Soil Microbiology", "biodiversity", "2. Zero hunger", "0303 health sciences", "SEQUENCES", "Fungi", "Biodiversity", "15. Life on land", "COMMUNITY", "13. Climate action", "BACTERIA", "MULTIFUNCTIONALITY", "ecosystems", "MICROBIAL DIVERSITY"]}, "links": [{"href": "https://escholarship.org/content/qt1938c590/qt1938c590.pdf"}, {"href": "https://doi.org/10.1038/s41559-019-1084-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Nature%20Ecology%20%26amp%3B%20Evolution", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1038/s41559-019-1084-y", "name": "item", "description": "10.1038/s41559-019-1084-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1038/s41559-019-1084-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-03T00:00:00Z"}}, {"id": "10.1039/c9ew00220k", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:18:30Z", "type": "Journal Article", "created": "2019-04-29", "title": "Long-term performance evaluation of an anoxic sulfur oxidizing moving bed biofilm reactor under nitrate limited conditions", "description": "

An anoxic sulfur-oxidizing moving bed biofilm reactor (MBBR) treating sulfur and nitrate-contaminated synthetic wastewater was monitored for 306 days under feed nitrogen-to-sulfur (N/S) molar ratios of 0.5, 0.3 and 0.1.

", "keywords": ["Aurora Universities Network", "570", "Horizon 2020", "EC", "Environmental Engineering", "218 Environmental engineering", "116 Chemical sciences", "H2020", "116", "6. Clean water", "218", "European Joint Doctorates", "11. Sustainability", "European Commission", "Knowmad Institut", "Netherlands", "Water Science and Technology"]}, "links": [{"href": "http://pubs.rsc.org/en/content/articlepdf/2019/EW/C9EW00220K"}, {"href": "https://doi.org/10.1039/c9ew00220k"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%3A%20Water%20Research%20%26amp%3B%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1039/c9ew00220k", "name": "item", "description": "10.1039/c9ew00220k", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1039/c9ew00220k"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-01-01T00:00:00Z"}}, {"id": "10.1039/d0mt00043d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:18:30Z", "type": "Journal Article", "created": "2020-05-20", "title": "Biomolecular approaches to understanding metal tolerance and hyperaccumulation in plants", "description": "Abstract

Trace metal elements are essential for plant growth but become toxic at high concentrations, while some non-essential elements, such as Cd and As, show toxicity even in traces. Thus, metal homeostasis is tightly regulated in plants. Plant species colonising metalliferous soils have evolved mechanisms to hypertolerate metals and, in rare cases, can hyperaccumulate them in excess amounts in their shoots. The molecular mechanisms of metal hypertolerance and hyperaccumulation are likely derived from alterations in the basic mechanisms involved in general metal homeostasis. Genes involved in metal transport, synthesis of metal chelators and oxidative stress responses are constitutively and highly expressed in metal hypertolerant and hyperaccumulator species. Plant specialized metabolites and cell wall components have been proposed as major players in these mechanisms. In addition, the high intra-specific natural variation of metal hypertolerance and hyperaccumulation suggests that various molecular mechanisms might be involved in the evolution of these traits. To date, the potential of wild plant populations as systems to study metal tolerance and hyperaccumulation has not been fully exploited. The advent of next-generation sequencing (NGS) has enabled the study of non-model species, providing an opportunity to study natural populations and new tolerant and/or hyperaccumulating species, and will provide new insights into metal tolerance and hyperaccumulation. In this review we highlight background knowledge about metal tolerance and hyperaccumulation in plants and the current state-of-the-art techniques to study and identify the underlying mechanisms of metal hypertolerance and hyperaccumulation. We also outline for the reader the importance of the multidisciplinarity of this research field and how the integration of multiomic approaches will benefit facing the future scientific challenges.A dramatic evolution of fruit size has accompanied the domestication and improvement of fruit-bearing crop species. In tomato (Solanum lycopersicum), naturally occurring cis-regulatory mutations in the genes of the CLAVATA-WUSCHEL signaling pathway have led to a significant increase in fruit size generating enlarged meristems that lead to flowers with extra organs and bigger fruits. In this work, by combining mapping-by-sequencing and CRISPR/Cas9 genome editing methods, we isolatedEXCESSIVE NUMBER OF FLORAL ORGANS(ENO), an AP2/ERF transcription factor which regulates floral meristem activity. Thus, theENOgene mutation gives rise to plants that yield larger multilocular fruits due to an increased size of the floral meristem. Genetic analyses indicate thatenoexhibits synergistic effects with mutations at theLOCULE NUMBER(encodingSlWUS) andFASCIATED(encodingSlCLV3) loci, two central players in the evolution of fruit size in the domestication of cultivated tomatoes. Our findings reveal that anenomutation causes a substantial expansion ofSlWUSexpression domains in a flower-specific manner. In vitro binding results show that ENO is able to interact with the GGC-box cis-regulatory element within theSlWUSpromoter region, suggesting that ENO directly regulatesSlWUSexpression domains to maintain floral stem-cell homeostasis. Furthermore, the study of natural allelic variation of theENOlocus proved that a cis-regulatory mutation in the promoter ofENOhad been targeted by positive selection during the domestication process, setting up the background for significant increases in fruit locule number and fruit size in modern tomatoes.

", "keywords": ["0301 basic medicine", "570", "Floral meristem", "[SPI] Engineering Sciences [physics]", "[SDV]Life Sciences [q-bio]", "Meristem", "Quantitative Trait Loci", "Genes", " Plant", "CLAVATA/WUSCHEL regulatory network", "Domestication", "[SPI]Engineering Sciences [physics]", "03 medical and health sciences", "Solanum lycopersicum", "Gene Expression Regulation", " Plant", "AP2/ERF transcription factor", "Promoter Regions", " Genetic", "Cell Proliferation", "Plant Proteins", "580", "Homeodomain Proteins", "2. Zero hunger", "Tomato (Solanum lycopersicum)", "0303 health sciences", "Stem Cells", "Biological Sciences", "15. Life on land", "fruit size", "Crop Production", "[SDV] Life Sciences [q-bio]", "CLAVATA-WUSCHEL regulatory network", "GENETICA", "Fruit", "Mutation", "Fruit size", "floral meristem", "Transcription Factors"]}, "links": [{"href": "https://pnas.org/doi/pdf/10.1073/pnas.1913688117"}, {"href": "https://doi.org/10.1073/pnas.1913688117"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Proceedings%20of%20the%20National%20Academy%20of%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1073/pnas.1913688117", "name": "item", "description": "10.1073/pnas.1913688117", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1073/pnas.1913688117"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-16T00:00:00Z"}}, {"id": "10.1093/bioinformatics/btz584", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:03Z", "type": "Journal Article", "created": "2019-08-19", "title": "MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network", "description": "Abstract Motivation

Analysis of differential expression of genes is often performed to understand how the metabolic activity of an organism is impacted by a perturbation. However, because the system of metabolic regulation is complex and all changes are not directly reflected in the expression levels, interpreting these data can be difficult.

Results

In this work, we present a new algorithm and computational tool that uses a genome-scale metabolic reconstruction to infer metabolic changes from differential expression data. Using the framework of constraint-based analysis, our method produces a qualitative hypothesis of a change in metabolic activity. In other words, each reaction of the network is inferred to have increased, decreased, or remained unchanged in flux. In contrast to similar previous approaches, our method does not require a biological objective function and does not assign on/off activity states to genes. An implementation is provided and it is available online. We apply the method to three published datasets to show that it successfully accomplishes its two main goals: confirming or rejecting metabolic changes suggested by differentially expressed genes based on how well they fit in as parts of a coordinated metabolic change, as well as inferring changes in reactions whose genes did not undergo differential expression.

Availability and implementation

github.com/htpusa/moomin.

Supplementary information

Supplementary data are available at Bioinformatics online.

", "keywords": ["0301 basic medicine", "570", "[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]", "Metabolic networks; omics data", "Genome", "[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]", "0206 medical engineering", "610", "Computational Biology", "[INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS]", "02 engineering and technology", "[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]", "Original Papers", "Models", " Biological", "03 medical and health sciences", "[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]", "Algorithms", "Metabolic Networks and Pathways", "[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]"]}, "links": [{"href": "https://iris.uniroma1.it/bitstream/11573/1321358/5/Pusa_MOOMIN_2020.pdf"}, {"href": "https://academic.oup.com/bioinformatics/article-pdf/36/2/514/48991611/btz584.pdf"}, {"href": "https://doi.org/10.1093/bioinformatics/btz584"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Bioinformatics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/bioinformatics/btz584", "name": "item", "description": "10.1093/bioinformatics/btz584", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/bioinformatics/btz584"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-08-22T00:00:00Z"}}, {"id": "10.1093/jxb/erab174", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:05Z", "type": "Journal Article", "created": "2020-12-03", "title": "Digging roots is easier with AI", "description": "Abstract

The scale of root quantification in research is often limited by the time required for sampling, measurement and processing samples. Recent developments in Convolutional Neural Networks (CNN) have made faster and more accurate plant image analysis possible which may significantly reduce the time required for root measurement, but challenges remain in making these methods accessible to researchers without an in-depth knowledge of Machine Learning. We analyzed root images acquired from three destructive root samplings using the RootPainter CNN-software that features an interface for corrective annotation for easier use. Root scans with and without non-root debris were used to test if training a model, i.e., learning from labeled examples, can effectively exclude the debris by comparing the end-results with measurements from clean images. Root images acquired from soil profile walls and the cross-section of soil cores were also used for training and the derived measurements were compared with manual measurements. After 200 minutes of training on each dataset, significant relationships between manual measurements and RootPainter-derived data were noted for monolith (R2=0.99), profile wall (R2=0.76) and core-break (R2=0.57). The rooting density derived from images with debris was not significantly different from that derived from clean images after processing with RootPainter. Rooting density was also successfully calculated from both profile wall and soil core images, and in each case the gradient of root density with depth was not significantly different from manual counts. Our results demonstrate that the proposed approach using CNN can lead to substantial reductions in root sample processing workloads, increasing the potential scale of future root investigations.

", "keywords": ["0301 basic medicine", "root phenotyping", "profile wall", "root washing", "segmentation", "deep learning", "Convolutional neural network", "04 agricultural and veterinary sciences", "15. Life on land", "Soil", "03 medical and health sciences", "core-break", "monolith", "soil coring", "Image Processing", " Computer-Assisted", "0401 agriculture", " forestry", " and fisheries", "Neural Networks", " Computer", "Software"]}, "links": [{"href": "http://academic.oup.com/jxb/article-pdf/72/13/4680/38807872/erab174.pdf"}, {"href": "https://doi.org/10.1093/jxb/erab174"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Experimental%20Botany", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/jxb/erab174", "name": "item", "description": "10.1093/jxb/erab174", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/jxb/erab174"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-02T00:00:00Z"}}, {"id": "10.1093/mnras/staa3201", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:06Z", "type": "Journal Article", "created": "2020-10-16", "title": "Quantifying the structure of strong gravitational lens potentials with uncertainty-aware deep neural networks", "description": "ABSTRACT

Gravitational lensing is a powerful tool for constraining substructure in the mass distribution of galaxies, be it from the presence of dark matter sub-haloes or due to physical mechanisms affecting the baryons throughout galaxy evolution. Such substructure is hard to model and is either ignored by traditional, smooth modelling, approaches, or treated as well-localized massive perturbers. In this work, we propose a deep learning approach to quantify the statistical properties of such perturbations directly from images, where only the extended lensed source features within a mask are considered, without the need of any lens modelling. Our training data consist of mock lensed images assuming perturbing Gaussian Random Fields permeating the smooth overall lens potential, and, for the first time, using images of real galaxies as the lensed source. We employ a novel deep neural network that can handle arbitrary uncertainty intervals associated with the training data set labels as input, provides probability distributions as output, and adopts a composite loss function. The method succeeds not only in accurately estimating the actual parameter values, but also reduces the predicted confidence intervals by 10\uffc2\uffa0per\uffe2\uff80\uff89cent in an unsupervised manner, i.e. without having access to the actual ground truth values. Our results are invariant to the inherent degeneracy between mass perturbations in the lens and complex brightness profiles for the source. Hence, we can quantitatively and robustly quantify the smoothness of the mass density of thousands of lenses, including confidence intervals, and provide a consistent ranking for follow-up science.

", "keywords": ["Physics", "Gravitational lens", "Space and Planetary Science", "Astrophysics of Galaxies (astro-ph.GA)", "0103 physical sciences", "Deep neural networks", "FOS: Physical sciences", "Astronomy and Astrophysics", "Statistical physics", "Astrophysics - Astrophysics of Galaxies", "01 natural sciences"]}, "links": [{"href": "http://academic.oup.com/mnras/article-pdf/499/4/5641/34141333/staa3201.pdf"}, {"href": "https://doi.org/10.1093/mnras/staa3201"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Monthly%20Notices%20of%20the%20Royal%20Astronomical%20Society", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/mnras/staa3201", "name": "item", "description": "10.1093/mnras/staa3201", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/mnras/staa3201"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-10-17T00:00:00Z"}}, {"id": "10.1186/s40168-018-0572-7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:20:05Z", "type": "Journal Article", "created": "2018-10-18", "title": "Consistent responses of soil microbial taxonomic and functional attributes to mercury pollution across China", "description": "The ecological consequences of mercury (Hg) pollution-one of the major pollutants worldwide-on microbial taxonomic and functional attributes remain poorly understood and largely unexplored. Using soils from two typical Hg-impacted regions across China, here, we evaluated the role of Hg pollution in regulating bacterial abundance, diversity, and co-occurrence network. We also investigated the associations between Hg contents and the relative abundance of microbial functional genes by analyzing the soil metagenomes from a subset of those sites.We found that soil Hg largely influenced the taxonomic and functional attributes of microbial communities in the two studied regions. In general, Hg pollution was negatively related to bacterial abundance, but positively related to the diversity of bacteria in two separate regions. We also found some consistent associations between soil Hg contents and the community composition of bacteria. For example, soil total Hg content was positively related to the relative abundance of Firmicutes and Bacteroidetes in both paddy and upland soils. In contrast, the methylmercury (MeHg) concentration was negatively correlated to the relative abundance of Nitrospirae in the two types of soils. Increases in soil Hg pollution correlated with drastic changes in the relative abundance of ecological clusters within the co-occurrence network of bacterial communities for the two regions. Using metagenomic data, we were also able to detect the effect of Hg pollution on multiple functional genes relevant to key soil processes such as element cycles and Hg transformations (e.g., methylation and reduction).Together, our study provides solid evidence that Hg pollution has predictable and significant effects on multiple taxonomic and functional attributes including bacterial abundance, diversity, and the relative abundance of ecological clusters and functional genes. Our results suggest an increase in soil Hg pollution linked to human activities will lead to predictable shifts in the taxonomic and functional attributes in the Hg-impacted areas, with potential implications for sustainable management of agricultural ecosystems and elsewhere.", "keywords": ["0301 basic medicine", "570", "China", "550", "Co-occurrence network", "Firmicutes", "333", "12. Responsible consumption", "Microbial ecology", "Soil", "03 medical and health sciences", "XXXXXX - Unknown", "Soil Pollutants", "Soil Microbiology", "2. Zero hunger", "Bacteroidetes", "Research", "Microbiota", "QR100-130", "Biodiversity", "Mercury", "Methylmercury Compounds", "15. Life on land", "Mercury pollution", "6. Clean water", "13. Climate action", "Soil microbial community", "Metagenome", "Metagenomics", "Functional gene", "Environmental Pollution", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1186/s40168-018-0572-7"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microbiome", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1186/s40168-018-0572-7", "name": "item", "description": "10.1186/s40168-018-0572-7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1186/s40168-018-0572-7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-18T00:00:00Z"}}, {"id": "10.1099/mic.0.000931", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:19:11Z", "type": "Journal Article", "created": "2020-05-22", "title": "Microbial metabolism of isoprene: a much-neglected climate-active gas", "description": "

The climate-active gas isoprene is the major volatile produced by a variety of trees and is released into the atmosphere in enormous quantities, on a par with global emissions of methane. While isoprene production in plants and its effect on atmospheric chemistry have received considerable attention, research into the biological isoprene sink has been neglected until recently. Here, we review current knowledge on the sources and sinks of isoprene and outline its environmental effects. Focusing on degradation by microbes, many of which are able to use isoprene as the sole source of carbon and energy, we review recent studies characterizing novel isoprene degraders isolated from soils, marine sediments and in association with plants. We describe the development and use of molecular methods to identify, quantify and genetically characterize isoprene-degrading strains in environmental samples. Finally, this review identifies research imperatives for the further study of the environmental impact, ecology, regulation and biochemistry of this interesting group of microbes.

", "keywords": ["0301 basic medicine", "0303 health sciences", "550", "Bacteria", "Review", "Plants", "15. Life on land", "03 medical and health sciences", "Biodegradation", " Environmental", "Hemiterpenes", "Genes", " Bacterial", "13. Climate action", "8. Economic growth", "Butadienes", "Seawater", "Metabolic Networks and Pathways", "Soil Microbiology"]}, "links": [{"href": "https://ueaeprints.uea.ac.uk/id/eprint/75324/1/Published_Version.pdf"}, {"href": "https://repository.essex.ac.uk/29368/1/Microbial%20metabolism%20of%20isoprene%20a%20much-neglected%20climate-active%20gas.pdf"}, {"href": "https://doi.org/10.1099/mic.0.000931"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1099/mic.0.000931", "name": "item", "description": "10.1099/mic.0.000931", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1099/mic.0.000931"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-07-01T00:00:00Z"}}, {"id": "10.3390/su12072578", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:02Z", "type": "Journal Article", "created": "2020-03-25", "title": "The Complex Pathway towards Farm-Level Sustainable Intensification: An Exploratory Network Analysis of Stakeholders\u2019 Knowledge and Perception", "description": "

Farm-level sustainable intensification of agriculture (SIA) has become an important concept to ensuring food security while minimising negative externalities. However, progress towards its achievement is often constrained by the different perceptions and goals of various stakeholders that affect farm management decisions. This study examines farm-level SIA as a dynamic system with interactive components that are determined by the interests of the stakeholders involved. A systems thinking approach was used to identify and describe the pathways towards farm-level SIA across the three main pillars of sustainability. An explanatory network analysis of fuzzy cognitive maps (FCMs) that were collectively created by representative groups of farmers, farm advisors and policy makers was performed. The study shows that SIA is a complex dynamic system, affected by cognitive beliefs and particular knowledge within stakeholder groups. The study concludes that, although farm-level SIA is a complex process, common goals can be identified in collective decision making.

", "keywords": ["2. Zero hunger", "S1", "fuzzy cognitive mapping", "sustainable intensification", "0211 other engineering and technologies", "02 engineering and technology", "S604.5_Agricultural", "15. Life on land", "01 natural sciences", "12. Responsible consumption", "mental models", "stakeholder views", "network analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://eprints.glos.ac.uk/8258/1/sustainability-12-02578.pdf"}, {"href": "http://www.mdpi.com/2071-1050/12/7/2578/pdf"}, {"href": "https://www.mdpi.com/2071-1050/12/7/2578/pdf"}, {"href": "https://doi.org/10.3390/su12072578"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/su12072578", "name": "item", "description": "10.3390/su12072578", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/su12072578"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-03-25T00:00:00Z"}}, {"id": "10.1111/gcb.14306", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:25Z", "type": "Journal Article", "created": "2018-05-11", "title": "Effects of climate legacies on above- and belowground community assembly", "description": "Abstract

The role of climatic legacies in regulating community assembly of above\uffe2\uff80\uff90 and belowground species in terrestrial ecosystems remains largely unexplored and poorly understood. Here, we report on two separate regional and continental empirical studies, including >500 locations, aiming to identify the relative importance of climatic legacies (climatic anomaly over the last 20,000\uffc2\uffa0years) compared to current climates in predicting the relative abundance of ecological clusters formed by species strongly co\uffe2\uff80\uff90occurring within two independent above\uffe2\uff80\uff90 and belowground networks. Climatic legacies explained a significant portion of the variation in the current community assembly of terrestrial ecosystems (up to 15.4%) that could not be accounted for by current climate, soil properties, and management. Changes in the relative abundance of ecological clusters linked to climatic legacies (e.g., past temperature) showed the potential to indirectly alter other clusters, suggesting cascading effects. Our work illustrates the role of climatic legacies in regulating ecosystem community assembly and provides further insights into possible winner and loser community assemblies under global change scenarios.

", "keywords": ["0301 basic medicine", "0303 health sciences", "Climate Change", "Australia", "Fungi", "Forests", "15. Life on land", "Bacterial Physiological Phenomena", "Invertebrates", "Trees", "Soil", "03 medical and health sciences", "13. Climate action", "XXXXXX - Unknown", "Vertebrates", "Animals", "Paleoclimate", " Bacteria", " Fungi", " Plants", " Animals", " Terrestrial ecosystems", " Ecological networks.", "Soil Microbiology"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/gcb.14306"}, {"href": "https://doi.org/10.1111/gcb.14306"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Global%20Change%20Biology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/gcb.14306", "name": "item", "description": "10.1111/gcb.14306", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/gcb.14306"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-05-30T00:00:00Z"}}, {"id": "10.1128/aem.02209-19", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:54Z", "type": "Journal Article", "created": "2019-12-04", "title": "Casimicrobium huifangae gen. nov., sp. nov., a Ubiquitous \u201cMost-Wanted\u201d Core Bacterial Taxon from Municipal Wastewater Treatment Plants", "description": "

The activated sludge process is the most widely applied biotechnology and is one of the best ecosystems to address microbial ecological principles. Yet, the cultivation of core bacteria and the exploration of their physiology and ecology are limited. In this study, the core and novel bacterial taxon C. huifangae was cultivated and characterized. This study revealed that C. huifangae functioned as an important module hub in the activated sludge microbiome, and it potentially plays an important role in municipal wastewater treatment plants.

", "keywords": ["0301 basic medicine", "activated sludge microbiome", "DATABASE", "DIVERSITY", "nitrogen and phosphorus removal", "GENOME ANNOTATION", "POLYPHOSPHATE-ACCUMULATING ORGANISMS", "12. Responsible consumption", "ACTIVATED-SLUDGE", "03 medical and health sciences", "SEARCH", "RNA", " Ribosomal", " 16S", "11. Sustainability", "microbial network", "Phylogeny", "WWTP", "0303 health sciences", "IDENTIFICATION", "Sewage", "Microbiota", "Betaproteobacteria", "core taxa", "15. Life on land", "6. Clean water", "COMMUNITY", "RNA", " Bacterial", "Casimicrobium huifangae", "13. Climate action", "Earth and Environmental Sciences", "BIOLOGICAL PHOSPHORUS REMOVAL", "municipal wastewater treatment plant", "CARBON SOURCE"]}, "links": [{"href": "https://journals.asm.org/doi/pdf/10.1128/AEM.02209-19"}, {"href": "https://doi.org/10.1128/aem.02209-19"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.02209-19", "name": "item", "description": "10.1128/aem.02209-19", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.02209-19"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-02-03T00:00:00Z"}}, {"id": "10.1111/nph.15123", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:48Z", "type": "Journal Article", "created": "2018-03-31", "title": "Quantifying soil moisture impacts on light use efficiency across biomes", "description": "Summary

Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology.

Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness.

This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub\uffe2\uff80\uff90humid, semi\uffe2\uff80\uff90arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions.

fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly\uffe2\uff80\uff90based drought indices. Counter to common assumptions, fLUE reductions are largest in drought\uffe2\uff80\uff90deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought\uffe2\uff80\uff90related assessments.

We present RootPainter, a GUI-based software tool for the rapid training of deep neural networks for use in biological image analysis. RootPainter facilitates both fully-automatic and semi-automatic image segmentation. We investigate the effectiveness of RootPainter using three plant image datasets, evaluating its potential for root length extraction from chicory roots in soil, biopore counting and root nodule counting from scanned roots. We also use RootPainter to compare dense annotations to corrective ones which are added during the training based on the weaknesses of the current model.

", "keywords": ["Buildings and machinery", "0301 basic medicine", "phenotyping", "root nodule", "biopore", "interactive machine learning", "Research", "segmentation", "deep learning", "rhizotron", "Breeding and genetics", "Machine Learning", "Soil", "03 medical and health sciences", "Deep Learning", "GUI", "Farm nutrient management", "Image Processing", " Computer-Assisted", "Neural Networks", " Computer"]}, "links": [{"href": "https://www.biorxiv.org/content/10.1101/2020.04.16.044461v1.full.pdf"}, {"href": "https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/nph.18387"}, {"href": "https://doi.org/10.1111/nph.18387"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/New%20Phytologist", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/nph.18387", "name": "item", "description": "10.1111/nph.18387", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/nph.18387"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-04-18T00:00:00Z"}}, {"id": "10.1111/pce.14143", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:50Z", "type": "Journal Article", "created": "2021-06-17", "title": "Convergent evolution of gene regulatory networks underlying plant adaptations to dry environments", "description": "

p1Plants transitioned from an aquatic to a terrestrial lifestyle during their evolution. On land, fluctuations on water availability in the environment became one of the major problems they encountered. The appearance of morpho-physiological adaptations to cope with and tolerate water loss from the cells was undeniably useful to survive on dry land. Some of these adaptations, such as carbon concentrating mechanisms (CCMs), desiccation tolerance (DT) and root impermeabilization, appeared in multiple plant lineages. Despite being crucial for evolution on land, it has been unclear how these adaptations convergently evolved in the various plant lineages. Recent advances on whole genome and transcriptome sequencing are revealing that co-option of genes and gene regulatory networks (GRNs) is a common feature underlying the convergent evolution of these adaptations. In this review we address how the study of CCMs and DT have provided insight into convergent evolution of GRNs underlying plant adaptation to dry environments, and how these insights could be applied to currently emerging understanding of evolution of root impermeabilization through different barrier cell types. We discuss examples of co-option, conservation, and innovation of genes and GRNs at the cell, tissue and organ levels revealed by recent phylogenomic (comparative genomic) and comparative transcriptomic studies.

", "keywords": ["0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Physiology", "desiccation tolerance", "exodermis", "Adaptation", " Biological", "Reviews", "Plant Science", "comparative genomics", "Plants", "15. Life on land", "Genes", " Plant", "Biological Evolution", "03 medical and health sciences", "apoplastic barriers", "Gene Regulatory Networks", "Desert Climate"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/pce.14143"}, {"href": "https://doi.org/10.1111/pce.14143"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Plant%2C%20Cell%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/pce.14143", "name": "item", "description": "10.1111/pce.14143", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/pce.14143"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-06-17T00:00:00Z"}}, {"id": "10.1111/wre.12255", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:19:52Z", "type": "Journal Article", "created": "2017-05-25", "title": "Big Data for weed control and crop protection", "description": "Summary

Farmers have access to many data\uffe2\uff80\uff90intensive technologies to help them monitor and control weeds and pests. Data collection, data modelling and analysis, and data sharing have become core challenges in weed control and crop protection. We review the challenges and opportunities of Big Data in agriculture: the nature of data collected, Big Data analytics and tools to present the analyses that allow improved crop management decisions for weed control and crop protection. Big Data storage and querying incurs significant challenges, due to the need to distribute data across several machines, as well as due to constantly growing and evolving data from different sources. Semantic technologies are helpful when data from several sources are combined, which involves the challenge of detecting interactions of potential agronomic importance and establishing relationships between data items in terms of meanings and units. Data ownership is analysed using the ethical matrix method to identify the concerns of farmers, agribusiness owners, consumers and the environment. Big Data analytics models are outlined, together with numerical algorithms for training them. Advances and tools to present processed Big Data in the form of actionable information to farmers are reviewed, and a success story from the Netherlands is highlighted. Finally, it is argued that the potential utility of Big Data for weed control is large, especially for invasive, parasitic and herbicide\uffe2\uff80\uff90resistant weeds. This potential can only be realised when agricultural scientists collaborate with data scientists and when organisational, ethical and legal arrangements of data sharing are established. Various agriculture management practices may have distinct influences on soil microbial communities and their ecological functions. In this study, we utilized GeoChip, a high-throughput microarray-based technique containing approximately 28,000 probes for genes involved in nitrogen (N)/carbon (C)/sulfur (S)/phosphorus (P) cycles and other processes, to evaluate the potential functions of soil microbial communities under conventional (CT), low-input (LI), and organic (ORG) management systems at an agricultural research site in Michigan. Compared to CT, a high diversity of functional genes was observed in LI. The functional gene diversity in ORG did not differ significantly from that of either CT or LI. Abundances of genes encoding enzymes involved in C/N/P/S cycles were generally lower in CT than in LI or ORG, with the exceptions of genes in pathways for lignin degradation, methane generation/oxidation, and assimilatory N reduction, which all remained unchanged. Canonical correlation analysis showed that selected soil (bulk density, pH, cation exchange capacity, total C, C/N ratio, NO 3 \uffe2\uff88\uff92 , NH 4 + , available phosphorus content, and available potassium content) and crop (seed and whole biomass) variables could explain 69.5% of the variation of soil microbial community composition. Also, significant correlations were observed between NO 3 \uffe2\uff88\uff92 concentration and denitrification genes, NH 4 + concentration and ammonification genes, and N 2 O flux and denitrification genes, indicating a close linkage between soil N availability or process and associated functional genes.

", "keywords": ["2. Zero hunger", "Michigan", "Nitrogen", "Agriculture", "Phosphorus", "04 agricultural and veterinary sciences", "15. Life on land", "Microarray Analysis", "Biota", "Carbon", "Soil", "Genes", " Bacterial", "Metagenome", "0401 agriculture", " forestry", " and fisheries", "Metabolic Networks and Pathways", "Soil Microbiology", "Sulfur"]}, "links": [{"href": "https://doi.org/10.1128/aem.03393-12"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.03393-12", "name": "item", "description": "10.1128/aem.03393-12", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.03393-12"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-02-15T00:00:00Z"}}, {"id": "10.1128/aem.04040-14", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:54Z", "type": "Journal Article", "created": "2015-01-24", "title": "Fungal Communities Respond To Long-Term Co2 Elevation By Community Reassembly", "description": "ABSTRACT

Fungal communities play a major role as decomposers in the Earth's ecosystems. Their community-level responses to elevated CO 2 (eCO 2 ), one of the major global change factors impacting ecosystems, are not well understood. Using 28S rRNA gene amplicon sequencing and co-occurrence ecological network approaches, we analyzed the response of soil fungal communities in the BioCON (biodiversity, CO 2 , and N deposition) experimental site in Minnesota, USA, in which a grassland ecosystem has been exposed to eCO 2 for 12 years. Long-term eCO 2 did not significantly change the overall fungal community structure and species richness, but significantly increased community evenness and diversity. The relative abundances of 119 operational taxonomic units (OTU; \uffe2\uff88\uffbc27% of the total captured sequences) were changed significantly. Significantly changed OTU under eCO 2 were associated with decreased overall relative abundance of Ascomycota, but increased relative abundance of Basidiomycota. Co-occurrence ecological network analysis indicated that eCO 2 increased fungal community network complexity, as evidenced by higher intermodular and intramodular connectivity and shorter geodesic distance. In contrast, decreased connections for dominant fungal species were observed in the eCO 2 network. Community reassembly of unrelated fungal species into highly connected dense modules was observed. Such changes in the co-occurrence network topology were significantly associated with altered soil and plant properties under eCO 2 , especially with increased plant biomass and NH 4 + availability. This study provided novel insights into how eCO 2 shapes soil fungal communities in grassland ecosystems.

", "keywords": ["580", "0301 basic medicine", "0303 health sciences", "electric network topology", "Minnesota", "Molecular Sequence Data", "Fungi", "carbon dioxide", "Sequence Analysis", " DNA", "Carbon Dioxide", "15. Life on land", "Biota", "DNA", " Ribosomal", "333", "03 medical and health sciences", "13. Climate action", "XXXXXX - Unknown", "RNA", " Ribosomal", " 28S", "11. Sustainability", "fungi", "ecology", "DNA", " Fungal", "Soil Microbiology", "biodiversity"]}, "links": [{"href": "https://doi.org/10.1128/aem.04040-14"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Applied%20and%20Environmental%20Microbiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/aem.04040-14", "name": "item", "description": "10.1128/aem.04040-14", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/aem.04040-14"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-04-01T00:00:00Z"}}, {"id": "10.1128/msystems.00344-21", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:19:55Z", "type": "Journal Article", "created": "2021-05-10", "title": "Network Properties of Local Fungal Communities Reveal the Anthropogenic Disturbance Consequences of Farming Practices in Vineyard Soils", "description": "

Soil fungal communities play a key role in agroecosystem sustainability. The complexity of fungal communities, at both taxonomic and functional levels, makes it difficult to find clear patterns connecting community composition with ecosystem function and to understand the impact of biotic (interspecies interactions) and abiotic (e.g., climate or anthropogenic disturbances) factors on it.

", "keywords": ["Ecolog\u00eda (Biolog\u00eda)", "0301 basic medicine", "2. Zero hunger", "0303 health sciences", "agroecosystems", "local networks", "Local networks", "Microbiolog\u00eda (Biolog\u00eda)", "579", "Ecolog\u00eda", "Emergent properties", "15. Life on land", "Microbiolog\u00eda", "fungal communities", "Microbiology", "574", "QR1-502", "Fungal communities", "03 medical and health sciences", "2401.06 Ecolog\u00eda animal", "emergent properties", "11. Sustainability", "2414 Microbiolog\u00eda", "Agroecosystems", "Research Article"]}, "links": [{"href": "https://journals.asm.org/doi/pdf/10.1128/mSystems.00344-21"}, {"href": "https://doi.org/10.1128/msystems.00344-21"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/mSystems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1128/msystems.00344-21", "name": "item", "description": "10.1128/msystems.00344-21", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1128/msystems.00344-21"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-06-29T00:00:00Z"}}, {"id": "10.1371/journal.pone.0303745", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:20:16Z", "type": "Journal Article", "created": "2024-05-23", "title": "Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania", "description": "

The Chesapeake Bay watershed is representative of governance challenges relating to agricultural nonpoint source pollution and, more generally, of sustainable resources governance in complex multi-actor settings. We assess information flows around Best Management Practices (BMPs) undertaken by dairy farmers in central Pennsylvania, a subregion of the watershed. We apply a mixed-method approach, combining Social Network Analysis, the analysis of BMP-messaging (i.e. information source, flow, and their influences), and qualitative content analysis of stakeholders\u2019 interviews. Key strategic actors were identified through network centrality measures such as degree of node, betweenness centrality, and clustering coefficient. The perceived influence/credibility (by farmers) of BMP-messages and their source, allowed for the identification of strategic entry points for BMP-messages diffusion. Finally, the inductive coding process of stakeholders\u2019 interviews revealed major hindrances and opportunities for BMPs adoption. We demonstrate how improved targeting of policy interventions for BMPs uptake may be achieved, by better distributing entry-points across stakeholders. Our results reveal governance gaps and opportunities, on which we draw to provide insights for better tailored policy interventions. We propose strategies to optimize the coverage of policy mixes and the dissemination of BMP-messages by building on network diversity and actors\u2019 complementarities, and by targeting intervention towards specific BMPs and actors. We suggest that (i) conservation incentives could target supply chain actors as conservation intermediaries; (ii) compliance-control of manure management planning could be conducted by accredited private certifiers; (iii) policy should focus on incentivizing inter-farmers interaction (e.g. farmers\u2019 mobility, training, knowledge-exchange, and engagement in multi-stakeholders collaboration) via financial or non-pecuniary compensation; (iv) collective incentives could help better coordinate conservation efforts at the landscape or (sub-)watershed scale; (v) all relevant stakeholders (including farmers) should be concerted and included in the discussion, proposition, co-design and decision process of policy, in order to take their respective interests and responsibilities into account.

", "keywords": ["2. Zero hunger", "Conservation of Natural Resources", "Farmers", "Science", "Q", "Water Pollution", "R", "Agriculture", "Pennsylvania", "15. Life on land", "6. Clean water", "12. Responsible consumption", "13. Climate action", "11. Sustainability", "Life Science", "Medicine", "Humans", "Social Network Analysis", "Research Article"]}, "links": [{"href": "https://doi.org/10.1371/journal.pone.0303745"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/PLOS%20ONE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1371/journal.pone.0303745", "name": "item", "description": "10.1371/journal.pone.0303745", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1371/journal.pone.0303745"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-05-23T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=network&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=network&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=network&", "hreflang": "en-US"}, {"rel": "next", "type": "application/geo+json", "title": "items (next)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=network&offset=50", "hreflang": "en-US"}], "numberMatched": 201, "numberReturned": 50, "distributedFeatures": [], "timeStamp": "2026-07-28T15:18:03.660340Z"}