Snowmelt induced hydrologic perturbations drive dynamic microbiological and geochemical behaviors across a shallow riparian aquifer

• Main Authors: Robert eDanczak, Steven eYabusaki, Kenneth eWilliams, Yilin eFang, Chad eHobson, Michael J Wilkins
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2016-05-01
• Series: Frontiers in Earth Science
• Subjects: Fermentation; aquifer; candidate phyla; reactive transport modeling; RIFLE
• Online Access: http://journal.frontiersin.org/Journal/10.3389/feart.2016.00057/full

Shallow riparian aquifers represent hotspots of biogeochemical activity in the arid western US. While these environments provide extensive ecosystem services, little is known of how natural environmental perturbations influence subsurface microbial communities and associated biogeochemical processes. Over a six-month period we tracked the annual snowmelt-driven incursion of groundwater into the vadose zone of an aquifer adjacent to the Colorado River, leading to increased dissolved oxygen (DO) concentrations in the normally suboxic saturated zone. Strong biogeochemical heterogeneity was measured across the site, with abiotic reactions between DO and sulfide minerals driving rapid DO consumption and mobilization of redox active species in reduced aquifer regions. Conversely, extensive DO increases were detected in less reduced sediments. 16S rRNA gene surveys tracked microbial community composition within the aquifer, revealing strong correlations between increases in putative oxygen-utilizing chemolithoautotrophs and heterotrophs and rising DO concentrations. The gradual return to suboxic aquifer conditions favored increasing abundances of 16S rRNA sequences matching members of the Microgenomates (OP11) and Parcubacteria (OD1) that have been strongly implicated in fermentative processes. Microbial community stability measurements indicated that deeper aquifer locations were relatively less affected by geochemical perturbations, while communities in shallower locations exhibited the greatest change. Reactive transport modeling of the geochemical and microbiological results supported field observations, suggesting that a predictive framework can be applied to develop a greater understanding of such environments.