Institute of Environmental Sciences, Hebrew University, Rehovot, Israel.
Elife. 2023 Feb 28;12:e83398. doi: 10.7554/eLife.83398.
Microorganisms are found in diverse communities whose structure and function are determined by interspecific interactions. Just as single species seldom exist in isolation, communities as a whole are also constantly challenged and affected by external species. Though much work has been done on characterizing how individual species affect each other through pairwise interactions, the joint effects of multiple species on a single (focal) species remain underexplored. As such, it is still unclear how single-species effects combine to a community-level effect on a species of interest. To explore this relationship, we assayed thousands of communities of two, three, and four bacterial species, measuring the effect of single, pairs of, and trios of 61 affecting species on six different focal species. We found that when multiple species each have a negative effect on a focal species, their joint effect is typically not given by the sum of the effects of individual affecting species. Rather, they are dominated by the strongest individual-species effect. Therefore, while joint effects of multiple species are often non-additive, they can still be derived from the effects of individual species, making it plausible to map complex interaction networks based on pairwise measurements. This finding is important for understanding the fate of species introduced into an occupied environment and is relevant for applications in medicine and agriculture, such as probiotics and biocontrol agents, as well as for ecological questions surrounding migrating and invasive species.
微生物存在于多样化的群落中,其结构和功能取决于种间相互作用。就像单个物种很少孤立存在一样,整个群落也经常受到外部物种的挑战和影响。尽管已经有很多工作致力于描述单个物种如何通过两两相互作用来影响彼此,但对多种物种对单个(焦点)物种的共同影响仍研究不足。因此,目前尚不清楚单个物种的影响如何组合成对感兴趣物种的群落水平影响。为了探索这种关系,我们检测了两种、三种和四种细菌群落的数千个群落,测量了 61 种有影响的物种中单一、两两和三对物种对六种不同焦点物种的影响。我们发现,当多个物种对一个焦点物种都有负面影响时,它们的共同影响通常不是单个影响物种的影响之和。相反,它们主要由最强的单物种效应决定。因此,虽然多种物种的共同作用通常不是加性的,但它们仍然可以从单个物种的作用中推导出来,这使得基于两两测量来绘制复杂的相互作用网络成为可能。这一发现对于理解引入已被占据环境的物种的命运非常重要,并且与医学和农业中的应用有关,例如益生菌和生物防治剂,以及与迁移和入侵物种有关的生态问题。