{"type": "FeatureCollection", "features": [{"id": "PMC6668394", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:28:03Z", "type": "Journal Article", "created": "2019-07-31", "title": "A new global gridded anthropogenic heat flux dataset with high spatial resolution and long-term time series", "description": "Abstract

Exploring global anthropogenic heat and its effects on climate change is necessary and meaningful to gain a better understanding of human\uffe2\uff80\uff93environment interactions caused by growing energy consumption. However, the variation in regional energy consumption and limited data availability make estimating long-term global anthropogenic heat flux (AHF) challenging. Thus, using high-resolution population density data (30 arc-second) and a top-down inventory-based approach, this study developed a new global gridded AHF dataset covering 1970\uffe2\uff80\uff932050 based historically on energy consumption data from the British Petroleum (BP); future projections were built on estimated future energy demands. The globally averaged terrestrial AHFs were estimated at 0.05, 0.13, and 0.16\uffe2\uff80\uff89W/m2 in 1970, 2015, and 2050, respectively, but varied greatly among countries and regions. Multiple validation results indicate that the past and future global gridded AHF (PF-AHF) dataset has reasonable accuracy in reflecting AHF at various scales. The PF-AHF dataset has longer time series and finer spatial resolution than previous data and provides powerful support for studying long-term climate change at various scales.The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.) Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), Journal of Maps, DOI: 10.1080/17445647.2022.2088305 Abstract In the Northern Apennines, significant modifications to the characteristic historic features of landscapes occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today European and national policies are promoting the repopulation of these regions in order to help preserve the cultural identity of territories and to reduce demographic pressure in urban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of a set of strategies to underpin the preservation of landscape heritage and to foster local development on the basis of the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components. Methods This dataset was explored with two spatial statistical tools using the programming language R (R Core Team 2021): Local Indicators for Categorical Data (LICD) and Point Pattern analysis (PPA). The LICD method is based on join-count statistics (JCS), a solid method to measure the correlation between binomial variables and the distance between observations. LICD has been recently employed in landscape archaeological studies for verifying visible patterns and disclosing hidden spatial relationships (article: Carrer et al. 2021, Data: Zenodo Repository) The application of PPA in landscape studies has been widely applied in Ecology and it is growing popular also in Archaeology (Knitter and Nakoinz 2018; Brandolini and Carrer 2020; Costanzo et al. 2021). In this study, PPA was employed to provide a quantitative assessment of the correlations between different components of the Vetto landscape. List of files included in Brandolini_Turner_tjom_2022.zip: R_script_code named 'tjom_supplementary' in .rmd format Output folder: png and .txt products of the R script code GeoTiff folder (.TIFF file format): Geomorphons Euclidean distances from Irregular Fields (IF) Euclidean distances from Combined Fields (CF) EsriSHP folder (.shp file format): H_sites folder: historic settlements (h_sites.shp) rural_ruins folder: abandoned rural ruins (rural_ruins.shp) hlc folder: HLC_periods.shp HLC_types.shp roi folder: Region Of Interest (roi.shp) Contacts dr. F. Brandolini: filippo.brandolini@newcastle.ac.uk Acknowledgements The authors would like to acknowledge the help of the mayor Mr Fabio Ruffini and all the staff of Vetto d\u2019 Enza, Dr. Alessandra Curotti and Dr. Chiara Cantini and (Unione Montana dei Comuni dell\u2019Appennino Reggiano) and Dott.ssa Annalisa Capurso (Soprintendenza Archeologia Belle Arti e Paesaggio per la citt\u00e0 metropolitana di Bologna e le province di Modena, Reggio Emilia e Ferrara) for their administrative assistance in preparation of the project fieldwork activities. Also, we wish to thank Dr Anna Campeol and Mr Davide Cavecchi (Provincia di Reggio Emilia - Ufficio Topografico) for their help in retrieving and digitising the Nuovo Catasto Terreni cadastral map. The authors also thank the AsRe (Archivio Stato di Reggio Emilia) and AsPr (Archivio Stato di Parma) administration and staff for giving the right to digitise the historical maps and for helping during the consultation at the archives. Finally, we thank Francesco Carrer (Newcastle University, Newcastle upon Tyne, UK) for his comments on the R script code, and Christopher Sevara (Newcastle University, Newcastle upon Tyne, UK) for his suggestions in retrieving historical satellite images.", "keywords": ["Landscape Heritage", "Landscape Management", "Landscape Archaeology", "Spatial Statistics", "11. Sustainability", "Spatial Humanities", "Digital Geoarchaeology", "15. Life on land", "Historic Landscape Characterisation", "Point Pattern Analysis", "Local Indicator for Categorical Data"], "contacts": [{"organization": "Brandolini, Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5907229"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5907229", "name": "item", "description": "10.5281/zenodo.5907229", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5907229"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-26T00:00:00Z"}}, {"id": "10.1038/s41598-019-56266-5", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:17:42Z", "type": "Journal Article", "created": "2019-12-27", "title": "Determining the effect of exogenous organic materials on spatial distribution of maize yield", "description": "Abstract

Knowledge on spatial distribution of crop yield in relation to fixed soil fertilisation with exogenous organic materials is essential for improving precise crop and soil management practices within a field. This study assessed the effect of various application rates and types of exogenous (recycled) organic materials (EOMs) containing different organic matter and nitrogen contents vs. mineral nitrogen on the yield of maize by means of linear regressions (trends), spatial kriging-interpolated maps, and Bland-Altman statistics. The experiments were conducted in 2013 and 2014 on two soils, i.e. loam silt in Braszowice (Poland) and clay silt loam in Pust\uffc3\uffa9 Jakartice (Czech Republic) under a cross-border cooperation project. The organic materials included compost from manure, slurry, and straw (Ag), industrial organic compost from sewage sludge (Ra), animal meal from animal by-products (Mb), and digestate from a biogas fries factory (Dg). The following 3 application rates of each EOM were adjusted according to the reference 100%\uffe2\uff80\uff89=\uffe2\uff80\uff89200\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921: 50 (50% N from EOM and 50% mineral N), 75 (75% N from EOM and 25% mineral N), and 100 (100% N from EOM). 100% mineral N was applied on control plots. All treatments were carried out in 4 replicates. The linear regressions between the EOM application rates and the maize yield were in general ascending in the Braszowice soil and descending in the more productive Pust\uffc3\uffa9 Jakartice soil. The spatial kriging-interpolated maps allowed separating zones of lower and higher yields with EOMs compared to the control. They were attributed in part to the different EOM application rates and soil water contents. The Bland-Altaman statistics showed that addition of 50% of N from EOMs in 2013 caused a decrease and an increase in the maize grain yield in Braszowice and Pust\uffc3\uffa9 Jakartice, respectively, whereas the inverse was true with the 75 and 100% EOM additions. In 2014, the yield of maize for silage increased with the increasing EOM application rate in Braszowice and decreased in Pust\uffc3\uffa9 Jakartice, but it was smaller on all EOM-amended plots than in the control. As shown by the limits of agreement lines, the maize yields were more even in Pust\uffc3\uffa9 Jakartice than Braszowice. These results provide helpful information for selection of the most yield-producing EOM rates depending on the site soil conditions and prevalent weather conditions.Exploring global anthropogenic heat and its effects on climate change is necessary and meaningful to gain a better understanding of human\uffe2\uff80\uff93environment interactions caused by growing energy consumption. However, the variation in regional energy consumption and limited data availability make estimating long-term global anthropogenic heat flux (AHF) challenging. Thus, using high-resolution population density data (30 arc-second) and a top-down inventory-based approach, this study developed a new global gridded AHF dataset covering 1970\uffe2\uff80\uff932050 based historically on energy consumption data from the British Petroleum (BP); future projections were built on estimated future energy demands. The globally averaged terrestrial AHFs were estimated at 0.05, 0.13, and 0.16\uffe2\uff80\uff89W/m2 in 1970, 2015, and 2050, respectively, but varied greatly among countries and regions. Multiple validation results indicate that the past and future global gridded AHF (PF-AHF) dataset has reasonable accuracy in reflecting AHF at various scales. The PF-AHF dataset has longer time series and finer spatial resolution than previous data and provides powerful support for studying long-term climate change at various scales. Saturated hydraulic conductivity (K) is a key property for evaluating soil water movement and quality. Most studies on spatial variability of K have been performed soil at a field or smaller scale. Therefore, the aim of this work was to assess (quantify) the spatial distribution of K at the larger regional scale in south-eastern Poland and its relationship with other soil properties, including intrinsic sand, silt, and clay contents, relatively stable organic carbon, cation exchange capacity (CEC) and temporally variable water content (WC), total porosity (FI), and dry bulk density (BD) in the surface layer (0\uffe2\uff80\uff9320\uffc2\uffa0cm). The spatial relationships were assessed using a semivariogram and a cross-semivariogram. The studied region (140\uffc2\uffa0km 2 ) with predominantly permeable sandy soils with low fertility and productivity is located in the south-eastern part of Poland (Podlasie region). The mean sand and organic carbon contents are 74 and 0.86 and their ranges (in %) are 45\uffe2\uff80\uff9395 and 0.002\uffe2\uff80\uff933.75, respectively. The number of individual samples varied from 216 to 228 (for K, WC, BD, FI) to 691 for the other soil properties. The best fitting models were adjusted to the empirical semivariogram (exponential) and the cross-semivariogram (exponential, Gaussian, or linear) used to draw maps with kriging. The results showed that, among the soil properties studied, K was most variable (coefficient of variation 77.3%) and significantly ( p \uffe2\uff80\uff89<\uffe2\uff80\uff890.05) positively correlated with total porosity (r\uffe2\uff80\uff89=\uffe2\uff80\uff890.300) and negatively correlated with soil bulk density (r\uffe2\uff80\uff89=\uffe2\uff80\uff89\uffe2\uff80\uff93\uffe2\uff80\uff890.283). The normal or close to the normal distribution was obtained by natural logarithmic and root square transformations. The mean K was 2.597\uffc2\uffa0m\uffc2\uffa0day \uffe2\uff88\uff921 and ranged from 0.01 up to 11.54\uffc2\uffa0m\uffc2\uffa0day \uffe2\uff88\uff921 . The spatial autocorrelation (range) of K in the single (direct) semivariograms was 0.081\uffc2\uffb0 (8.1\uffc2\uffa0km), while it favourably increased up to 0.149\uffc2\uffb0\uffe2\uff80\uff930.81\uffc2\uffb0 (14.9\uffe2\uff80\uff9381\uffc2\uffa0km) in the cross-semivariograms using the OC contents, textural fractions, and CEC as auxiliary variables. The generated spatial maps allowed outlining two sub-areas with predominantly high K above 3.0\uffc2\uffa0m\uffc2\uffa0day \uffe2\uff88\uff921 in the northern sandier (sand content\uffe2\uff80\uff89>\uffe2\uff80\uff8974%) and less silty (silt content\uffe2\uff80\uff89<\uffe2\uff80\uff8922%) part and, with lower K in the southern part of the study region. Generally, the spatial distribution of the K values in the study region depended on the share of individual intrinsic textural fractions. On the other hand, the ranges of the spatial relationship between K and the intrinsic and relatively stable soil properties were much larger (from\uffe2\uff80\uff89~\uffe2\uff80\uff8915 to 81\uffc2\uffa0km) than between K and the temporally variable soil properties (0.3\uffe2\uff80\uff930.9\uffc2\uffa0km). This knowledge is supportive for making decisions related to land management aimed at alteration of hydraulic conductivity to improve soil water resources and crop productivity and reduce chemical leaching. The future of terrestrial soil carbon stocks plays a crucial role in climate change prediction. Modern machine learning techniques are now widely applied in soil science to predict the spatial distribution of soil properties from observational data. Beyond prediction, the use of machine learning as a data-mining tool offers a promising pathway for improving soil carbon modelling and refining projections of climate\uffe2\uff80\uff93carbon feedbacks. In this paper, we review recent advances in the application of machine learning to global soil carbon modelling as a data-mining tool and highlight its potential to drive an iterative feedback loop that improves the representation of soil carbon dynamics in Earth System Models.Transformation products (TPs) of man-made chemicals, formed through microbially mediated transformation in the environment, can have serious adverse environmental effects, yet the analytical identification of TPs is challenging. Rule-based prediction tools are successful in predicting TPs, especially in environmental chemistry applications that typically have to rely on small datasets, by imparting the existing knowledge on enzyme-mediated biotransformation reactions. However, the rules extracted from biotransformation reaction databases usually face the issue of being over/under-generalized and are not flexible to be updated with new reactions.

Results

We developed an automatic rule extraction tool called enviRule. It clusters biotransformation reactions into different groups based on the similarities of reaction fingerprints, and then automatically extracts and generalizes rules for each reaction group in SMARTS format. It optimizes the genericity of automatic rules against the downstream TP prediction task. Models trained with automatic rules outperformed the models trained with manually curated rules by 30% in the area under curve (AUC) scores. Moreover, automatic rules can be easily updated with new reactions, highlighting enviRule\uffe2\uff80\uff99s strengths for both automatic extraction of optimized reactions rules and automated updating thereof.

Availability and implementation

enviRule code is freely available at https://github.com/zhangky12/enviRule.

", "keywords": ["10120 Department of Chemistry", "Statistics and Probability", "Original Paper", "1303 Biochemistry", "Computational Biology", "Biochemistry", "Computer Science Applications", "Computational Mathematics", "Computational Theory and Mathematics", "13. Climate action", "540 Chemistry", "1312 Molecular Biology", "1706 Computer Science Applications", "2613 Statistics and Probability", "2605 Computational Mathematics", "Molecular Biology", "Biotransformation", "1703 Computational Theory and Mathematics"]}, "links": [{"href": "https://doi.org/10.1093/bioinformatics/btad407"}, {"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/btad407", "name": "item", "description": "10.1093/bioinformatics/btad407", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/bioinformatics/btad407"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-06-24T00:00:00Z"}}, {"id": "10.1093/treephys/tpr121", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:18:21Z", "type": "Journal Article", "created": "2011-12-07", "title": "Leaf-Trait Responses To Irrigation Of The Endemic Fog-Oasis Tree Myrcianthes Ferreyrae: Can A Fog Specialist Benefit From Regular Watering?", "description": "Myrcianthes ferreyrae is an endemic, endangered species, with a small number of individuals located only in hyperarid, fog-oases known as lomas along the Peruvian desert in southern Peru, where fog is the main source of water. Following centuries of severe deforestation, reforestation with this native species was conducted in the Atiquipa lomas, Arequipa-Per\u00fa. On five slopes, five 2-year-old seedlings were irrigated monthly with water trapped by raschel-mesh fog collectors, supplementing natural rainfall with 0, 20, 40, 60 and 80 mm month(-1) from February to August 2008. We measured plant growth, increment in basal diameter, height and five leaf traits: leaf mass area (LMA), leaf carbon isotope composition (\u03b4(13)C), nitrogen per leaf area, total leaf carbon and stomatal density; which are indicative of the physiological changes resulting from increased water supply. Plant growth rates, estimated from the variation of either shoot basal diameter or maximum height, were highly correlated with total biomass. Only LMA and \u03b4(13)C were higher in irrigated than in control plants, but we found no further differences among irrigation treatments. This threshold response suggests an on-off strategy fitted to exploit pulses of fog water, which are always limited in magnitude in comparison with natural rain. The absence of a differential response to increased water supply is in agreement with the low phenotypic plasticity expected in plants from very stressful environments. Our results have practical implications for reforestation projects, since irrigating with 20 mm per month is sufficient to achieve the full growth capacity of this species.", "keywords": ["0106 biological sciences", "Carbon Isotopes", "Principal Component Analysis", "Agricultural Irrigation", "Geography", "Water", "15. Life on land", "01 natural sciences", "Statistics", " Nonparametric", "6. Clean water", "Trees", "Plant Leaves", "Quantitative Trait", " Heritable", "Multivariate Analysis", "Peru", "Plant Stomata", "Biomass", "Weather"]}, "links": [{"href": "https://doi.org/10.1093/treephys/tpr121"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Tree%20Physiology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1093/treephys/tpr121", "name": "item", "description": "10.1093/treephys/tpr121", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1093/treephys/tpr121"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-12-05T00:00:00Z"}}, {"id": "10.1111/1755-0998.12949", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:18:32Z", "type": "Journal Article", "created": "2018-09-29", "title": "Conditionally autoregressive models improve occupancy analyses of autocorrelated data: An example with environmental DNA", "description": "Abstract

Site occupancy\uffe2\uff80\uff90detection models (SODMs) are statistical models widely used for biodiversity surveys where imperfect detection of species occurs. For instance, SODMs are increasingly used to analyse environmental DNA (eDNA) data, taking into account the occurrence of both false\uffe2\uff80\uff90positive and false\uffe2\uff80\uff90negative errors. However, species occurrence data are often characterized by spatial and temporal autocorrelation, which might challenge the use of standard SODMs. Here we reviewed the literature of eDNA biodiversity surveys and found that most of studies do not take into account spatial or temporal autocorrelation. We then demonstrated how the analysis of data with spatial or temporal autocorrelation can be improved by using a conditionally autoregressive SODM, and show its application to environmental DNA data. We tested the autoregressive model on both simulated and real data sets, including chronosequences with different degrees of autocorrelation, and a spatial data set on a virtual landscape. Analyses of simulated data showed that autoregressive SODMs perform better than traditional SODMs in the estimation of key parameters such as true\uffe2\uff80\uff90/false\uffe2\uff80\uff90positive rates and show a better discrimination capacity (e.g., higher true skill statistics). The usefulness of autoregressive SODMs was particularly high in data sets with strong autocorrelation. When applied to real eDNA data sets (eDNA from lake sediment cores and freshwater), autoregressive SODM provided more precise estimation of true\uffe2\uff80\uff90/false\uffe2\uff80\uff90positive rates, resulting in more reasonable inference of occupancy states. Our results suggest that analyses of occurrence data, such as many applications of eDNA, can be largely improved by applying conditionally autoregressive specifications to SODMs.

", "keywords": ["0106 biological sciences", "Genetics", " Population", "Spatio-Temporal Analysis", "330", "DNA", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "Biostatistics", "15. Life on land", "Biota", "01 natural sciences", "conditionally autoregressive model; sedimentary DNA; spatial autocorrelation; species occupancy-detection model; temporal autocorrelation; true skill statistics; Biostatistics; DNA; Spatio-Temporal Analysis; Biota; Genetics", " Population; Biotechnology; Ecology", " Evolution", " Behavior and Systematics; Genetics"]}, "links": [{"href": "https://air.unimi.it/bitstream/2434/635968/2/Chen_et_al-2019-Molecular_Ecology_Resources.pdf"}, {"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1111/1755-0998.12949"}, {"href": "https://doi.org/10.1111/1755-0998.12949"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Molecular%20Ecology%20Resources", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/1755-0998.12949", "name": "item", "description": "10.1111/1755-0998.12949", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/1755-0998.12949"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-11-01T00:00:00Z"}}, {"id": "10.17169/refubium-31202", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:19:46Z", "type": "Journal Article", "created": "2021-05-21", "title": "Global data on earthworm abundance, biomass, diversity and corresponding environmental properties", "description": "Abstract

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.

", "keywords": ["2401.17 Invertebrados", "0301 basic medicine", "592", "Data Descriptor", "Ecology and Evolutionary Biology", "earthworms", "Data Descriptor ; Biodiversity ; Biogeography ; Community ecology", "Plan_S-Compliant-OA", "https://purl.org/becyt/ford/1.6", "[SDV.EE.ECO] Life Sciences [q-bio]/Ecology", " environment/Ecosystems", "Diversity data", "Biomass", "S Agriculture (General)", "Ekologia ja evoluutiobiologia", "[SDV.SA.SDS] Life Sciences [q-bio]/Agricultural sciences/Soil study", "biodiversity", "2. Zero hunger", "maaper\u00e4", "abundance", "Data", "Diversity", "0303 health sciences", "Ecology", "Q", "eli\u00f6yhteis\u00f6t", "Biodiversity", "maaper\u00e4eli\u00f6st\u00f6", "ddc:", "Computer Science Applications", "Biogeography", "2401.06 Ecolog\u00eda animal", "international", "Statistics", " Probability and Uncertainty", "environment/Ecosystems", "Information Systems", "Statistics and Probability", "Ecolog\u00eda (Biolog\u00eda)", "570", "lierot", "Science", "Invertebrados", "577", "Global database", "[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study", "Library and Information Sciences", "574", "333", "soil", "eli\u00f6maantiede", "Education", "diversity", "03 medical and health sciences", "[SDV.EE.ECO]Life Sciences [q-bio]/Ecology", " environment/Ecosystems", "BIODIVERSITY CHANGE", "Life Science", "Earthworms", "Datasets", "Animals", "Community ecology", "Oligochaeta", "https://purl.org/becyt/ford/1", "eartworm", "biogeography", "Ecosystem", "LAND-USE", "biomass", "500", "Biology and Life Sciences", "PLATFORM", "Global dataset", "Oligochaeta/classification", "500 Naturwissenschaften und Mathematik::570 Biowissenschaften; Biologie::570 Biowissenschaften; Biologie", "Ecolog\u00eda", "15. Life on land", "biodiversiteetti", "Environmental sciences", "[SDE.BE] Environmental Sciences/Biodiversity and Ecology", "maaper\u00e4el\u00e4imist\u00f6", "Ecology", " evolutionary biology", "13. Climate action", "Earthworm", "[SDV.EE.ECO]Life Sciences [q-bio]/Ecology", "570 Life sciences; biology", "[SDE.BE]Environmental Sciences/Biodiversity and Ecology", "eartworm ; abundance ; biomass ; diversity", "COMMUNITIES", "community ecology"]}, "links": [{"href": "https://www.nature.com/articles/s41597-021-00912-z.pdf"}, {"href": "https://pub.epsilon.slu.se/25868/1/phillips_h_r_p_et_al_211019.pdf"}, {"href": "https://boris.unibe.ch/165726/1/48.__Global_data_on_earthworm_abundance__biomass__diversity_and_corresponding_environmental_properties.pdf"}, {"href": "https://www.iris.unict.it/bitstream/20.500.11769/509583/1/SCIENTIFIC%20DATA%20%282021%29%20GLOBAL%20DATA%20ON%20EARTHWORMS.pdf"}, {"href": "https://rau.repository.guildhe.ac.uk/id/eprint/16454/1/Phillips_et_al-2021-Scientific_Data.pdf"}, {"href": "https://doi.org/10.17169/refubium-31202"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Scientific%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.17169/refubium-31202", "name": "item", "description": "10.17169/refubium-31202", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.17169/refubium-31202"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-05-21T00:00:00Z"}}, {"id": "10.3389/fenvs.2018.00061", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:20:40Z", "type": "Journal Article", "created": "2018-07-10", "title": "Recognizing Patterns: Spatial Analysis of Observed Microbial Colonization on Root Surfaces", "description": "Root surfaces are major sites of interactions between plants and associated microorganisms. Here, plants and microbes communicate via signaling molecules, compete for nutrients, and release substrates that may have beneficial or harmful effects on each other. Whilst the body of knowledge on the abundance and diversity of microbial communities at root-soil interfaces is now substantial, information on their spatial distribution at the microscale is still scarce. In this study, a standardized method for recognizing and analyzing microbial cell distributions on root surfaces is presented. Fluorescence microscopy was combined with automated image analysis and spatial statistics to explore the distribution of bacterial colonization patterns on rhizoplanes of rice roots. To test and evaluate the presented approach, a gnotobiotic experiment was performed using a potential nitrogen-fixing bacterial strain in combination with roots of wetland rice. The automated analysis procedure resulted in reliable spatial data of bacterial cells colonizing the rhizoplane. Among all replicate roots, the analysis revealed an increasing density of bacterial cells from the root tip to the region of root cell maturation. Moreover, bacterial cells showed significant spatial clustering and tended to be located around plant root cell borders. The quantitative data suggest that the structure of the root surface plays a major role in bacterial colonization patterns. Possible adaptations of the presented approach for future studies are discussed along with potential pitfalls such as inaccurate imaging. Our results demonstrate that standardized recognition and statistical evaluation of microbial colonization on root surfaces holds the potential to increase our understanding of microbial associations with roots and of the underlying ecological interactions.", "keywords": ["[SDE] Environmental Sciences", "0301 basic medicine", "570", "bacterial colonization", "[SDV]Life Sciences [q-bio]", "CATALYZED REPORTER DEPOSITION", "microbial ecology;root surface;bacterial colonization;point process;spatial statistics;image analysis;pattern recognition;wetland rice", "ECOLOGY", "microbial ecology", "Image analysis", "spatial statistics", "Microbial ecology", "03 medical and health sciences", "image analysis", "Pattern recognition", "root surface", "GE1-350", "Point process", "Wetland rice", "point process", "2. Zero hunger", "106022 Mikrobiologie", "0303 health sciences", "Spatial statistics", "IDENTIFICATION", "pattern recognition", "IN-SITU HYBRIDIZATION", "15. Life on land", "Bacterial colonization", "[SDV] Life Sciences [q-bio]", "SOIL", "Environmental sciences", "wetland rice", "Root surface", "[SDE]Environmental Sciences", "BACTERIA", "106022 Microbiology", "POPULATIONS", "COMMUNITIES"]}, "links": [{"href": "https://doi.org/10.3389/fenvs.2018.00061"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Environmental%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fenvs.2018.00061", "name": "item", "description": "10.3389/fenvs.2018.00061", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fenvs.2018.00061"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-10T00:00:00Z"}}, {"id": "10.1785/0220200337", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:19:49Z", "type": "Journal Article", "created": "2020-12-16", "title": "\"Inconsistencies and Lurking Pitfalls in the Magnitude–Frequency Distribution of High-Resolution Earthquake Catalogs\"", "description": "Abstract

Earthquake catalogs describe the distribution of earthquakes in space, time, and magnitude, which is essential information for earthquake forecasting and the assessment of seismic hazard and risk. Available high-resolution (HR) catalogs raise the expectation that their abundance of small earthquakes will help better characterize the fundamental scaling laws of statistical seismology. Here, we investigate whether the ubiquitous exponential-like scaling relation for magnitudes (Gutenberg\uffe2\uff80\uff93Richter [GR], or its tapered version) can be straightforwardly extrapolated to the magnitude\uffe2\uff80\uff93frequency distribution (MFD) of HR catalogs. For several HR catalogs such as of the 2019 Ridgecrest sequence, the 2009 L\uffe2\uff80\uff99Aquila sequence, the 1992 Landers sequence, and entire southern California, we determine if the MFD agrees with an exponential-like distribution using a statistical goodness-of-fit test. We find that HR catalogs usually do not preserve the exponential-like MFD toward low magnitudes and depart from it. Surprisingly, HR catalogs that are based on advanced detection methods depart from an exponential-like MFD at a similar magnitude level as network-based HR catalogs. These departures are mostly due to an improper mixing of different magnitude types, spatiotemporal inhomogeneous completeness, or biased data recording or processing. Remarkably, common-practice methods to find the completeness magnitude do not recognize these departures and lead to severe bias in the b-value estimation. We conclude that extrapolating the exponential-like GR relation to lower magnitudes cannot be taken for granted, and that HR catalogs pose subtle new challenges and lurking pitfalls that may hamper their proper use. The simplest solution to preserve the exponential-like distribution toward low magnitudes may be to estimate a moment magnitude for each earthquake.

", "keywords": ["statistical seismology", "earthquake statistics", "earthquake magnitude", "13. Climate action", "hypothesis testing", "0103 physical sciences", "earthquake catalog", "exponential distribution", "Gutenberg-Richter", "01 natural sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.iris.unina.it/bitstream/11588/849560/4/Herrmann%20%282020%29%20Marzocchi%20%5bSRL%5d%20Inconsistencies%20and%20Lurking%20Pitfalls%20in%20the%20Magnitude%e2%80%93Frequency%20Distribution%20of%20High-Resolution%20Earthquake%20Catalogs.pdf"}, {"href": "https://doi.org/10.1785/0220200337"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Seismological%20Research%20Letters", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1785/0220200337", "name": "item", "description": "10.1785/0220200337", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1785/0220200337"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-12-16T00:00:00Z"}}, {"id": "10.1890/03-0475", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-05-25T16:19:51Z", "type": "Journal Article", "created": "2007-06-06", "title": "Effects Of Past Land Use On Spatial Heterogeneity Of Soil Nutrients In Southern Appalachian Forests", "description": "

We examined patterns of nutrient heterogeneity in the mineral soil (0\uffe2\uff80\uff9315 cm depth) of 13 southern Appalachian forest stands in western North Carolina >60 yr after abandonment from pasture or timber harvest to investigate the long\uffe2\uff80\uff90term effects of land use on the spatial distribution and supply of soil resources. We measured soil carbon (C), nitrogen (N), acid\uffe2\uff80\uff90extractable phosphorus (P), potassium (K), calcium (Ca), and magnesium (Mg) concentrations and pools, and potential net N mineralization and nitrification rates to evaluate differences in mean values, variance at multiple scales, and fine\uffe2\uff80\uff90scale spatial structure.

While comparisons of averaged values rarely indicated that historical land use had an enduring effect on mineral soil or N cycling, differences in variance and spatial structure suggested that former activities continue to influence nutrient distributions by altering their spatial heterogeneity. Patterns differed by element, but generally variance of soil C, N, and Ca decreased and variance of soil P, K, and Mg increased with intensive past land use. Changes in variance were most conspicuous and consistent locally (<28 m), but C, Ca, P, and Mg also exhibited appreciable differences in variance at coarser scales (>150 m). High variability in soil compaction resulted in some changes in scale\uffe2\uff80\uff90dependent patterns of nutrient pool variance compared with nutrient concentration variance. It also affected the variance of N cycling rates, such that mass\uffe2\uff80\uff90based rates varied less and area\uffe2\uff80\uff90based rates varied more in intensively used areas than in reference stands. Geostatistical analysis suggested that past land use homogenized the spatial structure of soil C, K, and P in former pastures. In contrast, logged stands had highly variable spatial patterning for Ca.

These results suggest that land use has persistent, multi\uffe2\uff80\uff90decadal effects on the spatial heterogeneity of soil resources, which may not be detectable when values are averaged across sites. By interacting with patterns of variability in the plant and heterotrophic biota, differences in nutrient distribution and supply could alter the composition and diversity of forest ecosystems. Scale\uffe2\uff80\uff90dependent changes in nutrient heterogeneity could also complicate efforts to determine biogeochemical budgets and cycling rates.

", "keywords": ["Statistics and Probability", "2. Zero hunger", "570", "land-use history", "550", "carbon", "forest ecosystem recovery", "04 agricultural and veterinary sciences", "15. Life on land", "cations", "logging", "nitrogen", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "grazing", "phosphorus", "semivariograms", "Biology"]}, "links": [{"href": "https://doi.org/10.1890/03-0475"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecological%20Monographs", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1890/03-0475", "name": "item", "description": "10.1890/03-0475", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1890/03-0475"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2005-02-01T00:00:00Z"}}, {"id": "10.25678/00035v", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:20:35Z", "type": "Dataset", "title": "Data for: Non\u2010Gaussian parameter inference for hydrogeological models using Stein Variational Gradient Descent", "description": "This package includes the data and Python files for the publication 'Non\u2010Gaussian parameter inference for hydrogeological models using Stein Variational Gradient Descent'.", "keywords": ["SVGD", "modelling", "aquifer", "hydrogeology", "river", "groundwater", "Bayesian inference", "Stein Variational Gradient Descent", "ensemble-based", "modeling", "Bayesian statistics", "non-Gaussian", "Jacobian"], "contacts": [{"organization": "Ramgraber, M., Weatherl, R., Blumensaat, F., Schirmer, M.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.25678/00035v"}, {"rel": "self", "type": "application/geo+json", "title": "10.25678/00035v", "name": "item", "description": "10.25678/00035v", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.25678/00035v"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.2136/sssaj2000.641339x", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-25T16:20:13Z", "type": "Journal Article", "created": "2010-07-27", "description": "

Adoption of reduced\uffe2\uff80\uff90tillage fallow systems in the western USA is limited by winter annual grass weeds such as downy brome (Bromus tectorum L.). Moldboard plowing is an effective means of controlling downy brome in winter wheat (Tritcum aestivum L.)\uffe2\uff80\uff93fallow systems. The purpose of this study was to assess the influence of plowing and secondary tillage operations, for the purpose of weed control, on soil quality attributes of a silt loam soil that had been cropped in a sub\uffe2\uff80\uff90till or no\uffe2\uff80\uff90till (NT) winter wheat\uffe2\uff80\uff93fallow system for more than 20 yr. Compared with undisturbed NT, downy brome populations in plowed NT decreased 97 and 41% in the first and third crops following tillage, respectively. Wheat yields in plowed NT treatments were 30 and 9% greater in the first and third crops following tillage, respectively, compared with undisturbed NT. Soil quality indicators assessed were organic C (OC), total N, inorganic N, pH, electrical conductivity, bulk density, water infiltration rate, and pore\uffe2\uff80\uff90size distribution. Five years after tillage, soil OC decline in the 0\uffe2\uff80\uff90 to 7.5\uffe2\uff80\uff90cm depth was 20% in plowed compared with undisturbed NT; however, OC increased 15% in the 7.5\uffe2\uff80\uff90 to 15\uffe2\uff80\uff90cm depth and was not different in the 0\uffe2\uff80\uff90 to 30\uffe2\uff80\uff90cm depth. Total soil N followed similar trends. Soil inorganic N in plowed NT decreased 37%, and soil pH increased 9%, compared with undisturbed NT, at the 0\uffe2\uff80\uff90 to 7.5\uffe2\uff80\uff90cm depth. Occasional tillage with the moldboard plow in a reduced\uffe2\uff80\uff90 or no\uffe2\uff80\uff90tillage management system will help control winter annual grass weeds, while retaining many of the soil quality benefits of conservation\uffe2\uff80\uff90tillage management.

", "keywords": ["Statistics and Probability", "2. Zero hunger", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "630", "6. Clean water"], "contacts": [{"organization": "Kettler, Timothy A., Lyon, Drew J., Doran, John W., Powers, W. L., Stroup, Walter W.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.2136/sssaj2000.641339x"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Science%20Society%20of%20America%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2136/sssaj2000.641339x", "name": "item", "description": "10.2136/sssaj2000.641339x", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2136/sssaj2000.641339x"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2000-01-01T00:00:00Z"}}, {"id": "10.3389/fams.2019.00018", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:20:39Z", "type": "Journal Article", "created": "2019-04-12", "title": "Metabolic Games", "description": "Metabolic networks have been used to successfully predict phenotypes based on optimization principles. However, a general framework that would extend to situations not governed by simple optimization, such as multispecies communities, is still lacking. Concepts from evolutionary game theory have been proposed to amend the situation. Alternative metabolic states can be seen as strategies in a \u201cmetabolic game,\u201d and phenotypes can be predicted based on the equilibria of this game. In this survey, we review the literature on applying game theory to the study of metabolism, present the general idea of a metabolic game, and discuss open questions and future challenges.", "keywords": ["T57-57.97", "[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM]", "Applied mathematics. Quantitative methods", "flux balance analysis", "microbial interactions", "01 natural sciences", "QA273-280", "metabolic modeling", "0103 physical sciences", "metabolic networks", "[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation", "evolutionary game theory", "Probabilities. Mathematical statistics", "[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]"]}, "links": [{"href": "https://doi.org/10.3389/fams.2019.00018"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Applied%20Mathematics%20and%20Statistics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fams.2019.00018", "name": "item", "description": "10.3389/fams.2019.00018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fams.2019.00018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-12T00:00:00Z"}}, {"id": "10.3390/land10111199", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:20:54Z", "type": "Journal Article", "created": "2021-11-07", "title": "Quantifying Cereal Productivity on Sandy Soil in Response to Some Soil-Improving Cropping Systems", "description": "

Little information is available on the effect of soil-improving cropping systems (SICS) on crop productivity on low fertility sandy soils although they are increasingly being used in agriculture in many regions of the world due to the growing demand for food. The study aimed at quantifying the effect of four soil-improving cropping systems applied on sandy soil on cereal productivity (yield of grain and straw and plant height) in a 4-year field experiment conducted in Poland with spring cereal crops: oat (2017), wheat (2018), wheat (2019), and oat (2020). The experiment included the control (C) and the following SICS: liming (L), leguminous catch crops for green manure (LU), farmyard manure (M), and farmyard manure + liming + leguminous catch crops for green manure together (M + L + LU). To quantify the effect of the SICS, classic statistics and the Bland\u2013Altman method were used. It was shown that all yield trait components significantly increased in the last study year (2020) under SICS with M and M + L + LU. All yield trait components were significantly lower in the dry years (2018\u20132019) than in the wet years (2017 and 2020). The relatively large rainfall quantity in May during intensive growth at shooting and the scarce precipitation during later growth in the dry year 2019 resulted in a significantly greater straw yield compared to the other dry year 2018. The values of Bland\u2013Altman bias (mean difference between the particular SICS and the control) varied (in kg m\u22122) from \u22120.002 for LU in 2019 to 0.128 for M and 0.132 for M + L + LU in 2020. The highest limits of agreement (LoA) were in general noted for all yield trait components (the least even yield) in the most productive SICS including M and M + L + LU in the wet year 2020. The Bland\u2013Altman ratio (BAR) values indicate that quantification of the effects of all soil-improving practices was most uncertain in the dry year 2018 for the grain yield and in the wet year 2020 for the straw yield and much less uncertain for the plant height in all SICS and study years. The results of this study provide helpful information about the effect of the SICS on the different yield trait components depending on the period of their application and weather conditions prevailing during the growing season.

", "keywords": ["2. Zero hunger", "Bland\u2013Altman statistics", "S", "soil improving practices", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Podzol soil", "crop response", "weather conditions"]}, "links": [{"href": "http://www.mdpi.com/2073-445X/10/11/1199/pdf"}, {"href": "https://doi.org/10.3390/land10111199"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/land10111199", "name": "item", "description": "10.3390/land10111199", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/land10111199"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-05T00:00:00Z"}}, {"id": "10.5194/bg-10-3691-2013", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:36Z", "type": "Journal Article", "created": "2013-01-14", "title": "A meta-analysis on the impacts of partial cutting on forest structure and carbon storage", "description": "

Abstract. Partial cutting, which removes some individual trees from a forest, is one of the major and widespread forest management practices that can significantly alter both forest structure and carbon (C) storage. Using 746 observations from 82 publications, we synthesized the impacts of partial cutting on three variables associated with forest structure (i.e. mean annual growth of diameter at breast height (DBH), basal area (BA), and volume) and four variables related to various C stock components (i.e. aboveground biomass C (AGBC), understory C, forest floor C, and mineral soil C). Results shows that the growth of DBH elevated by 112% after partial cutting, compared to the uncut control, while stand BA and volume reduced immediately by 34% and 29%, respectively. On average, partial cutting reduced AGBC by 43%, increased understory C storage by 392%, but did not show significant effects on C storages on forest floor and in mineral soil. All the effects on DBH growth, stand BA, volume, and AGBC intensified linearly with cutting intensity (CI) and decreased linearly with the number of recovery years (RY). In addition to the strong impacts of CI and RY, other factors such as climate zone and forest type also affected forest responses to partial cutting. The data assembled in this synthesis were not sufficient to determine how long it would take for a complete recovery after cutting because long-term experiments were rare. Future efforts should be tailored to increase the duration of the experiments and balance geographic locations of field studies.

", "keywords": ["Biomass (ecology)", "0106 biological sciences", "Sustainable forest management", "Volume (thermodynamics)", "Diameter at breast height", "Forest Carbon Sequestration", "Estimation of Forest Biomass and Carbon Stocks", "Quantum mechanics", "01 natural sciences", "Environmental science", "Basal area", "Agricultural and Biological Sciences", "Life", "Forest structure", "QH501-531", "Development and Impacts of Bioenergy Crops", "FOS: Mathematics", "Climate change", "Carbon stock", "Agroforestry", "Biology", "QH540-549.5", "Nature and Landscape Conservation", "QE1-996.5", "Global and Planetary Change", "Understory", "Forest management", "Ecology", "Geography", "Physics", "Confidence interval", "Statistics", "Canopy", "Life Sciences", "Geology", "Forestry", "15. Life on land", "Clearcutting", "Climate Change Impacts on Forest Carbon Sequestration", "Forest Site Productivity", "FOS: Biological sciences", "Environmental Science", "Physical Sciences", "Tree Height-Diameter Models", "Agronomy and Crop Science", "Biomass Estimation", "Animal science", "Mathematics"]}, "links": [{"href": "https://doi.org/10.5194/bg-10-3691-2013"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biogeosciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-10-3691-2013", "name": "item", "description": "10.5194/bg-10-3691-2013", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-10-3691-2013"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-01-14T00:00:00Z"}}, {"id": "10.5194/bg-2021-323", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:39Z", "type": "Report", "created": "2021-12-15", "title": "Reviews and syntheses: The promise of big soil data, moving current practices towards future potential", "description": "

Abstract. In the age of big data, soil data are more available than ever, but -outside of a few large soil survey resources- remain largely unusable for informing soil management and understanding Earth system processes outside of the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for global relevance. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: data discovery, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.

", "keywords": ["FOS: Computer and information sciences", "Data Sharing", "Biomedical Ontologies and Text Mining", "Data management", "Leverage (statistics)", "01 natural sciences", "Data science", "Data Sharing and Stewardship in Science", "Database", "Big data", "Biochemistry", " Genetics and Molecular Biology", "Machine learning", "Molecular Biology", "Data mining", "0105 earth and related environmental sciences", "2. Zero hunger", "Metadata", "Ecology", "Data curation", "Physics", "Life Sciences", "Acoustics", "15. Life on land", "Computer science", "World Wide Web", "Harmonization", "13. Climate action", "FOS: Biological sciences", "Computer Science", "Physical Sciences", "Environmental Science", "Data Reuse", "Environmental DNA in Biodiversity Monitoring", "Information Systems"]}, "links": [{"href": "https://doi.org/10.5194/bg-2021-323"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/bg-2021-323", "name": "item", "description": "10.5194/bg-2021-323", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/bg-2021-323"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-12-15T00:00:00Z"}}, {"id": "10.5194/essd-13-3707-2021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:45Z", "type": "Journal Article", "created": "2021-01-07", "title": "C-band radar data and in situ measurements for the monitoring of wheat crops in a semi-arid area (center of Morocco)", "description": "

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

", "keywords": ["550", "Arid", "Soil Moisture", "0211 other engineering and technologies", "FOS: Mechanical engineering", "02 engineering and technology", "Digital Soil Mapping Techniques", "Normalized Difference Vegetation Index", "630", "Agricultural and Biological Sciences", "Engineering", "Pathology", "GE1-350", "2. Zero hunger", "QE1-996.5", "Vegetation Monitoring", "Water content", "Ecology", "Geography", "Statistics", "Life Sciences", "Hydrology (agriculture)", "Geology", "Remote Sensing in Vegetation Monitoring and Phenology", "04 agricultural and veterinary sciences", "Remote sensing", "Soil Erosion and Agricultural Sustainability", "6. Clean water", "Satellite Observations", "Archaeology", "Physical Sciences", "Leaf area index", "Telecommunications", "Medicine", "Vegetation (pathology)", "Environmental Engineering", "Data set", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Aerospace Engineering", "Soil Science", "Environmental science", "Digital Soil Mapping", "[SDU] Sciences of the Universe [physics]", "Global Soil Information", "FOS: Mathematics", "Biology", "Radar", "Synthetic Aperture Radar Interferometry", "Canopy", "FOS: Environmental engineering", "Soil Properties", "Paleontology", "FOS: Earth and related environmental sciences", "15. Life on land", "Remote Sensing of Soil Moisture", "Surface Deformation Monitoring", "Computer science", "Agronomy", "Environmental sciences", "Geotechnical engineering", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "0401 agriculture", " forestry", " and fisheries", "Mathematics"]}, "links": [{"href": "https://essd.copernicus.org/articles/13/3707/2021/essd-13-3707-2021.pdf"}, {"href": "https://doi.org/10.5194/essd-13-3707-2021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Earth%20System%20Science%20Data", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/essd-13-3707-2021", "name": "item", "description": "10.5194/essd-13-3707-2021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/essd-13-3707-2021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-07T00:00:00Z"}}, {"id": "10.5281/zenodo.11421746", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:22:11Z", "type": "Software", "title": "ConFire: State of Wildfires 2023/24", "description": "Project Overview: This is the first release of our Bayesian-based fire models, designed for fire prediction and analysis using Bayesian inference and simple fire models. The release here is the base code and information used in the 'State of Wildfire's report 2023/24'. https://doi.org/10.5194/essd-2024-218 Key Features: ConFire fire model now implemented with zero-inflated logistic link distribution Configuration files for near real-time, attribution and future projections for Greece, Canada, and NW Amazon. Utilizes various environmental and climatic data for isimip and Copernicus data store Robust statistical analysis now uses PyMC at version 5 and ArviZ. Installation and Usage: For detailed installation and usage instructions, please refer to the README, also in this repository archive. Acknowledgments: Special thanks to all contributors and the developers of the dependencies used in this project. Particularly Maria Lucia Ferreira Barbosa, Douglas Kelley, Chantelle Burton Full Changelog: https://github.com/douglask3/Bayesian_fire_models/compare/v0.1...SoW23_v0.1", "keywords": ["Canada", "Attribution", "Greece", "Amazonia", "Wildfire", "Climatic changes", "Fire", "Bayesian statistics", "Future projections"], "contacts": [{"organization": "Barbosa, Maria Lucia Ferreira, Kelley, Douglas, Burton, Chantelle, Anderson, Liana,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.11421746"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.11421746", "name": "item", "description": "10.5281/zenodo.11421746", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.11421746"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-03T00:00:00Z"}}, {"id": "10.5281/zenodo.11460232", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:22:11Z", "type": "Software", "title": "ConFire: State of Wildfires 2023/24", "description": "Project Overview: This is the first release of our Bayesian-based fire models, designed for fire prediction and analysis using Bayesian inference and simple fire models. The release here is the base code and information used in the 'State of Wildfire's report 2023/24'. https://doi.org/10.5194/essd-2024-218 Key Features: ConFire fire model now implemented with zero-inflated logistic link distribution Configuration files for near real-time, attribution and future projections for Greece, Canada, and NW Amazon. Utilizes various environmental and climatic data for isimip and Copernicus data store Robust statistical analysis now uses PyMC at version 5 and ArviZ. Installation and Usage: For detailed installation and usage instructions, please refer to the README, also in this repository archive. Acknowledgments: Special thanks to all contributors and the developers of the dependencies used in this project. Particularly Maria Lucia Ferreira Barbosa, Douglas Kelley, Chantelle Burton Full Changelog: https://github.com/douglask3/Bayesian_fire_models/compare/v0.1...SoW23_v0.1", "keywords": ["Canada", "Attribution", "Greece", "Amazonia", "Wildfire", "Climatic changes", "Fire", "Bayesian statistics", "Future projections"], "contacts": [{"organization": "Barbosa, Maria Lucia Ferreira, Kelley, Douglas, Burton, Chantelle, Anderson, Liana,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.11460232"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.11460232", "name": "item", "description": "10.5281/zenodo.11460232", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.11460232"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-06-03T00:00:00Z"}}, {"id": "10.5281/zenodo.15303209", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:22:49Z", "type": "Dataset", "title": "Yield, soil and management data of the Frick long-term experiment on tillage, fertilization and biodynamic preparations on a Stagnic Eutric Cambisol in Switzerland", "description": "This dataset is part of the database compiled as an outcome of Work Area 1 in project OrganicYieldsUP. Variable definitions can be found here: \u00a0https://doi.org/10.5281/zenodo.15276082 In Frick (Switzerland), a long-term experiment was established at the farm of the Research Institute of Organic Agriculture (FiBL) in autumn 2002 on a clay loam (Stagnic Eutric Cambisol). In this three-factorial experiment, a reduced tillage system with a chisel plough to a depth of 10 cm is compared to conventional ploughing to a depth of approx. 20 cm, a liquid manure system is compared to a compost manure system and the adding of biodynamic preparations is compared to none preparations. Biodynamic preparations had been assessed previously in system comparison experiments, however, their effect is difficult to elucidate separately in a system comparison approach. One reason for setting up this experiment was therefore a demand among farmers and researchers in early 2000 to disentangle the influence of biodynamic preparations from the influence of manure compost on soil fertility. On the other hand, it should be tested if and how reduced tillage is feasible in organic farming.\u00a0This dataset consists of plot data for yield, soil and management from 2002 to 2018. The crop rotation at the start of the experiment was winter wheat, sunflower, spelt and two years of grass clover. Sunflower was excluded after 2010 because of total yield loss due to slugs. For yield, total aboveground plant biomass is given for silage maize, grass-clover and cover crops, grain yield for winter wheat, spelt and sunflowers. Total nitrogen and phosphorus contents of the yield components are given as well. Weed data is given as total weed cover and/or total weed biomass in the years with row crops. For pests and diseases, Fusarium toxins (DON) are given for 2003 and slug emergence for 2010. For soil data, soil organic carbon content, total nitrogen content and pH are given plotwise for the layers 0-10 cm and 10-20 cm in three year intervals generally. Bulk density is available for some years and plots. This dataset has been evaluated and published in a research paper by Maike Krauss, Alfred Berner, Fr\u00e9d\u00e9ric Perrochet, Robert Frei, Urs Niggli and Paul M\u00e4der (2020): Enhanced soil quality with reduced tillage an solid manures in organic farming \u2013 a synthesis of 15 years. Scientific Reports 10:4403, https://doi.org/10.1038/s41598-020-61320-8 We are grateful for the financial support in running the field trial by the Swiss Federal Office for Agriculture (FOAG) and following foundations: Software AG - Stiftung (DE), Stiftung zur Pflege von Mensch, Mitwelt und Erde (CH), Stiftung Edith Maryon (CHF), the COOP Sustainability Fund and the CORE Organic II funding bodies, being partners of the FP7 ERA-Net project TILMAN-ORG (www.coreorganic2.org).", "keywords": ["Organic Agriculture", "Animal manure", "Weed Control/statistics & numerical data", "Organic farming", "Nitrogen", "Yield (agricultural)", "Plant Weeds", "Ph-value", "Compost", "Soil fertility", "Weed", "Tillage", "Field experiment", "Crop rotation", "Long-term experiment", "Agricultural pest", "Liquid manure", "biodynamic preparations", "Organic carbon"], "contacts": [{"organization": "Grosse, Meike, Berner, Alfred, Perrochet, Fr\u00e9d\u00e9ric, Frei, Robert, M\u00e4der, Paul, Krauss, Maike,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.15303209"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.15303209", "name": "item", "description": "10.5281/zenodo.15303209", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.15303209"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-04-30T00:00:00Z"}}, {"id": "10.5281/zenodo.5907228", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:23:19Z", "type": "Software", "title": "Spatial statistics to reveal patterns and connections in the historic landscape", "description": "The R script code was developed by dr. F. Brandolini (Newcastle University, UK) to accompany the paper: F. Brandolini & S. Turner (2022) Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy), Journal of Maps, DOI: 10.1080/17445647.2022.2088305 Abstract In the Northern Apennines, significant modifications to the characteristic historic features of landscapes occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today European and national policies are promoting the repopulation of these regions in order to help preserve the cultural identity of territories and to reduce demographic pressure in urban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of a set of strategies to underpin the preservation of landscape heritage and to foster local development on the basis of the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components. Methods This dataset was explored with two spatial statistical tools using the programming language R (R Core Team 2021): Local Indicators for Categorical Data (LICD) and Point Pattern analysis (PPA). The LICD method is based on join-count statistics (JCS), a solid method to measure the correlation between binomial variables and the distance between observations. LICD has been recently employed in landscape archaeological studies for verifying visible patterns and disclosing hidden spatial relationships (article: Carrer et al. 2021, Data: Zenodo Repository) The application of PPA in landscape studies has been widely applied in Ecology and it is growing popular also in Archaeology (Knitter and Nakoinz 2018; Brandolini and Carrer 2020; Costanzo et al. 2021). In this study, PPA was employed to provide a quantitative assessment of the correlations between different components of the Vetto landscape. List of files included in Brandolini_Turner_tjom_2022.zip: R_script_code named 'tjom_supplementary' in .rmd format Output folder: png and .txt products of the R script code GeoTiff folder (.TIFF file format): Geomorphons Euclidean distances from Irregular Fields (IF) Euclidean distances from Combined Fields (CF) EsriSHP folder (.shp file format): H_sites folder: historic settlements (h_sites.shp) rural_ruins folder: abandoned rural ruins (rural_ruins.shp) hlc folder: HLC_periods.shp HLC_types.shp roi folder: Region Of Interest (roi.shp) Contacts dr. F. Brandolini: filippo.brandolini@newcastle.ac.uk Acknowledgements The authors would like to acknowledge the help of the mayor Mr Fabio Ruffini and all the staff of Vetto d\u2019 Enza, Dr. Alessandra Curotti and Dr. Chiara Cantini and (Unione Montana dei Comuni dell\u2019Appennino Reggiano) and Dott.ssa Annalisa Capurso (Soprintendenza Archeologia Belle Arti e Paesaggio per la citt\u00e0 metropolitana di Bologna e le province di Modena, Reggio Emilia e Ferrara) for their administrative assistance in preparation of the project fieldwork activities. Also, we wish to thank Dr Anna Campeol and Mr Davide Cavecchi (Provincia di Reggio Emilia - Ufficio Topografico) for their help in retrieving and digitising the Nuovo Catasto Terreni cadastral map. The authors also thank the AsRe (Archivio Stato di Reggio Emilia) and AsPr (Archivio Stato di Parma) administration and staff for giving the right to digitise the historical maps and for helping during the consultation at the archives. Finally, we thank Francesco Carrer (Newcastle University, Newcastle upon Tyne, UK) for his comments on the R script code, and Christopher Sevara (Newcastle University, Newcastle upon Tyne, UK) for his suggestions in retrieving historical satellite images.", "keywords": ["Landscape Heritage", "Landscape Management", "Landscape Archaeology", "Spatial Statistics", "11. Sustainability", "Spatial Humanities", "Digital Geoarchaeology", "15. Life on land", "Historic Landscape Characterisation", "Point Pattern Analysis", "Local Indicator for Categorical Data"], "contacts": [{"organization": "Brandolini, Filippo", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.5907228"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.5907228", "name": "item", "description": "10.5281/zenodo.5907228", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.5907228"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-26T00:00:00Z"}}, {"id": "2996829913", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:46Z", "type": "Journal Article", "created": "2019-12-27", "title": "Determining the effect of exogenous organic materials on spatial distribution of maize yield", "description": "Abstract

Knowledge on spatial distribution of crop yield in relation to fixed soil fertilisation with exogenous organic materials is essential for improving precise crop and soil management practices within a field. This study assessed the effect of various application rates and types of exogenous (recycled) organic materials (EOMs) containing different organic matter and nitrogen contents vs. mineral nitrogen on the yield of maize by means of linear regressions (trends), spatial kriging-interpolated maps, and Bland-Altman statistics. The experiments were conducted in 2013 and 2014 on two soils, i.e. loam silt in Braszowice (Poland) and clay silt loam in Pust\uffc3\uffa9 Jakartice (Czech Republic) under a cross-border cooperation project. The organic materials included compost from manure, slurry, and straw (Ag), industrial organic compost from sewage sludge (Ra), animal meal from animal by-products (Mb), and digestate from a biogas fries factory (Dg). The following 3 application rates of each EOM were adjusted according to the reference 100%\uffe2\uff80\uff89=\uffe2\uff80\uff89200\uffe2\uff80\uff89kg\uffe2\uff80\uff89N ha\uffe2\uff88\uff921: 50 (50% N from EOM and 50% mineral N), 75 (75% N from EOM and 25% mineral N), and 100 (100% N from EOM). 100% mineral N was applied on control plots. All treatments were carried out in 4 replicates. The linear regressions between the EOM application rates and the maize yield were in general ascending in the Braszowice soil and descending in the more productive Pust\uffc3\uffa9 Jakartice soil. The spatial kriging-interpolated maps allowed separating zones of lower and higher yields with EOMs compared to the control. They were attributed in part to the different EOM application rates and soil water contents. The Bland-Altaman statistics showed that addition of 50% of N from EOMs in 2013 caused a decrease and an increase in the maize grain yield in Braszowice and Pust\uffc3\uffa9 Jakartice, respectively, whereas the inverse was true with the 75 and 100% EOM additions. In 2014, the yield of maize for silage increased with the increasing EOM application rate in Braszowice and decreased in Pust\uffc3\uffa9 Jakartice, but it was smaller on all EOM-amended plots than in the control. As shown by the limits of agreement lines, the maize yields were more even in Pust\uffc3\uffa9 Jakartice than Braszowice. These results provide helpful information for selection of the most yield-producing EOM rates depending on the site soil conditions and prevalent weather conditions. PLEASE ensure you download the latest version of the tool.
LATEST VERSION: EX-TRACT tool_1.2
EX-TRACT tool_1.2 UPDATES: this version solves a problem that occurred on PC with decimal separator set with comma rather than dot.

For further support or to report any bug, please write to marco.acutis@unimi.it", "keywords": ["10401 Applied Statistics", "Environmental Science", "Statistics", "FOS: Mathematics", "70105 Agricultural Systems Analysis and Modelling", "FOS: Other agricultural sciences"], "contacts": [{"organization": "Acutis, Marco, Tadiello, Tommaso, Perego, Alessia, Guardo, Andrea Di, Schillaci, Calogero, Valkama, Elena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.6084/m9.figshare.14987130"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.14987130", "name": "item", "description": "10.6084/m9.figshare.14987130", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.14987130"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.6084/m9.figshare.20477290", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:11Z", "type": "Journal Article", "created": "2022-08-11", "title": "Revealing patterns and connections in the historic landscape of the northern Apennines (Vetto, Italy)", "description": "In the Northern Apennines, significant modifications to the characteristic historical features of landscapes have occurred since the 1950s as agriculture declined in importance and villages were progressively depopulated. Today, European policies are promoting the repopulation of these regions to help preserve the cultural identity of territories and reduce demographic pressure inurban areas. Such initiatives increase the need for cultural and natural landscape management to be better integrated using interdisciplinary approaches. Sustainable landscape management is a dynamic process involving the formulation of strategies to underpin the preservation of landscape heritage and foster local development based on the values and opportunities provided by landscapes themselves. This study uses landscape archaeology and spatial statistics to provide insights into which parts of the historic landscape retain the greatest time-depth and which parts reflect the more recent radical change, enabling an understanding which goes beyond the basic spatial relationships between landscape components.", "keywords": ["local indicators for categorical data", "point pattern analysis", "G3180-9980", "Landscape archaeology", "Maps", "11. Sustainability", "landscape management", "15. Life on land", "01 natural sciences", "historic landscape characterisation", "spatial statistics", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.tandfonline.com/doi/pdf/10.1080/17445647.2022.2088305"}, {"href": "https://eprints.ncl.ac.uk/fulltext.aspx?url=284595/39618FDF-222E-4078-8426-E55819A569AD.pdf&pub_id=284595"}, {"href": "https://doi.org/10.6084/m9.figshare.20477290"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Maps", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.6084/m9.figshare.20477290", "name": "item", "description": "10.6084/m9.figshare.20477290", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.6084/m9.figshare.20477290"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-01T00:00:00Z"}}, {"id": "10037/33301", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:23Z", "type": "Journal Article", "created": "2024-03-21", "title": "Global consortium for the classification of fungi and fungus-like taxa", "description": "The Global Consortium for the Classification of Fungi and fungus-like taxa is an international initiative of more than 550 mycologists to develop an electronic structure for the classification of these organisms. The members of the Consortium originate from 55 countries/regions worldwide, from a wide range of disciplines, and include senior, mid-career and early-career mycologists and plant pathologists. The Consortium will publish a biannual update of the Outline of Fungi and fungus-like taxa, to act as an international scheme for other scientists. Notes on all newly published taxa at or above the level of species will be prepared and published online on the Outline of Fungi website (https://www.outlineoffungi.org/), and these will be finally published in the biannual edition of the Outline of Fungi and fungus-like taxa. Comments on recent important taxonomic opinions on controversial topics will be included in the biannual outline. For example, \u2018to promote a more stable taxonomy in Fusarium given the divergences over its generic delimitation\u2019, or \u2018are there too many genera in the Boletales?\u2019 and even more importantly, \u2018what should be done with the tremendously diverse \u2018dark fungal taxa?\u2019 There are undeniable differences in mycologists\u2019 perceptions and opinions regarding species classification as well as the establishment of new species. Given the pluralistic nature of fungal taxonomy and its implications for species concepts and the nature of species, this consortium aims to provide a platform to better refine and stabilise fungal classification, taking into consideration views from different parties. In the future, a confidential voting system will be set up to gauge the opinions of all mycologists in the Consortium on important topics. The results of such surveys will be presented to the International Commission on the Taxonomy of Fungi (ICTF) and the Nomenclature Committee for Fungi (NCF) with opinions and percentages of votes for and against. Criticisms based on scientific evidence with regards to nomenclature, classifications, and taxonomic concepts will be welcomed, and any recommendations on specific taxonomic issues will also be encouraged; however, we will encourage professionally and ethically responsible criticisms of others\u2019 work. This biannual ongoing project will provide an outlet for advances in various topics of fungal classification, nomenclature, and taxonomic concepts and lead to a community-agreed classification scheme for the fungi and fungus-like taxa. Interested parties should contact the lead author if they would like to be involved in future outlines.", "keywords": ["[SDE] Environmental Sciences", "570", "Biologisk systematik", "scientific criticism", "Evolution", "[SPI] Engineering Sciences [physics]", "[SDV]Life Sciences [q-bio]", "0607 Plant Biology", "Plant Science", "Biological Systematics", "Mycology", "FATTY-ACID-COMPOSITION", "[SPI]Engineering Sciences [physics]", "taxonomy", "Behavior and Systematics", "DNA-SEQUENCE DATA", "taksonomia", "Biowissenschaften; Biologie", "NOMENCLATURE", "INCORPORATING ANAMORPHIC FUNGI", "NATURAL CLASSIFICATION", "TREE", "580", "Science & Technology", "Ecology", "IDENTIFICATION", "klasyfikacja", "classification", " nomenclature", " scientific criticism", " taxonomy", "Botany", "Botanik", "15. Life on land", "classification; nomenclature; scientific criticism; taxonomy", "naukowy krytycyzm", "nomenklatura", "[STAT] Statistics [stat]", "SPECIES RECOGNITION", "[STAT]Statistics [stat]", "[SDV] Life Sciences [q-bio]", "3107 Microbiology", "classification", "[SDE]Environmental Sciences", "3108 Plant biology", "nomenclature", "LEVEL PHYLOGENETIC CLASSIFICATION", "Life Sciences & Biomedicine", "LEAF-LITTER", "QK01 Systematic botany / n\u00f6v\u00e9nyrendszertan", "0605 Microbiology"]}, "links": [{"href": "https://www.research.unipd.it/bitstream/11577/3509765/2/5.%20Hyde%20et%20al%202023.pdf"}, {"href": "https://doi.org/10037/33301"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Mycosphere", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10037/33301", "name": "item", "description": "10037/33301", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10037/33301"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-01-01T00:00:00Z"}}, {"id": "10419/266274", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:38Z", "type": "Journal Article", "created": "2021-09-06", "title": "Robust Bayesian insurance premium in a collective risk model with distorted priors under the generalised Bregman loss", "description": "Abstract

The article presents a collective risk model for the insurance claims. The objective is to estimate a premium, which is defined as a functional specified up to unknown parameters. For this purpose, the Bayesian methodology, which combines the prior knowledge about certain unknown parameters with the knowledge in the form of a random sample, has been adopted. The generalised Bregman loss function is considered. In effect, the results can be applied to numerous loss functions, including the square-error, LINEX, weighted square-error, Brown, entropy loss. Some uncertainty about a prior is assumed by a distorted band class of priors. The range of collective and Bayes premiums is calculated and posterior regret \uffce\uff93-minimax premium as a robust procedure has been implemented. Two examples are provided to illustrate the issues considered - the first one with an unknown parameter of the Poisson distribution, and the second one with unknown parameters of distributions of the number and severity of claims.The relationship between the spatial variability of soil multifunctionality (i.e., the capacity of soils to conduct multiple functions; SVM) and major climatic drivers, such as temperature and aridity, has never been assessed globally in terrestrial ecosystems. We surveyed 236 dryland ecosystems from six continents to evaluate the relative importance of aridity and mean annual temperature, and of other abiotic (e.g., texture) and biotic (e.g., plant cover) variables as drivers of SVM, calculated as the averaged coefficient of variation for multiple soil variables linked to nutrient stocks and cycling. We found that increases in temperature and aridity were globally correlated to increases in SVM. Some of these climatic effects on SVM were direct, but others were indirectly driven through reductions in the number of vegetation patches and increases in soil sand content. The predictive capacity of our structural equation\uffc2\uffa0modelling was clearly higher for the spatial variability of N\uffe2\uff80\uff90 than for C\uffe2\uff80\uff90 and P\uffe2\uff80\uff90related soil variables. In the case of N cycling, the effects of temperature and aridity were both direct and indirect via changes in soil properties. For C and P, the effect of climate was mainly indirect via changes in plant attributes. These results suggest that future changes in climate may decouple the spatial availability of these elements for plants and microbes in dryland soils. Our findings significantly advance our understanding of the patterns and mechanisms driving SVM in drylands across the globe, which is critical for predicting changes in ecosystem functioning in response to climate change.