Articles | Volume 8, issue 1
SOIL, 8, 223–235, 2022
https://doi.org/10.5194/soil-8-223-2022
SOIL, 8, 223–235, 2022
https://doi.org/10.5194/soil-8-223-2022
Original research article
25 Mar 2022
Original research article | 25 Mar 2022

Estimating soil fungal abundance and diversity at a macroecological scale with deep learning spectrotransfer functions

Yuanyuan Yang et al.

Data sets

Soil visible–near infrared (vis–NIR) spectra for the Biomes of Australian Soil Environments (BASE) soil microbial diversity database A. Bissett and R. Viscarra Rossel https://doi.org/10.5281/zenodo.6265730

Biomes of Australian Soil Environments (BASE) BioPlatforms Australia https://doi.org/10.4227/71/561c9bc670099

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Short summary
We present a new method to estimate the relative abundance of the dominant phyla and diversity of fungi in Australian soil. It uses state-of-the-art machine learning with publicly available data on soil and environmental proxies for edaphic, climatic, biotic and topographic factors, and visible–near infrared wavelengths. The estimates could serve to supplement the more expensive molecular approaches towards a better understanding of soil fungal abundance and diversity in agronomy and ecology.