The relationship between humanity and global environmental change is among the most interdisciplinary of intellectual topics (Chen et al., 1983; Kates et al., 1985). Because the driving forces of global change involve the interactions of various human systems with various environmental systems, and because human responses to global change often affect the driving forces, researchers investigating any one system need to treat other systems as intrinsic to their models. It is not satisfactory, for example, for economic models of agricultural production to assume the continuation of average weather conditions, as they normally do, or for models of ozone depletion to assume that international agreements on the phaseout of CFCs will achieve perfect compliance.
Understanding the human dimensions of global change requires creating bridges between disciplines—both between the social and behavioral sciences and the natural sciences and between the disciplines of social and behavioral science. Interdisciplinary work is not only essential but also potentially beneficial to the individual disciplines. It can improve the quality of the assumptions they make and allow each field to consider applying methods developed in other fields.
Global change studies typically make assumptions about at least three aspects of human behavior: what people are doing that might affect the environment (and how that behavior may change over time); how people are affected by changes in the environment (and how their sensitivity to such changes may vary over time); and what information people use (or might use or might desire in the future) in making choices about their relationship to the environment. These assumptions may be made explicitly or they may be embedded in models (e.g., projecting constant rates of increase of population, energy consumption, or CFC production). In either case, the quality of understanding is limited by the quality of the social science on which it is built.
If analysts make erroneous assumptions about how people affect the environment, they may err in estimating rates of environmental change and, perhaps more significantly, by underestimating the uncertainty of their analyses. If they make erroneous assumptions about how the environment affects people, they may neglect feedback processes that might be used to mitigate or adapt