title: Adaptive management for a turbulent future.
abstract: The challenges that face humanity today differ from the past because as the scale of human influence has increased, our biggest challenges have become global in nature, and formerly local problems that could be addressed by shifting populations or switching resources, now aggregate (i.e., "scale up") limiting potential management options. Adaptive management is an approach to natural resource management that emphasizes learning through management based on the philosophy that knowledge is incomplete and much of what we think we know is actually wrong. Adaptive management has explicit structure, including careful elucidation of goals, identification of alternative management objectives and hypotheses of causation, and procedures for the collection of data followed by evaluation and reiteration. It is evident that adaptive management has matured, but it has also reached a crossroads. Practitioners and scientists have developed adaptive management and structured decision making techniques, and mathematicians have developed methods to reduce the uncertainties encountered in resource management, yet there continues to be misapplication of the method and misunderstanding of its purpose. Ironically, the confusion over the term "adaptive management" may stem from the flexibility inherent in the approach, which has resulted in multiple interpretations of "adaptive management" that fall along a continuum of complexity and a priori design. Adaptive management is not a panacea for the navigation of 'wicked problems' as it does not produce easy answers, and is only appropriate in a subset of natural resource management problems where both uncertainty and controllability are high. Nonetheless, the conceptual underpinnings of adaptive management are simple; there will always be inherent uncertainty and unpredictability in the dynamics and behavior of complex social-ecological systems, but management decisions must still be made, and whenever possible, we should incorporate learning into management.
authors.affiliation: Nebraska Cooperative Fish and Wildlife Research Unit, U.S. Geological Survey, School of Natural Resources, University of Nebraska, Lincoln, NE, USA. allencr@unl.edu
authors.forename: Craig R
authors.initials: CR
authors.lastname: Allen
authors.forename: Joseph J
authors.initials: JJ
authors.lastname: Fontaine
authors.forename: Kevin L
authors.initials: KL
authors.lastname: Pope
authors.forename: Ahjond S
authors.initials: AS
authors.lastname: Garmestani
mesh_terms: D003247:Conservation of Natural Resources / Q000379:methods*; D003625:Data Collection; D003657:Decision Making; D017753:Ecosystem; D004777:Environment; D006040:Goals; D007722:Health Knowledge, Attitudes, Practice; D007858:Learning; D035501:Uncertainty