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Knowledge‐Based Risk Assessment Under Uncertainty for Species Invasion

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  • Iftikhar U. Sikder
  • Sanchita Mal‐Sarkar
  • Tarun K. Mal

Abstract

Management of invasive species depends on developing prevention and control strategies through comprehensive risk assessment frameworks that need a thorough analysis of exposure to invasive species. However, accurate exposure analysis of invasive species can be a daunting task because of the inherent uncertainty in invasion processes. Risk assessment of invasive species under uncertainty requires potential integration of expert judgment with empirical information, which often can be incomplete, imprecise, and fragmentary. The representation of knowledge in classical risk models depends on the formulation of a precise probabilistic value or well‐defined joint distribution of unknown parameters. However, expert knowledge and judgments are often represented in value‐laden terms or preference‐ordered criteria. We offer a novel approach to risk assessment by using a dominance‐based rough set approach to account for preference order in the domains of attributes in the set of risk classes. The model is illustrated with an example showing how a knowledge‐centric risk model can be integrated with the dominance‐based principle of rough set to derive minimal covering “if … , then…,” decision rules to reason over a set of possible invasion scenarios. The inconsistency and ambiguity in the data set is modeled using the rough set concept of boundary region adjoining lower and upper approximation of risk classes. Finally, we present an extension of rough set to evidence a theoretic interpretation of risk measures of invasive species in a spatial context. In this approach, the multispecies interactions in an invasion risk are approximated with imprecise probability measures through a combination of spatial neighborhood information of risk estimation in terms of belief and plausibility.

Suggested Citation

  • Iftikhar U. Sikder & Sanchita Mal‐Sarkar & Tarun K. Mal, 2006. "Knowledge‐Based Risk Assessment Under Uncertainty for Species Invasion," Risk Analysis, John Wiley & Sons, vol. 26(1), pages 239-252, February.
  • Handle: RePEc:wly:riskan:v:26:y:2006:i:1:p:239-252
    DOI: 10.1111/j.1539-6924.2006.00714.x
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    References listed on IDEAS

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    1. Lynn A. Maguire, 2004. "What Can Decision Analysis Do for Invasive Species Management?," Risk Analysis, John Wiley & Sons, vol. 24(4), pages 859-868, August.
    2. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    3. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 1999. "Rough approximation of a preference relation by dominance relations," European Journal of Operational Research, Elsevier, vol. 117(1), pages 63-83, August.
    4. Mark C. Andersen & Heather Adams & Bruce Hope & Mark Powell, 2004. "Risk Analysis for Invasive Species: General Framework and Research Needs," Risk Analysis, John Wiley & Sons, vol. 24(4), pages 893-900, August.
    5. Clark, Jim & Horváth, Lajos & Lewis, Mark, 2001. "On the estimation of spread rate for a biological population," Statistics & Probability Letters, Elsevier, vol. 51(3), pages 225-234, February.
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    Cited by:

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    2. Duncan A. Robertson, 2019. "Spatial Transmission Models: A Taxonomy and Framework," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 225-243, January.

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