Seasonal variation in near-surface seasonally thawed active layer and permafrost soil microbial communities

Abstract Understanding how soil microbes respond to permafrost thaw is critical to predicting the implications of climate change for soil processes. However, our knowledge of microbial responses to warming is mainly based on laboratory thaw experiments, and field sampling in warmer months when sites...

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Bibliographic Details
Published in:Environmental Research Letters
Main Authors: Baker, Christopher C M, Barker, Amanda J, Douglas, Thomas A, Doherty, Stacey J, Barbato, Robyn A
Other Authors: U.S. Department of Defense
Format: Article in Journal/Newspaper
Language:unknown
Published: IOP Publishing 2023
Subjects:
Online Access:http://dx.doi.org/10.1088/1748-9326/acc542
https://iopscience.iop.org/article/10.1088/1748-9326/acc542
https://iopscience.iop.org/article/10.1088/1748-9326/acc542/pdf
Description
Summary:Abstract Understanding how soil microbes respond to permafrost thaw is critical to predicting the implications of climate change for soil processes. However, our knowledge of microbial responses to warming is mainly based on laboratory thaw experiments, and field sampling in warmer months when sites are more accessible. In this study, we sampled a depth profile through seasonally thawed active layer and permafrost in the Imnavait Creek Watershed, Alaska, USA over the growing season from summer to late fall. Amplicon sequencing showed that bacterial and fungal communities differed in composition across both sampling depths and sampling months. Surface communities were most variable while those from the deepest samples, which remained frozen throughout our sampling period, showed little to no variation over time. However, community variation was not explained by trace metal concentrations, soil nutrient content, pH, or soil condition (frozen/thawed), except insofar as those measurements were correlated with depth. Our results highlight the importance of collecting samples at multiple times throughout the year to capture temporal variation, and suggest that data from across the annual freeze-thaw cycle might help predict microbial responses to permafrost thaw.