File Name: soil microbial diversity and the sustainability of agricultural soils .zip
Amongst scholars, there is a general consensus that a decline in biodiversity leads to a decrease in ecosystem functioning 2. These services make the planet habitable by supplying and purifying the air we breathe and the water we drink. Water, carbon, nitrogen, phosphorus, and sulfur are the major global biogeochemical cycles.
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We report the variation in bacterial community structures in greenhouse, orchard, paddy, and upland soils collected from sites across the Republic of Korea using 16S rRNA gene pyrosequencing analysis. Bacterial diversities and community structures were significantly differentiated by agricultural land-use types. Paddy soils, which are intentionally flooded for several months during rice cultivation, had the highest bacterial richness and diversity, with low community variation.
Soil chemical properties were dependent on agricultural management practices and correlated with variation in bacterial communities in different types of agricultural land use, while the effects of spatial components were little. Firmicutes , Chloroflexi , and Acidobacteria were enriched in greenhouse, paddy, and orchard soils, respectively. Members of these bacterial phyla are indicator taxa that are relatively abundant in specific agricultural land-use types.
A relatively large number of taxa were associated with the microbial network of paddy soils with multiple modules, while the microbial network of orchard and upland soils had fewer taxa with close mutual interactions.
These results suggest that anthropogenic agricultural management can create soil disturbances that determine bacterial community structures, specific bacterial taxa, and their relationships with soil chemical parameters. These quantitative changes can be used as potential biological indicators for monitoring the impact of agricultural management on the soil environment.
Diverse soil microbes play critical roles in plant growth and health. They decompose organic compounds and participate in the recycling of nutrients, such as nitrogen, phosphorus, and potassium, which are important for plant growth 1 , 2 , 3. Some soil microbes in the rhizosphere and endosphere of plants improve tolerance to abiotic and biotic stress 4. In addition to physicochemical properties of soils, soil microbial communities largely determine agricultural productivity 5.
To develop sustainable agriculture, understanding of ecological features of microbiomes in agroecosystems is needed. The biogeography of soil microbial communities has been investigated at various spatial scales. Fierer and Jackson observed that microbial biogeography is primarily controlled by edaphic variables, not geographic distance.
Another study of microbial communities in soils collected across the state of California, USA, showed that land-use types such as coastal grasslands, inland grasslands, deserts, coniferous forests, freshwater wetlands, and perennial and annual agricultural fields were closely associated with distinct microbial communities at a regional level 6.
A more recent and detailed characterization of soil microbial communities reported different biogeographic patterns of soil microbial communities across natural forests with vegetation gradients and distinct edaphic variables 7.
Different patterns of microbial diversity across different habitats e. These investigations together suggest that the types of habitats or land use affect biogeographic patterns of bacterial taxa from regional to continental scales.
Agricultural management such as fertilization, irrigation, and tillage are important factors that affect the biodiversity and function of terrestrial ecosystems and can also lead to soil ecosystem degradation 9 , 10 , 11 , 12 , Previous studies show that land management practices such as chemical fertilization have a significant effect on bacterial community structure 14 , 15 , Effects of soil parameters, including pH, electrical conductivity EC , carbon and nitrogen contents, salinity, and texture, on microbial community composition have been reported in many studies 17 , 18 , 19 , 20 , 21 , 22 , and this relationship was shown to be significant even in unique environments, such as the black soils of Northeast China 23 , 24 , Bacterial taxa with distinct relative abundance patterns have been proposed as potential biological indicators that reflect environmental conditions.
A recent study by Hermans et al. They also observed certain dominant taxa to be significantly related to specific soil parameters. These results support the use of specific bacterial taxa and their relative abundances as biological indicators that can be used to predict various soil attributes e. To explore interactions between microbial taxa in complex soil microbial ecology, co-occurrence network analysis has been widely used 27 , In the network, keystone taxa that have frequent interactions with many others are predicted to play an important role in microbial ecology Distinct co-occurrence patterns have been reported in different agricultural practices organic and conventional farming 16 and habitats bulk soil and rhizosphere However, the co-occurrence networks of soil bacterial communities in different types of agricultural land use have not been explored using a large number of samples.
To elucidate the soil microbial distributions in agricultural soils, we collected soil samples from four major types of agricultural land, including greenhouses, orchards, paddy fields, and uplands, throughout the Republic of Korea. We measured the edaphic factors of the soils and performed 16S rRNA gene pyrosequencing analysis of bacterial communities.
The specific objectives of this study were to characterize bacterial communities in different agricultural land-use types through analyses of bacterial community diversity, composition, indicator species, and co-occurrence patterns. To survey bacterial communities in agricultural soils across the Republic of Korea, we collected soil samples from four major types of agricultural land use: greenhouses , uplands , orchards , and paddy fields Supplementary Fig. S1 and Supplementary Data S1.
The variation in bacterial community structures was visualized with a nonmetric multidimensional scale NMDS plot based on Bray—Curtis distance. Bacterial communities in paddy soils were clearly differentiated from those in the other types of soil Fig. Bacterial communities in greenhouse soils were also differentiated from those in orchard and upland soils. Although bacterial communities of orchard and upland soils were closely positioned in the ordination plots Fig.
The dispersion of soil bacterial communities within each type of agricultural land use was examined by measuring the distance between the centroid.
Bacterial community dissimilarity within each type of agricultural land use was the lowest in paddy soils and the highest in upland soils Fig. Beta-diversity of soil bacterial communities in the four types of agricultural land use. Box plot illustrating the beta-dispersion of bacterial communities B.
Boxes represent the interquartile range IQR , and whiskers indicate the furthest point within 1. Values beyond this range are plotted as individual points.
The central line indicates the median. To compare alpha-diversity between the samples, the OTU dataset was sub-sampled to the smallest number of total reads within a sample 1, reads. Chao1 and ACE richness estimators were significantly higher in paddy soils, while those in upland soils were lower Table 1.
Similarly, paddy soils showed significantly higher Shannon and inverse-Simpson diversity indices, followed by orchard, greenhouse, and upland soils. Taken together, paddy soils had significantly higher bacterial richness and diversity, with lower bacterial community variation, while upland soils harbored bacterial communities with lower richness and diversity but greater variation compared to other types of agricultural land use.
Although the compositions of bacterial communities in upland and orchard soils look similar according to NMDS, the greater bacterial community variation in upland soils may partially explain the significant difference from orchard soils.
The principal component analysis PCA ordination plot showed that soil chemical properties were clearly separated between paddy and greenhouse soils along the first axis, which explains Soil chemical properties associated with the types of agricultural land use. Principal component analysis PCA of soil chemical properties using z-transformed soil variables A.
The association of bacterial richness Chao-1 and diversity Shannon index with soil pH in different types of agricultural soils B. Redundancy analysis RDA of bacterial communities constrained by soil chemical properties C. The joint biplot indicates the correlation between the chemical factors and ordination scores of RDA axes. EC electrical conductivity, OM organic matter. Venn diagram representing variation partitioning of bacterial communities explained by land-use types, edaphic and spatial variables D.
Among the edaphic factors measured, bacterial richness Chao-1 and diversity Shannon index had a significant association with soil pH Fig. Bacterial richness and diversity were the highest in neutral soils and lower in acidic soil, which is consistent with previous studies that utilized a variety of biogeographical scales and land uses 6 , 17 , 23 , 31 , In particular, bacterial richness and diversity in orchard soils showed the strongest correlation with soil pH, while those in paddy soils with lower pH levels pH 5.
S2 and S3. The redundancy analysis RDA ordination plot constrained by soil chemical properties also showed that bacterial communities were separated by agricultural land-use types along the first axis Fig. The chemical properties we measured in this study explained Although many studies have reported that microbial community similarity tends to decrease along increasing geographical distances 33 , 34 , no significant distance-decay patterns of bacterial communities in agricultural soils were observed Supplementary Fig.
Variation partitioning analysis was performed with three explanatory components—land-use types, edaphic and spatial variables. Variation partition analysis showed that Land-use type and edaphic variables jointly demonstrated 7.
For different types of agricultural land use, edaphic variables Taken together, despite the various unknown factors that influence community variation, soil chemical properties derived by agricultural land use significantly affect bacterial community structures.
Of the 68, OTUs obtained from soil samples across four types of agricultural land, 47, At lower taxonomic levels, 38, Relative abundances of Bacteroidetes The relative abundances of Chloroflexi Taxonomic distribution of the bacterial communities in the four types of agricultural land use. For Proteobacteria , the classes are indicated. The stacked column bar graph was generated using Microsoft Excel software. To identify individual OTUs sensitive to specific agricultural land-use type, indicator species analysis was performed based on point biserial correlation.
The sequence reads of these indictor OTUs accounted for Paddy soils had the most indicator OTUs , with a relative abundance of The indicator taxa of paddy soils comprised OTUs belonging mainly to the phyla Chloroflexi and Acidobacteria , and those of greenhouse soils contained OTUs belonging mainly to the phylum Firmicutes and the class Alphaproteobacteria.
The orchard soils had indicator taxa belonging to Acidobacteria , in particular, subgroup 6 and the phylum Nitrospirae. The upland soils had only one specific indicator taxon, which belonged to the genus Gemmatimonas. Edges node connection show the association of individual OTUs with each type of agricultural land use. OTUs are colored by phylum or class. The network analysis was visualized using Gephi 0. OTU was affiliated with Chloroflexi and clustered with uncultured bacterial clones detected in paddy soils.
OTU7 was phylogenetically close to Bacillus isolated from the rhizosphere soil of cucumber and tomato, which are the main vegetables grown in greenhouses. OTU8 was affiliated with Nitrospirae and clustered with uncultured bacterial clones observed in soils growing trees and grasses. OTU belongs to Gemmatimonadetes and was clustered with uncultured bacterial clones observed in cropping soils with peanut, tobacco, and vegetables. To conclude, the majority of bacterial communities in soils were not differentiated by the types of agricultural land use, and there were distinct taxa specific to agricultural land use.
To explore the complex microbial community structures in different types of agricultural land use, we performed co-occurrence network analysis using molecular ecological network analyses MENA based on random-metric theory RMT.
Metrics details. Exploiting soil microorganisms in the rhizosphere of plants can significantly improve agricultural productivity; however, the mechanism by which microorganisms specifically affect agricultural productivity is poorly understood. To clarify this uncertainly, the rhizospheric microbial communities of super rice plants at various growth stages were analysed using 16S rRNA high-throughput gene sequencing; microbial communities were then related to soil properties and rice productivity. The rhizospheric bacterial communities were characterized by the phyla Proteobacteria, Acidobacteria, Chloroflexi, and Verrucomicrobia during all stages of rice growth. Mantel tests showed a strong correlation between soil conditions and rhizospheric bacterial communities, and microorganisms had different effects on crop yield. The biological properties i.
Soil-based microorganisms assume a direct and crucial role in the promotion of soil health, quality and fertility, all factors known to contribute heavily to the quality and yield of agricultural products. Cover cropping, used in both traditional and organic farming, is a particularly efficient and environmentally favorable tool for manipulating microbiome composition in agricultural soils and has had clear benefits for soil quality and crop output. Several long-term investigations have evaluated the influence of multi-mix multiple species cover crop treatments on soil health and microbial diversity. The present study investigated the short-term effects of a seven species multi-mix cover crop treatment on soil nutrient content and microbial diversity, compared to a single-mix cover crop treatment and control. Analysis of 16S sequencing data of isolated soil DNA revealed that the single-mix cover crop treatment decreased overall microbial abundance and diversity, whereas the control and multi-mix treatments altered the overall microbial composition in similar fluctuating trends.
Sustainable agriculture is farming in sustainable ways meeting society's present food and textile needs, without compromising the ability for current or future generations to meet their needs. There are many methods to increase the sustainability of agriculture. When developing agriculture within sustainable food systems , it is important to develop flexible business process and farming practices. Agriculture has an enormous environmental footprint , playing a significant role in causing climate change , water scarcity , land degradation , deforestation and other processes;  it is simultaneously causing environmental changes and being impacted by these changes. For example, one of the best ways to mitigate climate change is to create sustainable food systems based on sustainable agriculture.
Many world ecosystems are in various states of decline evidenced by erosion, low productivity, and poor water quality caused by forest clearing, intensive agricultural production, and continued use of land resources for purposes that are not sustainable. The biological diversity of these systems is being altered. Little research has been conducted to quantify the beneficial relationships between microbial diversity, soil and plant quality, and ecosystem sustainability.
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