Dataset Information

Bacterial Community Structure and Predicted Function in Wheat Soil From the North China Plain Are Closely Linked With Soil and Plant Characteristics After Seven Years of Irrigation and Nitrogen Application.

ABSTRACT: The influence of water and nitrogen (N) management on wheat have been investigated, but studies on the impact of long-term interactive water and N management on microbial structure and function are limited. Soil chemical properties and plants determine the soil microbial communities whose functions involved in nutrient cycling may affect plant productivity. There is an urgent need to elucidate the underlying mechanisms to optimize these microbial communities for agricultural sustainability in the winter wheat production area of the North China Plain. We performed high-throughput sequencing and quantitative PCR of the 16S rRNA gene on soil from a 7-year-old stationary field experiment to investigate the response of bacterial communities and function to water and N management. It was observed that water and N management significantly influenced wheat growth, soil properties and bacterial diversity. N application caused a significant decrease in the number of operational taxonomic units (OTUs), and both Richness and Shannon diversity indices, in the absence of irrigation. Irrigation led to an increase in the relative abundance of Planctomycetes, Latescibacteria, Anaerolineae, and Chloroflexia. In addition, most bacterial taxa were correlated with soil and plant properties. Some functions related to carbohydrate transport, transcription, inorganic ion transport and lipid transport were enriched in irrigation treatment, while N enriched predicted functions related to amino acid transport and metabolism, signal transduction, and cell wall/membrane/envelope biogenesis. Understanding the impact of N application and irrigation on the structure and function of soil bacteria is important for developing strategies for sustainable wheat production. Therefore, concurrent irrigation and N application may improve wheat yield and help to maintain those ecosystem functions that are driven by the soil microbial community.

SUBMITTER: Ma G

PROVIDER: S-EPMC7136406 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Bacterial Community Structure and Predicted Function in Wheat Soil From the North China Plain Are Closely Linked With Soil and Plant Characteristics After Seven Years of Irrigation and Nitrogen Application.

Ma Geng G Kang Juan J Wang Jiarui J Chen Yulu Y Lu Hongfang H Wang Lifang L Wang Chenyang C Xie Yingxin Y Ma Dongyun D Kang Guozhang G

Frontiers in microbiology 20200331

The influence of water and nitrogen (N) management on wheat have been investigated, but studies on the impact of long-term interactive water and N management on microbial structure and function are limited. Soil chemical properties and plants determine the soil microbial communities whose functions involved in nutrient cycling may affect plant productivity. There is an urgent need to elucidate the underlying mechanisms to optimize these microbial communities for agricultural sustainability in th ...[more]

PMID: 32296405

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Project description:Scholars have proposed the practice of split nitrogen fertilizer application (SNFA), which has proven to be an effective approach for enhancing nitrogen use efficiency. However, the combined effects of SNFA on wheat plant nitrogen use efficiency, ammonia (NH3) emission flux, as well as the rates of nitrification and denitrification in different ecosystems remain unclear. Meanwhile, few studies have sought to understand the effects of the split nitrogen fertilizer method under water-saving irrigation technology conditions on nitrogen loss. The current study assessed soil NH3 volatilization, nitrification, and denitrification intensities, as well as the abundance of nitrogen cycle-related functional genes following application of different treatments. Specifically, we applied a nitrogen rate of 240 kg⋅ha-1, and the following fertilizer ratios of the percent base to that of topdressing under water-saving irrigation: N1 (basal/dressing, 100/0%), N2 (basal/dressing, 70/30%), N3 (basal/dressing, 50/50%), N4 (basal/dressing, 30/70%), and N5 (basal/dressing, 0/100%). N3 treatment significantly reduced NH3 volatilization, nitrification, and denitrification intensities, primarily owing to the reduced reaction substrate concentration (NO3 - and NH4 +) and abundance of functional genes involved in the nitrogen cycle (amoA-AOB, nirK, and nirS) within the wheat-land soil. 15N tracer studies further demonstrated that N3 treatments significantly increased the grain nitrogen accumulation by 9.50-28.27% compared with that under other treatments. This increase was primarily due to an increase in the amount of nitrogen absorbed by wheat from soil and fertilizers, which was caused by an enhancement in total nitrogen uptake (7.2-21.81%). Overall, N3 treatment (basal/dressing, 50/50%) was found to effectively reduce nitrogen loss through NH3 volatilization, nitrification and denitrification while improving nitrogen uptake by wheat. Thus, its application will serve to further maximize the yield and provide a fertilization practice that will facilitate cleaner wheat production in the North China Plain.

Project description:The North China Plain is one of the most important grain production regions in China, but is facing serious water shortages. To achieve a balance between water use and the need for food self-sufficiency, new water efficient irrigation strategies need to be developed that balance water use with farmer net return. The Crop Environment Resource Synthesis Wheat (CERES-Wheat model) was calibrated and evaluated with two years of data which consisted of 3-4 irrigation treatments, and the model was used to investigate long-term winter wheat productivity and water use from irrigation management in the North China Plain. The calibrated model simulated accurately above-ground biomass, grain yield and evapotranspiration of winter wheat in response to irrigation management. The calibrated model was then run using weather data from 1994-2016 in order to evaluate different irrigation strategies. The simulated results using historical weather data showed that grain yield and water use was sensitive to different irrigation strategies including amounts and dates of irrigation applications. The model simulated the highest yield when irrigation was applied at jointing (T9) in normal and dry rainfall years, and gave the highest simulated yields for irrigation at double ridge (T8) in wet years. A single simulated irrigation at jointing (T9) produced yields that were 88% compared to using a double irrigation treatment at T1 and T9 in wet years, 86% of that in normal years, and 91% of that in dry years. A single irrigation at jointing or double ridge produced higher water use efficiency because it obtained higher evapotranspiration. The simulated farmer irrigation practices produced the highest yield and net income. When the cost of water was taken into account, limited irrigation was found to be more profitable based on assumptions about future water costs. In order to increase farmer income, a subsidy will likely be needed to compensate farmers for yield reductions due to water savings. These results showed that there is a cost to the farmer for water conservation, but limiting irrigation to a single irrigation at jointing would minimize impact on farmer net return in North China Plain.

Project description:Spatial variation of soil respiration (Rs) in cropland ecosystems must be assessed to evaluate the global terrestrial carbon budget. This study aims to explore the spatial characteristics and controlling factors of Rs in a cropland under winter wheat and summer maize rotation in the North China Plain. We collected Rs data from 23 sample plots in the cropland. At the late jointing stage, the daily mean Rs of summer maize (4.74 ?mol CO2 m-2 s-1) was significantly higher than that of winter wheat (3.77?mol CO2 m-2 s-1). However, the spatial variation of Rs in summer maize (coefficient of variation, CV = 12.2%) was lower than that in winter wheat (CV = 18.5%). A similar trend in CV was also observed for environmental factors but not for biotic factors, such as leaf area index, aboveground biomass, and canopy chlorophyll content. Pearson's correlation analyses based on the sampling data revealed that the spatial variation of Rs was poorly explained by the spatial variations of biotic factors, environmental factors, or soil properties alone for winter wheat and summer maize. The similarly non-significant relationship was observed between Rs and the enhanced vegetation index (EVI), which was used as surrogate for plant photosynthesis. EVI was better correlated with field-measured leaf area index than the normalized difference vegetation index and red edge chlorophyll index. All the data from the 23 sample plots were categorized into three clusters based on the cluster analysis of soil carbon/nitrogen and soil organic carbon content. An apparent improvement was observed in the relationship between Rs and EVI in each cluster for both winter wheat and summer maize. The spatial variation of Rs in the cropland under winter wheat and summer maize rotation could be attributed to the differences in spatial variations of soil properties and biotic factors. The results indicate that applying cluster analysis to minimize differences in soil properties among different clusters can improve the role of remote sensing data as a proxy of plant photosynthesis in semi-empirical Rs models and benefit the acquisition of Rs in cropland ecosystems at large scales.

Project description:BACKGROUND:The relative importance of stochasticity versus determinism in soil bacterial communities is unclear, as are the possible influences that alter the balance between these. Here, we investigated the influence of spatial scale on the relative role of stochasticity and determinism in agricultural monocultures consisting only of wheat, thereby minimizing the influence of differences in plant species cover and in cultivation/disturbance regime, extending across a wide range of soils and climates of the North China Plain (NCP). We sampled 243 sites across 1092 km and sequenced the 16S rRNA bacterial gene using MiSeq. We hypothesized that determinism would play a relatively stronger role at the broadest scales, due to the strong influence of climate and soil differences in selecting many distinct OTUs of bacteria adapted to the different environments. In order to test the more general applicability of the hypothesis, we also compared with a natural ecosystem on the Tibetan Plateau. RESULTS:Our results revealed that the relative importance of stochasticity vs. determinism did vary with spatial scale, in the direction predicted. On the North China Plain, stochasticity played a dominant role from 150 to 900 km (separation between pairs of sites) and determinism dominated at more than 900 km (broad scale). On the Tibetan Plateau, determinism played a dominant role from 130 to 1200 km and stochasticity dominated at less than 130 km. Among the identifiable deterministic factors, soil pH showed the strongest influence on soil bacterial community structure and diversity across the North China Plain. Together, 23.9% of variation in soil microbial community composition could be explained, with environmental factors accounting for 19.7% and spatial parameters 4.1%. CONCLUSIONS:Our findings revealed that (1) stochastic processes are relatively more important on the North China Plain, while deterministic processes are more important on the Tibetan Plateau; (2) soil pH was the major factor in shaping soil bacterial community structure of the North China Plain; and (3) most variation in soil microbial community composition could not be explained with existing environmental and spatial factors. Further studies are needed to dissect the influence of stochastic factors (e.g., mutations or extinctions) on soil microbial community distribution, which might make it easier to predictably manipulate the microbial community to produce better yield and soil sustainability outcomes.

Project description:The accuracy of nitrogen (N) diagnosis is essential to improve N use efficiency. The standard critical N concentration (standard Nc) dilution curves, an expression of the dynamics of N uptake and dry matter accumulation in plants, are widely used to diagnose the N status of crops. Several standard Nc dilution curves were proposed and validated for several crops, based on experiments involving different N fertilizer treatments. However, standard Nc dilution curves are affected by crop water status, e.g., resulting from differences in irrigation management. This paper aimed at developing a N diagnostic model under the coupling effect of irrigation and fertilizer managements. For this purpose, Nc dilution curves were developed under different irrigation rates. Additionally, plant water content (PWC), leaf water content (LWC), leaf area index (LAI), equivalent water thickness (EWT), and leaf area duration (LAD) were introduced into the model, to construct a modified Nc (mNc) dilution curve. The mNc dilution curves were designed using the principle of hierarchical linear model (HLM), introducing aboveground dry biomass (AGB) as the first layer of information, whereas the second layer of information included the different agronomic variables (PWC, LWC, LAI, EWT, and LAD). The results showed that parameters "a" and "b" of the standard Nc dilution curves ranged from 5.17 to 6.52 and -0.69 to -0.38 respectively. Parameter "a" was easily affected by different management conditions. The performance of standard Nc dilution models obtained by the cross-validation method was worse than that of mNc dilution models. The Nc dilution curve based on 4 years of data was described by the negative power equation Nc = 5.05 × AGB-0.47, with R 2 and nRMSE of 0.63 and 0.21, respectively. The mNc dilution curve considers different treatments and was represented by the equation mNc = a×AGB-b , where a = 2.09 × PWC + 3.24, b = -0.02 × LAI + 0.51, with R 2 and nRMSE of 0.79 and 0.13, respectively. For winter wheat, C3 crop, there would be a few problems in using standard Nc dilution methods to guide field management, however, this study provides a reliable method for constructing mNc dilution curves under different water and N fertilizer management. Due to the significant differences in hereditary, CO2 fixation efficiency and N metabolism pathways for C3 and C4 crops, the construction of mNc dilution curve suitable for different N response mechanisms will be conducive to the sustainable N management in crop plants.

Dataset Information

Bacterial Community Structure and Predicted Function in Wheat Soil From the North China Plain Are Closely Linked With Soil and Plant Characteristics After Seven Years of Irrigation and Nitrogen Application.

Publications

Bacterial Community Structure and Predicted Function in Wheat Soil From the North China Plain Are Closely Linked With Soil and Plant Characteristics After Seven Years of Irrigation and Nitrogen Application.

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