Experimental or precautionary? Adaptive management over a range of time horizons

Hauser, C. and Possingham, H. (2008) Experimental or precautionary? Adaptive management over a range of time horizons. Journal of Applied Ecology, 45 1: 72-81. doi:10.1111/j.1365-2664.2007.01395.x

Author Hauser, C.
Possingham, H.
Title Experimental or precautionary? Adaptive management over a range of time horizons
Journal name Journal of Applied Ecology   Check publisher's open access policy
ISSN 0021-8901
Publication date 2008-02
Sub-type Article (original research)
DOI 10.1111/j.1365-2664.2007.01395.x
Open Access Status DOI
Volume 45
Issue 1
Start page 72
End page 81
Total pages 10
Place of publication United Kingdom
Publisher Wiley- Blackwell Publishing Ltd
Collection year 2009
Language eng
Subject C1
0501 Ecological Applications
960701 Coastal and Marine Management Policy
Abstract Many studies of adaptive harvest management already exist in the literature, but most (if not all) use long, sometimes infinite, time horizons. Such long-term objectives provide an opportunity to manage experimentally, so that poorly understood dynamics are learned and any returns sacrificed for experimentation are repaid by improved management over the remaining time horizon. However, a manager is unlikely to weight outcomes in the distant future equally against outcomes in the present. Furthermore, the most appropriate model of system dynamics may not remain constant over the time-frame required to experiment, learn and improve management. In these cases the use of discounting and/or a finite time horizon fit the manager's assumptions and goals more effectively, and the value of experimentation is likely to be diminished. In this paper we construct a simple model of a hypothetical population and compare optimal passive and active adaptive harvest strategies over a range of time horizons. This allows us to determine the optimal level of experimentation for short-, medium- and long-term goals. We discover that the optimal active adaptive harvest strategy may be precautionary over short to medium time horizons, rather than experimental. That is, an action with known moderate benefits is preferred over an action with uncertain but marginally larger expected benefits. This runs counter to the widespread assumption in the adaptive management literature that incorporating learning into an optimization of management will encourage experimentation. Synthesis and applications. The general results of this paper have potential application to any environmental management problem where adaptive management might be applied; for example, conservation, pest control, harvesting and management of water flows. We examine adaptive management over a range of finite time horizons to reflect a variety of possible management goals and assumptions. Our simple example demonstrates that in the face of model uncertainty, the management strategy that maximizes benefits does not necessarily include deliberate experimentation and learning. Optimal active adaptive management weighs experimentation against all its potential consequences, and this can yield a precautionary approach.
Keyword Decision Theory
Stochastic dynamic programming
Q-Index Code C1
Q-Index Status Confirmed Code

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Created: Tue, 09 Dec 2008, 17:14:40 EST by Gail Walter on behalf of School of Biological Sciences