Environmental Engineering Reference
In-Depth Information
European Environmental Agency (EEA
2002)
, and the Potential Natural Vegetation
map by Bohn et al.
(2000)
. All these stratifications were produced by expert
judgment and the resulting strata are useful for a general characterization and
simplification of the wide diversity in the European environment, but they are not
appropriate as a sampling and an up-scaling framework for producing representative
assessments of Europe.
The need for statistical environmental stratification was first recognized by field
ecologists at the Institute of Terrestrial Ecology (ITE) (now Centre for Ecology
and Hydrology [CEH]) in the UK in the 1970s. These scientists realized that strati-
fied random sampling was the only feasible way of assessing ecological resources,
such as habitats and vegetation, and enabling monitoring schemes to be developed
for large, heterogeneous areas (Bunce et al.
1996
a). Sheail and Bunce
(2003)
have
recently described the history and development of environmental classification
and strategic ecological survey in the UK. Several other countries and regions have
also adopted quantitative classifications as the basis for survey, monitoring and
management, e.g. Spain (Elena-Rosselló
1997)
, Austria (Wrbka et al.
1999)
,
New Zealand (Leathwick et al.
2003)
, and Senegal (Tappan et al.
2004)
.
Two earlier European statistical stratifications have been produced. In the first,
Jones and Bunce
(1985)
defined 11 classes on a 50 × 50 km grid for Europe. More
than a decade later, improved data availability, software and computing power
allowed the classification of 64 classes on a 0.5° grid (approximately 50 × 50 km)
(Bunce et al.
1996
b). Although this latter classification was used in a range of
studies, the coarse resolution limited its application for ecological sampling.
The Environmental Stratification of Europe (EnS; Metzger et al.
2005
; Jongman
et al.
2006)
forms the latest statistical classification of the European environment,
distinguishing 84 strata at a 1 km
2
resolution. Kappa's analysis of aggregations of
the strata shows they compare well with other European classifications (Metzger
et al.
2005)
. The EnS shows strong statistical correlations with other European
environmental datasets, including soil and agronomic variables (Metzger et al.
2005)
Fig.
7.1
gives a summary of two agronomic variables for 12 of the 13
Environmental Zones that are considered to be relevant for this study.
The EnS has been used in several European projects, e.g. in BioHab as a
framework for consistent monitoring of European habitats (Bunce et al.
2008)
, in
ATEAM to summarize outputs from global change impact models (Metzger
et al.
2006, 2008)
as well as by the European Environment Agency to assess
environmentally compatible bioenergy potential from agriculture (EEA
2007)
and
the distribution of high nature value farmland (EEA
2004)
.
The EnS, which is based mainly on climatic variables, partitions environmental
variation across a continental gradient, and therefore does not recognize regional
variation in soil properties. As such, the EnS does not provide a suitable stratification
framework for agricultural modelling, as at a regional scale soil factors determine
the agronomic potential and environmental impact of farming. For this reason
it was decided that for SEAMLESS soil information should be integrated with
the EnS. This will then result in an AEnZ of Europe suitable for SEAMLESS
purposes.
