Fiche du document
29 octobre 2019
- doi: 10.15454/TTEBWL
Sujets proches
Soil Mould, Vegetable Vegetable mold Earth (Soils) Mold, VegetableCiter ce document
Dirk Vrebos et al., « Science for policy 2: Leaving land alone: soil functions under GAEC 9 – datasets », Recherche Data Gouv, ID : 10.15454/TTEBWL
Métriques
Partage / Export
Résumé
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 shapefiles: PO2_GAEC9_05.shp PO2_GAEC9_10.shp Both shapefiles give an estimation of the change in six soil function performance across the EU in agricultural soils after implementation of the GAEC9 under the proposed CAP to reach 5% or 10% fallow land. This spatial variation is represented in change in z-scores compared to the current supply. The presence of fallow land is evaluated on a NUTS1 level. In the regions where the target of fallow land is not reached, productive arable land is converted into low-productive grassland to reach the 5% or 10% goal. This scenario allows us to evaluate the effect of GAEC5 on the different soil functions. The soil functions are then mapped by applying a number of crop specific Bayesian networks on a combination of spatial maps which describe soil properties, climate, adapted land use and land management on agricultural soils throughout the European Union. 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 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.