The International Institute for Applied Systems Analysis (IIASA) in Austria is involved in about a dozen projects studying and evaluating various causes and implications of global change. Project themes include land resources and land-use changes, sustainable use of forest resources, water resources, transboundary air pollution, and energy systems. Many of these projects involve complex modeling including representations of economic, social and physical systems. Günther Fischer presented results from IIASA's earlier Food and Agriculture project and described the issues and methods being studied by the current project on Modeling Land-Use and Land-Cover Changes in Europe and Northern Asia (LUC) which is focused on gaining a better understanding of land-use change and its effects in Europe and Northern Asia, and on developing improved methodologies and databases for projecting future scenarios of land-use and land-cover changes under a range of assumptions on future demographic, economic, technological and geobiophysical conditions.

Fischer gave a brief overview of the global general equilibrium model system developed by IIASA's Food and Agriculture Program (FAP), termed the Basic Linked System of National Agricultural Policy Models (BLS). It consists of 34 national and/or regional models: 18 national models, 2 models for regions with close economic cooperation (European Union and Eastern Europe + former USSR), and 14 aggregate models of country groupings. The individual models are linked together by means of a world market module. The outcome in terms of "real" variables is neutral with respect to monetary changes. The system is recursively dynamic, working in annual steps, the outcome of each step being affected by the outcomes of earlier ones. Each model covers the whole economy, for the purpose of international linkage aggregated to nine agricultural sectors and one non-agricultural sector. All accounts are closed and mutually consistent the production, consumption and financial accounts at the national level, and the trade and financial flows at the global level.

The concept of economic agents who decide on production and disappearance is the basis on which the BLS is built. Producers maximize returns to primary factors, i. e., capital, labor and land. Consumers are assumed to maximize utility. And governments follow prescribed objectives in their policy setting within the constraints of balancing expenditures with the revenues generated through taxes, tariffs or other means and international transfers.

The BLS has been used for several studies including an examination of the potential effects of climate change on world food supply, demand and trade. Using historical climate data and outputs from several General Circulation Models (GCMs), physiological crop models were used to track the effects of climate change on the yield of major crops, simulated at a number of sites representing a wide range of agro-ecological production conditions. These changes were then used to modify the yield functions used in the agriculture sector models of the BLS in order to examine the implications of climate change for the world food system.

A number of different scenarios were analyzed including current and doubled carbon dioxide (CO₂) climate scenarios and several different adaptation strategies that ranged from basic and simple adaptive changes to expensive and intensive changes in agricultural techniques. The results of these simulations suggest that food production on the global scale is not likely to be significantly affected by climate change during the next sixty years. However, the distribution of climate impacts may be fairly uneven and the differences between developed and developing countries seemed quite large. In general, mid and high latitude (mostly developed) countries experienced an increase in agricultural productivity while in tropical (mostly developing) countries, productivity generally decreased. For China (being the geographic focus of this Aspen Global Change Institute summer science session), all the simulations led to slightly positive changes in productivity.

If results of crop simulations, based on physiology but without economic feedbacks on production, are compared to dynamic simulations of crop and economic changes (including market forces that act upon changes in productivity), the addition of economic factors acts to reduce global scale changes in productivity, i. e., acts as an additional adaptive mechanism. But again, there are opposite effects in developed and developing countries. In developed countries, inclusion of economic factors in the simulations actually increases the benefits from climate change and in developing countries, the economic feedbacks exacerbate the reductions in yields due to climate change.

Fischer described a second example of agriculture sector modeling done at IIASA, related to land resources evaluation and agro-ecological analysis. To examine the effects of climate change at a national scale, a case study was done in Kenya. These simulations were performed using several layers of geographic data characterizing land resources and climate in a GIS environment. A major goal of this study was to examine the effects of climate change on land productivity considering a large number of different land utilization types. Using a number of climate sensitivity tests and GCM-derived climate scenarios, the simulations allowed the examination of the sensitivity of growing season length to factors such as temperature, soil moisture conditions and levels of atmospheric CO₂ concentrations. When examining the effects of temperature on productivity the results were highly spatially variable. Western, Nyanza and Central provinces ( i. e., highland areas of central and western Kenya) generally showed increases in productivity with warming, while decreases resulted elsewhere (i. e., the low lying parts in Eastern, North-Eastern and Coast provinces). Interestingly, Kenya as a whole, when aggregating the results, did not show a major change in productivity. An important conclusion that emerges from this study is that in heterogeneous regions, there can be very diverse impacts of climate change on agriculture and this could be important for demographic, social and economic changes within countries even if there is little overall effect on national agricultural productivity.

Returning to the geographic focus of the AGCI session, Fischer explained that several meetings on integrated assessment, concentrating on East Asia, had been held at IIASA. A number of factors were identified that must be addressed in order to project the future economic, demographic and environmental conditions in China. These factors include demographic aspects such as population size, its geographic distribution, the effects of rapid aging of Chinese society, level of education, changing lifestyles, and effectiveness of population policies. It is also important to understand the major dynamics in the economy, including level of savings rates, labor force, capital/labor ratios, technological development, distribution of economic sectors, and energy use. In addition to development issues, future environmental stability in China is a critical unknown factor and there are a number of problems that need to be examined including water supply and quality, land degradation, land transformation, air pollution, biogeochemical cycles, and potential climate change. Finally, political and institutional factors will need to be examined in order to make any predictions about future development.

Fischer also discussed work at IIASA currently in progress. IIASA has initiated a project on Modeling Land-Use and Land-Cover Changes in Europe and Northern Asia, to gain a better understanding of the critical social, technological and environmental factors and the constraints that have determined land-use change patterns. A better understanding of the sensitivity of land-use/cover change to different factors ( e. g., technology, demographic and economic development, policy and changing environmental conditions) can then be applied to develop projections of regional land-use/cover change for a range of scenarios. To do this, IIASA is developing an integrated system of dynamic and geographically explicit models. The project is organized into several distinct research phases. The primary task of research activities at IIASA is to develop the continental-scale model system and databases. In parallel, a number of case studies are conducted to refine the questions that will be addressed at the continental scale. These case studies will also be used to strengthen the research methodology and to provide a historical analysis of what land-use and land-cover changes have taken place. In Russia, five case studies were initiated, each in a prototypical ecological and socioeconomic setting. In China, four case studies are underway representing both agricultural land use changes and the effects of urbanization on land use change.

The modeling methodology of this analysis of land-use change includes components dealing with demography, the economy, land use, land cover and environmental impacts and resource accumulation/degradation. The focus is on the feedbacks between economics, changing land use, and land productivity. This requires that production functions in the economic model consider both resource and environmental limitations, and consumer demand functions differentiate, at least, between urban and rural classes. A number of regional models will be combined at the national scale and will also be sensitive to international trade and policies.

The IIASA LUC project aims to provide an advanced and innovative methodology for the analysis of biophysical and human dimensions of land-use/cover change in the study region at different spatial scales, based on improved knowledge and data.