By Tim Smith
Adaptive management is a bit of a buzzword in the field of environmental and natural resource management. It refers to the practice of learning by doing, and is best applied to complex social-ecological systems where both uncertainty and controllability are high.
Climate change, for example, is predicted to have a number of generally adverse effects on biodiversity such as habitat loss, geographical redistribution of species and widespread extinctions, however the exact responses of individual species and communities to climate mediated ecosystem changes are not clear. These issues are potentially amenable to an adaptive approach which tests strategies such as increasing the size of protected areas to include a range of altitudes, establishing habitat corridors and stepping stones, increasing resiliency and translocating species.
Adaptive management is a well defined process, with an explicit, cyclical structure that distinguishes it from other decision making processes:
- Define the goals
- Develop alternative management strategies
- Implement two or more of these strategies
- Monitor the outcomes
- Revise management strategies based on the results
- Repeat the cycle
Thus, over time, knowledge builds up and management improves. This may all sound like common sense, but it represents a clear shift away from the traditional overreliance on incomplete knowledge and inaccurate modelling, to acknowledge the complexity of ecosystems and associated human interactions. It confronts uncertainty, rather than regarding it as an admission of failure, and integrates research and implementation, rather than having scientists and managers working in isolation.
The concept of adaptive management is now well accepted, but its practical application is notoriously difficult, such that there are few examples of it being implemented correctly. Indeed Gregory (2006) suggests that many of the initiatives claiming to practice adaptive management bear few, if any of the essential components.
There are a number of reasons why this may be so. Practical and economic constraints are partly to blame, coupled with a natural tendency to resist new ways of thinking, which has resulted in managers favouring the implementation of one strategy at a time (passive adaptive management, using perceived best practice), rather than embracing uncertainty and experimenting with several options in parallel (active adaptive management).
The extensive monitoring required by adaptive management has also proved problematic, again partly due to the cost and time involved. In addition, it has been argued that the monitoring and evaluation process requires a high level of statistical and analytical expertise that may not be readily available in many institutions.
A further issue has been an incomplete understanding of the theory of adaptive management, resulting in its application in inappropriate contexts, where uncertainty may be high, but controllability is low. In these situations scenario planning is a better choice.
It is clear that further work is required in order to help managers implement this important tool appropriately and effectively, allowing it to achieve the benefits it tantalisingly promises.
Some good references:
ALLEN, C. R., FONTAINE, J. J., POPE, K. L. & GARMESTANI, A. S. 2011. Adaptive management for a turbulent future. Journal of Environmental Management, 92, 1339-1345.
GREGORY, R., OHLSON, D. & ARVAI, J. 2006. Deconstructing Adaptive Management: Criteria for Applications to Environmental Management. Ecological Applications, 16, 2411-2425.
KEITH, D. A., MARTIN, T. G., MCDONALD-MADDEN, E. & WALTERS, C. 2011. Uncertainty and adaptive management for biodiversity conservation. Biological Conservation, 144, 1175-1178.
MAWDSLEY, J. R., O’MALLEY, R. & OJIMA, D. S. 2009. A Review of Climate-Change Adaptation Strategies for Wildlife Management and Biodiversity Conservation. Conservation Biology, 23, 1080-1089.
PETERSON, G. D., CUMMING, G. S. & CARPENTER, S. R. 2003. Scenario Planning: a Tool for Conservation in an Uncertain World. Conservation Biology, 17, 358-366.