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1 × 1 km maps of abundances of eight enzyme functional classes for soil C, N, and P cycling across the CONUS

Dataset ·
 [1];  [2]
  1. Department of Hydrology and Atmospheric Science, the University of Arizona
  2. Department of Hydrology and Atmospheric Sciences, the University of Arizona
This dataset includes eight 1 × 1 km maps of the abundances of eight enzyme functional classes (EFC) for soil C, N, and P cycling across the CONUS. These mappings are predicted by the machine learning model trained using metagenomics and the corresponding environmental data. This item corresponds to our article: Fan, C., Song, Y., Mishra, U., Gautam, S., & Mayes, M. A. (2025). Harnessing the Power of Machine Learning and Omics to Identify Environmental Regulation on Microbial Functional Composition for Soil C, N, and P Cycling. Journal of Geophysical Research: Biogeosciences, 130(10).
Research Organization:
Arizona Board of Regents, The University of Arizona
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Earth & Environmental Systems Science (EESS)
DOE Contract Number:
SC0025551
OSTI ID:
3005541
Country of Publication:
United States
Language:
English

References (1)


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