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Visualizing Methane-Cycling Microbial Dynamics in Coastal Wetlands
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Published on: January 31, 2025

Bayesian spatial modeling of Lavaca Bay pollutants.

Wesley Bissett1, L Garry Adams, Robert Field

  • 1Texas A&M University, College of Veterinary Medicine, Department of Large Animal Clinical Sciences, 4475 TAMU, College Station, TX 77843-4475, USA. wbissett@cvm.tamu.edu

Marine Pollution Bulletin
|July 30, 2008
PubMed
Summary

Elevated mercury and polycyclic aromatic hydrocarbon (PAH) levels in Lavaca Bay, Texas sediments and oysters are highest near industrial sites. Bayesian geo-statistical analysis confirmed spatial risk factors for these pollutant concentrations.

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Area of Science:

  • Environmental Chemistry
  • Marine Biology
  • Geostatistics

Background:

  • Lavaca Bay, Texas, faces environmental concerns regarding pollutant accumulation.
  • Mercury and polycyclic aromatic hydrocarbons (PAHs) are significant environmental contaminants.
  • Eastern oysters (Crassostrea virginica) are important indicators of estuarine health.

Purpose of the Study:

  • To analyze the locational risk of increased mercury and PAH concentrations in Lavaca Bay sediments and oysters.
  • To compare the model fit of random effects versus a convoluted model incorporating spatial effects.
  • To create continuous surface maps of predicted pollutant values where the convoluted model showed a better fit.

Main Methods:

  • Chemical analysis of sediment and oyster samples from Lavaca Bay.
  • Application of Bayesian geo-statistical methods to evaluate pollutant concentrations.
  • Comparison of random effects models with convoluted models (random and spatial effects).
  • Generation of spatial risk maps for mercury and PAHs.

Main Results:

  • The convoluted model, including spatial effects, provided a better fit for mercury and most PAH concentrations in sediments and oysters.
  • Continuous surface maps revealed highest predicted concentrations of mercury and PAHs in areas near industrial facilities.
  • Locational risk for elevated pollutants was significantly correlated with proximity to industrial sources.

Conclusions:

  • Spatial factors significantly influence mercury and PAH distribution in Lavaca Bay sediments and oysters.
  • Industrial facilities are identified as key locational sources contributing to elevated pollutant levels.
  • The findings highlight the need for targeted environmental management strategies in proximity to industrial activities in Lavaca Bay.