Topological change of soil microbiota networks for forest resilience under global warming

IF 13.7 1区 生物学 Q1 BIOLOGY Physics of Life Reviews Pub Date : 2024-08-08 DOI:10.1016/j.plrev.2024.08.001
Huiying Gong , Hongxing Wang , Yu Wang , Shen Zhang , Xiang Liu , Jincan Che , Shuang Wu , Jie Wu , Xiaomei Sun , Shougong Zhang , Shing-Tung Yau , Rongling Wu
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Abstract

Forest management by thinning can mitigate the detrimental impact of increasing drought caused by global warming. Growing evidence shows that the soil microbiota can coordinate the dynamic relationship between forest functions and drought intensity, but how they function as a cohesive whole remains elusive. We outline a statistical topology model to chart the roadmap of how each microbe acts and interacts with every other microbe to shape the dynamic changes of microbial communities under forest management. To demonstrate its utility, we analyze a soil microbiota data collected from a two-way longitudinal factorial experiment involving three stand densities and three levels of rainfall over a growing season in artificial plantations of a forest tree – larix (Larix kaempferi). We reconstruct the most sophisticated soil microbiota networks that code maximally informative microbial interactions and trace their dynamic trajectories across time, space, and environmental signals. By integrating GLMY homology theory, we dissect the topological architecture of these so-called omnidirectional networks and identify key microbial interaction pathways that play a pivotal role in mediating the structure and function of soil microbial communities. The statistical topological model described provides a systems tool for studying how microbial community assembly alters its structure, function and evolution under climate change.

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土壤微生物群网络的拓扑变化促进全球变暖条件下的森林恢复能力
通过疏伐进行森林管理可以减轻全球变暖导致干旱加剧的不利影响。越来越多的证据表明,土壤微生物群可以协调森林功能与干旱强度之间的动态关系,但它们如何作为一个有凝聚力的整体发挥作用仍是一个未知数。我们概述了一个统计拓扑模型,以描绘每种微生物如何发挥作用并与其他微生物相互作用,从而形成森林管理下微生物群落动态变化的路线图。为了证明该模型的实用性,我们分析了从一个双向纵向因子实验中收集到的土壤微生物群数据,该实验涉及林木--拉里克(Larix kaempferi)人工种植园在一个生长季节中的三种林分密度和三种降雨水平。我们重建了最复杂的土壤微生物群网络,该网络编码了信息量最大的微生物相互作用,并追踪它们在不同时间、空间和环境信号下的动态轨迹。通过整合 GLMY 同源理论,我们剖析了这些所谓的全方位网络的拓扑结构,并确定了在介导土壤微生物群落的结构和功能方面发挥关键作用的关键微生物相互作用途径。所描述的统计拓扑模型为研究微生物群落如何在气候变化下改变其结构、功能和进化提供了一个系统工具。
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来源期刊
Physics of Life Reviews
Physics of Life Reviews 生物-生物物理
CiteScore
20.30
自引率
14.50%
发文量
52
审稿时长
8 days
期刊介绍: Physics of Life Reviews, published quarterly, is an international journal dedicated to review articles on the physics of living systems, complex phenomena in biological systems, and related fields including artificial life, robotics, mathematical bio-semiotics, and artificial intelligent systems. Serving as a unifying force across disciplines, the journal explores living systems comprehensively—from molecules to populations, genetics to mind, and artificial systems modeling these phenomena. Inviting reviews from actively engaged researchers, the journal seeks broad, critical, and accessible contributions that address recent progress and sometimes controversial accounts in the field.
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