Quantitative Life Sciences section, The Abdus Salam International Centre for Theoretical Physics (ICTP), Trieste, Italy.
PLoS Comput Biol. 2022 Apr 1;18(4):e1010043. doi: 10.1371/journal.pcbi.1010043. eCollection 2022 Apr.
The large taxonomic variability of microbial community composition is a consequence of the combination of environmental variability, mediated through ecological interactions, and stochasticity. Most of the analysis aiming to infer the biological factors determining this difference in community structure start by quantifying how much communities are similar in their composition, trough beta-diversity metrics. The central role that these metrics play in microbial ecology does not parallel with a quantitative understanding of their relationships and statistical properties. In particular, we lack a framework that reproduces the empirical statistical properties of beta-diversity metrics. Here we take a macroecological approach and introduce a model to reproduce the statistical properties of community similarity. The model is based on the statistical properties of individual communities and on a single tunable parameter, the correlation of species' carrying capacities across communities, which sets the difference of two communities. The model reproduces quantitatively the empirical values of several commonly-used beta-diversity metrics, as well as the relationships between them. In particular, this modeling framework naturally reproduces the negative correlation between overlap and dissimilarity, which has been observed in both empirical and experimental communities and previously related to the existence of universal features of community dynamics. In this framework, such correlation naturally emerges due to the effect of random sampling.
微生物群落组成的大分类学可变性是环境可变性通过生态相互作用以及随机性进行介导的结果。大多数旨在推断决定群落结构差异的生物因素的分析，首先通过β多样性指标来量化群落组成的相似程度。这些指标在微生物生态学中的核心作用与对其关系和统计特性的定量理解并不匹配。具体而言，我们缺乏一个能够再现β多样性指标经验统计特性的框架。在这里，我们采用宏观生态学的方法，引入了一个模型来再现群落相似性的统计特性。该模型基于单个群落的统计特性和一个可调参数（跨群落物种承载能力的相关性），该参数设定了两个群落之间的差异。该模型定量再现了几个常用β多样性指标的经验值，以及它们之间的关系。具体来说，这种建模框架自然再现了在经验和实验群落中观察到的重叠和差异性之间的负相关关系，先前已经将这种关系与群落动态的普遍特征联系起来。在这种框架下，由于随机抽样的影响，这种相关性自然出现。
