Soil bacterial abundance and diversity better explained and predicted with spectro-transfer functions

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Yang, Yuanyuan; Viscarra Rossel, Raphael; Li, Shuo; Bissett, Andrew; Lee, Juhwan; Shi, Zhou; Behrens, Thorsten; Court, Leon


2019-02-01


Journal Article


Soil Biology and Biochemistry


129


29-38


Soil bacteria play a critical role in the functioning of ecosystems but are challenging to investigate. Using a state-factor model framework, we developed spectro-transfer functions with a set of readily available proxies that represent the edaphic, climatic, biotic and topographic factors in the model. The spectro-transfer functions were used to understand better and to predict the abundance of 10 dominant phyla and bacterial diversities in Australian soil, the latter expressed by the Chao and Shannon indices. The proxies included soil properties, environmental variables, and visible{near infrared (vis-NIR) wavelengths. Our models explained 43{73% variance in bacterial phyla abundance and diversity. The vis-NIR wavelengths, which represent the organic and mineral components of soil, were prominent drivers of abundance and diversity in the models, as were the Prescott index (PI), potential evapotranspiration (PET), and soil nutrients. We validated the spectro-transfer functions externally and show that: they could accurately predict the bacterial phyla Acidobacteria, and Actinobacteria (R2 > 0.7), other dominant phyla and the Chao and Shannon diversities were well predicted (R2 > 0.5), and the prediction of Firmicutes was relatively weak. The visible{NIR wavelengths markedly improved the explanatory power of the models and their predictability.


Elsevier


Biological Sciences not elsewhere classified ; Soil Biology ; Soil Sciences not elsewhere classified


https://doi.org/10.1016/j.soilbio.2018.11.005


EP184119


Journal article - Refereed


English


Yang, Yuanyuan; Viscarra Rossel, Raphael; Li, Shuo; Bissett, Andrew; Lee, Juhwan; Shi, Zhou; Behrens, Thorsten; Court, Leon. Soil bacterial abundance and diversity better explained and predicted with spectro-transfer functions. Soil Biology and Biochemistry. 2019; 129:29-38.https://doi.org/10.1016/j.soilbio.2018.11.005



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