Skip to main content
ARS Home » Midwest Area » Madison, Wisconsin » U.S. Dairy Forage Research Center » Environmentally Integrated Dairy Management Research » Research » Publications at this Location » Publication #415130

Research Project: Managing Nutrients and Assessing Pathogen Emission Risks for Sustainable Dairy Production Systems

Location: Environmentally Integrated Dairy Management Research

Title: Recharge drives microbial heterogeneity in a karst aquifer of the northern United States

Author
item Heffron, Joseph
item Cook, Rachel
item FIRNSTAHL, AARON - Us Geological Survey (USGS)
item STOKDYK, JOEL - Us Geological Survey (USGS)
item Burch, Tucker

Submitted to: Swiss Society of Microbiology
Publication Type: Abstract Only
Publication Acceptance Date: 6/25/2024
Publication Date: 8/29/2024
Citation: Heffron, J.A., Cook, R.M., Firnstahl, A.D., Stokdyk, J.P., Burch, T.R. 2024. Recharge drives microbial heterogeneity in a karst aquifer of the northern United States. Swiss Society of Microbiology. August 28 - 30, 2024.

Interpretive Summary:

Technical Abstract: Aims Despite the importance of subsurface microbial communities to groundwater quality, little is known about how land use and other surface influences impact groundwater microbes. Our study aimed to better understand the microbial diversity and dynamics within a karst aquifer used for private drinking water, yet subject to domestic and agricultural contamination. Methods Large-volume, dead-end ultrafiltration was used to collect water samples (n=138) from private wells in a rural region of the United States. Wells (n = 22 to 30) were randomly selected from a pool of participants in each of 5 sampling events over the course of one year. Following ultrafilter backwashing, concentration, and DNA extraction, samples was analyzed using 16S (V4) Illumina sequencing. Amplicon sequence variants (ASVs) were generated from the demultiplexed reads and decontaminated using pre-amplified sample dsDNA concentrations. To relate microbial community composition to environmental and land use factors, sample communities were clustered by Bray-Curtis dissimilarity using a DBSCAN algorithm. Cluster assignment was evaluated relative to land use, geology, groundwater recharge, pathogen and antibiotic resistance gene (ARG) occurrence, and microbial source tracking (MST) markers for human and bovine fecal contamination. Random forest classification was used to select the most important attributes for predicting microbial clusters. Logistic regression was used to select only significant variables from this subset of attributes. Results Groundwater communities from across the county were highly homogenous. Core taxa, defined as microbial orders appearing in over 95% of samples, included representatives of Patescibacteria, Proteobacteria, Firmicutes, Verrucomicrobiota, Crenarchaeota, Dependentiae, and Nanoarchaeota. The median sample relative abundance of these core taxa was 94%, though some samples included as little as 19% core taxa. Marked change in community composition was particularly observed during the January sampling event. Multiple attributes related to water infiltration from the surface (snowmelt, recharge, and precipitation) were associated with clustering. Conclusion Recharge and infiltration were the main source of microbial variation in an otherwise homogeneous aquifer. Well water primarily represents the planktonic subsurface community, which may be more variable than the attached community.