Submitted to: Ecological Society of America Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 2/28/2004
Publication Date: 8/1/2004
Citation: Brown, J.R., Bestelmeyer, B.T., Herrick, J.E. 2004. A manager's dilemma: making logical decisions at the local scale [abstract]. 89th Annual Meeting of the Ecological Society of America, Lessons of Lewis and Clark: Ecological Exploration of Inhabited Landscapes, August 1-6, 2004, Portland, Oregon. p. 66.
Technical Abstract: General principles for land management within a region are usually derived from the extrapolation of nontemporally replicated, plot-scale experiments. To successfully implement recommendations, land managers ultimately must restrict the spatial extent of action to match available resources. Overextending scarce resources, whether financial or intellectual, usually results in failure at best, and at worst can initiate catastrophic degrading processes. Realistically, the extent at which managerial control can be exercised seldom exceeds 10 km2, a scale at which factors external to site-specific applications have as much influence on outcomes as internal factors. It is virtually impossible to adapt concepts, principles or guidelines consistently to site-specific application without a well developed understanding of spatial and temporal variability in driving factors. Improving chances of management success requires a combination of deductive (applying general principles at a site specific level) and inductive (using local observations to seek explanations) reasoning. Managers often rely on general assertions regarding the dominant factors driving change across a region because there is little guidance available to understand scale dependence, factor interactions and variability and their consequences for management decisions. We suggest that institutional management guidance for making site-specific decisions is inadequate unless we also develop a framework for testing local observations against multiple, scale-dependent, competing hypotheses to predict responses.