Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Bacteroides Abundance in River Sediments

Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the so...

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Bibliographic Details
Published in:Environmental science & technology 2021-08, Vol.55 (15), p.10451-10461
Main Authors: Wiesner-Friedman, Corinne, Beattie, Rachelle E, Stewart, Jill R, Hristova, Krassimira R, Serre, Marc L
Format: Article
Language:English
Subjects:
Abundance
Antibiotic resistance
Antibiotics
Bacteroides
Contaminants in Aquatic and Terrestrial Environments
Contamination
Decay
Ecological effects
Fluvial sediments
Hauling
Health risks
Land use
Manures
Markers
Microbial pollution
Microorganisms
Model testing
Pollution sources
Regression analysis
Relative abundance
River beds
Rivers
rRNA 16S
Sediment pollution
Sediment samplers
Sediments
Statistical analysis
Statistical methods
Water pollution
Water quality
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Summary:Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.e., hauling, decay overland, and downstream). We introduce the microbial Find, Inform, and Test (FIT) framework, which expands previous LUR approaches and develops novel spatial predictor models to characterize the transported contributions. We applied FIT to characterize the sources of BoBac, a ruminant Bacteroides MST marker, quantified in riverbed sediment samples from Kewaunee County, Wisconsin. A 1 standard deviation increase in contributions from land-applied manure hauled from animal feeding operations (AFOs) was associated with a 77% (p-value
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.1c01602