The taxonomic composition of microbial communities can vary substantially across habitats and within the same habitat over time. Efforts to build quantitative and predictive models of microbial population dynamics are underway, but fundamental questions remain. How different are population dynamics in different environments? Do communities that share the same taxa also exhibit identical dynamics? In vitro communities can help establish baseline expectations that are critical towards resolving these questions in natural communities. Here, we applied a recently developed tool, Dissimilarity–Overlap Analysis (DOA), to a set of experimental in vitro communities that differed in nutrient composition. The Dissimilarity and Overlap of these communities are negatively correlated in replicate habitats, as one would expect if microbial population dynamics were on average strongly convergent (or “universal”) across these replicate habitats. However, the existence of such a negative correlation does not necessarily imply that population dynamics are always universal in all communities. Even in replicate, identical habitats, two different communities may contain the same set of taxa at different abundances in equilibrium. The formation of alternative states in community assembly is strongly associated with the presence of specific taxa in the communities. Our results benchmark DOA, providing support for some of its core assumptions, and suggest that communities sharing the same taxa and external abiotic factors generally (but not necessarily) have a negative correlation between Dissimilarity and Overlap.

随着时间的推移，微生物群落的分类组成在不同栖息地以及同一栖息地内可能会有很大差异。建立微生物种群动态的定量和预测模型的努力正在进行中，但基本问题仍然存在。不同环境中的种群动态有何不同？共享相同分类群的群落是否也表现出相同的动态？体外群落可以帮助建立基线期望，这对于解决自然群落中的这些问题至关重要。在这里，我们将最近开发的工具相异重叠分析（DOA）应用于一组营养成分不同的实验体外群落。这些群落的差异和重叠在复制栖息地中呈负相关，正如人们所期望的那样，如果微生物种群动态在这些复制栖息地中平均强烈收敛（或“普遍”）。然而，这种负相关性的存在并不一定意味着人口动态在所有社区中总是普遍存在的。即使在重复的、相同的栖息地中，两个不同的群落也可能包含相同的类群，但平衡丰度不同。群落组装中替代状态的形成与群落中特定类群的存在密切相关。我们的结果以 DOA 为基准，为其一些核心假设提供支持，并表明共享相同分类群和外部非生物因素的群落通常（但不一定）在相异性和重叠之间具有负相关性。