Combining market and traditional values in tribal forestry using interactive forest decision synthesis (INFODS)

Abstract

Forestry joint production choices require clear relative values for multiple, and often conflicting, management objectives. Optimization is most difficult where values of forest attributes are: intangible, non-market, or sensitive. When most mathematical programming models are adapted for non-commensurable objectives, there is little guarantee that vague relative preference sets are met. We demonstrate how an iterative multiple objective programming approach finds preferred joint solutions in a Native American tribal forestry case where marketable outputs are managed in the context of traditional culturally based forest values. Without a priori specification of traditional tribal cultural values, conducting a series of feedback processes does appear to identify more preferable solutions than other types of multiple-objective models that do not use feedback.