Soil bacteria are closely related to soil environmental factors, and their community structure is an important indicator of ecosystem health and sustainability. A large number of artificial grasslands have been established to control rocky desertification in the karst areas of southern China, but the influence of different use patterns on the soil bacterial community in artificial grasslands is not clear. In this study, three grassland use patterns [i.e., grazing (GG), mowing (MG), and enclosure (EG)] were used to investigate the effects of different use patterns on the soil bacterial community in artificial grassland by using 16S rDNA Illumina sequencing and 12 soil environmental indicators. It was found that, compared with EG, GG significantly changed soil pH, increased alkaline hydrolyzable nitrogen (AN) content (P < 0.05), and decreased soil total phosphorus (TP) content (P < 0.05). However, MG significantly decreased the contents of soil organic carbon (SOC), total phosphorus (TP), available nitrogen (AN), ammonium nitrogen (NH4+-N), β-1,4-glucosidase (BG), and N-acetyl-β-D-glucamosonidase (NAG) (P < 0.05). The relative abundance of chemoheterotrophy was significantly decreased by GG and MG (P < 0.05). GG significantly increased the relative abundance of Acidobacteria and Gemmatimonadota (P < 0.05) and significantly decreased the relative abundance of Proteobacteria (P < 0.05), but the richness index (Chao 1) and diversity index (Shannon) of the bacterial community in GG, MG, and EG were not significantly different (P > 0.05). The pH (R2 = 0.79, P = 0.029) was the main factor affecting the bacterial community structure. This finding can provide a scientific reference for ecological restoration and sustainable utilization of grasslands in the karst desertification areas.

Effects of different grassland use patterns on soil bacterial communities in the karst desertification areas

Understanding soil bacterial diversity under nitrogen reduction is necessary for the crucial role in soil nitrogen cycling. However, the effects of combined fertilization on soil chemical properties, microbial community structure, and yield are unknown. This study was conducted to investigate the effect of nitrogen fertilizer reduction with bio-organic fertilizer on soil bacterial community diversity of red raspberry orchard. Six treatments were set in this study: NF-100%, NF-75%, NF-50%, NF-25% and CF, no nitrogen fertilizer and bio-organic fertilizer for CK. The bacterial community structures of soil were analyzed by 16S rRNA gene amplification high-throughput sequencing technology. Nitrogen fertilizer reduction with bio-organic fertilizer increased soil organic matter (SOM), total nitrogen (TN), alkali-hydrolyzable nitrogen (AN), available phosphorus (AP), available potassium (AK), and reduced soil pH. NF-50% and NF-25% treatments increased the yield of red raspberry. Nitrogen reduction combined with bio-organic fertilizer increased the relative abundance of copiotrophic bacteria and decreased the relative abundance of oligotrophic bacteria. The increase in copiotrophic bacteria in the soil of red raspberry orchard could indicate an increase in soil nutrient availability, which have positive implications for soil fertility and production. However, nitrogen fertilizer reduction with bio-organic fertilizer altered the abundance and diversity of soil bacteria, which was reduced compared to CF treatments. The PCoA analysis of the soil bacterial community showed that the community structure of NF-25% treatment was more different from other treatments, indicating that the fertilization method changed the community structure of soil bacteria. The results of a redundancy analysis showed that SOM, pH, AN, TN, and AP were the main factors affecting the microbial community structure. Overall, the reduction of nitrogen fertilizer with bio-organic fertilizer significantly increased the soil nutrient content, reduced the relative abundance and diversity of soil bacteria, increased the relative abundance of beneficial bacteria in the soil, changed the bacterial community structure of soil, increased production and created suitable soil conditions for the red raspberry growth.

Effects of nitrogen reduction combined with bio-organic fertilizer on soil bacterial community diversity of red raspberry orchard

A large number of bare patches (BP) were formed in alpine meadows on the Qinghai-Tibet Plateau (QTP) due to serious degradation. The recovery succession of BP may lead to changes in nutrient cycling in grassland ecosystems. However, changes in the intrinsic correlations of soil-microbe-enzyme stoichiometry in response to successional processes of bare patches recovery are uncertain. We selected five types of patches: bare patches (BP), initial recovery patches (IRP), mid-term recovery patches (MRP), long-term recovery patches (LRP) and healthy alpine meadow (AM), to analyze the variation characteristics of soil-microbe-enzyme carbon (C), nitrogen (N) and phosphorus (P) stoichiometry, as well as the changes in soil moisture at different natural succession stages of patchily degraded alpine meadows in the Source Zone of the Yellow River. The results showed that the successional recovery of patchily degraded alpine meadows promoted soil moisture, soil organic carbon (SOC) and total nitrogen (STN) content, soil microbial biomass carbon (MBC), nitrogen (MBN) and phosphorus (MBP), soil extracellular enzyme (alkaline phosphatase (AP) and L-leucine aminopeptidase (LAP)) activities, soil C/P, soil N/P, soil microbial biomass C/N. And C/P and N/P showed an opposite trend, while soil extracellular enzyme (β-1,4-glucosidase (BG), β-1,4-N-acetylglucosaminidase (NAG)) activity and enzyme C/N, C/P and N/P showed an opposite trend. Soil total phosphorus (STP), SOC, STN, MBC, MBN and MBP in the topsoil are higher than in the subsoil. The correlation between soil-microbe-enzyme ecological stoichiometry indicated that soil moisture was the main limiting factor affecting soil-microbe-enzyme nutrient cycling during the natural succession of degraded alpine meadows. 

Soil moisture regulates soil-microbe-enzyme stoichiometries during recovery succession in patchily degraded alpine meadows on the Qinghai-Tibet Plateau

The understanding of the molecular defensive mechanism of Echinacea purpurea (L.) Moench against polycyclic aromatic hydrocarbon (PAH) contamination plays a key role in the further improvement of phytoremediation efficiency. Here, the responses of E. purpurea to a defined mixture of phenanthrene (PHE) and pyrene (PYR) at different concentrations or a natural mixture from an oilfield site with a history of several decades were studied based on transcriptomics sequencing and widely targeted metabolomics approaches. The results showed that upon 60-day PAH exposure, the growth of E. purpurea in terms of biomass (p < 0.01) and leaf area per plant (p < 0.05) was negatively correlated with total PAH concentration and significantly reduced at high PAH level. The majority of genes were switched on and metabolites were accumulated after exposure to PHE + PYR, but a larger set of genes (3964) or metabolites (208) showed a response to a natural PAH mixture in E. purpurea. The expression of genes involved in the pathways, such as chlorophyll cycle and degradation, circadian rhythm, jasmonic acid signaling, and starch and sucrose metabolism, was remarkably regulated, enhancing the ability of E. purpurea to adapt to PAH exposure. Tightly associated with transcriptional regulation, metabolites mainly including sugars and secondary metabolites, especially those produced via the phenylpropanoid pathway, such as coumarins, flavonoids, and their derivatives, were increased to fortify the adaptation of E. purpurea to PAH contamination. These results suggest that E. purpurea has a positive defense mechanism against PAHs, which opens new avenues for the research of phytoremediation mechanism and improvement of phytoremediation efficiency via a mechanism-based strategy.

/pdf/molecular-defensive-mechanism-of-echinacea-purpurea-l-moench-2aphsndr.pdf

Molecular Defensive Mechanism of Echinacea purpurea (L.) Moench against PAH Contaminations

The accurate identification of different restoration stages of degraded alpine meadow patches is essential to effectively curb the deterioration trend of ‘Heitutan’ (areas of severely degraded alpine meadows in western China). In this study, hyperspectral imaging (HSI) and machine learning techniques were used to develop a method for accurately distinguishing the different restoration stages of alpine meadow patches. First, hyperspectral images representing the four restoration stages of degraded alpine meadow patches were collected, and spectral reflectance, vegetation indexes (VIs), color features (CFs), and texture features (TFs) were extracted. Secondly, valid features were selected by competitive adaptive reweighted sampling (CARS), ReliefF, recursive feature elimination (RFE), and F-test algorithms. Finally, four machine learning models, including the support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and extreme gradient boosting (XGBoost), were constructed. The results demonstrated that the SVM model based on the optimal wavelengths (OWs) and prominent VIs achieved the best value of accuracy (0.9320), precision (0.9369), recall (0.9308), and F1 score (0.9299). In addition, the models that combine multiple sets of preferred features showed a significant performance improvement over the models that relied only on a single set of preferred features. Overall, the method combined with HSI and machine learning technology showed excellent reliability and effectiveness in identifying the restoration stages of meadow patches, and provided an effective reference for the formulation of grassland degradation management measures. 

Identifying the Restoration Stages of Degraded Alpine Meadow Patches Using Hyperspectral Imaging and Machine Learning Techniques

MiSeq sequencing technology was used to investigate the bacterial compositions and diversities of active patch, non-active patch, recovered patch, and healthy alpine meadows so as to understand the changes in soil bacterial community diversity during altitude change and alpine meadow degradation. The relationship between bacterial diversity and environmental factors was analyzed using redundancy analysis (RDA). The results showed that the dominant bacterial phyla in the soil included Proteobacteria, Actinobacteriota, and Acidobacteriota in the study areas. The dominant bacterial genera that were identified via the MiSeq were RB41, Sphingomonas, and Bradyrhizobium. The relative abundance of these genera decreased with altitude increase and increased with the restoration progress of degraded patches but was significantly lower than that in the alpine meadow (P<0.05). The abundance of functional bacteria related to carbon fixation in degraded patches was higher than that in the healthy alpine meadow. The bacterial Chao1 index and species number in different types of degraded patches were significantly higher than those in the alpine meadow (P<0.05). The results of the RDA suggest that biological soil crust coverage and total nitrogen were the main influencing factors on dominant bacterial phyla at the altitude of 4013 m. Biomass, total nitrogen, and pH had a great influence on the dominant bacterial phyla at the altitude of 4224 m. Biomass and total potassium significantly affected the distribution of bacterial genera at the altitude of 4013 m. Sedge coverage and available nitrogen were the main influencing factors on bacterial dominant genera at the altitude of 4224 m. Biological soil crusts and pH had a great influence on bacterial diversities. The bacterial influence factors varied greatly at different altitude areas. Therefore, we should not only pay attention to the effect of alpine meadow degradation but also consider the effect of altitude in the study of bacterial diversity changes.

[Changes in Soil Bacterial Community Diversity in Degraded Patches of Alpine Meadow in the Source Area of the Yellow River].

Under polycyclic aromatic hydrocarbon (PAH) pollution conditions (149.17–187.54 mg/kg), we had found the dominant flora of PAHs by observing the response of the soil microbial community after planting purple coneflower (Echinacea purpurea (L.) Moench). In this study, pot experiments were conducted in a growth chamber to explore the changes in the rhizosphere microbial community structure during remediation of heavily PAH-contaminated soil using purple coneflower (Echinacea purpurea (L.) Moench). The phospholipid fatty acid (PLFA) content in the soil was measured during four periods before and after planting, and the results showed that: (i) at 120 days, E. purpurea can regulate the microbial community structure but had no significant effect on soil microbial diversity, (ii) at 120 days, the number of PLFAs characterizing actinomycetes, bacteria, and fungi increased, and both Gram-negative bacteria and Arbuscular mycorrhizal fungi (AMF) were significant with the observed PLFA level (p < 0.05), and (iii) the results indicated that AMF and Gram-negative bacteria represent some of the main factors that can promote the degradation of PAHs. The results obtained in this work are important to future research on PAH-degradation-functional genes and degradation mechanisms of the selection of flora.

/pdf/response-of-rhizosphere-microbial-community-in-high-pah-lis811h6.pdf

Response of Rhizosphere Microbial Community in High-PAH-Contaminated Soil Using Echinacea purpurea (L.) Moench

Introduction Deep insights into adhering soil of root zones (rhizosphere and rhizoplane) microbial community could provide a better understanding of the plant-microbe relationship. To better understand the dynamics of these microbial assemblies over the plant life cycle in rhizodeposition along rice roots. Methods Here, we investigated bacterial distribution in bulk, rhizosphere, and rhizoplane soils at tillering, heading, and mature stage, from rice (Oryza sativa) fields of the Northeast China. Results and Discussion Our results revealed that soil bacterial α-diversity and community composition were significantly affected by root compartment niches but not by temporal change. Compared to rhizoplane soils in the same period, bulk in the heading and rhizosphere in the mature had the largest increase in Shannon’s index, with 11.02 and 14.49% increases, respectively. Proteobacteria, Chloroflexi, Bacteroidetes, and Acidobacteria are predominant across all soil samples, bulk soil had more phyla increased across the growing season than that of root related-compartments. Deterministic mechanisms had a stronger impact on the bacterial community in the compartments connected to the roots, with the relative importance of the bulk soil, rhizoplane and rhizosphere at 83, 100, and 56%, respectively. Because of ecological niche drivers, the bacterial networks in bulk soils exhibit more complex networks than rhizosphere and rhizoplane soils, reflected by more nodes, edges, and connections. More module hub and connector were observed in bulk (6) and rhizoplane (5) networks than in rhizosphere (2). We also detected shifts from bulk to rhizoplane soils in some functional guilds of bacteria, which changed from sulfur and nitrogen utilization to more carbon and iron cycling processes. Taken together, our results suggest distinct bacterial network structure and distribution patterns among rhizosphere, rhizoplane, and bulk soils, which could possibly result in potential functional differentiation. And the potential functional differentiation may be influenced by plant root secretions, which still needs to be further explored.

/pdf/soil-bacterial-communities-of-paddy-are-dependent-on-root-2xdbtsb3.pdf

Soil bacterial communities of paddy are dependent on root compartment niches but independent of growth stages from Mollisols of Northeast China

This study was conducted to clarify the structure and function of the fungal community and the microecology change characteristics of farmland soil fertility response to different fallow rotation patterns. It aimed to provide a reference for promoting farmland ecological restoration and farmland quality improvement in the alluvial plain of the lower Yellow River. Farmland soil subject to a long-term rotation fallow experiment since 2018 was studied using Illumina MiSeq high-throughput sequencing technology, and the 'FUNGuild' fungal function prediction tool was used to analyze differences in soil fungal community structure and function under the following four rotation fallow regimes: long fallow (LF), winter wheat and summer fallow (WF), winter fallow and summer maize (FM), and annual rotation of winter wheat and summer maize (WM). The results showed that LF (fallow lasting two years) increased the richness and diversity of fungal communities in the topsoil (0-20 cm layer), whereas WF increased the richness and diversity of fungi in the deep soil (20-40 cm layer) after winter wheat harvest. A total of 2262 OTU were obtained from all soil samples, which were divided into 14 phyla, 34 classes, 75 orders, 169 families, 309 genera, and 523 species. OTU shared by the two soil layers included 420 types (0-20 cm layer) and 253 types (20-40 cm layer), respectively. The fungal community structure of the four rotation fallow soils was similar at the phylum level, mainly including Ascomycota, Basidiomycota, and Mortierellomycota. The total abundances of the three dominant bacteria were 91.69%-96.91% (0-20 cm layer) and 91.67%-94.86% (20-40 cm layer), respectively. Principal component analysis showed that the first principal component (PC1) and the second principal component (PC2) could explain the difference in community structure by 45.56% (0-20 cm layer) and 46.20% (20-40 cm layer). Additionally, the LDA results of LEfSe (threshold was 4.0) showed that there were 64 fungal evolutionary branches in LF, FM, WF, and WM with statistically significant differences (P<0.05). According to RDA analysis, total organic carbon (TOC), total phosphorus (TP), available nitrogen (AN), and soil water content (SWC) were the main environmental factors that significantly affected fungal community in the 0-40 cm soil layer (P<0.05). The functional prediction with FUNGuild showed that the main nutrient types among different treatments in different soil layers were saprotrophic, saprotrophic-symbiotrophic, pathotrophic-saprotrophic-symbiotrophic, and pathotrophic. In LF, the nutrient type of topsoil was mainly pathotrophic-saprotrophic-symbiotrophic, whereas in deep soil, the relative abundance of pathotrophic fungi was the highest. Additionally, in the treatments with planted wheat or corn (FM, WF, and WM), saprotrophic was the main type in both soil layers. Therefore, different fallow patterns were linked to variation in the structure, diversity, and nutrient types of soil fungal communities. Based on these results, seasonal fallow practices could regulate the farmland soil micro-ecological environment of intensive planting and promote the health and harmony of farmland soil ecosystems.

[Structure and Function of Soil Fungal Community in Rotation Fallow Farmland in Alluvial Plain of Lower Yellow River].

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[Changes in Soil Bacterial Community Diversity in Degraded Patches of Alpine Meadow in the Source Area of the Yellow River].

Response of Rhizosphere Microbial Community in High-PAH-Contaminated Soil Using Echinacea purpurea (L.) Moench

Soil bacterial communities of paddy are dependent on root compartment niches but independent of growth stages from Mollisols of Northeast China

[Structure and Function of Soil Fungal Community in Rotation Fallow Farmland in Alluvial Plain of Lower Yellow River].