Prior experience indicates that adaptive environmental assessment and management has been successful at identifying key points of intervention and developing lurches of understanding. That is, they have led to new management actions and improved understanding of resource dynamics. These include situations of adaptive waterfowl harvest in North America, harvest of fisheries in the reefs of Australia, and sediment transport in the Grand Canyon. Many other cases, however, point to a failure of adaptive management due to institutional rigidity, bureaucratic inertia, lack of ecological resilience, and lack of social capital in the form of trust and cooperation. Adaptive assessment and management is one approach that can help bridge the gap between science and resource management, but its implementation requires a small set of agreed-upon hypotheses, sufficient resources to conduct and evaluate experiments, and a social willingness to accept failure at appropriate scales.

Adaptive management proposes that ecological management be viewed as a series of experiments rather than the application of a solution. Adaptive management is an ongoing process that combines assessment with management actions that are structured in a way to learn about the complexities of system dynamics as well as to achieve social objectives. Assessing a system requires synthesizing available data to generate a set of competing alternative hypotheses about particular sets of resource problems and social objectives. Management actions are designed to sort among alternative hypotheses, prior to implementation. These actions are evaluated by monitoring key system indicators. While these activities are described linearly, adaptive management usually is designed to be an iterative process that develops a social dialog about a system. Modifying and creating ecological management institutions is difficult. Consequently, one of the main challenges of adaptive management is to develop new ways to enable social learning and experimentation.

See also: Applied Ecology; Ecosystem Services; Environmental Impact Assessment and Application -Part 1; Environmental Impact Assessment and Application - Part 2; Panarchy; Participatory Modeling; Sensitivity, Calibration, Validation, Verification.

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