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Article

Investigating the Diversity and Influencing Factors of the Rhizosphere Bacterial Community Associated with Salicornia europaea L. Populations in Semi-arid Grassland

by
Hai Wang
1,
Liang Chun
1,
Lei Ji
1,
Risu Na
1,
Zhijun Wei
2 and
Wenjun Han
1,*
1
Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot 010010, China
2
College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China
*
Author to whom correspondence should be addressed.
Agriculture 2024, 14(7), 1018; https://doi.org/10.3390/agriculture14071018
Submission received: 10 April 2024 / Revised: 23 June 2024 / Accepted: 24 June 2024 / Published: 27 June 2024
(This article belongs to the Section Agricultural Soils)
Browse Figures
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Abstract

:
Salicornia europaea L. is a well-known model plant for studying the mechanism of salt tolerance. A substantial decline in the S. europaea population has been observed in the semi-arid steppe of the Mongolian Plateau. The relationship between environmental factors and its population dynamics in the grassland ecosystem remains inadequately investigated. Rhizosphere microbial communities, representing the most direct and influential biological factors affecting plant populations, have received limited research attention in the context of halophytes. Four density treatments of S. europaea (bare land—SEB, low density—SEL, medium density—SEM, and high density—SEH) in a single-factor randomized-block design with five replications were established to evaluate the relationship between rhizosphere soil bacterial communities and environmental factors. The results showed that as the density of S. europaea increased, the soil pH decreased, while available phosphorus increased. Rhizosphere soil bacterial communities associated with S. europaea populations in the saline-alkali wetland were dominated by Proteobacteria, Bacteroidota, Actinobacteria, Gemmatimonadota, and Halobacterota. Notably, the genera Antarcticibacterium, Wenzhouxiangella, BD2-11_terrestrial_groupBD2-11, Halomonas, and Natronorubrum were found to be particularly abundant. The Simpson index of the rhizosphere soil bacterial community in the S. europaea treatments was significantly higher than that in bare land. Soil pH and nitrate nitrogen were the primary environmental drivers of the rhizosphere bacterial community. Overall, the rhizosphere soil’s bacterial diversity in saline wetlands under a high-salt environment was not affected by the decrease in the S. europaea population. S. europaea plays an important role in shaping soil bacterial community structure through its influence on the surrounding soil environment. The cultivation of S. europaea is a phytoremediation strategy to improve soil salinization.

1. Introduction

Salicornia europaea L. stands out as one of the most salt-tolerant higher land plants globally [1,2]. The genus Salicornia, comprising approximately 25–30 species primarily distributed in temperate and subtropical regions of the Northern Hemisphere [3,4], represents a valuable source of salt-tolerance genes and a model system for investigating salt tolerance mechanisms in plants [5,6]. S. europaea exhibits promising economic potential and holds application prospects in various fields, including agriculture, food production, environmental restoration, and pharmaceuticals [7,8,9].
The halophytic pioneer species, S. europaea, is exhibiting a marked decline in abundance across its seven geographically isolated populations on the Mongolian Plateau [10]. Plant distribution patterns emerge from a complex interplay of ecological niche, interspecific competition, and environmental adaptation [11]. These spatial arrangements reflect not only plant locations but also resource utilization and population roles within the community [12,13]. Notably, these patterns exhibit strong scale dependence. At smaller scales, habitat factors such as soil salinity, pH, and moisture significantly influence the horizontal structure of plant communities [14]. However, studies on larger scales highlight broader environmental pressures. For example, a comprehensive satellite-based analysis revealed a dramatic decline in Mongolian Plateau lake numbers due to climate change and human activities, leading to significant grassland degradation in recent decades [15]. Soil characteristics, including physical and chemical properties, play a crucial role in regulating plant growth, development, and community structure by affecting nutrient uptake by plant roots [16]. Despite these observations, a complete theory for plant density regulation across various environmental factors remains elusive, highlighting the need for further research in this area.
The exist of S. europae affected the diversity and composition of soil microorganisms, especially the rhizosphere microorganisms. Rhizosphere microorganisms constitute a key driver of plant growth and development, exerting a direct and potent biological impact on plant populations. The rhizosphere, the soil zone influenced by plant roots, profoundly effects both plant productivity and microbial activity. Root exudates, rich in carbon sources, serve as substrates for a diverse microbial community. This microbial activity, in turn, shapes the rhizosphere microbiome composition and function, impacting soil biological characteristics like nutrient cycling and decomposition. These processes ultimately influence soil structure and fertility, creating a complex feedback loop between plants and the soil ecosystem [17,18]. Field investigations in arid plateau lake wetlands revealed that the rhizosphere soil surrounding S. europaea exhibited a significant enrichment of microbial diversity compared to non-rhizosphere soil [19]. These studies also highlight the importance of vegetation composition and environmental factors in shaping the soil bacterial community’s structure and biodiversity. Therefore, the soil microbiome exerts a critical influence on plant nutrition, growth, and stress tolerance by facilitating nutrient acquisition, modulating plant hormonal profiles, and fostering resilience to environmental perturbations [20,21].
Soil microbial communities are recognized as critical drivers of biogeochemical processes within the soil matrix [22,23,24]. Emerging evidence suggests these microorganisms act as a crucial bridge between plant and soil properties, with optimal plant growth contingent upon tailored modulation of soil microbial community adaptability and subsequent regulation of nutrient availability [25,26]. However, soil microbial communities exhibit a high degree of sensitivity to environmental perturbations, particularly in salinized grasslands [27]. Soil salinity stress can lead to declines in microbial abundance, metabolic activity, and ultimately, plant health [28,29]. Conversely, studies have documented the remarkable ability of soil microorganisms to adapt to saline environments [23]. For instance, the isolation and identification of salt-tolerant microbial strains from saline-alkali soils hold promise as novel biofertilizers for crop production [30,31]. Compared with fungi and archaea, soil bacteria are the most adaptable in extreme salinity environments, and their numbers dominate the soil microbial community [32]. Understanding the response mechanisms of soil microbial communities to long-term ecosystem restoration efforts is, therefore, crucial. Notably, knowledge gaps exist regarding rhizosphere nutrient cycling and the associated microbial communities of S. europaea within saline-alkali wetlands, highlighting the need for further exploration of the full potential of soil microorganisms within these ecosystems [33,34].
Previous studies mainly focused on the soil and saline-alkali bare land microbial communities associated with S. europaea populations within extremely arid salt lake environments. However, there is a paucity of information regarding the composition and diversity of the microbial community in soils associated with those declining populations. In this study, a field experiment was conducted to investigate the impact of S. europaea population decline on the rhizosphere bacterial community structure in saline-alkali wetlands of the Inner Mongolian steppe. Using high-throughput sequencing, we analyzed the soil bacterial community composition associated with S. europaea populations. The objectives of this study were to (1) examine how the decline of S. europaea alters rhizosphere bacterial community diversity and structure, and (2) elucidate the environmental factors affecting the rhizosphere microflora of typical wetlands.

2. Materials and Methods

2.1. Site Description

The study area is located in the typical steppe (N43°55′, E115°36′, and altitude of 1032 m) in Xilinhot, Inner Mongolia area of China, which is a salt lake within the core area of the Mongolian Plateau. This experimental region was characterized by a mid-temperate zone semi-arid continental climate with a −0.1 °C average annual temperature and a frost-free period of about 100 days. The long-term average annual precipitation was 350 mm, mostly concentrated in the period from June to September. The local soil type is saline-alkaline, characterized by high moisture content and elevated salt levels. Land salinization in the area primarily results from a declining water table, which is closely linked to high evaporation rates. The vegetation type is a salinized meadow with saline herbs and shrubs as the foundation species, and the main dominant species are S. europaea L., Suaeda salsa (L.) Pall., Kalidium cuspidatum (Ung.-Sternb.) Grubov, Nitraria sibirica Pall., Phragmites australis (Cav.) Trin. ex Steud, and Achnatherum splendens (Trin.) Nevski. The associated species are Saussurea salsa (Pall.) Spreng., Salsola passerina Bunge, and Limonium bicolor (Bunge) Kuntze.
Prior to the year 2000, the study area was utilized for grazing. Subsequently, the area was fenced to exclude grazing and promote ecological conservation (Figure 1). The number of S. europaea at the study site was influenced by both natural and anthropogenic factors. Natural factors, such as decreasing saline lake area and groundwater levels, can limit growth and survival. Additionally, anthropogenic activities, specifically the cutting and harvesting of salicornia by herders for livestock feed supplementation, directly reduce population size.

2.2. Experiment Design and Sample Collection

A single-factor randomized-block design with four different density treatments of S. europaea was applied. Four treatments represented a gradient of S. europaea population densities (Table 1): there was bare land (SEB), low-density population site (SEL), medium-density population site (SEM), and high-density population site (SEH). There were five replicate plots per treatment. The bare land formed by the decrease in the area of the salt lake and the decrease in the groundwater level around the salt lake, led to the disappearance of plants. Each plot was 10 m × 10 m and there was a total of 20 plots. Within each plot, 1 m × 1 m quadrats were established, and rhizosphere soil samples were collected from around S. europaea individuals by using the root drilling method at 0–20 cm depth following a natural precipitation event, and, as the soil moisture reached saturated field capacity within each plot, soil samples were thoroughly homogenized to create a composite sample. To collect rhizosphere soil, intact soil cores were extracted around plant roots using an auger. Loose soil was gently shaken off the roots, and adhering soil was carefully brushed off with a sterile brush. The collected rhizosphere soil was used for analysis of soil microorganisms. The remaining soil was used for soil chemical analysis. In bare soil, rhizosphere soil was collected from around dead underground roots. A subsample of 5 mL was aseptically transferred to a sterile centrifuge tube and stored at −80 °C in a liquid nitrogen tank for subsequent rhizosphere bacterial community analysis. The remaining soil was stored in a sealed bag and transported back to the laboratory for further analysis.

2.3. The Measurement of Soil Physiochemical Properties

Soil properties were determined using the following methods: pH was measured for a 1:2.5 soil:water (w/v) mixture using a meter with a glass electrode. Total dissolved salts (TDS) were quantified gravimetrically. Soil organic carbon (SOC) content was analyzed using a Costech ECS4010 elemental analyzer (Valencia, Spain). Available soil phosphorus (AP) was extracted via the NaHCO3 extraction method followed by molybdenum antimony anticoloration analysis. Ammonium nitrogen (AN) and nitrate nitrogen (NN) were extracted with 2 M KCl solution (soil:water = 1:2.5) and analyzed on a continuous flow analyzer (Skalar, The Netherlands).

2.4. DNA Extraction and PCR Amplification

Genomic DNA was isolated from soil samples using CATB method. Purity and concentration of the extracted DNA were subsequently assessed by agarose gel electrophoresis. An appropriate volume of the isolated DNA was then transferred to a centrifuge tube and diluted to a final concentration of 1 ng/μL using sterile nuclease-free water. For polymerase chain reaction (PCR) amplification, specific primers containing barcode sequences were chosen based on the targeted amplicon region (16S V4 region) to ensure efficient and accurate bacterial diversity analysis. Phusion® High-Fidelity PCR Master Mix with GC Buffer and a high-efficiency, high-fidelity enzyme were employed to further enhance amplification fidelity. The PCR products were visualized on a 2% agarose gel. Following quantification, samples were pooled in equal amounts based on their PCR product concentration. The pooled amplicons were then re-analyzed on a 2% agarose gel. Finally, the desired fragment was excised from the gel and purified using a commercially available gel extraction kit (e.g., Qiagen Gel Extraction Kit, Hilden, Germany).

2.5. Sequence Analysis

We constructed a sequencing library using the NEBNext® Ultra™ II DNA Library Prep Kit (NEB, Ipswich, MA, USA), following the manufacturer’s instructions. The library was quantified using both a Qubit fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) and quantitative PCR (qPCR). After quality control, sequencing was performed on an Illumina NovaSeq6000 platform (Illumina, San Diego, CA, USA). First of all, following library preparation with unique barcode and PCR primer sequences, samples were demultiplexed based on these known sequences. Adapter and primer sequences were subsequently removed from the reads. Paired-end reads were then merged using FLASH software (v1.2.11) to generate raw tags. Secondly, quality filtering of raw tags was performed using Fastp software (v0.23.2) to obtain high-quality clean tags. Usearch software (v11) was employed for chimera detection and removal within the clean tags, resulting in the final effective tags dataset. Additionally, DADA2 within QIIME2 software was utilized for noise reduction within the effective tags. Finally, sequences with a relative abundance below a 5% threshold were filtered. This process yielded the final OTU table and corresponding feature table. Finally, taxonomic classification of the OUTs was performed using the classify-sklearn module within QIIME2 software.

2.6. Statistical Analysis

Statistical comparisons between treatment groups were performed using R software (version 3.0.2). One-way ANOVAs were used to examine the effects of density treatments on pH, TDS, AP, AN, NN, and SOC. To analyze the 16S sequencing data, the OTU table generated in QIIME2 was used to calculate key alpha diversity parameters and indexes, including the Chao1 richness estimator index, the Shannon diversity index, the Simpson’s index, and the coverage. Unweighted pairwise group method with arithmetic means (UPGMA) clustering was performed based on UniFrac distance matrices. Redundancy analysis (RDA) via the vegan package in R was used to assess the influence of environmental factors on bacterial distribution. Significant factors (based on rda and envfit functions) were identified for further analysis. Spearman correlation coefficients were calculated (using the corr.test function in the psych package) to evaluate relationships between bacterial taxa and environmental variables. The pheatmap package was then employed to visualize these correlations.

3. Results

3.1. Soil Characteristics

Soil chemical properties at sampling sites with varying S. europaea population densities are presented in Table 2. These sites were designated as bare land (SEB), low-density population site (SEL), medium-density population site (SEM), and high-density population site (SEH). S. europaea population density exhibited a negative correlation with soil pH. Notably, pH values in bare land soil were significantly greater than those observed in the other sites (p < 0.05), suggesting soil pH was a potential environmental factor influencing S. europaea populations. Available soil phosphorus (AP) was highest in the high-density areas, showing a significant difference (p < 0.05) compared to the low-density areas. Ammonium nitrogen (AN) levels in saline and alkaline bare ground were significantly higher (p < 0.05) than in areas designated as SEL, SEM, and SEH. Similarly, the total dissolved salts’ (TDS) content was significantly greater (p < 0.05) in saline bare ground compared to SEL, SEM, and SEH. Soil nitrate nitrogen (NN) levels displayed no significant variation between sampling areas (p > 0.05). Soil organic carbon (SOC) in SEL was significantly lower (p < 0.05) than in the other three sampling sites.

3.2. Sequencing Results and Assessment of Soil Samples

Rarefaction analysis at 97% sequence similarity is depicted in Figure 2, illustrating the observed richness of the S. europaea population within the soil samples. To characterize the bacterial communities associated with the rhizosphere of S. europaea and saline-alkali bare land, we sequenced the 16S rRNA gene amplicons. The plateauing of the rarefaction curve with increasing sequencing depth indicates sufficient sampling effort to capture the major bacterial taxa present in the samples. This ensures a high degree of confidence in the characterization of the resident bacterial communities, enabling a more accurate representation of the microbiota associated with the S. europaea rhizosphere and bare soil.
A Venn diagram was employed to elucidate the relationships between operational taxonomic units (OTUs) within the bacterial communities of rhizosphere soil under varying S. salsa population densities (Figure 3). A total of 1415 OTUs were identified across the SEB, SEL, SEM, and SEH soil samples. Notably, the number of OTUs in SEB (3582) and SEL (3735) was significantly higher (p < 0.05) compared to SEH (3380) and SEM (3334). Furthermore, the number of OTUs unique to each S. europaea population in the rhizosphere soil and saline-alkali bare land were 976 (SEB), 1037 (SEL), 692 (SEM), and 752 (SEH), representing 27.2%, 27.7%, 20.7%, and 22.2% of their respective total OTUs, respectively.

3.3. Bacterial Alpha Diversity

The sequencing analysis revealed high coverage values (Table 3), signifying successful detection of most sample sequences. The sequencing data likely reflect the true composition of microbial communities within the rhizosphere soil of S. europaea populations. Bacterial diversity was assessed using Shannon and Simpson indices, while Chao1 richness index was employed to estimate bacterial abundance. Chao1 values for soil bacteria exhibited a decreasing trend with increasing S. europaea population density, indicating higher bacterial richness and abundance in soils with lower population densities of S. europaea. Conversely, the Shannon diversity index of the bacterial community in saline-alkali bare land was relatively low. Interestingly, neither the abundance nor the Shannon diversity index of the rhizosphere bacterial community exhibited significant variations across sampling intervals. However, the Simpson diversity index of the bacterial community in bare land was significantly lower compared to that observed in the rhizosphere soil of S. europaea populations (p < 0.05). With the exception of bare land conditions, variation in S. europaea population density did not significantly influence bacterial alpha diversity within the rhizosphere soil.

3.4. Bacterial Community Structure

Rhizosphere soil bacterial communities associated with S. europaea populations in the saline-alkali wetland were dominated by Proteobacteria, Bacteroidota, Actinobacteria, Gemmatimonadota, and Halobacterota (Figure 4A). These phyla were also abundant in bare land, but their relative proportions differed. Proteobacteria abundance was highest in the rhizosphere and decreased with decreasing S. europaea population density. Conversely, halophilic Halobacterota abundance was highest in bare land soil. At the genus level (Figure 4B), Antarcticabacterium (aerobic denitrifier), Wenzhouxiangella, BD2-11_terrestrial_group, Halomonas, Salegentibacter, Natronorubrum, PAUC43f-marine-benthic-group, and Rhodohalobacter dominated the rhizosphere of each S. europaea population, differing from the bare land community. Antarcticabacterium abundance was highest in bare land (9.21%), while BD2-11_terrestrial_group abundance peaked in SEL (5.82%) and SEM (6.78%) rhizosphere soil, and Wenzhouxiangella abundance peaked in SEH rhizosphere soil (6.12%).
Cluster analysis of bacterial communities revealed two distinct categories: SEB soil formed a separate cluster, while SEL, SEM, and SHE soils clustered together with high similarity, with particularly close similarity between SEM and SHE soils (Figure 5A). Among the ten most abundant bacterial phyla in the rhizosphere soil, two distinct assemblages emerge. The first group comprises Desulfobacterota, Gemmatimonadota, Acidobacteriota, Myxococcota, and Proteobacteria. The second assemblage is composed of Firmicutes, Bacteroidota, Halobacterota, Actinobacteria, and Chloroflexi. The abundance of Gemmatimonadota, Acidobacteriaota, Myxococcota, and Proteobacteria increased significantly in SEB rhizosphere soil, while Firmicutes, Bacteroidota, and Halobacterota abundance decreased significantly and were nearly absent in SEB soil (Figure 5A). Similarly, the abundance of Halomonas, Rhodohalobacter, BD2-11_terrestrial_group, PAUC43f_marine-benthic_group, and Subgroup_10 decreased significantly and were scarce in SEB soil, whereas Natronorubrum, Salegentibacter, Halovivax, and Antarcticibacterium abundance increased significantly (Figure 5B).

3.5. Correlation between Bacterial Community in Rhizosphere Soil and Soil Properties

Rhizosphere soil bacterial community composition of S. europaea was analyzed using redundancy analysis (RDA) at the genus level (Figure 6). The RDA explained 83.61% of the variance, with horizontal and vertical axes contributing 74.16% and 9.45%, respectively. Soil properties like pH (R2 = 0.8163, p = 0.0004), AP (R2 = 0.3171, p = 0.0404), NN (R2 = 0.8952, p = 0.0004), and SOC (R2 = 0.3739, p = 0.0224) significantly correlated with the bacterial community composition, suggesting their role as key environmental factors shaping the rhizosphere microbiome. Further analysis using a Spearman’s rank correlation heatmap revealed significant correlations between the top 35 bacterial genera and soil properties (Figure 7). Soil pH exhibited significant correlations (p < 0.05) with 19 genera. Positive correlations were observed for Antarcticabacterium, Halovivax, Aliifodinibius, Haloruss, Nitriliruptoraceae, Gillisia, and Salinimicrobium, while negative correlations were found for Wenzhouxiangella, BD2.11_terrestrial_group, Halomonas, Rhodohalobacter, S0134_terrestrial_group, KI89A_clade, Cm1.21, Pelagibius, Escherichia-Shigella, and Saccharospirillum. Similarly, NN exhibited significant correlations with the abundance of twelve genera among the top 35 identified in the bacterial communities (p < 0.05). Soil NN displayed positive correlations with Antarcticabacterium, Halovivax, Salegentibacter, Natronorubrum, Haloruss, Natronococcus, and Salinimicrobium. Conversely, negative correlations were observed with Halomonas, Rhodohalobacter, Marinobacter, Marinimicrobium, and Saccharospirillum.

4. Discussion

4.1. Effects of Soil Physical and Chemical Properties on S. europaea Population Density

This study investigated a saline wetland within a semi-arid steppe region of Inner Mongolia known for its abundance and concentration of soil nutrients and stress-tolerant species. It is also recognized as a crucial foundation for steppe-based animal husbandry [35,36,37]. The research identified a significant increase in water-soluble salts and soil pH within salinized bare patches following the degradation of the salt-pioneer plant S. europaea populations. These findings align with observations of soil salinization and pH shifts documented after S. europaea decline in the Aibi Lake wetland (Xinjiang) and the Tarim and Euphrates poplar forests [38,39,40]. The decrease in vegetation cover due to declining S. europaea density likely intensified bare soil evaporation, promoting further salt accumulation. Conversely, the presence of S. europaea, a true halophyte, facilitated salt enrichment, potentially reducing the overall soil salt burden. Interestingly, nitrate nitrogen levels in salinized bare land were significantly higher compared to other S. europaea sampling areas. This observation suggests a possible link between S. europaea population density and soil nutrient uptake during plant growth and development.
Our investigation revealed a significant impact of salt stress on soil nutrient availability. Increased soil salinity disrupts soil particle aggregation, leading to reduced microbial activity and consequently affecting soil fertility [41,42]. Interestingly, the SEB region exhibited an enrichment of TDS, AN, and SOC, with particularly high AN values. This aligns with the findings of Guo et al., suggesting that salt stress promotes ammonia nitrogen accumulation in soil by inhibiting nitrification [43,44]. Additionally, we observed a decrease in soil pH and an increase in AP with increasing planting density. This could be attributed to enhanced nutrient uptake by plant roots and the creation of additional non-capillary pores, hindering salt migration back to the surface soil [45,46]. Overall, these findings suggest that the salt-tolerant plant employed in this study may contribute to soil phosphorus accumulation.

4.2. Effects of Soil Rhizosphere Bacterial Structure and Diversity on S. europaea Population Density

Several studies suggest a strong influence of soil nitrogen content on microbial communities [47,48], with higher bacterial abundance observed in well-vegetated grasslands compared to degraded ones. However, Chabrerie et al. [49] reported no direct correlation between plant community changes and soil microbial shifts in artificial grasslands. Our findings align with these observations. The soil bacterial diversity index remained statistically unchanged across sampling intervals, suggesting that within a specific range, population growth of S. europaea in a high-salt environment does not significantly impact bacterial diversity. Therefore, the results of this study are similar to the results of bacterial diversity in the artificial grassland [49,50]. We hypothesize that both high-salt and artificial grassland environments may possess such thresholds, where only substantial shifts in vegetation succession beyond these thresholds would trigger significant changes in soil bacterial diversity.
Soil microbial community structure is primarily driven by a complex interplay of abiotic and biotic factors. Notably, the composition of the surface plant community, including successional stages, population dynamics, and plant growth characteristics, is intricately linked to the enrichment patterns of soil microbes [51,52,53]. This study demonstrates a clear trend in the abundance of bacterial OTUs across different S. europaea population densities. Low-density plots harbored the least diverse bacterial communities, followed by saline-alkali bare land, medium-density, and finally high-density S. europaea plots. Proteobacteria emerged as the dominant bacterial community across all plots, exhibiting increasing abundance with rising S. europaea population density. These dominant groups, including Proteobacteria, Bacteroidota, and Actinobacterota, are known fast-growing eutrophs that facilitate plant root uptake of essential minerals like potassium, phosphorus, and trace elements, thereby promoting plant growth and development. The high abundance of Campylobacter (Gemmatimonadota) across all plots might be attributed to anthropogenic influences, such as waterbird activity and concentrated livestock waste near the polluted lake. Saline-alkali bare land displayed the highest abundance of Firmicutes, likely due to their inherent resistance to dehydration and extreme environments. Genus-level analysis revealed distinct bacterial communities in saline-alkali bare land versus S. europaea samples. The bare land was dominated by aerobic denitrifying bacteria (Antarcticabacterium), halophilic bacteria (Wenzhouxiangella, BD2-11_terrestrial_groupBD2-11, and Halomonas), while S. europaea plots shared dominance with Wenzhouxiangella and BD2-11_terrestrial_groupBD2-11 but exhibited a decrease in the previously mentioned denitrifying and halophilic bacteria (Antarcticabacterium and Halomonas). The high proportion of unclassified bacterial taxa at the genus level in the S. europaea plots suggests a potentially novel microbial community associated with this specific habitat, warranting further investigation.
Plants and soil microorganisms engage in a dynamic interplay of mutual regulation. Adjustments in the adaptability and composition of soil microbial communities, as evidenced by studies on rice cultivation [54] and Jerusalem artichoke [55], influence plant growth through regulation of soil nutrient availability [26]. Conversely, plant root exudates can significantly shape the structure of the soil microbiome, promoting diversity and richness [54]. For instance, rice cultivation enhanced the overall diversity and richness of soil microbes while specifically reducing the relative abundance of Ascomycetes and Basidiomycetes fungi [55].
The soil bacterial community exhibited greater resistance and resilience to environmental perturbations compared to other microbial taxa [56]. Our investigation revealed that the SEB region exerted differential effects on bacterial diversity, abundance, and OTU richness across bacterial communities. However, the magnitude of these changes was minimal. This limited response might be attributed to the inherent metabolic versatility of bacteria, allowing them to utilize a broader range of substrates [57]. This metabolic flexibility potentially contributes to their enhanced stability in response to environmental fluctuations.
Our investigation revealed significant variation in the relative abundance of microbial flora within the community. This heterogeneity likely stems from the adaptive disparities observed in soil microflora [58]. Notably, this study demonstrated that increased plant population density led to a diminished relative abundance of Halobacterota within the microbial community. This phenomenon could be attributed to the imposition of salt stress. Notably, Halobacterota possesses the unique ability to maintain osmotic homeostasis by accumulating high intracellular concentrations of KCl [59]. Conversely, the relative abundances of Proteobacteria and Antarcticabacterium increased with rising plant population density. Proteobacteria encompass a phylum of predominantly aerobic bacteria. The surface soil is characterized by increased fertility, improved aeration, and a more favorable environment for aerobic microorganisms [60]. The increase in the relative abundance of Antarcticabacterium is potentially linked to the indirect improvement in soil physicochemical properties. This improvement is likely mediated by the adsorption of salt by the roots of salt-tolerant plants, thereby creating a protective environment for Antarcticabacterium [42].

4.3. Analysis of the Relationship between Soil Bacterial Community Composition and Soil Properties

Previous research has established that variations in soil nutrient content, along with physical properties and chemical characteristics, directly influence the survival and composition of microbial communities within plant root zones, subsequently impacting plant growth and reproduction [61,62,63,64]. This study investigated the relationship between soil bacterial community composition and environmental factors within a semi-arid steppe wetland populated by S. europaea. The results demonstrated that soil pH, available phosphorus, nitrate nitrogen, and organic carbon significantly affected the bacterial community composition. Here, we focused on the diversity of soil bacterial communities and the influence of key environmental factors in the context of saline-alkali land and changes in S. europaea populations. However, the composition and functional prediction of the rhizosphere bacterial community associated with dominant plant species were not addressed. Future research will emphasize the functional diversity analysis of rhizosphere bacterial communities for dominant plants in the saline-alkali wetland. This will contribute a more comprehensive foundation for the study, conservation, and utilization of microbial resources in the core steppe region.
Our findings demonstrate that soil bacterial communities exhibit greater sensitivity to soil pH and NN, corroborating the observations of Wu et al. and Xu et al. [34,65]. Furthermore, compared with fungi, bacterial has a lower tolerance to pH [66]. This disparity might be due to bacteria’s dependence on soil physicochemical properties, while fungi prioritize resource availability. As plant density increases, bacterial communities display greater instability while fungal communities undergo enhanced succession processes [67]. Studies suggest that carbon and phosphorus primarily limit soil microbial community structure [68,69], which is often linked to plant photosynthetic activity. However, the alkaline soil ecosystem presents distinct nutrient requirements. Discrepancies in research on soil microbial community structure with NN may be due to the strong influence of abiotic factors on bacterial communities. Factors such as plant community biomass, litter accumulation, and the ability to supply microorganisms were all significantly influenced by external environmental conditions [70]. Microbial communities exhibit diverse adaptations to external environments and nutrient resources [71], with these limitations being closely connected to the structure of soil microbial communities [72]. Our study area, characterized by strong alkalinity, harbors dominant bacterial genera well adapted to this harsh environment. At the genus level, distinct positive and negative correlations between specific bacterial taxa and pH or NN were observed. These correlations likely reflect the varying capacity of bacteria to adapt to nutrient scarcity and salinity gradients [73]. In conclusion, the degradation of grassland represents a coordinated transformation involving plant characteristics, soil fertility, and microbial activity [74]. A comprehensive understanding of the key factors that limit soil nutrients and microorganisms during alkaline soil grassland degradation can provide a theoretical foundation and data for formulating effective restoration strategies.

5. Conclusions

The decline in S. europaea population led to an increase in soil pH and a decrease in available phosphorus content. Soil pH and nitrate nitrogen content are the significant environmental factors affecting the composition of the rhizosphere soil bacterial community of S. europaea.

Author Contributions

Conceptualization, H.W., Z.W. and W.H.; investigation, H.W., L.C. and L.J.; methodology, R.N. and Z.W.; formal analysis, H.W.; visualization, H.W., L.J. and W.H.; writing—original draft, H.W.; writing—review and editing, H.W., R.N. and Z.W. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the National Major Agricultural Science and Technology Project in China (Grant No. NK2022181003), the Inner Mongolia Science and Technology Program (Grant Nos. 2021GG0054; 2022YFHH0144; 2022YFDZ0026), the Inner Mongolia Natural Science Foundation Program (Grant No. 2021MS3022), and the Ordos Science and Technology Program (Grant No. 2021EEDSCXQDFZ004).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Agriculture 14 01018 g001
Figure 1. Study site location and S. europaea treatments.
Figure 1. Study site location and S. europaea treatments.
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Figure 2. Rarefaction curves of soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
Figure 2. Rarefaction curves of soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
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Figure 3. Venn diagram showing the unique and shared OTUs among the different rhizosphere soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
Figure 3. Venn diagram showing the unique and shared OTUs among the different rhizosphere soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
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Figure 4. Major phyla (A) and genera (B) of bacterial communities in rhizosphere soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
Figure 4. Major phyla (A) and genera (B) of bacterial communities in rhizosphere soil samples. Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
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Figure 5. Clustering of bacterial colonies at phylum level (A) and genus level (B). Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
Figure 5. Clustering of bacterial colonies at phylum level (A) and genus level (B). Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
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Figure 6. Redundancy analysis (RDA) between environmental variables and soil bacteria genera. Note: Genera are displayed as points and variables as vectors. The arrows point to the direction of the most rapid change in the environmental variable. pH, soil pH value; TDS, total dissolved salts’ content; AP, available soil phosphorus content; AN, soil ammonium nitrogen content; NN, soil nitrate nitrogen content; SOC, soil organic carbon content; SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
Figure 6. Redundancy analysis (RDA) between environmental variables and soil bacteria genera. Note: Genera are displayed as points and variables as vectors. The arrows point to the direction of the most rapid change in the environmental variable. pH, soil pH value; TDS, total dissolved salts’ content; AP, available soil phosphorus content; AN, soil ammonium nitrogen content; NN, soil nitrate nitrogen content; SOC, soil organic carbon content; SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site.
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Figure 7. Spearman correlationship analysis of environmental factors and soil bacteria communities (genus level). Note: pH, soil pH value; TDS, total dissolved salts’ content; AP, available soil phosphorus content; AN, soil ammonium nitrogen content; NN, soil nitrate nitrogen content; and SOC, soil organic carbon content. “*” means significant (p < 0.05); “**” means significant (p < 0.01).
Figure 7. Spearman correlationship analysis of environmental factors and soil bacteria communities (genus level). Note: pH, soil pH value; TDS, total dissolved salts’ content; AP, available soil phosphorus content; AN, soil ammonium nitrogen content; NN, soil nitrate nitrogen content; and SOC, soil organic carbon content. “*” means significant (p < 0.05); “**” means significant (p < 0.01).
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Table 1. Density of S. europaea population at different sampling sites.
Table 1. Density of S. europaea population at different sampling sites.
Sampling SitesPopulation Density (Plants m−2)
SEB0
SEL125 ± 84
SEM473 ± 375
SEH1743 ± 653
Note: SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site. Values represent mean ± standard deviation (n = 5).
Table 2. Soil chemical parameters at four sites with different S. europaea population densities.
Table 2. Soil chemical parameters at four sites with different S. europaea population densities.
Sampling SitespHTDS (g kg−1)AP (mg kg−1)AN (mg kg−1)NN (mg Kg−1)SOC (g kg−1)
SEB9.8 ± 0.2 a31.18 ± 4.09 a27.83 ± 3.03 a144.04 ± 3.07 a10.93 ± 2.94 a13.42 ± 2.26 a
SEL8.9 ± 0.1 b16.58 ± 4.39 b7.37 ± 6.67 b17.38 ± 5.12 b12.47 ± 6.30 a7.65 ± 1.52 b
SEM8.8 ± 0.2 b12.62 ± 3.00 b20.23 ± 10.09 a18.61 ± 2.81 b10.79 ± 4.27 a11.32 ± 0.87 a
SEH8.5 ± 0.2 b16.41 ± 7.54 b35.10 ± 10.73 a17.96 ± 7.88 b12.45 ± 5.71 a11.38 ± 2.41 a
Note: Lowercase letters (a, b) indicate that means are significantly different among different population densities (p < 0.05). pH, soil pH value; TDS, total dissolved salts’ content; AP, available soil phosphorus content; AN, soil ammonium nitrogen content; NN, soil nitrate nitrogen content; SOC, soil organic carbon content; SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site. Values represent mean ± standard deviation (n = 5).
Table 3. Diversity indices obtained from sequencing analysis.
Table 3. Diversity indices obtained from sequencing analysis.
Sampling SitesShannonSimpsonChao1Coverage/%
SEB8.7474 ± 0.2625 a0.9898 ± 0.0031 b1589.2206 ± 86.0630 a0.9998 ± 0.0004 a
SEL9.0500 ± 0.0808 a0.9942 ± 0.0008 a1631.1136 ± 80.1024 a1.0000 ± 0.0000 a
SEM8.9122 ± 0.2011 a0.9940 ± 0.0007 a1515.3380 ± 83.4295 a1.0000 ± 0.0000 a
SEH8.8932 ± 0.2431 a0.9942 ± 0.0018 a1488.7896 ± 118.0765 a1.0000 ± 0.0000 a
Note: Lowercase letters (a and b) indicate that means are significantly different among different population densities (p < 0.05). SEB, bare land; SEL, low-density population site; SEM, medium-density population site; and SEH, high-density population site. Values represent mean ± standard deviation (n = 5).
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Wang, H.; Chun, L.; Ji, L.; Na, R.; Wei, Z.; Han, W. Investigating the Diversity and Influencing Factors of the Rhizosphere Bacterial Community Associated with Salicornia europaea L. Populations in Semi-arid Grassland. Agriculture 2024, 14, 1018. https://doi.org/10.3390/agriculture14071018

AMA Style

Wang H, Chun L, Ji L, Na R, Wei Z, Han W. Investigating the Diversity and Influencing Factors of the Rhizosphere Bacterial Community Associated with Salicornia europaea L. Populations in Semi-arid Grassland. Agriculture. 2024; 14(7):1018. https://doi.org/10.3390/agriculture14071018

Chicago/Turabian Style

Wang, Hai, Liang Chun, Lei Ji, Risu Na, Zhijun Wei, and Wenjun Han. 2024. "Investigating the Diversity and Influencing Factors of the Rhizosphere Bacterial Community Associated with Salicornia europaea L. Populations in Semi-arid Grassland" Agriculture 14, no. 7: 1018. https://doi.org/10.3390/agriculture14071018

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