4.8 Article

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework

Journal

ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 56, Issue 7, Pages 4231-4240

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.2c00224

Keywords

land-use regression; molecular microbial source tracking; surface water; sediment; river networks; animal feeding operations; septic systems

Funding

  1. National Institute of Environmental Health Sciences (NIEHS) [T32ES007018]
  2. Marquette University Innovation Grant
  3. NSF [1316318]

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Surface water monitoring and microbial source tracking are essential for identifying sources of fecal pollution. New framework can help identify spatial sources and their impact on human and bovine markers. Sediment samples may offer more time-integrated information compared to transient surface water.
Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovinedense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.

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