School of Grassland Science, Beijing Forestry University, Beijing 100083, China; Beijing Institute of Mathematical Sciences and Applications, Beijing 101408, China.
State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China.
Phys Life Rev. 2024 Sep;50:228-251. doi: 10.1016/j.plrev.2024.08.001. Epub 2024 Aug 8.
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.
森林抚育间伐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，土壤微生物群落可以协调森林功能和干旱强度之间的动态关系，但它们如何作为一个整体发挥作用仍不清楚。我们概述了一个统计拓扑模型，以阐明每个微生物如何与其他微生物相互作用，从而塑造森林管理下微生物群落的动态变化。为了展示其效用，我们分析了从一项涉及三个林分密度和三个降雨水平的双向纵向析因实验中收集的土壤微生物群落数据，该实验在人工种植的林树——落叶松（Larix kaempferi）中进行了一个生长季节。我们重建了最复杂的土壤微生物群落网络，这些网络编码了最大信息量的微生物相互作用，并追踪了它们在时间、空间和环境信号上的动态轨迹。通过整合 GLMY 同源理论，我们剖析了这些所谓的全向网络的拓扑结构，并确定了在调节土壤微生物群落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组装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。
