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Value of sample information in dynamic, structurally uncertain resource systems

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  • Byron K Williams
  • Fred A Johnson

Abstract

Few if any natural resource systems are completely understood and fully observed. Instead, there almost always is uncertainty about the way a system works and its status at any given time, which can limit effective management. A natural approach to uncertainty is to allocate time and effort to the collection of additional data, on the reasonable assumption that more information will facilitate better understanding and lead to better management. But the collection of more data, either through observation or investigation, requires time and effort that often can be put to other conservation activities. An important question is whether the use of limited resources to improve understanding is justified by the resulting potential for improved management. In this paper we address directly a change in value from new information collected through investigation. We frame the value of information in terms of learning through the management process itself, as well as learning through investigations that are external to the management process but add to our base of understanding. We provide a conceptual framework and metrics for this issue, and illustrate them with examples involving Florida scrub-jays (Aphelocoma coerulescens).

Suggested Citation

  • Byron K Williams & Fred A Johnson, 2018. "Value of sample information in dynamic, structurally uncertain resource systems," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
  • Handle: RePEc:plo:pone00:0199326
    DOI: 10.1371/journal.pone.0199326
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    References listed on IDEAS

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    1. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Literature Analysis: A Review of Applications in Health Risk Management," Medical Decision Making, , vol. 24(3), pages 287-298, June.
    2. Maxine E. Dakins & John E. Toll & Mitchell J. Small & Kevin P. Brand, 1996. "Risk‐Based Environmental Remediation: Bayesian Monte Carlo Analysis and the Expected Value of Sample Information," Risk Analysis, John Wiley & Sons, vol. 16(1), pages 67-79, February.
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