Skip to main content
padlock icon - secure page this page is secure

'Learning by doing': adaptive planning as a strategy to address uncertainty in planning

Buy Article:

$53.00 + tax (Refund Policy)

Adaptive management, an established method in natural resource and ecosystem management, has not been widely applied to landscape planning due to the lack of an operational method that addresses the role of uncertainty and standardized monitoring protocols and methods. A review of adaptive management literature and practices reveals several key concepts and principles for adaptive planning: (1) management actions are best understood and practiced as experiments; (2) several plans/experiments can be implemented simultaneously; (3) monitoring of management actions are key; and (4) adaptive management can be understood as 'learning by doing'. The paper identifies various uncertainties in landscape planning as the major obstacles for the adoption of an adaptive approach. To address the uncertainty in landscape planning, an adaptive planning method is proposed where monitoring plays an integral role to reduce uncertainty. The proposed method is then applied to a conceptual test in water resource planning addressing abiotic-biotic-cultural resources. To operationalize adaptive planning, it is argued that professionals, stakeholders and researchers need to function in a genuinely transdisciplinary mode where all contribute to, and benefit from, decision making and the continuous generation of new knowledge.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: adaptive management; adaptive planning; monitoring; transdisciplinarity; uncertainty; water resource planning

Document Type: Research Article

Affiliations: Department of Landscape Architecture and Regional Planning, University of Massachusetts, Amherst, MA, USA

Publication date: July 1, 2008

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more