allocation of land-use change. The only possible way
around this limitation is the use of empirical relations
derived in an area with very similar characteristics.
The model is suitable for scenario analysis and the
simulation of trajectories of land-use change. For different
scenarios the model can therefore identify critical
areas of land-use change (hot spots). Scenarios can
be used to evaluate the impact of macro-level changes,
such as price developments of agricultural products
and/or changes in demographic characteristics or consumption
patterns. Other scenarios can be used to
evaluate the effects of local level conditions, such as
nature reserve protection, on the surrounding region.
The possibility to simulate different scenarios makes
the model a powerful tool for natural resource management.
When projections of future land use are compared
with the location of vulnerable places in the light
of biodiversity, landscape stability, and/or food production,
it is possible to target interventions. A dynamic
coupling with specific models simulating the effects of
land-use change for landscape features should, therefore,
be established. The incorporation of feedback
mechanisms between the CLUE-S model and these impact
models will also improve the land-use simulations.
A typical example is the feedback between land degradation
and land use: land-use change affects land degradation
through erosion and sedimentation patterns.
In its turn, land degradation will affect future land-use
possibilities.
The visualization of the dynamics under different
development pathways make the model also a powerful
tool for participatory land use planning and stakeholder
negotiations (Harms and others 1993). The presented
methodology should therefore be seen as a new
tool that supplements existing methodologies for improved
environmental manageme