Understanding the contribution of soil microbial communities to ecosystem processes is critical for predicting terrestrial ecosystem feedbacks under changing climate. Our current understanding lacks ...a consistent strategy to formulate the linkage between microbial systems and ecosystem processes due to the presumption of functional redundancy in soil microbes. Here we present a global soil microbial metagenomic analysis to generalize patterns of microbial taxonomic compositions and functional potentials across climate and geochemical gradient. Our analyses show that soil microbial taxonomic composition varies widely in response to climate and soil physicochemical gradients, while microbial functional attributes based on metagenomic gene abundances are redundant. Among 17 climate zones, microbial taxonomic compositions were more distinct than functional potentials, as climate and edaphic properties showed more significant influence on microbial taxonomic compositions than on functional potentials. Microbial taxonomies formed a larger and more complex co-occurrence network with more module structures than functional potentials. Functional network was strongly inter-connected among different categories, whereas taxonomic network was more positively interactive in the same taxonomic groups. This study provides strong evidence to support the hypothesis of functional redundancy in soil microbes, as microbial taxonomic compositions vary to a larger extent than functional potentials based on metagenomic gene abundances in terrestrial ecosystems across the globe.
Well-acclimatized nitrifiers in high-nitrate agricultural soils can quickly nitrify NH4(+) into NO3(-) subject to leaching and denitrifying loss. A 120-day incubation experiment was conducted using a ...greenhouse soil to explore the fates of applied fertilizer N entering into seven soil N pools and to examine if green manure (as ryegrass) co-application can increase immobilization of the applied N into relatively stable N pools and thereby reduce NO3(-) accumulation and loss. We found that 87-92% of the applied (15)N-labelled NH4(+) was rapidly recovered as NO3(-) since day 3 and only 2-4% as microbial biomass and soil organic matter (SOM), while ryegrass co-application significantly decreased its recovery as NO3(-) but enhanced its recovery as SOM (17%) at the end of incubation. The trade-off relationship between (15)N recoveries in microbial biomass and SOM indicated that ryegrass co-application stabilized newly immobilized N via initial microbial uptake and later breakdown. Nevertheless, ryegrass application didn't decrease soil total NO3(-) accumulation due to its own decay. Our results suggest that green manure co-application can increase immobilization of applied N into stable organic N via microbial turnover, but the quantity and quality of green manure should be well considered to reduce N release from itself.
Low molecular weight organic acids exuded by plants roots enhance inorganic Pᵢ release into soil solution and thereby increases plant‐available Pi in soils. Low molecular weight organic acids may ...also induce organic P (Pₒ) release into soil solution, but kinetics of both Pi and Po displacement from the soil matrix into soil solution of agricultural soils is poorly understood, and the mechanism for Pₒ release is not well explained. This study used kinetic experiments to determine the concentrations and release rates of Pᵢ and Pₒ induced by oxalic acid, citric acid, and malic acid in calcareous, neutral and acidic soils. Kinetic data were well described by Elovich (r² = 0.801–0.993, P < 0.001) and power functions models (r² = 0.721–0.977, P < 0.001). Low molecular weight organic acids at 10 mmol kg⁻¹ soil induced the exponential release of both Pᵢ and Pₒ, which reached a plateau approx. 480– 2,880 min after the start of the experiment. Cumulative Pₒ release induced by low molecular weight organic acids was ranked as oxalic acid (0.63–3.17 mg kg⁻¹) > citric acid (0.61–2.82 mg kg⁻¹) > malic acid (0.52–1.76 mg kg⁻¹) and mainly resulted from the release of labile Pₒ (NaHCO₃‐Pₒ) regardless of soil type. By contrast, oxalic acid was most effective in enhancing Pᵢ release from the HCl‐Pᵢ (Ca‐Pᵢ) fraction of the calcareous soil, and citric acid was most effective in releasing Pᵢ from the NaOH‐Pᵢ (Fe/Al‐Pᵢ) fraction of the neutral and acidic soils. Therefore, the mechanism for the kinetics of Pₒ release induced by low molecular weight organic acids is ascribed to their ability to mobilize the labile Pₒ (NaHCO₃‐Pₒ) rather than their ability to chelate cations (i.e., Fe³⁺, Al³⁺) bound to Pₒ in soil.
To reach the target yield of crops, nutrient management is essential. Selecting the appropriate prediction model and adjusting the nutrient supply based on the actual situation can effectively ...improve the nutrient utilization efficiency, crop yield, and product quality. Therefore, a prediction model of the NPK fertilizer application rate for greenhouse tomatoes under the target yield was studied in this study. Under low, medium, and high soil fertility conditions, a neural network prediction model based on the sparrow search algorithm (SSA-NN), a neural network prediction model based on the improved sparrow search algorithm (ISSA-NN), and a neural network prediction model based on the hybrid algorithm (HA-NN) were used to predict the NPK fertilizer application rate for greenhouse tomatoes. The experimental results indicated that the evaluation indexes (i.e., the mean square error (MSE), explained variance score (EVS), and coefficient of determination (R2)) of the HA-NN prediction model proposed in this study were superior than the SSA-NN and ISSA-NN prediction models under three different soil fertility conditions. Under high soil fertility, compared with the SSA-NN prediction model, the MSE of the ISSA-NN and HA-NN prediction models decreased to 0.007 and 0.005, respectively; the EVS increased to 0.871 and 0.908, respectively; and the R2 increased to 0.862 and 0.899, respectively. This study showed that the HA–NN prediction model was superior in predicting the NPK fertilizer application rate for greenhouse tomatoes under three different soil fertility conditions. Due to the significance of NPK fertilizer application rate prediction for greenhouse tomatoes, this technique is expected to bring benefits to agricultural production management and decision support.
Tomato yield prediction plays an important role in agricultural production planning and management, market supply and demand balance, and agricultural risk management. To solve the problems of low ...accuracy and high uncertainty of tomato yield prediction methods in solar greenhouses, based on experimental data for water and fertilizer consumption by greenhouse tomatoes in different regions over many years, this paper investigated the prediction models of greenhouse tomato yields under three different soil fertility conditions (low, medium, and high). Under these three different soil fertility conditions, greenhouse tomato yields were predicted using the neural network prediction model (NN), the neural network prediction model based on particle swarm optimization (PSO–NN), the neural network prediction model based on an adaptive inertia weight particle swarm optimization algorithm (AIWPSO–NN), and the neural network prediction model based on the improved particle swarm optimization algorithm (IPSO–NN). The experimental results demonstrate that the evaluation indexes (mean square error, mean absolute error, and R2) of the IPSO–NN prediction model proposed in this paper were superior to the other three prediction models (i.e., NN prediction model, AIWPSO–NN prediction model, and IPSO–NN prediction model) under three different soil fertility conditions. Among them, compared with the NN prediction model, the MSE of the other three prediction models under high soil fertility decreased to 0.0082, 0.0041, and 0.0036; MAE decreased to 0.0759, 0.0511, and 0.0489; R2 decreased to 0.8641, 0.9323, and 0.9408. These results indicated that the IPSO–NN prediction model had a higher predictive ability for greenhouse tomato yields under three different soil fertility conditions. In view of the important role of tomato yield prediction in greenhouses, this technology may be beneficial to agricultural management and decision support.
Although the influence of ozone (O(3)) on plants has been well studied in agroecosystems, little is known about the effect of elevated O(3) (eO(3)) on soil microbial functional communities. Here, we ...used a comprehensive functional gene array (GeoChip 3.0) to investigate the functional composition, and structure of rhizosphere microbial communities of Yannong 19 (O(3)-sensitive) and Yangmai 16 (O(3)-relatively sensitive) wheat (Triticum aestivum L.) cultivars under eO(3). Compared with ambient O(3) (aO(3)), eO(3) led to an increase in soil pH and total carbon (C) percentages in grain and straw of wheat plants, and reduced grain weight and soil dissolved organic carbon (DOC). Based on GeoChip hybridization signal intensities, although the overall functional structure of rhizosphere microbial communities did not significantly change by eO(3) or cultivars, the results showed that the abundance of specific functional genes involved in C fixation and degradation, nitrogen (N) fixation, and sulfite reduction did significantly (P<0.05) alter in response to eO(3) and/or wheat cultivars. Also, Yannong 19 appeared to harbor microbial functional communities in the rhizosphere more sensitive in response to eO(3) than Yangmai 16. Additionally, canonical correspondence analysis suggested that the functional structure of microbial community involved in C cycling was largely shaped by soil and plant properties including pH, DOC, microbial biomass C, C/N ratio and grain weight. This study provides new insight into our understanding of the influence of eO(3) and wheat cultivars on soil microbial communities.
Few studies have investigated the extractable organic nitrogen (EON) formation mechanisms, and the sources of EON have long been debated. Using 15N labeling, we performed a 120-day laboratory ...incubation experiment to explore the dynamic contributions of different types of added N (ammonium-N, ryegrass-N and their combination) to soil EON and the role that microorganisms play in N transformation into EON. We show that the 15N abundances and recoveries in soil EON pool were relatively low during the incubation, except the first hours after ryegrass addition in 15N-ryegrass addition treatments. In general, most of the EON during the incubation was soil derived, and both ammonium-N (80 mg kg−1) and ryegrass-N (160 mg kg−1) additions made minor contributions (3–4% and 8–13% during day 1–120) to the soil EON pool. Moreover, along with the decline in 15N recoveries in microbial biomass nitrogen (MBN) pool, the lost MB15N did not enter into the EO15N pool. Our study demonstrates 1) that EON is a stable N pool in agricultural soil and is less affected by exogenous N addition and 2) that microbial N uptake and release processes contribute little to the soil EON pool.
•The sources and dynamics of soil EON were studied using 15N labeling.•< 2% of the added N was recovered in the EON pool from the 2nd day after tracer addition.•Detected soil EON is a stable pool and mainly composed of recalcitrant components.•Microbial N uptake and release processes contributed little to soil EON production.
Time-of-flight secondary ion mass spectrometry and atomic force microscopy are employed to characterize a wedge-shaped crater eroded by a 40-keV C60 + cluster ion beam on an organic film of Irganox ...1010 doped with Irganox 3114 delta layers. From an examination of the resulting surface, the information about depth resolution, topography, and erosion rate can be obtained as a function of crater depth for every depth in a single experiment. It is shown that when measurements are performed at liquid nitrogen temperature, a constant erosion rate and reduced bombardment induced surface roughness is observed. At room temperature, however, the erosion rate drops by ∼1/3 during the removal of the 400 nm Irganox film and the roughness gradually increased to from 1 nm to ∼4 nm. From SIMS lateral images of the beveled crater and AFM topography results, depth resolution was further improved by employing glancing angles of incidence and lower primary ion beam energy. Sub-10 nm depth resolution was observed under the optimized conditions on a routine basis. In general, we show that the wedge-crater beveling is an important tool for elucidating the factors that are important for molecular depth profiling experiments.
Large nitrogen (N) losses during fertilization in agricultural production may result in energy wastage, soil and water contamination, and potentially influence crop development. Thus, with the help ...of a 15N-labeled tracer, we carried out a field monitoring analysis of NH3 emissions in a long-term (9-year) conservation tillage agroecosystem of Mollisols in northeast China, in order to determine whether a no-tillage regime and four levels of stover mulching (0%, 33%, 67%, and 100%), combined with urease and nitrification inhibitors, could improve fertilizer utilization efficiency in agricultural systems by reducing ammonia volatilization. Our results showed that in comparison with ridge tillage, no-tillage with stover mulching levels of 33%, 67%, and 100% significantly reduced NH3 emission rates and cumulative volatilization from 159.67 to 130.42 g N ha−1 and 15N-NH3 cumulative volatilization emission by 26% (on average). Furthermore, the application of urease and nitrification inhibitors significantly reduced 15N-NH3 volatilization levels from 1.19 to 0.98 g N ha−1. Our research results demonstrate that a long-term no-tillage regime and straw mulching can significantly reduce NH3 volatilization in fertilizers. Furthermore, when combined with the use of urease and nitrification inhibitors, these practices further enhance the reduction in NH3 volatilization. Although the volatilization of 15N-NH3 is minimally studied in Mollisols, these findings provide a solid foundation for improving fertilizer utilization efficiency, reducing crop production costs and mitigating subsequent environmental pollution.
Soil processes are driven by soil organisms and their interactions with plants and soil abiotic conditions. Climate changes may directly or indirectly alter soil processes and the organisms mediating ...these processes. Although aboveground influences of ozone have been studied widely on agroecosystems, the effects on belowground processes are poorly understood. This study aimed to investigate the effects of elevated ozone concentration O3 on the components of soil microbial food webs and compare their responses between ozone-sensitive and ozone-tolerant wheat cultivars. The responses of soil biota to elevated O3 varied between the two wheat cultivars. Fungal PLFA and the fungi to bacteria ratio decreased following elevated O3, especially in the rhizospheric soil of ozone-tolerant wheat. Nematode functional guilds were sensitive to elevated O3 and cultivar effects. At wheat jointing stage, bacterivores belonging to K-strategies decreased following elevated O3, while fungivores exhibited a reverse trend. The abundance of flagellates decreased in ozone-tolerant wheat, but increased in ozone-sensitive wheat following elevated O3. However, an opposite trend was found in the bacterivores belonging to r-strategies. In conclusion, wheat cultivars play an important role in determining the effects of elevated O3 on soil food web. The responses of soil biota to elevated O3 were greater in ozone-tolerant wheat than in ozone-sensitive wheat, which may in turn have influenced soil organic matter decomposition and nutrient turnover.
► Wheat cultivars are important in determining soil biota responses to elevated O3. ► Soil microbial communities were sensitive to elevated O3 in O3-tolerant cultivar. ► Higher abundance of flagellates was found in O3-tolerant cultivar. ► Nematode functional guilds were sensitive to elevated O3 and wheat cultivars.
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