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Adaptive resource management and the value of information


  • Williams, Byron K.
  • Eaton, Mitchell J.
  • Breininger, David R.


The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.

Suggested Citation

  • Williams, Byron K. & Eaton, Mitchell J. & Breininger, David R., 2011. "Adaptive resource management and the value of information," Ecological Modelling, Elsevier, vol. 222(18), pages 3429-3436.
  • Handle: RePEc:eee:ecomod:v:222:y:2011:i:18:p:3429-3436
    DOI: 10.1016/j.ecolmodel.2011.07.003

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    References listed on IDEAS

    1. Williams, Byron K., 2007. "Optimal management of non-Markovian biological populations," Ecological Modelling, Elsevier, vol. 200(1), pages 234-242.
    2. Bas Groot Koerkamp & M. G. Myriam Hunink & Theo Stijnen & Milton C. Weinstein, 2006. "Identifying key parameters in cost‐effectiveness analysis using value of information: a comparison of methods," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 383-392, April.
    3. Richard D. Smallwood & Edward J. Sondik, 1973. "The Optimal Control of Partially Observable Markov Processes over a Finite Horizon," Operations Research, INFORMS, vol. 21(5), pages 1071-1088, October.
    4. Williams, Byron K., 2009. "Markov decision processes in natural resources management: Observability and uncertainty," Ecological Modelling, Elsevier, vol. 220(6), pages 830-840.
    5. Thomas, Alban & Bontems, Philippe, 1998. "Information Value And Risk Premium In Agricultural Production Under Risk: The Case Of Split Nitrogen Application For Corn," 1998 Annual meeting, August 2-5, Salt Lake City, UT 20844, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Karnon, Jonathan, 2002. "Planning the efficient allocation of research funds: an adapted application of a non-parametric Bayesian value of information analysis," Health Policy, Elsevier, vol. 61(3), pages 329-347, September.
    7. Philippe Bontems & Alban Thomas, 2000. "Information Value and Risk Premium in Agricultural Production: The Case of Split Nitrogen Application for Corn," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(1), pages 59-70.
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    Cited by:

    1. Jeffrey, Scott R. & Pannell, David J., 2013. "Economics of Prioritising Environmental Research: An Expected Value of Partial Perfect Information (EVPPI) Framework," Working Papers 144944, University of Western Australia, School of Agricultural and Resource Economics.
    2. Brownson, Katherine & Fowler, Laurie, 2020. "Evaluating how we evaluate success: Monitoring, evaluation and adaptive management in Payments for Watershed Services programs," Land Use Policy, Elsevier, vol. 94(C).
    3. Stephen M Pawson & Bruce G Marcot & Owen G Woodberry, 2017. "Predicting forest insect flight activity: A Bayesian network approach," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-22, September.
    4. Johnson, Fred A. & Smith, Brian J. & Bonneau, Mathieu & Martin, Julien & Romagosa, Christina & Mazzotti, Frank & Waddle, Hardin & Reed, Robert N. & Eckles, Jennifer Kettevrlin & Vitt, Laurie J., 2017. "Expert Elicitation, Uncertainty, and the Value of Information in Controlling Invasive Species," Ecological Economics, Elsevier, vol. 137(C), pages 83-90.
    5. Kling, David M. & Sanchirico, James N. & Fackler, Paul L., 2017. "Optimal monitoring and control under state uncertainty: Application to lionfish management," Journal of Environmental Economics and Management, Elsevier, vol. 84(C), pages 223-245.
    6. Johnson, Fred A. & Jensen, Gitte H. & Madsen, Jesper & Williams, Byron K., 2014. "Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population," Ecological Modelling, Elsevier, vol. 273(C), pages 186-199.
    7. Debarun Bhattacharjya & Jo Eidsvik & Tapan Mukerji, 2013. "The Value of Information in Portfolio Problems with Dependent Projects," Decision Analysis, INFORMS, vol. 10(4), pages 341-351, December.
    8. David Breininger & Brean Duncan & Mitchell Eaton & Fred Johnson & James Nichols, 2014. "Integrating Land Cover Modeling and Adaptive Management to Conserve Endangered Species and Reduce Catastrophic Fire Risk," Land, MDPI, Open Access Journal, vol. 3(3), pages 1-24, July.


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