Crop and land management practices affect both the quality and quantity of soil organic matter (SOM) and hence are driving forces for soil organic carbon (SOC) sequestration. The objective of this study was to assess the long\uffe2\uff80\uff90term effects of tillage, fertilizer application and crop rotation onSOCin an agricultural area of southern Norway, where a soil fertility and crop rotation experiment was initiated in 1953 and a second experiment on tillage practices was initiated in 1983. The first experiment comprised 6\uffe2\uff80\uff90yr crop rotations with cereals only and 2\uffe2\uff80\uff90yr cereal and 4\uffe2\uff80\uff90yr grass rotations with recommended (base) and more than the recommended (above base) fertilizer application rates; the second experiment dealt with autumn\uffe2\uff80\uff90ploughed (conventional\uffe2\uff80\uff90till) plots and direct\uffe2\uff80\uff90drilled plots (no\uffe2\uff80\uff90till). Soil samples at 0\uffe2\uff80\uff9310 and 10\uffe2\uff80\uff9330\uffc2\uffa0cm depths were collected in autumn 2009 and analysed for their C and N contents. The quality ofSOMin the top layer was determined by13C solid\uffe2\uff80\uff90stateNMRspectroscopy. TheSOCstock did not differ significantly because of rotation or fertilizer application types, even after 56\uffc2\uffa0yr. However, the no\uffe2\uff80\uff90till system showed a significantly higherSOCstock than the conventional\uffe2\uff80\uff90till system at the 0\uffe2\uff80\uff9310\uffc2\uffa0cm depth after the 26\uffc2\uffa0yr of experiment, but it was not significantly different at the 10\uffe2\uff80\uff9330\uffc2\uffa0cm depth. In terms of quality,SOMwas found to differ by tillage type, rate of fertilizer application and crop rotation. The no\uffe2\uff80\uff90till system showed an abundance of O\uffe2\uff80\uff90alkyl C, while conventional\uffe2\uff80\uff90till system indicated an apparently indirect enrichment in alkyl C, suggesting a more advanced stage ofSOMdecomposition. The long\uffe2\uff80\uff90term quantitative and qualitative effects onSOMsuggest that adopting a no\uffe2\uff80\uff90tillage system and including grass in crop rotation and farmyard manure in fertilizer application may contribute to preserve soil fertility and mitigate climate change.
", "keywords": ["Fertilizer application", "2. Zero hunger", "Crop rotation", " fertilizer application", " soil organic carbon (SOC)", " soil organic matter (SOM)", " tillage", " NMR spectroscopy.", "NMR spectroscopy", "Crop rotation", "Soil organic matter (SOM)", "13. Climate action", "Soil organic carbon (SOC)", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "Tillage"]}, "links": [{"href": "https://doi.org/10.1111/sum.12198"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20Use%20and%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1111/sum.12198", "name": "item", "description": "10.1111/sum.12198", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1111/sum.12198"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-07-31T00:00:00Z"}}, {"id": "10.17026/dans-z8z-5t4e", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:18:50Z", "type": "Dataset", "title": "Consumers' attitudes towards microbial applications in food production", "description": "The data was collected using an online survey as part of the research activities of the European Horizon 2020 project SIMBA (Sustainable Innovation of Microbiome Applications in the Food System). Online surveys were used to collect consumer respondent data for three food products (wheat bread, consumer potatoes and tomato sauce). These food products were selected as part of the EU Horizon 2020 SIMBA project for reflecting the diversity of food value chains in terms of organisation, technology, climatic conditions and consumption patterns across the EU. Three questionnaires corresponding to the three food products were prepared. The questionnaires consisted of four main parts: (1) socio-demographic characteristics (e.g. gender, education, income; Part One), (2) health and environmental concerns related to chemical use in farming, knowledge about microbial applications, perceived microbial health risks and attitude towards microbial applications in food production (Part Two), (3) questions for eliciting a consumer\u2019s willingness-to-pay (WTP) for a food product that had been obtained through a microbial-enhanced production system with reduced or no chemical use (Part Three), and (4) questions for eliciting a respondent\u2019s food choice motives (FCMs) using de Boer et al.\u2019s (2007) FCM questionnaire (Part Four). In addition, the questionnaire had an introduction section containing information sheet about the study and a consent form. The consent form and the information sheet for safeguarding the ethical aspects of this study (e.g. data handling, privacy and potential risks to respondents) were approved by the General Assembly of the SIMBA project as well as the Social Sciences Ethics Committee of Wageningen University prior to distributing the surveys. We collected data primarily from three countries: Germany, Italy and Netherlands.The data was collected to undertake a study to support the uptake of food products that are produced and/or processed using microbial applications. The aim of the survey was to get some insights about food choice motives of consumers, and the socio-demographic and behavioural factors influencing their food choices. The survey specifically aimed to assess the preferences and perceptions, and willingness-to-pay of consumers to wheat, potato and tomato-based food products that are produced and/or processed using microbial applications.", "keywords": ["2. Zero hunger", "13. Climate action", "Economics", "Social and Behavioural Sciences", "Business and Management", "Food economics", "12. Responsible consumption"], "contacts": [{"organization": "BM Ali", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.17026/dans-z8z-5t4e"}, {"rel": "self", "type": "application/geo+json", "title": "10.17026/dans-z8z-5t4e", "name": "item", "description": "10.17026/dans-z8z-5t4e", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.17026/dans-z8z-5t4e"}, {"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": "10.5194/acp-10-7017-2010", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:20:08Z", "type": "Journal Article", "created": "2010-04-29", "description": "Abstract. We present and discuss a new dataset of gridded emissions covering the historical period (1850\uffe2\uff80\uff932000) in decadal increments at a horizontal resolution of 0.5\uffc2\uffb0 in latitude and longitude. The primary purpose of this inventory is to provide consistent gridded emissions of reactive gases and aerosols for use in chemistry model simulations needed by climate models for the Climate Model Intercomparison Program #5 (CMIP5) in support of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Our best estimate for the year 2000 inventory represents a combination of existing regional and global inventories to capture the best information available at this point; 40 regions and 12 sectors are used to combine the various sources. The historical reconstruction of each emitted compound, for each region and sector, is then forced to agree with our 2000 estimate, ensuring continuity between past and 2000 emissions. Simulations from two chemistry-climate models is used to test the ability of the emission dataset described here to capture long-term changes in atmospheric ozone, carbon monoxide and aerosol distributions. The simulated long-term change in the Northern mid-latitudes surface and mid-troposphere ozone is not quite as rapid as observed. However, stations outside this latitude band show much better agreement in both present-day and long-term trend. The model simulations indicate that the concentration of carbon monoxide is underestimated at the Mace Head station; however, the long-term trend over the limited observational period seems to be reasonably well captured. The simulated sulfate and black carbon deposition over Greenland is in very good agreement with the ice-core observations spanning the simulation period. Finally, aerosol optical depth and additional aerosol diagnostics are shown to be in good agreement with previously published estimates and observations.
", "keywords": ["info:eu-repo/classification/ddc/550", "550", "IPCC", "[SDE.MCG]Environmental Sciences/Global Changes", "Physics", "QC1-999", "emissions", "551", "01 natural sciences", "7. Clean energy", "J", "[SDE.MCG] Environmental Sciences/Global Changes", "Chemistry", "13. Climate action", "[SDE.ES] Environmental Sciences/Environment and Society", "CMIP5", "[SDE.ES]Environmental Sciences/Environment and Society", "QD1-999", "AR5", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "http://pure.iiasa.ac.at/id/eprint/9279/1/acp-10-7017-2010.pdf"}, {"href": "https://doi.org/10.5194/acp-10-7017-2010"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Atmospheric%20Chemistry%20and%20Physics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/acp-10-7017-2010", "name": "item", "description": "10.5194/acp-10-7017-2010", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/acp-10-7017-2010"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-02-19T00:00:00Z"}}, {"id": "10.7910/DVN/M4ZGXP", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:22:10Z", "type": "Dataset", "title": "MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory", "description": "<b>MSZSI: Multi-Scale Zonal Statistics [AgriClimate] Inventory</b> <br><br> -------------------------------------------------------------------------------------- <br> MSZSI is a data extraction tool for Google Earth Engine that aggregates time-series remote sensing information to multiple administrative levels using the FAO GAUL data layers. The code at the bottom of this page (metadata) can be pasted into the Google Earth Engine JavaScript code editor and ran at https://code.earthengine.google.com/. <br><br> <i>Please refer to the associated publication</i>: <br> Peter, B.G., Messina, J.P., Breeze, V., Fung, C.Y., Kapoor, A. and Fan, P., 2024. Perspectives on modifiable spatiotemporal unit problems in remote sensing of agriculture: evaluating rice production in Vietnam and tools for analysis. <i>Frontiers in Remote Sensing</i>, 5, p.1042624. <br> <a href='https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624'>https://www.frontiersin.org/journals/remote-sensing/articles/10.3389/frsen.2024.1042624</a> <br><br> <i>Input options:</i> <br> [1] Country of interest <br> [2] Start and end year <br> [3] Start and end month <br> [4] Option to mask data to a specific land-use/land-cover type <br> [5] Land-use/land-cover type code from CGLS LULC <br> [6] Image collection for data aggregation <br> [7] Desired band from the image collection <br> [8] Statistics type for the zonal aggregations <br> [9] Statistic to use for annual aggregation <br> [10] Scaling options <br> [11] Export folder and label suffix <br><br> <i>Output:</i> Two CSVs containing zonal statistics for each of the FAO GAUL administrative level boundaries <br> <i>Output fields:</i> system:index, 0-ADM0_CODE, 0-ADM0_NAME, 0-ADM1_CODE, 0-ADM1_NAME, 0-ADMN_CODE, 0-ADMN_NAME, 1-AREA_PERCENT_LULC, 1-AREA_SQM_LULC, 1-AREA_SQM_ZONE, 2-X_2001, 2-X_2002, 2-X_2003, ..., 2-X_2020, .geo <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_input_v5.PNG?raw=true' width='1000' height='auto'</img> <br><br> <b>PREPROCESSED DATA DOWNLOAD</b> <br><br> The datasets available for download contain zonal statistics at 2 administrative levels (FAO GAUL levels 1 and 2). Select countries from Southeast Asia and Sub-Saharan Africa <b>(Cambodia, Indonesia, Lao PDR, Myanmar, Philippines, Thailand, Vietnam, Burundi, Kenya, Malawi, Mozambique, Rwanda, Tanzania, Uganda, Zambia, Zimbabwe)</b> are included in the current version, with plans to extend the dataset to contain global metrics. Each zip file is described below and two example NDVI tables are available for preview. <br><br> <b>Key</b>: [source, data, units, temporal range, aggregation, masking, zonal statistic, notes] <br><br> Currently available: <br><b>MSZSI-V2_V-NDVI-MEAN.tar</b>: [NASA-MODIS, NDVI, index, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-DAY-MEAN.tar</b>: [NASA-MODIS, LST Day, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_T-LST-NIGHT-MEAN.tar</b>: [NASA-MODIS, LST Night, \u00b0C, 2001\u20132020, annual mean, agriculture, mean, n/a] <br><b>MSZSI-V2_R-PRECIP-SUM.tar</b>: [UCSB-CHG-CHIRPS, Precipitation, mm, 2001\u20132020, annual sum, agriculture, mean, n/a] <br><b>MSZSI-V2_S-BDENS-MEAN.tar</b>: [OpenLandMap, Bulk density, g/cm3, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-ORGC-MEAN.tar</b>: [OpenLandMap, Organic carbon, g/kg, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-PH-MEAN.tar</b>: [OpenLandMap, pH in H2O, pH, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-WATER-MEAN.tar</b>: [OpenLandMap, Soil water, % at 33kPa, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SAND-MEAN.tar</b>: [OpenLandMap, Sand, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-SILT-MEAN.tar</b>: [OpenLandMap, Silt, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_S-CLAY-MEAN.tar</b>: [OpenLandMap, Clay, %, static, n/a, agriculture, mean, at depths 0-10-30-60-100-200] <br><b>MSZSI-V2_E-ELEV-MEAN.tar</b>: [MERIT, [elevation, slope, flowacc, HAND], [m, degrees, km<sup>2</sup>, m], static, n/a, agriculture, mean, n/a] <br><br><i>Coming soon</i> <br><b>MSZSI-V2_C-STAX-MEAN.tar</b>: [OpenLandMap, Soil taxonomy, category, static, n/a, agriculture, area sum, n/a] <br><b>MSZSI-V2_C-LULC-MEAN.tar</b>: [CGLS-LC100-V3, LULC, category, 2015\u20132019, mode, none, area sum, n/a] <br><br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_diagram_v2.png?raw=true' width='1000' height='auto'</img> <br><br> <b>Data sources:</b> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD13Q1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2'>https://developers.google.com/earth-engine/datasets/catalog/MODIS_006_MOD11A2</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD'>https://developers.google.com/earth-engine/datasets/catalog/UCSB-CHG_CHIRPS_PENTAD</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_BULKDENS-FINEEARTH_USDA-4A1H_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_ORGANIC-CARBON_USDA-6A1C_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_PH-H2O_USDA-4C1A2A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_WATERCONTENT-33KPA_USDA-4B1C_M_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_CLAY-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_SAND-WFRACTION_USDA-3A1A1A_M_v02</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01'>https://developers.google.com/earth-engine/datasets/catalog/OpenLandMap_SOL_SOL_GRTGROUP_USDA-SOILTAX_C_v01</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global'>https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1'>https://developers.google.com/earth-engine/datasets/catalog/MERIT_Hydro_v1_0_1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1</a> <br><li><a href='https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2'>https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2</a></li> <br> <b>Project information:</b> <br> SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes <br> <a href='http://seagul.info/'>http://seagul.info/</a>; <a href='https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental'>https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental</a> <br> This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) <br><br> For an additional interactive visualization, visit: <a href='https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi'>https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi</a> <br><br> <img src ='https://github.com/cartoscience/seagul/blob/main/mszsi/mszsi_app.png?raw=true' width='1000' height='auto'</img> <br><br><br> <i> Google Earth Engine code</i> <pre> /*/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// MSZSI: Multi-Scale Zonal Statistics Inventory Authors: Brad G. Peter, Department of Geography, University of Alabama Joseph Messina, Department of Geography, University of Alabama Austin Raney, Department of Geography, University of Alabama Rodrigo E. Principe, AgriCircle AG Peilei Fan, Department of Geography, Environment, and Spatial Sciences, Michigan State University Citation: Peter, Brad; Messina, Joseph; Raney, Austin; Principe, Rodrigo; Fan, Peilei, 2021, 'MSZSI: Multi-Scale Zonal Statistics Inventory', https://doi.org/10.7910/DVN/YCUBXS, Harvard Dataverse, V# SEAGUL: Southeast Asia Globalization, Urbanization, Land and Environment Changes http://seagul.info/ https://lcluc.umd.edu/projects/divergent-local-responses-globalization-urbanization-land-transition-and-environmental This project was made possible by the the NASA Land-Cover/Land-Use Change Program (Grant #: 80NSSC20K0740) ///////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////*/ /*----------------------------------------------------------------------------------------------------------------------------------- Description: MSZSI is a data extraction tool for aggregating time-series remote sensing information to multiple administrative levels using the FAO GAUL data layers. Input parameterization: [1] Enter the country code for the desired country [2] Select a start and end year. Be sure to check for data availability in the collection selected in input 6. [3] Select a start month and end month to specify a temporal range within each year. [4] Select an image collection for data aggregation. [5] Select the desired band from the image collection. [6] Option to mask data to a specific land-use/land-cover type. Enter 'TRUE' or 'FALSE'. [7] Enter a land-use/land-cover type code from CGLS LULC. Ignore this option if no masking is desired and set input 4 to 'FALSE'. [8] Select a statistics type for the zonal aggregations (defaults to mean) [9] Select a statistic for temporal aggregation (see available options in the parameterization below) [10] Scaling options [11] Export folder output file label suffix Check tasks tab for CSV exports. Select a point on the map to view timeseries statistics. Hover over the layers panel to turn layers on/off and set visualization parameters. For an additional interactive visualization, visit: https://cartoscience.users.earthengine.app/view/maup-mapper-multi-scale-modis-ndvi Boundary data Layers: https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level0 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level1 https://developers.google.com/earth-engine/datasets/catalog/FAO_GAUL_2015_level2 -----------------------------------------------------------------------------------------------------------------------------------*/ // \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022 USER PARAMETERIZATION \u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022\u2022 /*[1]*/ var countryCode = 264 // Refer to http://www.fao.org/in-action/countrystat/news-and-events/events/training-material/gaul-codes2014/en/ /*[2]*/ var startYear = 2001 // Check data availability for the collection selected in input 4 var endYear = 2020 /*[3]*/ var startMonth = 1 var endMonth = 12 /*[4]*/ var ic = ee.ImageCollection('MODIS/006/MOD13Q1') /*[5]*/ var band = 'NDVI' /*[6]*/ var maskToLULC = 'TRUE' // Set to 'TRUE' or 'FALSE' /*[7]*/ var lcType = 40 // Refer to https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_Landcover_100m_Proba-V-C3_Global /*[8]*/ var zonalStatType = ee.Reducer.mean() // examples: ee.Reducer.mean(), ee.Reducer.median(), ee.Reducer.stdDev(), // ee.Reducer.min(), ee.Reducer.max(), ee.Reducer.sum() /*[9]*/ var temporalAggregateType = 'mean' // available options: 'mean', 'median', 'stddev', 'min', 'max', 'sum' /*[10]*/ var nativeScale = 'TRUE' // Set to 'TRUE' or 'FALSE' var scale = 1000 // option to increase the scale to avoid memory crashes /*[11]*/ var exportFolder = 'GEE_Exports' var labelSuffix = 'NDVI-MEAN_VIETNAM' // sample export name: MSZSI-V2_2001-2020_1-12_LC40_GAUL-152-L1_NDVI-MEAN_VIETNAM, but can be changed during download prompt // note that some country names will need to be adjusted in the download prompt if they contain special characters ///////////////////////////////////////////////////// NO USER INPUT NEEDED BELOW //////////////////////////////////////////////////// // Administrative zones and preprocessing ------------------------------------------------------------------------------------------- ic = ic.select(band) var years = ee.List.sequence(startYear,endYear) var fc_L0 = ee.FeatureCollection('FAO/GAUL/2015/level0').filterMetadata('ADM0_CODE','equals',countryCode) var fc_L1 = ee.FeatureCollection('FAO/GAUL/2015/level1').filterMetadata('ADM0_CODE','equals',countryCode) .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME'], ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME']) fc_L1 = fc_L1.map(function(f) { return f.set('0-ADM2_CODE','NULL').set('0-ADM2_NAME','NULL') }) var fc_L2 = ee.FeatureCollection('FAO/GAUL/2015/level2').filterMetadata('ADM0_CODE','equals',countryCode) .select(['ADM0_CODE','ADM0_NAME','ADM1_CODE','ADM1_NAME','ADM2_CODE','ADM2_NAME'], ['0-ADM0_CODE','0-ADM0_NAME','0-ADM1_CODE','0-ADM1_NAME','0-ADM2_CODE','0-ADM2_NAME']) // LULC preprocessing --------------------------------------------------------------------------------------------------------------- var lulc = ee.ImageCollection('COPERNICUS/Landcover/100m/Proba-V-C3/Global').select('discrete_classification') var lulcMode = lulc.mode().eq(lcType) var lcLabel = '_LC'+lcType var lulcClip = lulcMode.clip(fc_L0) var lulcZone = lulcClip.remap([0,1],[1,1]).rename('zoneArea') var mask = lulcClip.updateMask(lulcClip.eq(1)).rename('mask') if(maskToLULC == 'FALSE') { lcLabel = '' mask = lulcZone } if(nativeScale == 'TRUE') { scale = lulc.first().projection().nominalScale() } // Add area fields ------------------------------------------------------------------------------------------------------------------ var temporal = ee.ImageCollection(years.map(function(y) { var filterYear = ic.filter(ee.Filter.calendarRange(y,y,'year')) .filter(ee.Filter.calendarRange(startMonth, endMonth, 'month')) var aggregate // the temporal aggregation type is set in input 9 if (temporalAggregateType == 'mean') { aggregate = filterYear.mean() } if (temporalAggregateType == 'median') { aggregate = filterYear.median() } if (temporalAggregateType == 'stddev') { aggregate = filterYear.stdDev() } if (temporalAggregateType == 'min') { aggregate = filterYear.min() } if (temporalAggregateType == 'max') { aggregate = filterYear.max() } if (temporalAggregateType == 'sum') { aggregate = filterYear.sum() } return aggregate.where(aggregate.eq(0),1e-10) // True zeroes are currently set to 1e-10 to avoid false no data flags .updateMask(mask) .set('extract',ee.String('2-'+labelSuffix+'_').cat(ee.Number(y).toInt())) .set('year',ee.Number(y).toInt()) .rename('band') })) // Run functions for each administrative level -------------------------------------------------------------------------------------- var zonal_L1 = zonalStat(fc_L1) var zonal_L2 = zonalStat(fc_L2) var merge = zonal_L1.combine(zonal_L2) var fcAreas_L1 = getAreas(fc_L1) var fcAreas_L2 = getAreas(fc_L2) var samples_L1 = createSamples(fc_L1) var samples_L2 = createSamples(fc_L2) var added_L1 = addFields(samples_L1,fcAreas_L1.select('zoneAreas'),fcAreas_L1.select('lulcAreas')) var added_L2 = addFields(samples_L2,fcAreas_L2.select('zoneAreas'),fcAreas_L2.select('lulcAreas')) exporter(added_L1,zonal_L1,1) exporter(added_L2,zonal_L2,2) // Calculate zonal statistics ------------------------------------------------------------------------------------------------------- function zonalStat(fc) { return temporal.map(function(i) { var year = i.get('year') return i.reduceRegions({ collection: fc, reducer: ee.Reducer.mean().setOutputs(['zStat']), scale: scale }).reduceToImage({ properties: ['zStat'], reducer: ee.Reducer.first() }).set('extract',i.get('extract')).set('year',year).rename('band') }) } // Calculate areas ------------------------------------------------------------------------------------------------------------------ function getAreas(fc) { var zoneAreas = ee.Image.pixelArea().updateMask(lulcZone).reduceRegions({ collection: fc, reducer: ee.Reducer.sum(), scale: scale }).reduceToImage({ properties: ['sum'], reducer: ee.Reducer.first() }).rename('zoneAreas') var lulcAreas = ee.Image.pixelArea().updateMask(mask).reduceRegions({ collection: fc, reducer: ee.Reducer.sum(), scale: scale }).reduceToImage({ properties: ['sum'], reducer: ee.Reducer.first() }).rename('lulcAreas') return zoneAreas.addBands(lulcAreas) } // Feature to points ---------------------------------------------------------------------------------------------------------------- function createSamples(fc) { return fc.map(function(g) { return ee.Feature(ee.FeatureCollection.randomPoints({ region: g.geometry(), points: 1, seed: 0 }).geometry()).copyProperties(g) }) } // Add area fields ------------------------------------------------------------------------------------------------------------------ function addFields(samples, areaGridZone, areaGridLULC) { return samples.map(function(p) { var point = p.geometry() var zoneArea = areaGridZone.rename('area').reduceRegion({ reducer: ee.Reducer.first(), geometry: point, scale: 1, maxPixels: 1e13 }).get('area') var lulcArea = areaGridLULC.rename('area').reduceRegion({ reducer: ee.Reducer.first(), geometry: point, scale: 1 }).get('area') var percLULC = ee.Number(lulcArea).divide(zoneArea).multiply(100) return ee.Feature(p).set('1-AREA_SQM_LULC',0) .set('1-AREA_SQM_ZONE',zoneArea).set('1-AREA_SQM_LULC',ee.Algorithms.If(lulcArea,lulcArea,0)) .set('1-AREA_PERCENT_LULC',ee.Algorithms.If(lulcArea,percLULC,0)) }) } // Export function ------------------------------------------------------------------------------------------------------------------ function exporter(e,zones,n) { var extracted = e.map(extractToPoints) function extractToPoints(feature) { var geom = feature.geometry() var addField = function(image, f) { var newFeature = ee.Feature(f) var getName = image.get('extract') var setValue = image.reduceRegion({ reducer: ee.Reducer.first(), geometry: geom, scale: 1, maxPixels: 1e13 }).get('band') return ee.Feature(ee.Algorithms.If(setValue, newFeature.set(getName, ee.String(setValue)), newFeature.set(getName, ee.String('No data')))) } var newFeature = ee.Feature(zones.iterate(addField, feature)) return newFeature } Export.table.toDrive({ collection: extracted, description: 'MSZSI-V2_'+startYear+'-'+endYear+'_'+startMonth+'-'+endMonth +lcLabel+'_GAUL-'+countryCode+'-L'+n+'_'+labelSuffix, folder: exportFolder }) } // Map display settings ------------------------------------------------------------------------------------------------------------- var leftMap = ui.Map() var rightMap = ui.Map() ui.Map.Linker([leftMap, rightMap]) ui.root.widgets().reset([leftMap,rightMap]) leftMap.centerObject(fc_L0) leftMap.setOptions('HYBRID').style().set('cursor', 'crosshair') rightMap.setOptions('HYBRID').style().set('cursor', 'crosshair') // Adds each image to the map displays var len = years.length().getInfo() for (var i = 0; i < len; i++) { var year = i+startYear var namer = 'ZSTATS_'+year var image_L1 = ee.Image(zonal_L1.toList(zonal_L1.size()).get(i)).rename(band) var image_L2 = ee.Image(zonal_L2.toList(zonal_L2.size()).get(i)).rename(band) leftMap.addLayer(image_L1,{},namer,false) rightMap.addLayer(image_L2,{},namer,false) } var hollow = {color: 'white', width: 0.3, fillColor: '00000000'} leftMap.addLayer(fc_L1.style(hollow),{},'FAO-GAUL-L1') rightMap.addLayer(fc_L2.style(hollow),{},'FAO-GAUL-L2') // Chart display settings ----------------------------------------------------------------------------------------------------------- var chartOptions = { fontSize: 11, width: '100px', curveType: 'function', format: 'short', margin: '0 0 0 0', hAxis: {format: '0000', textStyle: {fontSize: 10, color: '303030'}, gridlines: {color: 'transparent'}}, vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}}, trendlines: {0: {color: '303030', lineWidth: 0.5, visibleInLegend: false}}, series: {0: {color: '303030', lineWidth: 0.8}}, legend: {textStyle: {color: '303030'}}, } var panelStyle = { width: '235px', position: 'bottom-left', margin: '0 0 0 0', border: '1px solid #303030' } var leftChart = ui.Panel({ widgets: ui.Label('Select a point to chart regional time-series',{margin: '0 0 0 0', color:'303030'}), style: panelStyle }) leftMap.add(leftChart) // onClick function to query time-series -------------------------------------------------------------------------------------------- function pickLocation(location) { leftChart.widgets().set(0,ui.Label('Time-series',{fontSize: '14px', fontWeight: 'bold', color: '303030', margin: '7px 0 7px 10px'})) var chartOptions = { fontSize: 10, height: '200px', curveType: 'function', format: 'short', margin: '0 0 0 0', hAxis: {format: '0000', textStyle: {fontSize: 11, color: '303030'}, gridlines: {color: 'transparent'}}, vAxis: {textStyle: {fontSize: 10, color: '303030'}, gridlines: {}}, trendlines: {0: {color: 'blue', lineWidth: 0.5, visibleInLegend: false}, 1: {color: 'red', lineWidth: 0.5, visibleInLegend: false} }, series: {0: {color: 'blue', lineWidth: 0.8}, 1: {color: 'red', lineWidth: 0.8} }, legend: {position:'none'} } leftChart.widgets().set(1,ui.Label('Loading...',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'})) leftChart.widgets().set(2,ui.Label('',{fontSize: '13px',color:'9C9C9C', margin: '0 0 7px 10px'})) var pLat = location.lat var pLon = location.lon var point = ee.Geometry.Point([pLon,pLat]) var selection_L1 = fc_L1.filterBounds(point) var selection_L2 = fc_L2.filterBounds(point) var zone_L1_name = ee.Feature(selection_L1.first()).get('0-ADM1_NAME') var zone_L2_name = ee.Feature(selection_L2.first()).get('0-ADM2_NAME') leftChart.widgets().set(3,ui.Chart.image.series({ imageCollection: merge, region: point, scale: scale, xProperty: 'year' }).setOptions(chartOptions)) zone_L1_name.evaluate(function(result_L1) { zone_L2_name.evaluate(function(result_L2) { leftChart.widgets().set(1,ui.Label(result_L1+' (L1)',{fontSize: '13px', color: 'blue', margin: '0 0 7px 10px'})) leftChart.widgets().set(2,ui.Label(result_L2+' (L2)',{fontSize: '13px', color: 'red', margin: '0 0 0 10px'})) }) }) leftMap.layers().set(len+1, ui.Map.Layer(point,{color: 'blue', opacity: 0.6},'Selected point')) rightMap.layers().set(len+1, ui.Map.Layer(point,{color: 'red', opacity: 0.6},'Selected point')) } leftMap.onClick(pickLocation) rightMap.onClick(pickLocation) </pre>", "keywords": ["Computer and Information Science", "Agricultural Sciences", "Earth and Environmental Sciences", "Social Sciences"], "contacts": [{"organization": "Peter, Brad, Messina, Joseph, Raney, Austin, Principe, Rodrigo, Fan, Peilei,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.7910/DVN/M4ZGXP"}, {"rel": "self", "type": "application/geo+json", "title": "10.7910/DVN/M4ZGXP", "name": "item", "description": "10.7910/DVN/M4ZGXP", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7910/DVN/M4ZGXP"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.1016/j.foodpol.2010.11.009", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:06Z", "type": "Journal Article", "created": "2011-01-23", "title": "The New Competition For Land: Food, Energy, And Climate Change", "description": "Abstract The paper addresses the new competition for land arising from growing and changing demand for food when combined with increasing global demand for transport energy, under conditions of declining petro-chemical resources and the urgent need to reduce greenhouse gas emissions. The paper starts from the premise of a \u2018food, energy and environment trilemma\u2019 ( Tilman et al., 2009 ), where all demands to expand the area of cultivated land present high risks of increasing the carbon footprint of agriculture. Having reviewed the main drivers of demand for food and for liquid transport fuels, the paper weighs the controversies surrounding biofuels arising from food-price spikes, the demand for land, and consequent direct and indirect land-use change. It suggests that we need a more complex, and geographically differentiated, analysis of the interactions between direct and indirect land-use change. The paper then reviews evidence of land availability, and suggests that in addition to technical availability in terms of soil, water, and climate, political, social, and technological factors have significantly shaped the competition for land in different global regions, particularly the three major biofuel producing ones of the USA, Brazil and Europe. This point is further developed by reviewing the different innovation pathways for biofuels in these three regions. The main conclusion of this review is firstly that any analysis requires an integrated approach to the food-energy-environment trilemma, and secondly that strategic political direction of innovation and sustainability regulation are required to bring about major shifts in agriculture leading to sustainable intensification of cultivation ( Royal Society, 2009 ), rather than the continued expansion of cultivated area. The consequent perspective is one of considerable global variety in technologies, agricultural productive systems, and use of natural resources. This contrasts sharply with the world of a dominant global and integrated technology platform based on petro-chemicals to which we have become accustomed.", "keywords": ["2. Zero hunger", "330", "food", "0211 other engineering and technologies", "HM Sociology", "02 engineering and technology", "15. Life on land", "7. Clean energy", "630", "biofuels", "innovation", "12. Responsible consumption", "competition for land", "climate change", "13. Climate action", "11. Sustainability", "0202 electrical engineering", " electronic engineering", " information engineering"]}, "links": [{"href": "https://doi.org/10.1016/j.foodpol.2010.11.009"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Food%20Policy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.foodpol.2010.11.009", "name": "item", "description": "10.1016/j.foodpol.2010.11.009", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.foodpol.2010.11.009"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-01-01T00:00:00Z"}}, {"id": "10.1007/s10646-011-0619-z", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:01Z", "type": "Journal Article", "created": "2011-03-04", "title": "Investigations Of Responses To Metal Pollution In Land Snail Populations (Cantareus Aspersus And Cepaea Nemoralis) From A Smelter-Impacted Area", "description": "A cross-transplantation field experiment was performed to investigate about possible adaptation/acclimatization to metal pollution in common garden snail Cantareus aspersus (ex-Helix aspersa) and brown-lipped grove snail Cepaea nemoralis populations. Adults were collected from an area surrounding a former smelter (ME), highly polluted by trace metals (TMs) for decades, and from an unpolluted site (BE). Subadults of first generation (F1) were exposed in microcosms in a 28-day kinetic study. Four exposure sites were chosen around the smelter along a soil pollution gradient (vegetation and soil otherwise comparable). Bioaccumulation in snail soft tissues globally increased with soil contamination, with Cd, Pb and Zn concentrations reaching 271, 187, 5527\u00a0\u03bcg\u00a0g(-1), respectively. Accumulation kinetic patterns were similar between snail species but C. nemoralis showed greater TM levels than C. aspersus. Some inter-population differences were revealed in TM accumulation (bioaccumulation factors, accumulation kinetics) but did not suggest consistent adaptive responses. We did not detect negative effects of TM exposure on snail condition (body weight, shell size, shell weight). ME C. aspersus snails produced heavier shells than BE snails under exposure to TMs at the highest level, suggesting an adaptive response. The protocol used in this study, however, did not allow unambiguously distinguishing whether this response was due to genetic adaptation or to maternal effects. Abnormal but reversible shell development of adult ME C. nemoralis suggested physiological acclimatization. Differences in responses to TMs between populations are observed for conchological parameters, not for bioaccumulation, with different strategies according to the species (acclimatization or adaptation/maternal effects).", "keywords": ["550", "invertebrate", "Snails", "590", "0211 other engineering and technologies", "02 engineering and technology", "heavy metal", "Adaptation", " Physiological", "01 natural sciences", "Kinetics", "bioaccumulation", "Models", " Chemical", "Metals", "13. Climate action", "adaptive response", "Metallurgy", "Animals", "Body Size", "Soil Pollutants", "[SDE.ES]Environmental Sciences/Environment and Society", "Environmental Monitoring", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1007/s10646-011-0619-z"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecotoxicology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10646-011-0619-z", "name": "item", "description": "10.1007/s10646-011-0619-z", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10646-011-0619-z"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2011-03-03T00:00:00Z"}}, {"id": "10.1016/j.agee.2014.02.014", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:30Z", "type": "Journal Article", "created": "2014-03-22", "title": "Long-Term Effect Of Contrasted Tillage And Crop Management On Soil Carbon Dynamics During 41 Years", "description": "Although numerous studies have been conducted on the effect of tillage on soil organic carbon (SOC), there is still no consensus on the importance of sequestration which can be expected from reduced tillage. Most studies have used a synchronic approach in fields or long-term experiments which were often poorly characterized with respect to initial conditions. In this paper, we used a diachronic approach to quantify SOC changes in a 41 years experiment comparing no-till (NT), shallow till (ST) and full inversion tillage (FIT) combined with crop managements (residues removal, rotation and catch crops). It included SOC measurements at time 0 and every 4 years, calculations at equivalent soil mass within or below the old ploughed layer. Results show that tillage or crop management had no significant effect on SOC stocks after 41 years both in the old ploughed layer (ca. 0-28 cm) and deeper (ca. 0-58 cm). Tillage had no effect on crop yields and residues. In the reduced tillage treatments (ST and NT), SOC accumulated in the surface layer (0-10 cm), reaching a plateau after 24 years but declined continuously in the lower layer (10-28 cm) at a rate of 0.42-0.44% yr(-1). The difference in SOC stocks (ST or NT minus FIT) over the old ploughed layer followed a non-monotonic pattern over time. Reduced tillage caused a rapid SOC sequestration during the first 4 years which remained more or less constant (mean = 2.17 and 1.31 t ha(-1), resp.) during the next 24 years and disappeared after 28 years. The drop was attributed to the higher water balance recorded during years 24-28. In the reduced tillage treatments, the changes in SOC over time were negatively correlated with the water balance, indicating that sequestration rate was positive in dry periods and negative in wet conditions. This study highlights the interest of diachronic approaches to understand the effect of tillage and its interaction with environmental and management factors.", "keywords": ["[SDE] Environmental Sciences", "2. Zero hunger", "Soil organic carbon", "[SDV]Life Sciences [q-bio]", "04 agricultural and veterinary sciences", "15. Life on land", "630", "Tillage", "Dynamics", "[SDV] Life Sciences [q-bio]", "Long-term", "[SDE]Environmental Sciences", "[SDV.BV]Life Sciences [q-bio]/Vegetal Biology", "0401 agriculture", " forestry", " and fisheries", "[SDV.BV] Life Sciences [q-bio]/Vegetal Biology", "SOC", "Crop production", "Crop management"], "contacts": [{"organization": "Dimassi, Bassem, Mary, Bruno, B., Wylleman, Richard, Labreuche, Jerome, Couture, Daniel, Piraux, Fran\u00e7ois, Cohan, Jean-Pierre,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2014.02.014"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2014.02.014", "name": "item", "description": "10.1016/j.agee.2014.02.014", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2014.02.014"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-04-01T00:00:00Z"}}, {"id": "10.1016/j.agee.2014.02.021", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:30Z", "type": "Journal Article", "created": "2014-03-15", "title": "Biochar Does Not Affect Soil N-Transformations Or Microbial Community Structure Under Ruminant Urine Patches But Does Alter Relative Proportions Of Nitrogen Cycling Bacteria", "description": "Abstract Nitrogen (N) cycling, especially denitrification, can be significantly altered when biochar is used as a soil conditioner. These alterations in N-cycling have been attributed to a combination of physicochemical change, alterations in microbial community ecology and pervading climatic conditions. This study investigated seasonal bacterial community change over two years in combination with a short-term winter study of N-transformations under bovine urine patches. A silt-loam pastoral soil in Canterbury, New Zealand was amended with either 0, 15 or 30\u00a0t\u00a0ha \u22121 of Pinus radiata biochar (pyrolysed at \u223c450\u00a0\u00b0C) and bovine urine was added to patches within the 0 and 30\u00a0t\u00a0ha \u22121 biochar amended plots (designated as 0\u00a0U and 30\u00a0U treatments, where U indicates \u2018urine\u2019). No discernible differences in bacterial community structure were observed during the two year study or the short term N-transformation study when comparing non-amended and biochar-amended soil. Differences in bacterial community structure were only evident when comparing seasons, with data pertaining to each season from successive years clustering together. During the short-term N-transformation study, bacterial communities formed 3 distinct clusters corresponding to elevated levels of urine derived NH 4 + -N (days 0\u201310), increases in NO 3 \u2212 -N and N 2 O (days 10\u201322) and a decline in NO 3 \u2212 -N and N 2 O (day 20 onward). Biochar amendment did increase the relative abundance of up to 50% of individual operational taxonomic units (OTUs or \u2018species\u2019), including key nitrite oxidisers and nitrate reducers. Biochar amendment did not affect the concentrations of inorganic-N compounds. The nir S (nitrite reductase) gene became elevated in the 30\u00a0U treatment relative to the 0\u00a0U treatment \u223c10 days after the initial urine application. The nos Z (nitrous oxide reductase) gene became elevated in the 30\u00a0U plots during the latter part of the experiment. Conclusions: \u2022 Biochar did not have a significant impact on the microbial community structure in pastoral soil over the course of two years. \u2022 The relative proportion of nitrifiers and denitrifiers increased in biochar amended soils subjected to large influxes of urine derived N. \u2022 Differences in N-transformation dynamics in the presence of biochar during the winter months were not statistically significant.", "keywords": ["2. Zero hunger", "N\u2082O emissions", "570", "denitrification", "bovine urine", "silt-loam soil", "ANZSRC::30 Agricultural", "04 agricultural and veterinary sciences", "15. Life on land", "soil microbial ecology", "winter", "nitrification", "630", "6. Clean water", "veterinary and food sciences", "T-RFLP", "new generation sequencing", "13. Climate action", "ANZSRC::41 Environmental sciences", "XXXXXX - Unknown", "0401 agriculture", " forestry", " and fisheries", "biochar", "ANZSRC::44 Human society"], "contacts": [{"organization": "Timothy J. Clough, Kelly Hamonts, Leo M. Condron, Craig Anderson, Craig Anderson,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2014.02.021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2014.02.021", "name": "item", "description": "10.1016/j.agee.2014.02.021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2014.02.021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-06-01T00:00:00Z"}}, {"id": "10.5281/zenodo.7050652", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:21:30Z", "type": "Report", "title": "Tailored environmental and socio-economic performance indicators for selected measures. Deliverable D2.2 of the EU Horizon 2020 project OPTAIN.", "description": "Deliverable report D2.2 of the EU Horizon 2020 Project OPTAIN (Grant agreement No. 862756). List of tailored and case-specific performance indicators (environmental and socio-economical) that help to evaluate the effectiveness of NSWRM monitored (existing measures) and modelled (potential future measures) in the OPTAIN case studies as well as used to establish a common language across project members and activities and to facilitate the knowledge sharing with stakeholders and the wider dissemination of project results. Summary: The content of this deliverable addresses the activities of the task 2.2 \u201cIdentification of performance indicators for the selected NSWRM\u201d within the H2020 project OPTAIN. The core purpose of the task is to develop a customized set of indicators that allow assessing the effectiveness of selected (either existing or potential future) Natural/Small Water Retention Measures (NSWRMs) in and across the OPTAIN case studies (CS). The relevance of specific NSWRMs to face local challenges, their multifunctional nature and the manifold impacts they may have in the territory require identifying key elements that easily resume such features, while being flexible and adaptable enough to be used in different contexts. Therefore, task 2.2 elaborated a pathway to produce a list of Performance Indicators (PI), to set the focus for model parametrisation at different scales as well as to ensure an appropriate model setup and utilisation of modelling outcomes (WP4, WP5). For this reason, the screening, selection and tailoring of the most relevant indicators, to be used as PI, have been conducted from both the environmental (EPIs) and socio-economic (SPIs) points of view. The selection process was built at the interface between science and society, in a fruitful process of knowledge co-creation and sharing. As such, agreed lists of indicators can be used to support the harmonized approach of OPTAIN by establishing a common language across project members and activities, favour the understanding and the comparison of modelling results across CS, facilitating the dialogue with stakeholders and the wider dissemination of project results. The methodology followed to outline the customized list of indicators, to be used as PIs, was based upon the initial contribution of scientific / academic partners\u2019 expertise to compile all the potential or candidate indicators and preselect the most relevant ones for the selected NSWRMs. As a result, we ended up with short lists of both environmental (25) and socio-economic (17) indicators that cover the most relevant issues of the OPTAIN case studies. In the second instance a participative approach involved local research teams and stakeholders in the valuation, adjustment and prioritisation of the most important indicators, also owing to the intensive consultation with OPTAINs Multi-Actor-Reference Groups (MARG). Based on the feedback obtained, the task 2.2 partners conducted an analysis of the commonalities and differences between CSs and scales. This allowed drawing the conclusion that, despite CS are experiencing diverse challenges, the most important issues covered by the selected indicators, and priorities given are very similar. Finally, for comparison purposes across CSs, a common set of PIs is proposed, including first discussions on the best way to represent selected PIs based on monitoring and/or modelling results to be available in CS.", "keywords": ["environmental performance", "Multi-Actor-Reference Groups (MARG)", "13. Climate action", "NSWRM", "11. Sustainability", "socio-economic performance", "H2020", "OPTAIN", "indicators", "12. Responsible consumption"], "contacts": [{"organization": "Krzeminska, Dominika, Monaco, Federica,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.7050652"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.7050652", "name": "item", "description": "10.5281/zenodo.7050652", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.7050652"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-05-31T00:00:00Z"}}, {"id": "10.1016/j.fcr.2011.11.011", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:04Z", "type": "Journal Article", "created": "2011-12-14", "title": "Long-Term Effect Of Different Integrated Nutrient Management On Soil Organic Carbon And Its Fractions And Sustainability Of Rice\u2013Wheat System In Indo Gangetic Plains Of India", "description": "Abstract Rice\u2013wheat rotation is the most important cropping system of the Indo-Gangetic Plains (IGP) and is responsible for the food security of the region. The effect of different integrated nutrient management practices on soil organic carbon (SOC) stocks and its fractions, SOC sequestration potential as well as the sustainability of the rice\u2013wheat system were evaluated in long term experiments at different agro-climatic zones of IGP. Application of NPK either through inorganic fertilizers or through combination of inorganic fertilizer and organics such as farm yard manure (FYM) or crop residue or green manure improved the SOC, particulate organic carbon (POC), microbial biomass carbon (MBC) concentration and their sequestration rate. Application of 50% NPK\u00a0+\u00a050%\u00a0N through FYM in rice and 100% NPK in wheat, sequestered 0.39, 0.50, 0.51 and 0.62\u00a0Mg\u00a0C\u00a0ha\u22121\u00a0yr\u22121 over control (no N\u2013P\u2013K fertilizers or organics), respectively at Ludhiana, Kanpur, Sabour and Kalyani using the mass of SOC in the control treatment as reference point. Soil carbon sequestration with response to application of fertilizer partially substituted (50% on N basis) with organics were higher in Kalyani and Sabour lying in humid climate than Ludhiana and Kanpur lying in semiarid climate. The rice yield recorded a significant declining trend in Ludhiana and Kanpur where as the yield trend was stable at Sabour and Kalyani under unfertilized control. The system productivity in N\u2013P\u2013K fertilized plots and NPK along with organics showed either an increasing trend or remained stable at all locations during last two and half decades of the experiment.", "keywords": ["Carbon sequestration", "2. Zero hunger", "Kanpur", "Soil organic carbon", "Indo-Gangetic Plains", "Kalyani", "Nutrient management", "India", "Green manure", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "12. Responsible consumption", "Semiarid zones", "Ludhiana", "Humid zones", "Wheat", "0401 agriculture", " forestry", " and fisheries", "Rice", "SOC", "Field Scale", "Sabour"]}, "links": [{"href": "https://doi.org/10.1016/j.fcr.2011.11.011"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Field%20Crops%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.fcr.2011.11.011", "name": "item", "description": "10.1016/j.fcr.2011.11.011", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.fcr.2011.11.011"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-02-01T00:00:00Z"}}, {"id": "78F40629-3272-40F6-B0AA-C0A353F7A391", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:24:18Z", "type": "Dataset", "language": "en", "title": "Soil Regions of the European Union and Adjacent Countries 1:5,000,000", "description": "The map of the \"Soil Regions of the European Union and Adjacent Countries 1:5,000,000 (Version 2.0)\" is published by the Federal Institute of Geosciences and Natural Resources (BGR), in partnership with the Joint Research Center (JRC, Ispra). The soil regions map is intended to support the current national mapping activities towards a European 1:250,000 datbase by stratifying similar regional soil associations into a hierarchical concept. Only by stratification, the complexity of soils can be systematically structured so that the complex 1:250,000 legend can be handled in cross-national and contintental-level applications. Soil regions are natural, cross-regional soil geographical units which perform the highest spatial and content-based aggregation of European soils. They represent the frame conditions for soil development at the landscape level. The soil regions are presented at scale 1:5,000,000. Thus, its borders are highly generalized. Because of its low resolution, the map units absorb atypical soils and associations of soils, which are only described in higher resolution soil maps. The delineation of the soil regions is expected to be refined (and probably improved by its content) during the actual 1:250,000 mapping process. Thus, updating can be expected in the future. Currently, the soil regions map is the only graphical soil representation in Europe which has been developed using fully comparable and harmonized basic data at the continental level (climate, hydrography, relief, geology, vegetation): the interpretation of this input data, and the utilization of expert knowledge (including the interpretation of regional soil maps) has been done using one common methodology, developed and applied consistently throughout the whole mapping area by an experienced international soil mapper (Dr. Reinhard Hartwich, former member of BGR, and co-author of the 1998 Manual of Procedures). The methodology is extensively described in the Explanatory Notes (German), and in the revised Manual of Procedures which is expected to be completed soon. It is highly recommended to apply and interpret the map using the map comments and descriptions as provided in the explanatory notes (German: Hartwich et al. 2005; English: revision of the Manual of Procedures, initial version: Finke et al. 2001).", "formats": [{"name": "PDF"}], "keywords": ["bodeneigenschaften", "bodenlandschaften", "bodenregionen", "bodenverbreitung", "climate-areas", "egdi", "entstehungsart", "europa", "europe", "io", "landscape-stratification", "soil", "soil-landscapes", "soil-parent-material-associations", "soil-regions", "soil-scapes"], "contacts": [{"organization": "Eberhardt, Einar, Dr.", "roles": ["creator"]}]}, "links": [{"href": "https://download.bgr.de/bgr/Boden/EUSR5000/jpg/eusr5000.zip"}, {"href": "https://download.bgr.de/bgr/Boden/EUSR5000/mdb/eusr5000.zip"}, {"href": "https://download.bgr.de/bgr/Boden/EUSR5000/pdf/eusr5000.zip"}, {"href": "https://download.bgr.de/bgr/Boden/EUSR5000/png/eusr5000.zip"}, {"href": "https://download.bgr.de/bgr/Boden/EUSR5000/shp/eusr5000.zip"}, {"href": "https://download.bgr.de/bgr/Boden/EUSR5000/tiff/eusr5000.zip"}, {"href": "http://data.europa.eu/88u/dataset/ae71ffee-1ae9-4624-ae3f-f49513fe9dcb"}, {"rel": "self", "type": "application/geo+json", "title": "78F40629-3272-40F6-B0AA-C0A353F7A391", "name": "item", "description": "78F40629-3272-40F6-B0AA-C0A353F7A391", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/78F40629-3272-40F6-B0AA-C0A353F7A391"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "10.5061/dryad.0zpc86730", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:19:59Z", "type": "Dataset", "title": "Data for: Vegetation and soil ecology of threatened Himalayan Trillium habitats in Kashmir, Himalaya", "description": "unspecifiedData was collected by carrying out field surveys across the different sampling sites. The data was written on already prepared datasheets and arranged on spreadsheets for further ananlysis using different softwares.", "keywords": ["threatened species", "FOS: Biological sciences", "Soil Analysis", "Himalaya", "Biodiversity", "Conservation", "15. Life on land", "Phytosociology"], "contacts": [{"organization": "Rashid, Kausar, Rashid, Sufiya, Islam, Tajamul, Ganie, Aijaz, Nawchoo, Irshad, Khuroo, Anzar,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.0zpc86730"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.0zpc86730", "name": "item", "description": "10.5061/dryad.0zpc86730", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.0zpc86730"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2023-05-17T00:00:00Z"}}, {"id": "10.1016/j.jenvman.2023.119500", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:26Z", "type": "Journal Article", "created": "2023-11-10", "title": "Water quality in a large complex catchment: Significant effects of land use and soil type but limited ability to detect trends", "description": "Globally, significant societal resources are devoted to mitigating negative effects of eutrophication from excessive phosphorus (P) and nitrogen (N) loading. Potential effectiveness of mitigation measures and possible confounding factors are often assessed using studies conducted in headwater catchments. However, success is often evaluated based on trends in river mouth water chemistry. It is not clear how transferrable insights from headwater catchments are to larger rivers. Here, relationships between P and suspended solids (SS) identified in small agricultural headwater catchments were applied to 30 larger, mixed land use catchments draining into M\u00e4laren, a Swedish great lake. Relationships identified in headwater streams between SS concentration, catchment agricultural land percentage and arable land clay content were corroborated for the larger catchments (R2\u00a0=\u00a00.59, p-value<0.001. The same was true for connections between SS and particulate P (R2\u00a0=\u00a00.74, p-value<0.001). This study highlights the importance of agricultural land, clay content and SS for P transport, on both smaller headwater as well as larger catchment scales, supporting the use of headwater findings on larger, management relevant scales. Consequently, these relationships should be used to target mitigation measures to reduce SS and P losses. To explore the effectiveness of mitigation measures on water quality, we assessed long-term (20 year) trends in tributary water quality and compared these trends to the amount of mitigation measures implemented in the catchment. Overall improving trends were detected using regional Mann Kendall tests, but few decreasing trends in nutrient concentrations were found for individual sites using Generalized Additive Models (GAM). The lack of significant trends and identifiable connections to amount of mitigation measures implemented could be due to several reasons, e.g. insufficient time for recently implemented measures to have an effect, ongoing release of legacy P as well as low areal coverage and poor spatial placement of implemented measures. In addition, trend detection requires large amounts of data and the results should be carefully interpreted and communicated.", "keywords": ["Environmental Sciences (social aspects to be 507)", "Agriculture", "Phosphorus", "Oceanography", " Hydrology", " Water Resources", "15. Life on land", "Oceanography", "6. Clean water", "Soil", "Lakes", "Rivers", "13. Climate action", "Water Quality", "Water Resources", "Clay", "Hydrology", "Environmental Monitoring"]}, "links": [{"href": "https://pub.epsilon.slu.se/32300/1/sandstr%C3%B6m-s-et-al-20231212.pdf"}, {"href": "https://doi.org/10.1016/j.jenvman.2023.119500"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jenvman.2023.119500", "name": "item", "description": "10.1016/j.jenvman.2023.119500", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jenvman.2023.119500"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-01-01T00:00:00Z"}}, {"id": "AFC47F2E-43ED-42AA-8EBB-85FCD47FA1D7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:24:40Z", "type": "Dataset", "title": "Soil Regions of the European Union and Adjacent Countries 1:5,000,000 (WMS)", "description": "The map of the \"Soil Regions of the European Union and Adjacent Countries 1:5,000,000 (Version 2.0)\" is published by the Federal Institute of Geosciences and Natural Resources (BGR), in partnership with the Joint Research Center (JRC, Ispra). The soil regions map is intended to support the current national mapping activities towards a European 1:250,000 datbase by stratifying similar regional soil associations into a hierarchical concept. Only by stratification, the complexity of soils can be systematically structured so that the complex 1:250,000 legend can be handled in cross-national and contintental-level applications. Soil regions are natural, cross-regional soil geographical units which perform the highest spatial and content-based aggregation of European soils. They represent the frame conditions for soil development at the landscape level. The soil regions are presented at scale 1:5,000,000. Thus, its borders are highly generalized. Because of its low resolution, the map units absorb atypical soils and associations of soils, which are only described in higher resolution soil maps. The delineation of the soil regions is expected to be refined (and probably improved by its content) during the actual 1:250,000 mapping process. Thus, updating can be expected in the future. Currently, the soil regions map is the only graphical soil representation in Europe which has been developed using fully comparable and harmonized basic data at the continental level (climate, hydrography, relief, geology, vegetation): the interpretation of this input data, and the utilization of expert knowledge (including the interpretation of regional soil maps) has been done using one common methodology, developed and applied consistently throughout the whole mapping area by an experienced international soil mapper (Dr. Reinhard Hartwich, former member of BGR, and co-author of the 1998 Manual of Procedures). The methodology is extensively described in the Explanatory Notes (German), and in the revised Manual of Procedures which is expected to be completed soon. It is highly recommended to apply and interpret the map using the map comments and descriptions as provided in the explanatory notes (German: Hartwich et al. 2005; English: revision of the Manual of Procedures, initial version: Finke et al. 2001).", "formats": [{"name": "WMS_SRVC"}], "keywords": ["bodeneigenschaften", "bodenlandschaften", "bodenregionen", "bodenverbreitung", "climate-areas", "egdi", "entstehungsart", "europa", "europe", "infomapaccessservice", "io", "landscape-stratification", "soil", "soil-landscapes", "soil-parent-material-associations", "soil-regions", "soil-scapes"], "contacts": [{"organization": "Eberhardt, Einar, Dr.", "roles": ["creator"]}]}, "links": [{"href": "https://services.bgr.de/wms/boden/eusr5000/?"}, {"href": "http://data.europa.eu/88u/dataset/f5624c2a-d5be-4810-8d66-c0139d471118~~1"}, {"rel": "self", "type": "application/geo+json", "title": "AFC47F2E-43ED-42AA-8EBB-85FCD47FA1D7", "name": "item", "description": "AFC47F2E-43ED-42AA-8EBB-85FCD47FA1D7", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/AFC47F2E-43ED-42AA-8EBB-85FCD47FA1D7"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "oai:DiVA.org:miun-38173", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:28:31Z", "type": "Other", "title": "M\u00e4ns v\u00e5ld mot kvinnor : Diskurser och kunskap i det sociala arbetets praktik", "description": "Open AccessI avhandlingen analyseras vilken kunskap och diskurser som v\u00e4gleder socialtj\u00e4nstens arbete med m\u00e4ns v\u00e5ld mot kvinnor. Avhandlingens \u00f6vergripande fr\u00e5gest\u00e4llningar fokuserar p\u00e5: diskurser om m\u00e4ns v\u00e5ld i Socialstyrelsens utbildningsmaterial, socialarbetares kunskapsbehov och hur dessa tillgodoses, samt socialarbetares uppfattningar om m\u00e4ns v\u00e5ld mot kvinnor. Avhandlingen har ett feministiskt och intersektionellt perspektiv och bygger p\u00e5 tv\u00e5 delstudier. I den f\u00f6rsta delstudien anv\u00e4nds kvalitativa metoder, och empirin best\u00e5r av fem utbildningsmaterial om m\u00e4ns v\u00e5ld mot kvinnor som publicerats av Socialstyrelsen. Empirin analyserats med hj\u00e4lp av Carol Bacchis policy approach What\u2019s the Problem Represented to be?, och Norman Faircloughs kritiska diskursanalys. Empirin i den andra delstudien utg\u00f6rs av enk\u00e4tdata som inh\u00e4mtats bland 153 socialarbetare verksamma i socialtj\u00e4nsten i tre svenska kommuner med olika demografi och geografisk placering. Avhandlingen visar tre centrala resultat. F\u00f6r det f\u00f6rsta framst\u00e4lls m\u00e4ns v\u00e5ld i k\u00f6nsneutrala termer och v\u00e5ldet beskrivs som ett relationsv\u00e5ld och/eller familjev\u00e5ld. F\u00f6r det andra problematiserar utbildningsmaterialens texter inte m\u00e4ns \u00f6verordning, de f\u00e4ster inte heller n\u00e5gon s\u00e4rskild vikt vid strukturella orsakssammanhang. F\u00f6r det tredje centreras kunskapen och diskurserna kring individuella behov och orsaker. Fr\u00e4mst fokuseras behoven hos de grupper av kvinnor som Regeringen menar \u00e4r s\u00e4rskilt s\u00e5rbara f\u00f6r v\u00e5ld. Det senare leder till att kvinnor kollektiviseras och att m\u00e4ns ansvar f\u00f6r v\u00e5ldet, i synnerhet svenska m\u00e4n, och sambandet mellan v\u00e5ld, j\u00e4mlikhet och andra sociala strukturer f\u00f6rbises. Professionell erfarenhet i \u00e4renden d\u00e4r v\u00e5ld f\u00f6rekommer och utbildning inom omr\u00e5det \u00e4r faktorer som socialarbetarna anser bidragit till att \u00f6ka deras kunskap. Trots detta uppger respondenter med l\u00e5ng arbetslivserfarenhet, h\u00f6g utbildning, och fortbildning att de saknar kunskap om m\u00e4ns v\u00e5ld mot kvinnor. \u00c4ven fast att socialarbetarna upplever kunskapsbrist, visar resultatet att socialarbetarna endast tagit del st\u00f6ddokument i begr\u00e4nsad omfattning. Den h\u00e4r avhandlingen bidrar med kunskap om vikten av spr\u00e5kanv\u00e4ndning och hur vi f\u00f6rst\u00e5r m\u00e4ns v\u00e5ld mot kvinnor. Resultatet kan anv\u00e4ndas f\u00f6r att ifr\u00e5gas\u00e4tta och utmana r\u00e5dande normer om m\u00e4ns v\u00e5ld i samh\u00e4llet.", "keywords": ["Socialt arbete", "knowledge", "education", "policys", "Social Work", "social work", "socialarbetare", "diskurs", "socialt arbete", "utbildning", "social workers", "socialtj\u00e4nst", "policies", "social service", "kunskap", "discourse", "m\u00e4ns v\u00e5ld mot kvinnor", "male violence against women"], "contacts": [{"organization": "Hoppstadius, Helena", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/oai:DiVA.org:miun-38173"}, {"rel": "self", "type": "application/geo+json", "title": "oai:DiVA.org:miun-38173", "name": "item", "description": "oai:DiVA.org:miun-38173", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/oai:DiVA.org:miun-38173"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.1002/cc.36819730306", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:29Z", "type": "Journal Article", "created": "2006-10-13", "title": "The eops story in california", "description": "AbstractCalifornia has responded to the needs of disadvantaged young people with new community college programs and services that raise critical problems of evaluation.The exponential rise of information available means we can now, in theory, access knowledge on almost any question we ask. However, as the amount of unverified information increases, so too does the challenge in deciding which information to trust. Farmers, when learning about agricultural innovations, have historically relied on in-person advice from traditional \uffe2\uff80\uff98experts\uffe2\uff80\uff99, such as agricultural advisers, to inform farm management. As more farmers go online for information, it is not clear whether they are now using digital information to corroborate in-person advice from traditional \uffe2\uff80\uff98experts\uffe2\uff80\uff99, or if they are foregoing \uffe2\uff80\uff98expert\uffe2\uff80\uff99 advice in preference for peer-generated information. To fill this knowledge gap, we sought to understand how farmers in two contrasting European countries (Hungary and the UK) learnt about sustainable soil innovations and who influenced them to innovate. Through interviews with 82 respondents, we found farmers in both countries regularly used online sources to access soil information; some were prompted to change their soil management by farmer social media \uffe2\uff80\uff98influencers\uffe2\uff80\uff99. However, online information and interactions were not usually the main factor influencing farmers to change their practices. Farmers placed most trust in other farmers to learn about new soil practices and were less trusting of traditional \uffe2\uff80\uff98experts\uffe2\uff80\uff99, particularly agricultural researchers from academic and government institutions, who they believed were not empathetic towards farmers\uffe2\uff80\uff99 needs. We suggest that some farmers may indeed have had enough of traditional \uffe2\uff80\uff98experts\uffe2\uff80\uff99, instead relying more on their own peer networks to learn and innovate. We discuss ways to improve trustworthy knowledge exchange between agricultural stakeholders to increase uptake of sustainable soil management practices, while acknowledging the value of peer influence and online interactions for innovation and trust building.Establishing Lupinus mutabilis as a protein and oil crop requires improved varieties adapted to EU climates. The genetic regulation of strategic breeding traits, including plant architecture, growing cycle length and yield, is unknown. This study aimed to identify associations between 16 669 single nucleotide polymorphisms (SNPs) and 9 agronomic traits on a panel of 223 L. mutabilis accessions, grown in four environments, by applying a genome wide association study (GWAS). Seven environment-specific QTLs linked to vegetative yield, plant height, pods number and flowering time, were identified as major effect QTLs, being able to capture 6 to 20% of the phenotypic variation observed in these traits. Furthermore, two QTLs across environments were identified for flowering time on chromosome 8. The genes FAF, GAMYB and LNK, regulating major pathways involved in flowering and growth habit, as well as GA30X1, BIM1, Dr1, HDA15, HAT3, interacting with these pathways in response to hormonal and environmental cues, were prosed as candidate genes. These results are pivotal to accelerate the development of L. mutabilis varieties adapted to European cropping conditions by using marker-assisted selection (MAS), as well as to provide a framework for further functional studies on plant development and phenology in this species.Shifting from a linear to a circular bio\uffe2\uff80\uff90economy requires new business models. The objective was getting insights into the uncharted research field of business model innovation for a circular and sustainable bio\uffe2\uff80\uff90economy within the agrifood sector. Eight European cases valorising agricultural waste and by\uffe2\uff80\uff90products by closing loops or cascading were studied regarding their innovation drivers and elements, via interviews, on\uffe2\uff80\uff90site visits and secondary data. In this domain, the findings highlight that business model innovations are depending on the (i) macro\uffe2\uff80\uff90environmental institutional\uffe2\uff80\uff90legal conditions and market trends, (ii) driven by internal economic, environmental and/or social objectives, but especially strongly linked to (iii) other actors often from different sectors seeking synergies and (iv) value co\uffe2\uff80\uff90creation via combined organisational and technological innovations. Business models for a circular bio\uffe2\uff80\uff90economy thus depend on various action levels and need radical combined organisational and technological innovations for a most efficient usage of agricultural waste and by\uffe2\uff80\uff90products. This also means new business configurations instead of linear innovation strategies currently still being dominant due to economic viability.
", "keywords": ["330", "9. Industry and infrastructure", "circular economy", "bio-economy", "650", "sustainability", "7. Clean energy", "innovation", "[SHS]Humanities and Social Sciences", "12. Responsible consumption", "agricultural waste and by-products", "13. Climate action", "11. Sustainability", "business models", "[SHS] Humanities and Social Sciences", "co-creation"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1002/bse.2725"}, {"href": "https://doi.org/10.1002/bse.2725"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Business%20Strategy%20and%20the%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/bse.2725", "name": "item", "description": "10.1002/bse.2725", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/bse.2725"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-12T00:00:00Z"}}, {"id": "10.1002/eap.1460", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:29Z", "type": "Journal Article", "created": "2016-10-21", "title": "Forest Management Scenarios In A Changing Climate: Trade-Offs Between Carbon, Timber, And Old Forest", "description": "AbstractBalancing economic, ecological, and social values has long been a challenge in the forests of the Pacific Northwest, where conflict over timber harvest and old\uffe2\uff80\uff90growth habitat on public lands has been contentious for the past several decades. The Northwest Forest Plan, adopted two decades ago to guide management on federal lands, is currently being revised as the region searches for a balance between sustainable timber yields and habitat for sensitive species. In addition, climate change imposes a high degree of uncertainty on future forest productivity, sustainability of timber harvest, wildfire risk, and species habitat. We evaluated the long\uffe2\uff80\uff90term, landscape\uffe2\uff80\uff90scale trade\uffe2\uff80\uff90offs among carbon (C) storage, timber yield, and old forest habitat given projected climate change and shifts in forest management policy across 2.1 million hectares of forests in the Oregon Coast Range. Projections highlight the divergence between private and public lands under business\uffe2\uff80\uff90as\uffe2\uff80\uff90usual forest management, where private industrial forests are heavily harvested and many public (especially federal) lands increase C and old forest over time but provide little timber. Three alternative management scenarios altering the amount and type of timber harvest show widely varying levels of ecosystem C and old\uffe2\uff80\uff90forest habitat. On federal lands, ecological forestry practices also allowed a simultaneous increase in old forest and natural early\uffe2\uff80\uff90seral habitat. The ecosystem C implications of shifts away from current practices were large, with current practices retaining up to 105\uffc2\uffa0Tg more C than the alternative scenarios by the end of the century. Our results suggest climate change is likely to increase forest productivity by 30\uffe2\uff80\uff9341% and total ecosystem C storage by 11\uffe2\uff80\uff9315% over the next century as warmer winter temperatures allow greater forest productivity in cooler months. These gains in C storage are unlikely to be offset by wildfire under climate change, due to the legacy of management and effective fire suppression. Our scenarios of future conditions can inform policy makers, land managers, and the public about the potential effects of land management alternatives, climate change, and the trade\uffe2\uff80\uff90offs that are inherent to management and policy in the region.
", "keywords": ["Carbon sequestration", "Forest management -- Economic aspects", "0106 biological sciences", "Climate Change", "Forestry", "Forest fires -- Effect of climate change on", "Forests", "15. Life on land", "Wood", "01 natural sciences", "Carbon", "Trees", "Oregon", "Forest management -- Social aspects", "13. Climate action", "Northwest Forest Plan (U.S.)", "Environmental Sciences", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1002/eap.1460"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecological%20Applications", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/eap.1460", "name": "item", "description": "10.1002/eap.1460", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/eap.1460"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-02-17T00:00:00Z"}}, {"id": "10.1007/s00267-022-01647-2", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:45Z", "type": "Journal Article", "created": "2022-04-22", "title": "Trust Versus Content in Multi-functional Land Management: Assessing Soil Function Messaging in Agricultural Networks", "description": "AbstractGrowing sustainability demands on land have a high knowledge requirement across multiple scientific domains. Exploring networks can expose opportunities for targeting. Using mixed-methods combining social network analysis (SNA) and surveys, networks for key soil functions in case studies in Germany, Ireland and the Netherlands are explored. We find a diversity of contrasting networks that reflect local conditions, sustainability challenges and governance structure. Farmers were found to occupy a central role in the agri-environmental governance network. A comparison of the SNA and survey results indicate low acceptance of messages from many central actors indicating scope to better harness the network for sustainable land management. The source of the messages was important when it came to the implementation of farm management actions. Two pathways for enhanced farmer uptake of multi-functionality are proposed that have wider application are; to increase trust between farmers and actors that are agents of multi-functional messages and/or to increase the bundling or multi-functionality of messages (mandate) of actors trusted by farmers.This 4\uffe2\uff80\uff90year on\uffe2\uff80\uff90farm study reports the effects of different agricultural practices on yield and soil organic carbon (SOC) in kiwifruit and apricot orchards grown in a Mediterranean area. Groups of plants under local orchard management (LOM,\uffc2\uffa7
Correction made here after initial publication.
) practices (i.e. soil tillage, removing of pruning residues and mineral fertilisers) were compared with plots under soil\uffe2\uff80\uff90protecting orchard management (SPOM) actions (i.e. cover crop, no\uffe2\uff80\uff90tillage, compost application and mulching of pruning residues). In the SPOM blocks fertilisation rate was based on plant demand and irrigation volumes calculated on the evapotranspiration values, while they were empirically calculated in the LOM plots. Results show that yield was 28\uffe2\uff80\uff9350 per cent enhanced by SPOM practices while SOC remained close to the initial values. In comparison with LOM plots, changed practices increased up to 28\uffe2\uff80\uff9390 per cent the amount of P and K, and 13 per cent that of N annually incorporated into soil increasing their reservoir in the soil. The study demonstrates that appropriate land management can increase the mean annual carbon soil inputs from about 1\uffc2\uffb75 to 9\uffc2\uffb70\uffe2\uff80\uff89t\uffe2\uff80\uff89ha\uffe2\uff88\uff921 per year. Copyright \uffc2\uffa9 2009 John Wiley & Sons, Ltd.", "keywords": ["2. Zero hunger", "soil organic carbon", "Crop residues; land use; organic matter; soil carbon input; SOC; Mediterranean soil; soil organic carbon", "Crop residue", "land use", "0401 agriculture", " forestry", " and fisheries", "soil carbon input", "SOC", "04 agricultural and veterinary sciences", "15. Life on land", "Mediterranean soil", "organic matter"]}, "links": [{"href": "https://doi.org/10.1002/ldr.917"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Land%20Degradation%20%26amp%3B%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/ldr.917", "name": "item", "description": "10.1002/ldr.917", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/ldr.917"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2009-03-31T00:00:00Z"}}, {"id": "10.1016/j.agee.2013.01.012", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:15:29Z", "type": "Journal Article", "created": "2013-03-20", "title": "Changes In Soil Carbon And Nitrogen Following Tillage Conversion In A Long-Term Experiment In Northern France", "description": "Although continuous no-till (NT) is recommended for erosion control and carbon sequestration, it often has a limited duration since farmers alternate between NT and full inversion tillage (FIT) to control weed infestation and avoid soil compaction. In this paper, we evaluate the effect of continuous tillage and tillage conversion of NT to FIT and vice versa on SOC and SON stocks, in a long-term experiment at Boigneville in Northern France. Continuous NT (CNT) and FIT (CFIT) treatments were established in 1991 and maintained until 2011 while half of the plots were converted in 2005: from CNT to new FIT (NFIT) and CFIT to new NT (NNT). Bulk densities and organic C and N contents were determined in 2001 and 2011 down to the old ploughing depth (opd) which was also measured. SOC and SON stocks were calculated at equivalent soil mass by correcting either bulk densities or the opd. Both methods produced very close results and similar conclusions. A typical gradient of SOC and SON concentrations vs depth was observed in CNT as opposed to a rather uniform distribution in CFIT. CNT resulted in SOC concentration in the top soil (0-5 cm) higher by 38% in 2001 and 53% in 2011 compared to CFIT. Conversely, it led to a SOC reduction in the deeper layer (ca. 10-28 cm) by 14% in 2001 and 18% in 2011. The global effect was no significant change in SOC and SON stocks between treatments over the old ploughed layer (4060 t soil ha(-1)) in both years: 43.2 and 45.0 t C ha(-1) in 2001 and 44.7 and 45.8 t C ha(-1) in 2011, in CNT and CFIT, respectively. In 2011, six years after tillage conversion, the stratification of SOC and SON had disappeared in NFIT whereas a new one had appeared in NNT with a smaller gradient than in CNT. SOC or SON stocks over the old ploughed layer did not differ significantly between treatments after 6 years of conversion: SOC stocks were 45.8, 43.2, 44.7 and 43.1 t C ha(-1) in the CFIT, NFIT, CNT and NNT treatments, respectively. Furthermore, SOC stocks below the old ploughed layer (ca. 28-40 cm) were slightly greater in FIT than in NT treatment (10.9 vs 8.7 t C ha(-1)). In this experiment, continuous or conversion tillage did not result in any C sequestration benefit. (c) 2013 Elsevier B.V. All rights reserved.", "keywords": ["IMPACTS", "[SDE] Environmental Sciences", "Soil nitrogen", "[SDV]Life Sciences [q-bio]", "SEQUESTRATION", "630", "Tillage", "MOIST", "Long-term", "ORGANIC-CARBON", "[SDV.BV]Life Sciences [q-bio]/Vegetal Biology", "Full inversion tillage", "[SDV.BV] Life Sciences [q-bio]/Vegetal Biology", "SOC", "CONSERVATION TILLAGE", "2. Zero hunger", "GREAT-PLAINS", "Soil organic carbon", "TEMPERATE", "04 agricultural and veterinary sciences", "15. Life on land", "No till", "NO-TILL", "[SDV] Life Sciences [q-bio]", "[SDE]Environmental Sciences", "0401 agriculture", " forestry", " and fisheries", "MATTER", "SYSTEM"], "contacts": [{"organization": "Dimassi, Bassem, Cohan, Jean-Pierrre, Labreuche, Jerome, Mary, Bruno, B.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.1016/j.agee.2013.01.012"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture%2C%20Ecosystems%20%26amp%3B%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agee.2013.01.012", "name": "item", "description": "10.1016/j.agee.2013.01.012", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agee.2013.01.012"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-04-01T00:00:00Z"}}, {"id": "10.1007/978-3-031-50780-9", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:37Z", "type": "Journal Article", "created": "2024-03-19", "title": "Quantum Technology for Economists", "description": "Open Access106 pages, 13 figures", "keywords": ["FOS: Computer and information sciences", "Computational Economics", "Central Banks", "Quantum Physics", "Computer Science - Cryptography and Security", "General Economics (econ.GN)", "ddc:330", "05 social sciences", "Money", "FOS: Physical sciences", "C60", "FOS: Economics and business", "C50", "E50", "0502 economics and business", "Quantum Computing", "Econometrics", "E40", "Quantum Physics (quant-ph)", "Cryptography and Security (cs.CR)", "Economics - General Economics"]}, "links": [{"href": "https://doi.org/10.1007/978-3-031-50780-9"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/SSRN%20Electronic%20Journal", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/978-3-031-50780-9", "name": "item", "description": "10.1007/978-3-031-50780-9", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/978-3-031-50780-9"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-01-01T00:00:00Z"}}, {"id": "10.1007/s00122-021-03815-0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:44Z", "type": "Journal Article", "created": "2021-03-25", "title": "Genomic prediction models trained with historical records enable populating the German ex situ genebank bio-digital resource center of barley (Hordeum\u00a0sp.) with information on resistances to soilborne barley mosaic viruses", "description": "Abstract Key messageGenomic prediction with special weight of major genes is a valuable tool to populate bio-digital resource centers.
AbstractPhenotypic information of crop genetic resources is a prerequisite for an informed selection that aims to broaden the genetic base of the elite breeding pools. We investigated the potential of genomic prediction based on historical screening data of plant responses against the Barley yellow mosaic viruses for populating the bio-digital resource center of barley. Our study includes dense marker data for 3838 accessions of winter barley, and historical screening data of 1751 accessions for Barley yellow mosaic virus (BaYMV) and of 1771 accessions for Barley mild mosaic virus (BaMMV). Linear mixed models were fitted by considering combinations for the effects of genotypes, years, and locations. The best linear unbiased estimations displayed a broad spectrum of plant responses against BaYMV and BaMMV. Prediction abilities, computed as correlations between predictions and observed phenotypes of accessions, were low for the marker-assisted selection approach amounting to 0.42. In contrast, prediction abilities of genomic best linear unbiased predictions were high, with values of 0.62 for BaYMV and 0.64 for BaMMV. Prediction abilities of genomic prediction were improved by up to\uffe2\uff80\uff89~\uffe2\uff80\uff895% using W-BLUP, in which more weight is given to markers with significant major effects found by association mapping. Our results outline the utility of historical screening data and W-BLUP model to predict the performance of the non-phenotyped individuals in genebank collections. The presented strategy can be considered as part of the different approaches used in genebank genomics to valorize genetic resources for their usage in disease resistance breeding and research.
", "keywords": ["Genetic Markers", "0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Genotype", "Chromosome Mapping", "Genetic Variation", "Hordeum", "Genomics", "Potyviridae", "Linkage Disequilibrium", "Plant Breeding", "03 medical and health sciences", "Phenotype", "Databases", " Genetic", "Original Article", "Genetic Association Studies", "Disease Resistance", "Plant Diseases"]}, "links": [{"href": "https://link.springer.com/content/pdf/10.1007/s00122-021-03815-0.pdf"}, {"href": "https://doi.org/10.1007/s00122-021-03815-0"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Theoretical%20and%20Applied%20Genetics", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s00122-021-03815-0", "name": "item", "description": "10.1007/s00122-021-03815-0", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s00122-021-03815-0"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-25T00:00:00Z"}}, {"id": "10.1016/j.still.2013.06.002", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:16:54Z", "type": "Journal Article", "created": "2013-07-04", "title": "Contrasting approaches for estimating soil carbon changes in Amazon and Cerrado biomes", "description": "The Brazilian Amazon and Cerrado are among the principal agricultural frontiers of the world, and have attracted global attention because of their potential to be a source or sink of atmospheric CO2. However, accurately quantifying alterations in soil organic carbon (SOC) due to land-use changes remains to be a major challenge. Using a meta-analysis, our objective was to evaluate tillage effects on SOC stocks in Brazil's Amazon and Cerrado biomes. Two approaches: (1) the classical SOC annual change rate which provides only an arithmetic average of SOC changes, and (2) the rate of annual change adjusted from management factors derived according to the Intergovernmental Panel on Climate Change (IPCC) SOC methodology, which allows a temporal dataset adjustment, were used. Regardless of approach, conservation technologies such as no-tillage (NT) and integrated crop-livestock (ICL) systems were identified as viable options for SOC sequestration, increasing it between 9 and 16%. One exception was adoption of NT in the Amazon forest, where SOC decreased by 9% over 20 years. Comparing results of the two approaches showed substantial differences between them. For conversions from NT to ICL or from native vegetation to full tillage (FT), the IPCC-based approach produced SOC stock estimates that were 65 and 47% lower, respectively, than with the classical approach. The IPCC approach also identified modeling covariate effects and was influenced less by outliers, thus reducing the risk of under or overestimating soil management effects on SOC.", "keywords": ["land use change", "2. Zero hunger", "330", "[SDV]Life Sciences [q-bio]", "ipcc based method", "15. Life on land", "CO2 emissions", "630", "[SDV] Life Sciences [q-bio]", "co2 emissions", "IPCC-based method", "13. Climate action", "SOC stock rates", "Land use change", "soc stock rates"]}, "links": [{"href": "https://doi.org/10.1016/j.still.2013.06.002"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Soil%20and%20Tillage%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.still.2013.06.002", "name": "item", "description": "10.1016/j.still.2013.06.002", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.still.2013.06.002"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-10-01T00:00:00Z"}}, {"id": "10.1007/s003740050613", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:50Z", "type": "Journal Article", "created": "2002-08-25", "title": "Changes In Soil Microbial Biomass, Metabolic Quotient, And Organic Matter Turnover Under Hieracium (H-Pilosella L.)", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "Hieracium invasion", "Organic C and N turnover", "Microbial biomass", "0401 agriculture", " forestry", " and fisheries", "04 agricultural and veterinary sciences", "15. Life on land", "High country", "Tussock grassland"]}, "links": [{"href": "https://doi.org/10.1007/s003740050613"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biology%20and%20Fertility%20of%20Soils", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s003740050613", "name": "item", "description": "10.1007/s003740050613", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s003740050613"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "1999-12-10T00:00:00Z"}}, {"id": "10.1007/s10021-022-00779-0", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:55Z", "type": "Journal Article", "created": "2022-09-27", "title": "Biocrusts Modulate Climate Change Effects on Soil Organic Carbon Pools: Insights From a 9-Year Experiment", "description": "AbstractAccumulating evidence suggests that warming associated with climate change is decreasing the total amount of soil organic carbon (SOC) in drylands, although scientific research has not given enough emphasis to particulate (POC) and mineral-associated organic carbon (MAOC) pools. Biocrusts are a major biotic feature of drylands and have large impacts on the C cycle, yet it is largely unknown whether they modulate the responses of POC and MAOC to climate change. Here, we assessed the effects of simulated climate change (control, reduced rainfall (RE), warming (WA), and RE\uffe2\uff80\uff89+\uffe2\uff80\uff89WA) and initial biocrust cover (low (<\uffe2\uff80\uff8920%) versus high (>\uffe2\uff80\uff8950%)) on the mineral protection of soil C and soil organic matter quality in a dryland ecosystem in central Spain for 9\uffc2\uffa0years. At low initial biocrust cover levels, both WA and RE\uffe2\uff80\uff89+\uffe2\uff80\uff89WA increased SOC, especially POC but also MAOC, and promoted a higher contribution of carbohydrates, relative to aromatic compounds, to the POC fraction. These results suggest that the accumulation of soil C under warming treatments may be transitory in soils with low initial biocrust cover. In soils with high initial biocrust cover, climate change treatments did not affect SOC, neither POC nor MAOC fraction. Overall, our results indicate that biocrust communities modulate the negative effect of climate change on SOC, because no losses of soil C were observed with the climate manipulations under biocrusts. Future work should focus on determining the long-term persistence of the observed buffering effect by biocrust-forming lichens, as they are known to be negatively affected by warming.\u00a0SX67\u00a0>\u00a09882-41. Leaf input was higher in the intercropping system (1,961\u00a0kg\u00a0ha\u22121) than in the conventional system (1,673\u00a0kg\u00a0ha\u22121). Clonal differences in leaf inputs followed the same trends as those for root biomass and yield: SV1\u00a0>\u00a0SX67\u00a0>\u00a09882-41. Soil organic carbon was significantly higher in the agroforestry field (1.94\u00a0%) than in the conventional field (1.82\u00a0%). A significant difference in soil organic carbon was found between the three clones: soils under clone 9882-41 had the lowest soil organic carbon at 1.80\u00a0%.", "keywords": ["F08 - Syst\u00e8mes et modes de culture", "culture associ\u00e9e", "http://aims.fao.org/aos/agrovoc/c_28066", "production foresti\u00e8re", "Juglans nigra", "http://aims.fao.org/aos/agrovoc/c_24367", "rotation de coupe", "http://aims.fao.org/aos/agrovoc/c_6754", "http://aims.fao.org/aos/agrovoc/c_3086", "http://aims.fao.org/aos/agrovoc/c_33452", "http://aims.fao.org/aos/agrovoc/c_3061", "m\u00e9thode statistique", "biomasse", "http://aims.fao.org/aos/agrovoc/c_3048", "http://aims.fao.org/aos/agrovoc/c_4059", "agroforesterie", "clone", "2. Zero hunger", "http://aims.fao.org/aos/agrovoc/c_35927", "http://aims.fao.org/aos/agrovoc/c_24696", "http://aims.fao.org/aos/agrovoc/c_1678", "Salix", "04 agricultural and veterinary sciences", "15. Life on land", "plantation foresti\u00e8re", "Quercus rubra", "croissance", "http://aims.fao.org/aos/agrovoc/c_331583", "http://aims.fao.org/aos/agrovoc/c_207", "K10 - Production foresti\u00e8re", "s\u00e9questration du carbone", "http://aims.fao.org/aos/agrovoc/c_926", "http://aims.fao.org/aos/agrovoc/c_3394", "Fraxinus", "Robinia pseudoacacia", "culture en couloirs", "http://aims.fao.org/aos/agrovoc/c_6625", "http://aims.fao.org/aos/agrovoc/c_1236", "0401 agriculture", " forestry", " and fisheries", "Salix dasyclados", "http://aims.fao.org/aos/agrovoc/c_7377"]}, "links": [{"href": "https://doi.org/10.1007/s10457-012-9572-y"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agroforestry%20Systems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s10457-012-9572-y", "name": "item", "description": "10.1007/s10457-012-9572-y", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s10457-012-9572-y"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-09-27T00:00:00Z"}}, {"id": "10.1007/s10460-020-10186-7", "type": "Feature", "geometry": null, "properties": {"updated": "2026-10-06T16:14:58Z", "type": "Journal Article", "created": "2021-02-21", "title": "Framing of sustainable agricultural practices by the farming press and its effect on adoption", "description": "Abstract
There is growing political pressure for farmers to use more sustainable agricultural practices to protect people and the planet. The farming press could encourage farmers to adopt sustainable practices through its ability to manipulate discourse and spread awareness by changing the salience of issues or framing topics in specific ways. We sought to understand how the UK farming press framed sustainable agricultural practices and how the salience of these practices changed over time. We combined a media content analysis of the farming press alongside 60 qualitative interviews with farmers and agricultural advisors to understand whether the farming press influenced farmers to try more sustainable practices. Salience of sustainable agricultural practices grew between 2009 and 2020. Many of the practices studied were framed by the press around economic and agronomic aspects, and farmer respondents said the most common reasons for trying sustainable agricultural practices were for economic and agronomic reasons. The farming press tended to use more positive rather than negative tones when covering sustainable agricultural practices. Respondents used the farming press as a source of information, though many did not fully trust these outlets as they believed the farming press were mouthpieces for agribusinesses. Whilst a minority of farmers stated they were motivated to try a new sustainable agricultural practice after learning about it in the farming press, this was rare. Instead, the farming press was used by respondents to raise their awareness about wider agricultural topics. We reflect on the role and power given to agribusinesses by the farming press and what this means for agricultural sustainability.Quantifying the upper limit of stable soil carbon storage is essential for guiding policies to increase soil carbon storage. One pool of carbon considered particularly stable across climate zones and soil types is formed when dissolved organic carbon sorbs to minerals. We quantified, for the first time, the potential of mineral soils to sorb additional dissolved organic carbon (DOC) for six soil orders. We compiled 402 laboratory sorption experiments to estimate the additional DOC sorption potential, that is the potential of excess DOC sorption in addition to the existing background level already sorbed in each soil sample. We estimated this potential using gridded climate and soil geochemical variables within a machine learning model. We find that mid- and low-latitude soils and subsoils have a greater capacity to store DOC by sorption compared to high-latitude soils and topsoils. The global additional DOC sorption potential for six soil orders is estimated to be 107 $$ pm$$ \uffc2\uffb1 13 Pg C to 1\uffc2\uffa0m depth. If this potential was realized, it would represent a 7% increase in the existing total carbon stock.This paper investigated occupational gender segregation and its vertical and horizontal dimensions in Turkey. In order to explore the extent of inequality entailed in occupational gender segregation (measured by the vertical dimension), average pay levels across occupations were used. In addition to the economic inequalities captured by pay, aiming to explore the social inequalities inherent in occupational segregation, Cambridge Social Interaction and Stratification Scale scores across occupations were used. The results showed that the extent of inequality associated with occupational gender segregation was substantial, operating to the detriment of women. Women were more likely to be employed in lower-paid jobs and in occupations that ranked lower across the overall stratification structure, while men remained at an advantaged position in terms of both the pay levels and the positions of the occupations they held in the social hierarchy.Over the last two decades, the design practice has been expanding to the public sphere to generate solutions for public challenges. In particular, the reflections on the design practice of public sector innovation (PSI) units, working in or with governments, are increasingly contributing to a growing body of literature attempting to characterise the practice in policy making. Although scholars conclude that design\uffe2\uff80\uff99s significant contribution in policy refers to the implementation of public services and programs, there is also an urgent advocacy for a deeper study of the nature of design practices within earlier stages of policy processes addressing more specifically policy proposals and reforms. As part of a broader investigation, this paper seeks to shed light to this matter by identifying design-led activities and methods of PSI units in the policy making process and positioning them in the stages of the policy cycle. This research examines academic, grey literature and web content to uncover and position design activities of 46 PSI units from different continents in a policy cycle model based on Howlett, Ramesh and Perl (2009). Our work confirms that most design activities develop in the implementation stage rather than in early stages of the policy process. While design interventions are growing within policy formulation and agenda-setting stages, few of them were identified in the stage of policy evaluation. Decision-making stage remains purely political. This research may serve to a further understanding of the design practice and its potential contribution to policy making in the future.The present study reports findings related to the treatment of polluted groundwater using macrophyte-assisted phytoremediation. The potential of three macrophyte species (Phragmites australis, Scirpus holoschoenus, and Typha angustifolia) to tolerate exposure to multi-metal(loid) polluted groundwater was first evaluated in mesocosms for 7- and 14-day batch testing. In the 7-day batch test, the polluted water was completely replaced\uffc2\uffa0and renewed after 7\uffc2\uffa0days, while for\uffc2\uffa014\uffc2\uffa0days exposure, the same polluted water, added in the first week, was maintained. The initial biochemical screening\uffc2\uffa0results of macrophytes indicated that the selected plants were more tolerant to the provided conditions with 14\uffc2\uffa0days of exposure. Based on these findings, the plants were exposed to HRT regimes of 15 and 30\uffc2\uffa0days. The results showed that P. australis and S. holoschoenus performed better than T. angustifolia, in terms of metal(loid) accumulation and removal, biomass production, and toxicity reduction. In addition, the translocation and compartmentalization of metal(loid)s were dose-dependent. At the 30-day loading rate (higher HRT), below-ground phytostabilization was greater than phytoaccumulation, whereas at the 15-day loading rate (lower HRT), below- and above-ground phytoaccumulation was the dominant metal(loid) removal mechanism. However, higher levels of toxicity were noted in the water at the 15-day loading rate. Overall, this\uffc2\uffa0study provides valuable insights for macrophyte-assisted phytoremediation of polluted (ground)water streams that can help to improve the design and implementation of phytoremediation systems.