Interdomain ecological networks between plants and microbes. (24th September 2019)

• Record Type: Journal Article
• Authors: Feng, Kai; Zhang, Yuguang; He, Zhili; Ning, Daliang; Deng, Ye
• Is Part Of: Molecular ecology resources. Volume 19:Number 6(2019:Nov.)
• Page Start: 1565
• Page End: 1577
• Publication Date: 2019-09-24
• Subjects: above–belowground ecology -- interdomain ecological networks -- network analysis -- plant–microbe association -- topological structure; Molecular ecology -- Periodicals; 572.8
• DOI: 10.1111/1755-0998.13081
• Languages: English
• ISSNs: 1755-098X

Abstract

Abstract: While macroscopic interkingdom relationships have been intensively investigated in various ecosystems, the above–belowground ecology in natural ecosystems has been poorly understood, especially for the plant–microbe associations at a regional scale. In this study, we proposed a workflow to construct interdomain ecological networks (IDEN) between multiple plants and various microbes (bacteria and archaea in this study). Across 30 latitudinal forests in China, the regional IDEN showed particular topological features, including high connectance, nested structure, asymmetric specialization and modularity. Also, plant species exhibited strong preference to specific microbial groups, and the observed network was significantly different from randomly rewired networks. Network module analysis indicated that a majority of microbes associated with plants within modules rather than across modules, suggesting specialized associations between plants and microorganisms. Consistent plant–microbe associations were captured via IDENs constructed within individual forest locations, which reinforced the validity of IDEN analysis. In addition, the plant–forest link distribution showed the geographical distribution of plants had higher endemicity than that of microorganisms. With cautious experimental design and data processing, this study shows interdomain species associations between plants and microbes in natural forest ecosystems and provides new insights into our understanding of meta‐communities across different domain species.