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Soil salinization accelerates microbiome stabilization in iterative selections for plant performance
Author(s) -
King William L.,
Kaminsky Laura M.,
Gannett Maria,
Thompson Grant L.,
KaoKniffin Jenny,
Bell Terrence H.
Publication year - 2022
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.17774
Subject(s) - microbiome , biology , soil salinity , biomass (ecology) , selection (genetic algorithm) , brassica rapa , soil water , ecology , agronomy , brassica , genetics , artificial intelligence , computer science
Summary Climate change‐related soil salinization increases plant stress and decreases productivity. Soil microorganisms are thought to reduce salt stress through multiple mechanisms, so diverse assemblages could improve plant growth under such conditions. Previous studies have shown that microbiome selection can promote desired plant phenotypes, but with high variability. We hypothesized that microbiome selection would be more consistent in saline soils by increasing potential benefits to the plants. In both salt‐amended and untreated soils, we transferred forward Brassica rapa root microbiomes (from high‐biomass or randomly selected pots) across six planting generations while assessing bacterial (16S rRNA) and fungal (ITS) composition in detail. Uniquely, we included an add‐back control (re‐adding initial frozen soil microbiome) as a within‐generation reference for microbiome and plant phenotype selection. We observed inconsistent effects of microbiome selection on plant biomass across generations, but microbial composition consistently diverged from the add‐back control. Although salt amendment strongly impacted microbial composition, it did not increase the predictability of microbiome effects on plant phenotype, but it did increase the rate at which microbiome selection plateaued. These data highlight a disconnect in the trajectories of microbiomes and plant phenotypes during microbiome selection, emphasizing the role of standard controls to explain microbiome selection outcomes.