植物自然拥有不同的微生物群,可以极大地影响它们的健康和生产力。然而,目前尚不清楚真菌微生物组的多样性,尤其是在叶圈,影响微生物间的相互作用以及随之而来的对植物生产力的非加性效应。结合操纵实验,字段集合,培养,微生物组测序,和合成财团,我们首次通过实验测试了叶面真菌群落多样性如何影响植物生产力。我们用32个低或高多样性的叶球聚生体或单个真菌分类群接种了牵牛花(IpomoeahederifoliaL.),并测量了对植物生产力和分配的影响。我们发现:(1)非加性效应普遍存在,其中56%的真菌聚生体协同或拮抗相互作用以影响植物生产力,包括一些能够产生急性协同作用的财团(例如,生产率提高>1000%,高于累加预期),(2)“共生真菌”之间的相互作用是不同群体中这种非可加性的原因,(3)协同作用大约是拮抗作用的四倍,(4)真菌多样性影响非可加性的大小,但不影响频率或方向,(5)多样性影响植物性能的非线性,在低多样性处理中表现最高。这些发现强调了在结合微生物间相互作用和非加性结果的框架下解释植物-微生物组相互作用以理解自然复杂性的重要性。
Plants naturally harbor diverse microbiomes that can dramatically impact their health and productivity. However, it remains unclear how fungal microbiome diversity, especially in the phyllosphere, impacts intermicrobial interactions and consequent nonadditive effects on plant productivity. Combining manipulative experiments, field collections, culturing, microbiome sequencing, and synthetic consortia, we experimentally tested for the first time how foliar fungal community diversity impacts plant productivity. We inoculated morning glories (Ipomoea hederifolia L.) with 32 phyllosphere consortia of either low or high diversity or with single fungal taxa, and measured effects on plant productivity and allocation. We found the following: (1) nonadditive effects were pervasive with 56% of fungal consortia interacting synergistically or antagonistically to impact plant productivity, including some consortia capable of generating acute synergism (e.g. > 1000% increase in productivity above the additive expectation), (2) interactions among \'commensal\' fungi were responsible for this nonadditivity in diverse consortia, (3) synergistic interactions were approximately four times stronger than antagonistic effects, (4) fungal diversity affected the magnitude but not frequency or direction of nonadditivity, and (5) diversity affected plant performance nonlinearly with the highest performance in low-diversity treatments. These findings highlight the importance of interpreting plant-microbiome interactions under a framework that incorporates intermicrobial interactions and nonadditive outcomes to understand natural complexity.