Simulating the Socio-Economic and Biogeophysical Driving Forces of Land-Use and Land-Cover Change: The IIASA Land-Use Change Model

Fischer, G., Ermoliev, Y.M., Keyzer, M.A., & Rosenzweig, C. (1996). Simulating the Socio-Economic and Biogeophysical Driving Forces of Land-Use and Land-Cover Change: The IIASA Land-Use Change Model. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-010

Preview

Text WP-96-010.pdf Download (2MB) | Preview

Abstract

In 1995, a new project Modeling Land-Use and Land-Cover Changes in Europe and Northern Asia (LUC) was established at IIASA with the objective of analyzing the spatial characteristics, temporal dynamics, and environmental consequences of land-use and land-cover changes that have occurred in Europe and Northern Asia over the period 1900 to 1990 as a result of a range of socio-economic and biogeophysical driving forces. The analysis will then be used to project plausible future changes in land use and land cover for the period 1990 to 2050 under different assumptions of future demographic, economic, technological, social and political development. The study region, Europe and Northern Asia, has been selected because of its diversity in social, economic and political organization, the rapid changes in recent history, and the significant implications for current and future land-use and land-cover change.

Land-cover change is driven by a multitude of processes. Natural processes, such as vegetation dynamics, involve alterations in cover due to natural changes in climate and soils. However, changes of land cover driven by anthropogenic forcing are currently the most important and most rapid of all changes (Turner et al. 1990). Therefore, any sound effort to project the future state of land cover must consider the determinants of human requirements and activities, e.g., demand for land-based products such as food, fiber and fuel, or use of land for recreation.

In the past, major land-cover conversions have occurred as a consequence of deforestation to convert land for crop and livestock production; removal of wood for fuel and timber; conversion of wetlands to agricultural and other uses; conversion of land for habitation, infrastructure and industry; and conversion of land for mineral extraction (Turner et al. 1993). These human-induced conversions of land cover, particularly during the past two centuries, have resulted in a net release of CO2 to the atmosphere, changes in the characteristics of land surfaces (e.g., albedo and roughness), and decreased biodiversity.

More subtle processes, termed land-cover modifications, affect the character of the land cover without changing its overall classification. For instance, land-cover degradation through erosion, overgrazing, desertification, salinization and acidification, is currently considered a major environmental problem. Although the effects of land-cover modifications may be small at local scales, their aggregate impact may be considerable. For example, use of fertilizers locally has no significance for atmospheric concentrations of greenhouse gases. However, when practiced frequently in many locations, nitrogen fertilizer can make a significant contribution to emissions of nitrous oxide (N2O) globally.

The implementation of a comprehensive land-use change model poses a number of methodological challenges. These include the complexity of the issues involved and the large number of interacting agents and factors; the nonlinear interactions between prices, the supply of and the demand for land-based commodities and resources; the importance of intertemporal aspects; the intricacy of biogeophysical feedbacks; and the essential role of uncertainty in the overall evaluation of strategies.

The interaction mechanisms between biophysical cycles and economic processes have mainly been studied in dynamic simulation models that follow recursive chains of causation, where the past and present events determine what will happen tomorrow. Not surprisingly, many of these studies have led to dramatic predictions, basically because the agents whose behavior is described within the model are themselves assumed to be unable to predict at all. By contrast, in micro-economics it is usually assumed that agents do have the capacity to make informed predictions and to plan so as to avoid the probability of disaster in the future. However, even full information and rationality of individual choice are not always sufficient to avoid disaster. The coordination mechanisms that prevail among economic agents often tend to be of decisive importance.

The aim of this paper is to summarize the LUC project approach and to extend our earlier writings on modeling of land-use and land-cover change dynamics. We discuss the adequacy and applicability of welfare analysis as a conceptual framework for the LUC project at IIASA. We recognize from the outset the complexity of socio-economic and environmental driving forces and the fundamental uncertainties involved in their spatial and temporal interactions (and outcomes). Unlike physical particles, economic agents have the ability to anticipate, and they possess the freedom to change their behavior. This inherent unpredictability, in particular the multiplicity of possible outcomes, calls for a normative approach, and for comparative policy analysis rather than exact prediction. Therefore, we adopt an approach that enables the explicit representation of various policy measures, thus providing a means to search for "better futures", i.e., for trajectories of future development that may alleviate environmental stresses while improving human welfare.

Actions (login required)

View Item