R. Hogue

An Interpretable Machine Learning Approach to Ecologically Characterize Soil Carbon and Structure From Multi‐Kingdom Microbiome, Texture and Climate

This study evaluates the predictive power of multi‐kingdom microbiome data for three key soil functions: soil organic carbon stock, mean weight diameter and macroporosity and proposes shifting from static pedotransfer functions to a dynamic biotransfer framework that leverages multi‐kingdom omic signatures to monitor s...