3.3.2.3. Integrated Assessment Models
Most scenarios applied in climate change impact assessments fail to account
satisfactorily for LUC-LCC. By incorporating land-use activities and land-cover
characteristics, it becomes feasible to obtain comprehensive estimates of carbon
fluxes and other GHG emissions, the role of terrestrial dynamics in the climate
system, and ecosystem vulnerability and mitigation potential. Currently, the
only tools for delivering this are IAMs (Weyant et al., 1996; Parson
and Fisher-Vanden, 1997; Rotmans and Dowlatabadi, 1998), but only a few successfully incorporate LUC-LCC, including Integrated
Climate Assessment Model (ICAM—Brown and Rosenberg, 1999), Asian-Pacific
Integrated Model (AIM—Matsuoka et al., 1995), Integrated Model for
the Assessment of the Greenhouse Effect (IMAGE—Alcamo et al., 1998b),
and Tool to Assess Regional and Global Environmental and Health Targets for
Sustainability (TARGETS—Rotmans and de Vries, 1997). These models simulate
interactions between global change and LUC-LCC at grid resolution (IMAGE, AIM)
or by regions (ICAM, TARGETS). All of these models, however, remain too coarse
for detailed regional applications.
LUC-LCC components of IAMs generally are ecosystem and crop models, which are
linked to economic models that specify changes in supply and demand of different
land-use products for different socioeconomic trends. The objectives of each
model differ, which has led to diverse approaches, each characterizing a specific
application.
ICAM, for example, uses an agricultural sector model, which integrates environmental
conditions, different crops, agricultural practices, and their interactions
(Brown and Rosenberg, 1999). This model is implemented for a set of typical
farms. Productivity improvements and management are explicitly simulated. Productivity
levels are extrapolated toward larger regions to parameterize the production
functions of the economic module. The model as a whole is linked to climate
change scenarios by means of a simple emissions and climate module. A major
advantage of ICAM is that adaptive capacity is included explicitly. Furthermore,
new crops, such as biomass energy, can be added easily. Land use-related emissions
do not result from the simulations. ICAM is used most effectively to assess
impacts but is less well suited for the development of comprehensive spatially
explicit LUC-LCC scenarios.
IMAGE uses a generic land-evaluation approach (Leemans and van den Born, 1994),
which determines the distribution and productivity of different crops on a 0.5°
grid. Achievable yields are a fraction of potential yields, set through scenario-dependent
regional "management" factors. Changing regional demands for land-use
products are reconciled with achievable yields, inducing changes in land-cover
patterns. Agricultural expansion or intensification lead to deforestation or
afforestation. IMAGE simulates diverse LUC-LCC patterns, which define fluxes
of GHGs and some land-climate interactions. Changing crop/vegetation distributions
and productivity indicate impacts. Emerging land-use activities (Leemans et
al., 1996a,b) and carbon sequestration activities defined in the Kyoto Protocol,
which alter land-cover patterns, are included explicitly. This makes the model
very suitable for LUC-LCC scenario development but less so for impact and vulnerability
assessment because IMAGE does not explicitly address adaptive capacity.
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