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Reducing uncertainty about objective functions in adaptive management

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  • Williams, Byron K.

Abstract

This paper extends the uncertainty framework of adaptive management to include uncertainty about the objectives to be used in guiding decisions. Adaptive decision making typically assumes explicit and agreed-upon objectives for management, but allows for uncertainty as to the structure of the decision process that generates change through time. Yet it is not unusual for there to be uncertainty (or disagreement) about objectives, with different stakeholders expressing different views not only about resource responses to management but also about the appropriate management objectives. In this paper I extend the treatment of uncertainty in adaptive management, and describe a stochastic structure for the joint occurrence of uncertainty about objectives as well as models, and show how adaptive decision making and the assessment of post-decision monitoring data can be used to reduce uncertainties of both kinds. Different degrees of association between model and objective uncertainty lead to different patterns of learning about objectives.

Suggested Citation

  • Williams, Byron K., 2012. "Reducing uncertainty about objective functions in adaptive management," Ecological Modelling, Elsevier, vol. 225(C), pages 61-65.
    • Handle: RePEc:eee:ecomod:v:225:y:2012:i:c:p:61-65
    DOI: 10.1016/j.ecolmodel.2011.11.009
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    References listed on IDEAS

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    1. Williams, Byron K., 2009. "Markov decision processes in natural resources management: Observability and uncertainty," Ecological Modelling, Elsevier, vol. 220(6), pages 830-840.
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    Cited by:

    1. Ashley B. C. Goode & Erin Rivenbark & Jessica A. Gilbert & Conor P. McGowan, 2023. "Prioritization of Species Status Assessments for Decision Support," Decision Analysis, INFORMS, vol. 20(4), pages 311-325, December.
    2. Williams, Perry J. & Kendall, William L., 2017. "A guide to multi-objective optimization for ecological problems with an application to cackling goose management," Ecological Modelling, Elsevier, vol. 343(C), pages 54-67.

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