Europes ecological backbone.pdf

Mountain economies and accessibility
3 Mountain economies and accessibility
3.1 Economic structures
There is a great diversity in economic structures
across the mountains of Europe (Map 3.1), and many
of these have been changing rapidly in recent years,
especially in the new Member States (UNEP, 2007).
The cultural identity and external image of many
mountain areas remains tied to the primary sector
(i.e. agriculture and forestry) and cultural landscapes
are very important elements of the attractiveness
of mountain areas for tourism. Today, the primary
sector remains particularly important as a source of
employment in southern and Eastern Europe, but
is often experiencing significant internal change
as the result of factors such as land reform and
abandonment in areas further from settlements, and
intensification nearer to settlements (see Chapter 7
and Box 3.1). However, the tertiary sector is the
greatest source of employment in the mountains of
all members of the EU‐27 as well as Switzerland and
Norway, except for the Czech Republic (European
Commission, 2004) and Romania (UNEP, 2007).
The public sector accounts for a particularly high
proportion of this employment in the mountains of
the Nordic countries and the French Alps (Borsdorf,
2008). A number of mountain areas have had
relatively high employment in the secondary sector
for decades or longer, usually due to the availability
of specific geological and energy resources and also,
historically, of labour in the form of agricultural
workers in winter (Box 3.2).
3.2 Economic density and accessibility
Previous work on the mountains of Europe,
including all states that are now members of the EU,
states of the former Yugoslavia, Albania, Moldova,
Norway and Switzerland (Copus and Price 2002),
has focused on the interactions between economic
performance (in terms of GDP per capita) and
peripherality (as defined by Schurmann and Talaat,
2000). This work used data at the NUTS 3 level and
suggested that economic performance declined with
increasing peripherality for NUTS 3 regions with
at least 40 % of their area defined as mountainous,
but that the impact of the presence of mountains
'is very entangled with that of peripherality, and
can be improved by the presence of a large town
or city' (Copus and Price, 2002: 33). The authors
also concluded that 'NUTS 3 geography is clearly
inadequate for such as exercise' (Copus and Price,
2002) because most NUTS 3 regions are large in
area and have both mountain and lowland areas,
usually with most of the population and economic
activity in the latter. This conclusion has been borne
out by subsequent analysis, for example for the Alps
(Tappeiner et al., 2008).
For the present report, economic performance is
expressed in terms of economic density, defined
as the income generated per square kilometre
(EUR km 2 ). This can be considered as an integrative
indicator of economic power and population density,
which has been used to rank countries by their
level of development (Gallup et al., 1999). Economic
density is defined in terms of GDP PPP (i.e. domestic
product (GDP) at purchasing power parity (PPP)
per capita, the value of all final goods and services
produced within a nation in a given year divided by
the average (or mid-year population for the same
year) per capita, and is derived from CLC and EEA
population density map. This work could only be
done for the EU‐27.
Accessibility through transportation and
communication networks is a significant determinant
of access of people to markets and other services.
Accessibility is frequently used as a proxy for urban
influence in rural areas; its converse is peripherality,
as examined for Europe's mountain areas in
European Commission (2004). A time‐cost model was
used, based on the cost-distance algorithms (ESRI
2006), to avoid interference with the economic density
dataset and to use a comparable spatial unit and
resolution. This approach calculates, for each square
kilometre in Europe, the travel time to the nearest
destination of interest given the transportation
network. Since cities and towns of different sizes offer
different opportunities and facilities, the travel time
was calculated separately to towns and cities of more
than 25 000, 60 000, 100 000, 250 000, 500 000 and
750 000 inhabitants. The final measure of accessibility
is based on the average time‐cost to these different
Europe's ecological backbone: recognising the true value of our mountains
45