Soft systems thinking and social learning for adaptive management

No Thumbnail Available
File version
Author(s)
Cundill, G
Cumming, GS
Biggs, D
Fabricius, C
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2012
Size
File type(s)
Location
License
Abstract

The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning.

Journal Title

Conservation Biology

Conference Title
Book Title
Edition
Volume

26

Issue

1

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Environmental sciences

Conservation and biodiversity

Biological sciences

Agricultural, veterinary and food sciences

Persistent link to this record
Citation
Collections