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29 octobre 2019
- doi: 10.15454/OIXOMR
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Dirk Vrebos et al., « Science for policy 4: Manure: spreading the load? – datasets. », Recherche Data Gouv, ID : 10.15454/OIXOMR
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This dataset is part of Deliverable 5.3 and was produced by the WP4 team of the Landmark H2020 project. It contains the following tiffs and shapefiles: PO4_35km_Borders.shp PO4_35km_NoBorders.shp PO4_100km_Borders.shp PO4_100km_NoBorders.shp PO4_Max_Borders.shp PO4_Max_NoBorders.shp These shapefiles give an estimation of the change in soil function performance across the EU in agricultural soils after nitrogen surplus redistribution within a 35km, 100km and no limited range, with and without limitation in cross-border transport. The spatial variation is represented in change in z-scores compared to the current SF supply. To develop the scenario, current nutrient applications in areas where concentrations in ground water are above 50 mg nitrates per liter (mg/L), were decreased in order to reach the 50 mg /L level. The excess organic nutrient surplus was then redistributed on other fields within a range of 35km, 100km or no distance limitation, which can receive additional nutrients without exceeding the 50 mg N /L threshold for each location. Excess nutrient surpluses were allowed or not to cross borders and no increases in N application were allowed in Natura 2000 sites. Z-scores are calculated from the spatial SF maps. Environmental zones are derived from the Metzger et al. (2013). The z-scores give the signed fractional number of standard deviations by which SF means for an environmental zone are above or below the mean value and allow us indicate which areas have a higher or lower soil function performance compared to the mean value. Z-scores from the current SF maps and scenario maps were then compared to each other to calculate the change in z-scores. This change in z-scores is given in the shapefiles and describes the relative change in soil function performance. Positive values indicate an improvement in soil functioning compared to the current situation, negative values a decrease. More information regarding calculation and interpretation of both this dataset and the soil function maps used to calculate the z-scores can be found in: Vrebos D., F. Bampa, R. Creamer, A. Jones, E. Lugato, L. O’Sullivan, P. Meire, R.P.O. Schulte, J. Schröder and J. Staes (2018). Scenarios maps: visualizing optimized scenarios where supply of soil functions matches demands. LANDMARK Report 4.3. and Jones A. et al. (2019). An options document to propose future policy tools for functional soil management. LANDMARK 5.3. All available from www.landmark2020.eu.