Science for policy 1: FaST hidden benefits: needs based targeting of cleaner water through better use of nutrients - datasets

This dataset is part of both Deliverable 4.3 and 5.3 and was produced by the WP4 team of the Landmark H2020 project. It contains the following shapefile: PO1_GAEC5.shp The shapefile gives an estimation of the change in soil function performance across the EU in agricultural soils after implementation of the GAEC5 under the proposed CAP. This spatial variation is represented in change in z-scores compared to the current supply on a NUTS1 level. To implement the scenario, for each crop within each environmental zone the 20% area with the lowest values of the N Cycling indicator are selected from the current SF supply map and this indicator is increased to the lowest values in the other 80% of the same crop – environmental zone combination. In a second step, for each crop within each environmental zone the 20% area with the lowest values of the water purification indicator from the current SF supply map are selected and this indicator is increased to the lowest values in the other 80% of the crop – environmental zone combination, while maintaining the N Cycling improvements. This simulates potential improvements in both N Cycling and water purification due to the implementation of the Farm Sustainability Tool for Nutrients (GAEC 5) Z-scores are calculated from the spatial SF maps for each of the NUTS1 zones. The z-scores give the signed fractional number of standard deviations by which SF means for a NUTS1 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.