This dataset is part of both Deliverable 5.3 and was produced by the WP4 team of the Landmark H2020 project. It contains the following shapefiles:  

PO3_RCP26_NoIrrigation.shp PO3_RCP45_Irrigation.shp PO3_RCP45_NoIrrigation.shp PO3_RCP85_Irrigation.shp PO3_RCP85_NoIrrigation.shp

 These shapefiles give estimations of the change in soil function performance across the EU in agricultural soils by 2050 under an RCP2.6, RCP4.5 and RCP8.5 scenario with and without current permanent irrigation. This spatial variation is represented in change in z-scores compared to the soil function supply under a RCP2.6 scenario with current permanent irrigation by 2050. The soil functions are mapped by applying a number of crop specific Bayesian networks on a combination of spatial maps which describe soil properties, climate, land use and land management on agricultural soils throughout the European Union. Climate data were derived from the Driving model: CNRM-CERFACS-CNRM-CM5, RCM model: KNMI-RACMO22E RCP2.6 model runs available on CORDEX and mean value indicators for temperature and rainfall were calculated for the period 2045 – 2055. Z-scores are calculated from the spatial SF maps. Environmental zones are derived from 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 of each of the scenarios and were then compared to the RCP2.6 calculations with permanent irrigation 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 RCP2.6 calculations with permanent irrigation, 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