Phylogenetic farming: Can evolutionary history predict crop rotation via the soil microbiome?

Abstract Agriculture has long employed phylogenetic rules whereby farmers are encouraged to rotate taxonomically unrelated plants in shared soil. Although this forms a central tenet of sustainable agriculture, strangely, this on‐farm “rule of thumb” has never been rigorously tested in a scientific f...

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Bibliographic Details
Main Authors: Ian Kaplan, Nicholas A. Bokulich, J. Gregory Caporaso, Laramy S. Enders, Wadih Ghanem, Kathryn S. Ingerslew
Format: Article
Language:English
Published: Wiley 2020-09-01
Series:Evolutionary Applications
Subjects:
Online Access:https://doi.org/10.1111/eva.12956
Description
Summary:Abstract Agriculture has long employed phylogenetic rules whereby farmers are encouraged to rotate taxonomically unrelated plants in shared soil. Although this forms a central tenet of sustainable agriculture, strangely, this on‐farm “rule of thumb” has never been rigorously tested in a scientific framework. To experimentally evaluate the relationship between phylogenetic distance and crop performance, we used a plant–soil feedback approach whereby 35 crops and weeds varying in their relatedness to tomato (Solanum lycopersicum) were tested in a two‐year field experiment. We used community profiling of the bacteria and fungi to determine the extent to which soil microbes contribute to phenotypic differences in crop growth. Overall, tomato yield was ca. 15% lower in soil previously cultivated with tomato; yet, past the species level there was no effect of phylogenetic distance on crop performance. Soil microbial communities, on the other hand, were compositionally more similar between close plant relatives. Random forest regression predicted log10 phylogenetic distance to tomato with moderate accuracy (R2 = .52), primarily driven by bacteria in the genus Sphingobium. These data indicate that, beyond avoiding conspecifics, evolutionary history contributes little to understanding plant–soil feedbacks in agricultural fields; however, microbial legacies can be predicted by species identity and relatedness.
ISSN:1752-4571