Phylogenetic farming: Can evolutionary history predict crop rotation via the soil microbiome?
Phylogenetic farming: Can evolutionary history predict crop rotation via the soil microbiome?
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DOI：
10.1111/eva.12956
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发表时间：
2020-04-22
影响因子：
4.1
通讯作者：
Ingerslew, Kathryn S.
中科院分区：
文献类型：
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作者：
Kaplan, Ian;Bokulich, Nicholas A.;Ingerslew, Kathryn S.
农业长期以来一直采用系统发育规则，鼓励农民在共享土壤中轮换分类学上无关的植物。虽然这是可持续农业的核心原则，但奇怪的是，这一农场上的“经验法则”从未在科学框架中得到严格的检验。为了通过实验评估系统发育距离与作物表现之间的关系，我们使用了植物-土壤反馈方法，在为期两年的田间实验中测试了35种与番茄（Solanum lycopersicum）相关性不同的作物和杂草。我们使用细菌和真菌的群落分析来确定土壤微生物对作物生长表型差异的贡献程度。总体而言，番茄产量约为。15%，以前种植番茄的土壤中，然而，过去的物种水平上没有影响作物性能的系统发育距离。土壤微生物群落，另一方面，组成更接近植物的亲戚之间。随机森林回归预测log（10）番茄的系统发育距离具有中等精度（R-2 = .52），主要由鞘氨醇菌属中的细菌驱动。这些数据表明，除了避免同种，进化史有助于了解植物土壤反馈在农业领域，但是，微生物的遗产可以预测物种的身份和相关性。
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 log(10) phylogenetic distance to tomato with moderate accuracy (R-2 = .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.