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Monitoring in the Context of Structured Decision‐Making and Adaptive Management
Abstract
Abstract: In a natural resource management setting, monitoring is a crucial component of an informed process for making decisions, and monitoring design should be driven by the decision context and associated uncertainties. Monitoring itself can play ≥3 roles. First, it is important for state‐dependent decision‐making, as when managers need to know the system state before deciding on the appropriate course of action during the ensuing management cycle. Second, monitoring is critical for evaluating the effectiveness of management actions relative to objectives. Third, in an adaptive management setting, monitoring provides the feedback loop for learning about the system; learning is sought not for its own sake but primarily to better achieve management objectives. In this case, monitoring should be designed to reduce the critical uncertainties in models of the managed system. The United States Geological Survey and United States Fish and Wildlife Service are conducting a large‐scale management experiment on 23 National Wildlife Refuges across the Northeast and Midwest Regions. The primary management objective is to provide habitat for migratory waterbirds, particularly during migration, using water‐level manipulations in managed wetlands. Key uncertainties are related to the potential trade‐offs created by management for a specific waterbird guild (e.g., migratory shorebirds) and the response of waterbirds, plant communities, and invertebrates to specific experimental hydroperiods. We reviewed the monitoring program associated with this study, and the ways that specific observations fill ≥1 of the roles identified above. We used observations from our monitoring to improve state‐dependent decisions to control undesired plants, to evaluate management performance relative to shallow‐water habitat objectives, and to evaluate potential trade‐offs between waterfowl and shorebird habitat management. With limited staff and budgets, management agencies need efficient monitoring programs that are used for decision‐making, not comprehensive studies that elucidate all manner of ecological relationships.
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Markov decision processes: Discrete stochastic dynamic programming
Hazeghi, K., & Puterman, M. L. (1995) · Journal of the American Statistical Association · doi:10.2307/2291177 · Cited by 8,037
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Metadata
- Authors
- LYONS, J. E., RUNGE, M. C., LASKOWSKI, H. P., & KENDALL, W. L.
- Venue
- The Journal of Wildlife Management
- Publisher
- Wiley
- Published
- 2008-11
- Volume
- 72
- Issue
- 8
- Pages
- 1683-1692
- ISSN
- 0022-541X (ISSN-L)
- 1937-2817
- OpenAlex
- W2143988373
- Cited by
- 322
- References
- 1
- FWCI
- 22.62
- Type
- journal article
- Language
- en
- Open access
- closed
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- LYONS, J. E., RUNGE, M. C., LASKOWSKI, H. P., & KENDALL, W. L. (2008). Monitoring in the Context of Structured Decision‐Making and Adaptive Management. The Journal of Wildlife Management. https://doi.org/10.2193/2008-141
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