Environmental Engineering Reference
In-Depth Information
peer-reviewed journals. Furthermore, it shows high correlations with climate
factors. However, the EnS has to be extended with one or more soil variables to
come to a spatial framework that covers the wide range of agri-environmental
diversity in Europe.
The AEnZ typology proved to be a useful agri-environmental modelling frame-
work for the SEAMLESS project. However, some remarks on the limitations of
the typology can be made. In general it can be stated that to build a biophysical
typology there exists a need for more detailed input data than currently available.
More efforts should therefore be invested in the collection of biophysical data and
the building of better bio-physical databases that represent more precisely the
diversity and spatial detail of the European environment. The quality of the soil
information used is well described in the SINFO study (Baruth et al. 2006). One
major drawback of the soil data in the European soil database (ESDBv2) is the incon-
sistency between countries. The statistical procedure to select the soil variable which
explains best the variation of soils in Europe shows preferences for selecting homo-
geneous databases as the OCTOP database with continuous variables. This problem
can be overcome only by improving soil databases (detail, homogeneous).
Climate Zones
The description of the EnZ by the JRC MARS climate data reflects very well the
spatial homogeneity of these EnZ units. It did not lead to additional zones as climate
variables were only one factor in the definition of the EnZ. Climatic gradients are
partly reflected in the Climate Zones (NUTS2/EnZ units), but this has mainly to do
with the size of the administrative regions. Large administrative regions have still
different climatic conditions. Furthermore, the level of detail coming from the MARS
climate database (50 km
2
) reflects only regional climatic conditions. A description of
Seamzones by climate data does not make sense as soils vary more than climate.
Seamzones
For modelling purposes Seamzones are defined as the spatially most detailed
combination of administrative NUTS2 regions, weather and soil characteristics.
They are by definition a unique combination of a NUTS2 region, an environmental
zone and a soil type (topsoil organic carbon class). The Agri-mask of the AEnZ is
not taken into account as this would result into too many regions to be modelled.
The resulting Seamzones are 270 NUTS2 regions subdivided by environmental
zones into 591 regions with a mean of 2.2 environmental zones per NUTS2 region.
Combined with the soil type layer, this resulted in 3,513 regions ranging from 1 ha
up to more than 7.5 million hectares (average size 132,013 ha, 50% of Seamzones
smaller than 29,400 ha). The 3,513 Seamzones do not have a continuous extent in
