Microbial eDNA Predicts Hydrologic Recession Dynamics
Abstract
Both the quantity and quality of water in streams is influenced by the flowpaths of water as it moves through the subsurface. Hydrologic flowpaths are interconnected with streamflow recession dynamics as highly nonlinear recessions are indicative of the drainage front rapidly receding towards the hydrologic divide. However, quantifying these flow paths remains a challenge with geochemical or isotope-based tracer methods when underlying geologic or temporal structures have limited variation. As DNA sequencing has advanced rapidly, it has been observed that microbial communities are also affected by changes in hydrologic dynamics and thus might indicate flow paths. Currently, the predictive capacity of genomic information about hydrologic flowpaths is unknown. Here we show that Amplicon Sequence Variants (ASVs) and the microbial metagenome is predictive of various summertime baseflow recession dynamics in the Pacific Northwest of the United States. Evaluation of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with genes measured during recessions demonstrates that multiple plant specific genes such as zeatin biosynthesis show elevated presence during highly nonlinear recession periods (p =0.051). Overall, we find the phylogenetic annotated metagenome is able to accuracy predict bi-weekly mean log discharge (R2 = 0.79), sample date discharge (R2 = 0.22) and recession non-linearity (R2 = 0.66). By linking microbial metabolic pathway profiles to hydrologic behavior, we identify potential biological indicators of watershed recession dynamics and the pathways that water flows through in the subsurface. These findings offer a promising approach for integrating microbial ecology with hydrologic modeling, advancing our understanding of how water drains from catchments.
Fields of Study & Subjects
Groundwater and Isotope Geochemistry
Microbial Community Ecology and Physiology
Hydrology and Watershed Management Studies
Publication details
- Journal / source
- EGU General Assembly Conference Abstracts
- Publication date
- 14 March 2026
- Language
- EN