TY - JOUR
T1 - Adaptive management
T2 - A synthesis of current understanding and effective application
AU - Schreiber, E. Sabine G
AU - Bearlin, Andrew R.
AU - Nicol, Simon J.
AU - Todd, Charles R.
PY - 2004/12/1
Y1 - 2004/12/1
N2 - 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.
AB - 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.
KW - Adaptive environmental assessment and management
KW - Modelling
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=9644282931&partnerID=8YFLogxK
U2 - 10.1111/j.1442-8903.2004.00206.x
DO - 10.1111/j.1442-8903.2004.00206.x
M3 - Review article
AN - SCOPUS:9644282931
SN - 1442-7001
VL - 5
SP - 177
EP - 182
JO - Ecological Management and Restoration
JF - Ecological Management and Restoration
IS - 3
ER -