Conclusions

Given the widespread increase in danger of wildland fire throughout the Western United States over the past 70 years or more, the sustainability of Western forest ecosystems is clearly at stake. Decision support systems such as EMDS can play a role in assisting with restoration to improve or maintain their sustainability. Issues surrounding decisions about fuels management are complex and often require abstraction, but logic and decision models are well suited to representing the inherent complexities and abstractness of the problem, thus rendering the analytical problem more manageable. This particular application of EMDS also is an example of how decision support systems can not only be used as tools for technical specialists and decision makers, but as tools for communicating clearly and effectively with the general public who understandably have a strong interest in the topic of wildfire and want to understand, and be involved in, any proposed solution. Both logic and decision models are good at explaining themselves in relatively intuitive terms, and thus provide a basis for an effective public dialog.

Finally, there is an important interdependency between science, policy, and decision support systems such as EMDS. Although logic models are sometimes used for prediction, they are fundamentally concerned with interpretation (Reynolds and others 2003). In other words, what does the information mean? Meaning can be highly normative or highly subjective, and usually falls somewhere in between the two extremes. As a result, virtually all interpretation embeds some degree of subjectivity; that is, to some degree, values and policy are inextricable aspects of logic and decision models. The practical implication is that successful application of most decision support systems to real-world situations ultimately depends on a close collaboration between the scientific community that brings its facts to the table and the policy makers that need to reach decisions based on that information and additional social and economic considerations. Decision support systems provide a conspicuous advantage in this context—detailed documentation of a decision making process. With ongoing monitoring and evaluation, lessons learned can be readily incorporated into decision models providing increasing effectiveness to decision making and an explicit vehicle for adapting management.