Adaptive management: a synthesis of current understanding and effective application

Adaptive management: a synthesis of current understanding and effective application Summary Adaptive management (AM) remains a commonly cited, yet frequently misunderstood, management approach. The aim of AM is to improve environmental management through ‘learning by doing’ and understand the impact of incomplete knowledge, but AM more commonly consists of ad hoc changes in managing environmental resources in the absence of adequate planning and monitoring. Here, we trace and review the development of AM, the central roles of consultation, collaboration and of monitoring, and of quantitative models and simulations. We identify a series of formalized, structured steps included in one AM cycle and review how current AM programs build upon such cycles. We conclude that the best AM outcomes require rigorous and formalized approaches to planning, collaboration, modelling and evaluation. Finally, simulating potential outcomes of an AM cycle in the presence of existing uncertainty can help to identify management strategies that are most likely to succeed in relation to clearly articulated goals. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Ecological Management & Restoration Wiley

Adaptive management: a synthesis of current understanding and effective application

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Publisher
Wiley
Copyright
Copyright © 2004 Wiley Subscription Services, Inc., A Wiley Company
ISSN
1442-7001
eISSN
1442-8903
DOI
10.1111/j.1442-8903.2004.00206.x
Publisher site
See Article on Publisher Site

Abstract

Summary Adaptive management (AM) remains a commonly cited, yet frequently misunderstood, management approach. The aim of AM is to improve environmental management through ‘learning by doing’ and understand the impact of incomplete knowledge, but AM more commonly consists of ad hoc changes in managing environmental resources in the absence of adequate planning and monitoring. Here, we trace and review the development of AM, the central roles of consultation, collaboration and of monitoring, and of quantitative models and simulations. We identify a series of formalized, structured steps included in one AM cycle and review how current AM programs build upon such cycles. We conclude that the best AM outcomes require rigorous and formalized approaches to planning, collaboration, modelling and evaluation. Finally, simulating potential outcomes of an AM cycle in the presence of existing uncertainty can help to identify management strategies that are most likely to succeed in relation to clearly articulated goals.

Journal

Ecological Management & RestorationWiley

Published: Dec 1, 2004

References

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