Rhizosphere provides a habitat for various microorganisms in agricultural ecosystems, and complex plant-microbe interactions play a vital role in disease inhibition, decomposition rates of organic materials, and resistance to abiotic stress (Cheng, 2009; Bulgarelli et al., 2013; Reinhold-Hurek et al., 2015). The biogeographic distribution of soil bacteria has been extensively explored in natural and agricultural ecosystems (Carlson et al., 2012; Fierer and Jackson, 2006; Gumiere et al., 2016; Xue et al., 2021). The rhizosphere is a biological hotspot whose biogeographic patterns, community composition, and structure are different from those of bulk soil (Zhang et al., 2018). However, only a few studies have investigated the biogeographic patterns of rhizosphere-associated bacterial communities (Fan et al., 2017).
It is common knowledge that environmental filtering, as a critical determinant of species distribution patterns and abundance, inevitably leads to a reduction in trait value range and an increase in niche overlap (Yi et al., 2019). Archaeal taxa between crops in different habitats demonstrate diverse responses to environmental changes (Jiao et al., 2019). However, the response thresholds of rhizosphere-associated bacterial communities to environmental changes have not been reported in agricultural fields. Environmental thresholds of species represent the change in taxon distribution along the spatial or temporal environmental gradient (Baker and King, 2010). Environmental thresholds of fungi in maize and rice soils across eastern China have been estimated using the accumulated values of change points for all the species in a given community (Zhang et al., 2021). Available environmental thresholds rarely reflect the occurrence, richness, and directionality of species-level responses, and very few studies have focused on large-scale standardized datasets of natural locations (van der Linde et al., 2018). However, the environmental thresholds for rhizosphere-associated bacteria at the species level must be identified in agricultural fields, thereby assisting calculation of the responses of different crop genotypes to environmental change. Whether foxtail millet (Setaria italica L.), proso millet (Panicum miliaceum L.), and sorghum (Sorghum bicolor L.) appear to have analogous thresholds for rhizosphere-associated bacterial community changes across environmental gradients is poorly understood.
Biogeography is the subject of biological distribution patterns over temporal and spatial scales (Hanson et al., 2012). Disentangling the fundamental mechanisms and ecological processes governing the diversity and assembly of microbial communities is a critical goal in microbial ecology (Nemergut et al., 2013; Zhou and Ning, 2017), which would help to better predict the response of the ecosystem to environmental change. Several studies have confirmed the biogeographic patterns of microbial communities in a wide range of habitats (Nuccio et al., 2016; Wang et al., 2017; Chen et al., 2019) at regional (Griffiths et al., 2011; Fan et al., 2017; Jiao et al., 2020), continental (Fierer and Jackson, 2006; Lauber et al., 2009) and global scales (Tedersoo et al., 2012; Delgado-Baquerizo et al., 2018). Currently, the debate on the relative quantitative contribution of deterministic (e.g., homogeneous selection) and stochastic (e.g., dispersal limitation) processes to microbial community assembly is topical (Jiao and Lu, 2019; Aguilar and Sommaruga, 2020). Deterministic processes are mainly based on the concept of the ecological niche and emphasize the major role of environmental selection imposed by adversity factors in microbial community assembly (Stegen et al., 2013; Wang et al., 2013). Conversely, stochastic processes are related to neutral theory, which holds that all organisms have the same ecological characteristics and demonstrates that community structure is largely dominated by the history of stochastic events such as death, random birth, dispersal, extinction, or speciation (Chase and Myers, 2011). Meanwhile, the distance-decay relationship (DDR) is also a biogeographic pattern, which is considered the best-documented basic law of community ecology (Nekola and White, 1999; Horner-Devine et al., 2004). It is well known that both deterministic and stochastic processes affect DDR (Hanson et al., 2012; Wang et al., 2017), but the relative contributions of both processes vary with habitats (Wang et al., 2013). When investigating microbial communities on large spatial scales, species sorting and dispersal limitation are deterministic and stochastic processes, respectively, affecting DDR (Hanson et al., 2012; Wu et al., 2018). The balance between deterministic and stochastic processes is regulated by environmental factors. For example, the variation in soil available sulfur could shift from the relative contribution of deterministic processes to the stochasticity of fungal communities (Jiao and Lu, 2020). Acidic and alkaline soils cause deterministic processes in soil bacterial communities, whereas neutral pH contributes to stochastic processes during pedogenic processes (Tripathi et al., 2018). Currently, it is still unclear how the relative contribution of stochasticity versus determinism will regulate the biogeographic patterns and what are the main environmental factors governing the dominance of rhizosphere-associated bacterial community assembly processes among three minor grain crop fields.
Foxtail millet, proso millet, and sorghum are one of the traditional minor grain crops with drought-tolerant crops in northern China, making it possible to sample in a wide range of geographical locations and environmental factors. Meanwhile, the development of broomcorn millet industry plays an irreplaceable role in the adjustment of agricultural structure in arid and semi-arid areas of northern China. In this study, We addressed these questions using high-throughput 16S ribosomal RNA (rRNA) gene Illumina sequencing of rhizosphere bacteria along with nine environmental variables in adjacent pairs of foxtail millet, proso millet, and sorghum-cultivated fields across northern China. We attempted to examine the following hypotheses: (i) rhizosphere-associated bacteria in the three minor grain crops exhibit different biogeographic patterns, (ii) environmental thresholds and phylogenetic signals are different among the three minor grain crops, and (iii) relative contributions of community assembly processes vary among the three minor grain crops. Our findings could improve the understanding of the generation and maintenance of rhizosphere bacterial diversity, and facilitate the prediction of bacterial responses to global change in agricultural ecosystems.