Approaches to setting forestry research priorities: considering the benefits of reducing uncertainty

This paper reviews current approaches to research topic selection in forest management. Most current approaches are based on soliciting expert opinion of researchers within an environment where research demands may enter through media and political events. A number of potential problems are identified with these types of approaches including: research issues changing too rapidly for research programs to adapt, inability of surveys to capture long term trends in priorities, potential for processes to be captured by special interests of particular stakeholders, potential for consensus seeking to lead to research priorities that are too broad, a lack of statistical differences between topics leading to no significant priorities, a lack of explicit linking of the supply and demand for forestry research, and the potential for media to misrepresent research demands. Building on this literature, we suggest that current research selection methods be supplemented by developing new frameworks to provide more explicit information for research topic selection in forest management that would reduce the current pervasive role of subjectivity, provide research guidelines for local regions, and incorporate quantitative methods. This framework could be based upon the idea that one value of information is the reduction of costly mistakes. We suggest that sensitivity analyses on savings from potentially reduced uncertainty, within the context of different institutional constraints, could provide explicit information to assist with research topic selection. Key words: forestry research priorities, returns to research, value of information