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A Bayesian Approach to Integrated Ecological and Human Health Risk Assessment for the South River, Virginia Mercury‐Contaminated Site

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  • Meagan J. Harris
  • Jonah Stinson
  • Wayne G. Landis

Abstract

We conducted a regional‐scale integrated ecological and human health risk assessment by applying the relative risk model with Bayesian networks (BN‐RRM) to a case study of the South River, Virginia mercury‐contaminated site. Risk to four ecological services of the South River (human health, water quality, recreation, and the recreational fishery) was evaluated using a multiple stressor–multiple endpoint approach. These four ecological services were selected as endpoints based on stakeholder feedback and prioritized management goals for the river. The BN‐RRM approach allowed for the calculation of relative risk to 14 biotic, human health, recreation, and water quality endpoints from chemical and ecological stressors in five risk regions of the South River. Results indicated that water quality and the recreational fishery were the ecological services at highest risk in the South River. Human health risk for users of the South River was low relative to the risk to other endpoints. Risk to recreation in the South River was moderate with little spatial variability among the five risk regions. Sensitivity and uncertainty analysis identified stressors and other parameters that influence risk for each endpoint in each risk region. This research demonstrates a probabilistic approach to integrated ecological and human health risk assessment that considers the effects of chemical and ecological stressors across the landscape.

Suggested Citation

  • Meagan J. Harris & Jonah Stinson & Wayne G. Landis, 2017. "A Bayesian Approach to Integrated Ecological and Human Health Risk Assessment for the South River, Virginia Mercury‐Contaminated Site," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1341-1357, July.
  • Handle: RePEc:wly:riskan:v:37:y:2017:i:7:p:1341-1357
    DOI: 10.1111/risa.12691
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    References listed on IDEAS

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    1. Marcot, Bruce G., 2012. "Metrics for evaluating performance and uncertainty of Bayesian network models," Ecological Modelling, Elsevier, vol. 230(C), pages 50-62.
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    2. Peng Tian & Jialin Li & Hongbo Gong & Ruiliang Pu & Luodan Cao & Shuyao Shao & Zuoqi Shi & Xiuli Feng & Lijia Wang & Riuqing Liu, 2019. "Research on Land Use Changes and Ecological Risk Assessment in Yongjiang River Basin in Zhejiang Province, China," Sustainability, MDPI, vol. 11(10), pages 1-20, May.
    3. Ana Cristina González-Valoys & José María Esbrí & Juan Antonio Campos & Jonatha Arrocha & Eva María García-Noguero & Tisla Monteza-Destro & Ernesto Martínez & Raimundo Jiménez-Ballesta & Eric Gutiérre, 2021. "Ecological and Health Risk Assessments of an Abandoned Gold Mine (Remance, Panama): Complex Scenarios Need a Combination of Indices," IJERPH, MDPI, vol. 18(17), pages 1-22, September.
    4. Yanping Lan & Jianjun Chen & Yanping Yang & Ming Ling & Haotian You & Xiaowen Han, 2023. "Landscape Pattern and Ecological Risk Assessment in Guilin Based on Land Use Change," IJERPH, MDPI, vol. 20(3), pages 1-19, January.

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