Statistical Learning and Uncommon Soil Microbiota Explain Biogeochemical Responses after Wildfire.

ABSTRACT: Wildfires are a perennial event globally, and the biogeochemical underpinnings of soil responses at relevant spatial and temporal scales are unclear. Soil biogeochemical processes regulate plant growth and nutrient losses that affect water quality, yet the response of soil after variable intensity fire is difficult to explain and predict. To address this issue, we examined two wildfires in Colorado, United States, across the first and second postfire years and leveraged statistical learning (SL) to predict and explain biogeochemical responses. We found that SL predicts biogeochemical responses in soil after wildfire with surprising accuracy. Of the 13 biogeochemical analytes analyzed in this study, 9 are best explained with a hybrid microbiome + biogeochemical SL model. Biogeochemical-only

SUBMITTER: Honeyman AS 

PROVIDER: S-EPMC9275219 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature