Rhizosphere-associated bacterial network structure and spatial distribution differ significantly from bulk soil in wheat crop fields

Abstract

The spatial distribution of bacteria in bulk soil has been well studied, but little is known about the bacterial biogeography in the rhizosphere of crops. Here, we investigated bacterial distribution in bulk soil, loosely-and tightly-bound soils, from wheat fields distributed across 800,000 km 2 of the North China Plain. Bacterial community composition differed dramatically among bulk and rhizospheric soils, and bacterial diversity decreased with the root proximity. Soil pH correlated with bacterial community composition and diversity in three compartments. Bacterial community in tightly bound soil formed a hub-based network topology with higher transitivity and greater number of central nodes compared with loosely bound and bulk soils, potentially as a result of more direct ecological interactions between the members of the tightly bound soil compartment. Bulk and rhizospheric soils maintained similar compositional distance decay patterns (with equal decay rates), but distinct phylogenetic distance decay patterns (with steeper slope of tightly bound soil). Geographical distance described a relatively greater proportion of bacterial spatial distribution in tightly bound soil, compared with loosely bound soil and bulk soil. Deterministic processes dominated the assemblage of bacterial communities in all soil compartments, while phylogenetic clustering was weaker in tightly bound soil. Taken together, our results suggest distinct bacterial network structure and distribution patterns among bulk soil, loosely bound soil and tightly bound rhizospheric soil, which could possibly result in potential functional differentiation.

Interpreting distance‐decay pattern of soil bacteria via quantifying the assembly processes at multiple spatial scales

“…This agreed with the result of the Mantel test, that soil pH had the biggest correlation of bacterial community composition ( r = 0.64, p < 0.001 in Appendix Table A2). Many studies have identified soil pH as the most important variable influencing bacterial community in both natural and agricultural ecosystems (Fan et al, ; Fierer & Jackson, ; Liu et al, ; Shen et al, ; Sun, Zhang, Guo, Wang, & Chu, ; Tripathi et al, ). The reason for this could be that bacterial species or strains are capable of optimal growth only within a narrow pH range (Lauber, Hamady, Knight, & Fierer, ; Ramirez, Craine, & Fierer, ), such that changes in environmental pH would directly deterministically select for species with different pH optima.…”

“…In other words, ecological communities that are geographically close to one another tend to have more similar species composition than geologically distant ones. Many studies have confirmed the existence of distance‐decay pattern in soil microbial communities (Chemidlin et al, ; Chu et al, ; Durrer et al, ; Fan et al, ; Martiny, Eisen, Penn, Allison, & Horner‐Devine, ; Shi et al, ; Terrat et al, ; Tuomisto, Ruokolainen, & Yli‐Halla, ; Wang, Lu, et al, ; Yang et al, ; Zhang et al, ). Such studies have also disentangled the contribution of habitat heterogeneity and biogeographic differences to distance‐decay patterns (Fan et al, ; Langenheder & Ragnarsson, ; Ramette & Tiedje, ; Ranjard et al, ; Shi et al, ; Zhang et al, ).…”

“…Many studies have confirmed the existence of distance‐decay pattern in soil microbial communities (Chemidlin et al, ; Chu et al, ; Durrer et al, ; Fan et al, ; Martiny, Eisen, Penn, Allison, & Horner‐Devine, ; Shi et al, ; Terrat et al, ; Tuomisto, Ruokolainen, & Yli‐Halla, ; Wang, Lu, et al, ; Yang et al, ; Zhang et al, ). Such studies have also disentangled the contribution of habitat heterogeneity and biogeographic differences to distance‐decay patterns (Fan et al, ; Langenheder & Ragnarsson, ; Ramette & Tiedje, ; Ranjard et al, ; Shi et al, ; Zhang et al, ). Recently, the development of methods for understanding community assembly processes has enabled us to explore the underlying processes that result in the observed microbial biogeographic patterns (Hanson, Fuhrman, Horner‐Devine, & Martiny, ; Shi et al, ; Stegen et al, ; Stegen, Lin, Fredrickson, & Konopka, ; Stegen, Lin, Konopka, & Fredrickson, ; Wang, Li, et al, ).…”

Fungal community demonstrates stronger dispersal limitation and less network connectivity than bacterial community in sediments along a large river

“…Bacteria and fungi, two major microbial communities, are vastly different in regard to their morphological traits, growth rates, environmental sensitivities and substrate utilizations . Numerous studies on soil ecosystems have demonstrated that both bacterial and fungal communities have responded to ecological mechanisms that drive compositional variations Fan et al, 2017). Until recently, dispersal limitation and environmental selection have been widely accepted as two of the principal forces driving microbial distribution (Martiny et al, 2006;Chu et al, 2016;Zhang et al, 2017;Zhang et al, 2018b), and the relative importance of these factors depends on spatial scales, habitat types and taxon traits (Hanson et al, 2012;Wu et al, 2013;Wang et al, 2017b).…”

“…Interactions among different microbial species through mutualism, parasitism, competition or predation can cause complex co-occurrence networks (Faust and Raes, 2012). Network analysis has been increasingly used as a powerful analytical approach to explore the results of a set of interactions among microorganisms and biological complexity in microbial ecology in oceans (Aylward et al, 2015), soils (Fan et al, 2017;Xiao et al, 2018) and lakes (Kara et al, 2013). The topological network characteristics such as node number, edge number and clustering coefficient have been used to define the importance of species interactions in affecting community stability and ecosystem function (Cardona et al, 2016;Deng et al, 2016).…”