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Adaptive management: a synthesis of current understanding and effective application
Author(s) -
Schreiber E. Sabine G.,
Bearlin Andrew R.,
Nicol Simon J.,
Todd Charles R.
Publication year - 2004
Publication title -
ecological management and restoration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.472
H-Index - 42
eISSN - 1442-8903
pISSN - 1442-7001
DOI - 10.1111/j.1442-8903.2004.00206.x
Subject(s) - adaptive management , computer science , trace (psycholinguistics) , relation (database) , risk analysis (engineering) , management science , process management , data science , environmental resource management , business , engineering , data mining , environmental science , philosophy , linguistics
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.