Articles | Volume 8, issue 1
https://doi.org/10.5194/soil-8-223-2022
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, Zefang Shen, Andrew Bissett, and Raphael A. Viscarra Rossel

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Latest update: 22 Apr 2024
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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.