The streamwater microbiome encodes hydrologic data across scales.

Area of Science:

• Environmental microbiology
• Hydrology
• Biogeochemistry

Background:

• Hydrology faces unanswered questions due to limited data.
• Microbial communities offer novel environmental data, reflecting biotic and abiotic factors.
• These microscale communities can indicate macroscale hydrologic conditions.

Purpose of the Study:

• To assess streamwater microbial communities' ability to encode catchment hydrology information across scales.
• To quantify the information shared between microbial taxa and hydrologic metrics.

Main Methods:

• Analyzed 64 summer streamwater DNA samples from Oregon river basins.
• Applied information theory to quantify microbial taxa's information content regarding hydrologic metrics.
• Characterized microbial communities using 16S gene amplicon sequence abundance.

Main Results:

• 9.6% of microbial taxa shared information with hydrologic metrics, reducing uncertainty by a median of 15.6%.
• All assessed hydrologic metrics, including discharge and flow durations, were encoded within microbial communities.
• Summer microbial taxa showed the strongest correlation with winter mean flows.

Conclusions:

• Quantifiable relationships exist between streamwater microbial taxa and hydrologic metrics at various scales.
• Microbial communities integrate multiple drivers, providing a rich source of hydrologic information.
• This research offers novel insights into unresolved hydrologic questions using microbial data.