Assessing mechanisms for microbial taxa and community dynamics using process models
Assessing mechanisms for microbial taxa and community dynamics using process models
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DOI：
10.1002/mlf2.12076
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发表时间：
2023-09-01
期刊：
影响因子：
--
通讯作者：
Zhou，Jizhong
中科院分区：
文献类型：
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作者：
Wu，Linwei;Yang，Yunfeng;Zhou，Jizhong
解开控制群落组成、结构、分布、功能和动态的组装机制是生态学的核心问题。虽然已经提出了各种方法来检查群落组装机制，但定量表征是具有挑战性的，特别是在微生物生态学中。本文提出了一种将消费者-资源模型与随机微分方程中的中性模型结合起来定量描述群落组装机制的新方法。利用针对微生物16S rRNA基因的厌氧生物反应器的时间序列数据，我们测试了三种生态模型的适用性：消费者-资源模型、中性模型和组合模型。我们的研究结果表明，模型的性能随着种群丰度和/或过程条件的变化而变化很大。在控制工艺条件的处理生物反应器中，该组合模型对丰富的生物类群表现最佳。而中性模型对稀有类群表现最好。进一步分析表明，移民率随类群丰度的增加而降低，类群间的竞争与系统发育密切相关，但仅在一定的系统发育距离内。对分类群和群落动态的确定性进行了定量评估，结果表明，处理生物反应器与随后的异常系统功能相一致，具有更大的确定性。鉴于其机制基础，这里开发的框架有望适用于微生物生态学之外的潜在应用。
Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer–resource model with a neutral model in stochastic differential equations. Using time‐series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer–resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.