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 (ICAMBrown and Rosenberg, 1999), Asian-Pacific Integrated Model (AIMMatsuoka et al., 1995), Integrated Model for the Assessment of the Greenhouse Effect (IMAGEAlcamo et al., 1998b), and Tool to Assess Regional and Global Environmental and Health Targets for Sustainability (TARGETSRotmans 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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