Search Results (2,910)

Altered precipitation regimes, both in intensity and duration, can profoundly influence the structure and function of soil microbial communities, yet the patterns and drivers of these responses remain unclear across ecosystem types. Here, using data exclusively from 101 field experiments conducted in China (yielding 695 observations), we investigated the impacts of altered precipitation on soil microbial biomass, diversity, and enzymatic activity in forest and grassland ecosystems. Soil microbial biomass carbon (MBC) and nitrogen (MBN) increased in response to precipitation addition, particularly in grasslands, but they decreased under reduced precipitation, with the decline being more pronounced in forests. The magnitude and duration of precipitation manipulation significantly influenced these effects, with moderate and long-term changes producing divergent responses. Bacterial diversity was largely unaffected by all precipitation treatments, whereas fungal diversity decreased significantly under intense and short-term reductions in precipitation. Enzyme activities exhibited the following element-specific patterns: carbon- and phosphorus-cycling enzymes and antioxidant enzymes were suppressed by precipitation reduction, especially in grasslands, while nitrogen-cycling enzymes showed no consistent response. Moreover, microbial responses were significantly shaped by environmental factors, including mean annual temperature (MAT), mean annual precipitation (MAP), and elevation. Our region-specific analysis highlights precipitation-driven microbial dynamics across China’s diverse climatic and ecological conditions. These findings demonstrate that soil microbial communities respond asymmetrically to precipitation changes, with responses shaped by both ecosystem type and climatic context, underscoring the need to account for environmental heterogeneity when predicting belowground feedback to climate change. Full article

Organic farming systems, which prohibit synthetic fertilizers, often rely on legumes for their ability to fix atmospheric nitrogen (N). In orchards, legumes can be established as cover crops between tree rows to enhance nutrient cycling. This study evaluated the effects of two legume cover crops, white lupin (Lupinus albus L.) and hairy vetch (Vicia villosa Roth), compared to a Control treatment with conventional tillage, which is the most commonly used method of soil management in the region, in an organically managed almond [Prunus dulcis (Mill.) D.A.Webb] orchard compliant with European Union standards, in an experiment arranged as a completely randomized design. In the first year, kernel yield was highest in the Control treatment (404 kg ha⁻¹), while significantly lower yields were recorded for white lupin (246 kg ha⁻¹) and hairy vetch (283 kg ha⁻¹), likely due to competition for resources between cover crops and trees. In the second year, however, the trend reversed, with cover crop treatments yielding significantly more (Lupin: 313 kg ha⁻¹; Vetch: 296 kg ha⁻¹) than the Control (199 kg ha⁻¹). The cover crops accumulated over 150 kg ha⁻¹ of N in their tissues, enhancing soil N availability and increasing N concentrations in almond leaves. In addition to N, cover crops influenced the cycling of other nutrients, increasing potassium (K) and boron (B) concentrations while reducing calcium (Ca) and manganese (Mn) in plant tissues. Despite being derived from a two-year study, these results highlight the complexity of interpreting cover crop effects, underscoring the need for further long-term research to provide more comprehensive guidance to growers. Full article

Nitrogen dioxide (NO₂) plays a crucial role in environmental processes and public health. In recent years, NO₂ pollution has been monitored using a combination of in situ measurements and satellite remote sensing, supported by the development of advanced retrieval algorithms. With advancements in satellite technology, large-scale NO₂ monitoring is now feasible through instruments such as GOME-2C and TROPOMI. However, the fixed local overpass times of polar-orbiting satellites limit their ability to capture the complete diurnal cycle of NO₂, introducing uncertainties in emission estimation and pollution trend analysis. In this study, we evaluated differences in NO₂ observations between GOME-2C (morning overpass at ~09:30 LT) and TROPOMI (afternoon overpass at ~13:30 LT) across three representative regions—East Asia, Central Africa, and Europe—that exhibit distinct emission sources and atmospheric conditions. By comparing satellite-derived tropospheric NO₂ column densities with ground-based measurements from the Pandora network, we analyzed spatial distribution patterns and seasonal variability in NO₂ concentrations. Our results show that East Asia experiences the highest NO₂ concentrations in densely populated urban and industrial areas. During winter, lower boundary layer heights and weakened photolysis processes lead to stronger accumulation of NO₂ in the morning. In Central Africa, where biomass burning is the dominant emission source, afternoon fire activity is significantly higher, resulting in a substantial difference (1.01 × 10¹⁶ molecules/cm²) between GOME-2C and TROPOMI observations. Over Europe, NO₂ pollution is primarily concentrated in Western Europe and along the Mediterranean coast, with seasonal peaks in winter. In high-latitude regions, weaker solar radiation limits the photochemical removal of NO₂, causing concentrations to continue rising into the afternoon. These findings demonstrate that differences in polar-orbiting satellite overpass times can significantly affect the interpretation of daily NO₂ variability, especially in regions with strong diurnal emissions or meteorological patterns. This study highlights the observational limitations of fixed-time satellites and offers an important reference for the future development of geostationary satellite missions, contributing to improved strategies for NO₂ pollution monitoring and control. Full article

In order to precisely improve the quality of major tree species in northern China, near-natural differentiated management has been gradually introduced into forestry practice, aiming to optimize forest structure, enhance forest quality, and promote nutrient cycling and water conservation. As an essential element of forest ecosystems, soil microbes contribute to biodiversity preservation and nutrient turnover in soils. This study selected three typical forest types (Quercus acutissima forest, Pinus tabulaeformis forest, and Pinus tabulaeformis × Quercus mixed forest) that have been managed with target trees on Zhongtiao Mountain. Using 16S/ITS rRNA high-throughput sequencing, this study systematically assessed the influences of forest type and soil depth (0–60 cm) on the soil properties and microbial communities. The results showed that the fungal alpha diversity indices were the highest in Pinus tabulaeformis forest, which decreased with soil depth. Actinobacteriota exhibited the greatest relative abundance in mixed forest, whereas Ascomycota predominated in the Pinus tabulaeformis forest. The microbial co-occurrence network exhibited greater complexity compared to the pure forest. Microbial carbon and nitrogen cycling functions showed strong correlation with soil pH and nutrient levels. Symbiotrophs dominated the fungal community, and ectomycorrhizae were significantly abundant in mixed forests. pH is the dominant factor driving changes in microbial communities. In summary, the mixed forest improved soil nutrients, enhanced the complexity of microbial networks, and supported higher ectomycorrhizal abundance. These findings provide practical guidance for improving soil health and stability of forest ecosystems through near-natural management. Full article

Global agricultural intensification has exacerbated soil compaction and nitrogen (N) inefficiency, thereby threatening sustainable crop production. Sub-soiling, a tillage technique that fractures subsurface layers while preserving surface structure, offers potential solutions by modifying soil physical properties and enhancing microbial-mediated N cycling. This study investigated the effects of subsoiling depth (0, 20, and 40 cm) on soil microbial communities and N transformations in a semi-arid maize system in China. The results demonstrated that subsoiling to a depth of 40 cm (D2) significantly enhanced the retention of nitrate-N and ammonium-N, which correlated with improved soil porosity and microbial activity. High-throughput 16S rDNA sequencing revealed subsoiling depth-driven reorganization of microbial communities, with D2 increasing the abundance of Proteobacteria (+11%) and ammonia-oxidizing archaea (Nitrososphaeraceae, +19.9%) while suppressing denitrifiers (nosZ gene: −41.4%). Co-occurrence networks indicated greater complexity in microbial interactions under subsoiling, driven by altered aeration and carbon redistribution. Functional gene analysis highlighted a shift from denitrification to nitrification-mineralization coupling, with D2 boosting maize yield by 9.8%. These findings elucidate how subsoiling depth modulates microbiome assembly to enhance N retention, providing a mechanistic basis for optimizing tillage practices in semi-arid agroecosystems. Full article

This study presents a four-year evaluation (2020–2024) of an integrated climate mitigation project on a pig farm in Ávila, Spain, at an elevation of over 1100 m above sea level with continental climate conditions. The project aimed to reduce greenhouse gas emissions (GHG) and nitrogen pollution by implementing solid–liquid filtration followed by biological treatment in a 625 m³ Sequencing Batch Reactor (SBR) operating under a nitrification–denitrification (N-DN) regime. The SBR carried out four daily cycles, alternating aerobic and anoxic phases, with 5 and 8 m³ inlets. Aeration intensity and redox potential were continuously monitored to optimize bacterial activity. Analytical parameters (pH, electrical conductivity, solids content, nitrogen, phosphorus, and potassium) were measured using ISO methods and tracked frequently. Annual emission reductions were 75% for N₂O, up to 97% for NH₃, and 80% for N₂. In the summer months, we observed higher efficiency reduction for N₂, NH₃, and NO₂. Additionally, there was a 75% average reduction for COD and up to 92% for total GHG emissions. This real-world case study highlights the effectiveness of SBR-based N-DN systems for nutrient removal and emission reduction in high-altitude, climate-sensitive regions, contributing to EU nitrate directive compliance and circular economy practices. Full article

This study demonstrates that hydrogen enrichment in lean-burn spark-ignition engines can simultaneously improve three key performance metrics, thermal efficiency, combustion stability, and nitrogen oxide emissions, without requiring modifications to the engine hardware or ignition timing. This finding offers a novel control approach to a well-documented trade-off in existing research, where typically only two of these factors are improved at the expense of the third. Unlike previous studies, the present work achieves simultaneous improvement of all three metrics without hardware modification or ignition timing adjustment, relying solely on the optimization of the air–fuel equivalence ratio $\lambda$. Experiments were conducted on a six-cylinder engine for combined heat and power application, fueled with hydrogen–natural gas blends containing up to 30% hydrogen by volume. By optimizing only the air–fuel equivalence ratio, it was possible to extend the lean-burn limit from $\lambda \approx 1.6$ to $\lambda >1.9$, reduce nitrogen oxide emissions by up to 70%, enhance thermal efficiency by up to 2.2 percentage points, and significantly improve combustion stability, reducing cycle-by-cycle variationsfrom 2.1% to 0.7%. A defined $\lambda$ window was identified in which all three key performance indicators simultaneously meet or exceed the natural gas baseline. Within this window, balanced improvements in nitrogen oxide emissions, efficiency, and stability are achievable, although the individual maxima occur at different operating points. Cylinder pressure analysis confirmed that combustion dynamics can be realigned with original equipment manufacturer characteristics via mixture leaning alone, mitigating hydrogen-induced pressure increases to just 11% above the natural gas baseline. These results position hydrogen as a performance booster for natural gas engines in stationary applications, enabling cleaner, more efficient, and smoother operation without added system complexity. The key result is the identification of a $\lambda$ window that enables simultaneous optimization of nitrogen oxide emissions, efficiency, and combustion stability using only mixture control. Full article

Microbial communities, as critical functional components of riverine ecosystems, play a pivotal role in biogeochemical cycles and water quality regulation. The South-to-North Water Diversion Middle Route Project (SNWD-MRP) is a major cross-basin water transfer initiative, and bacteria are essential for the stability of water quality in the project. This study employed environmental DNA (eDNA) metabarcoding targeting the 16S rRNA gene to investigate spatiotemporal variations in water quality and bacterial communities along the SNWD-MRP during summer and winter. Integrated analyses, including redundancy analysis (RDA), Mantel tests, and ecological network modeling, were applied to unravel the driving mechanisms of microbial succession. The water quality along the SNWD-MRP is generally classified as Grade I, with significant seasonal variations in water quality parameters and microbial community composition. In the summer, higher temperatures lead to an increased abundance of cyanobacteria. In contrast, during the winter, lower water temperatures and higher dissolved oxygen levels result in the dominance of Pseudomonas and Bacillota species. RDA identified the permanganate index as the primary driver of microbial composition across seasons, with total phosphorus and total nitrogen having a greater influence in winter. Mantel tests highlighted significant correlations between Cyanobacteria and total phosphorus during winter. Ecological network analysis revealed that the complexity and connectivity of the winter network increased, likely due to suitable nutrient levels rendering the microbial network more complex and stable. These findings underscore the synergistic effects of temperature and nutrient availability on microbial succession, providing actionable insights for optimizing water quality management and ecological stability in large-scale water diversion systems. Full article

The development of new techniques to improve crop management, especially through precision agriculture methods and innovations, is crucial for increasing crop yield and ensuring high-quality production. The horticultural sector is particularly vulnerable to inefficiencies in crop management due to the complex and costly processes required for producing marketable products. Optimal nutritional inputs and effective disease management are crucial for maintaining commercial standards. This two-year study investigated the physiological differences between organic and conventional crop management of the Sardinian `Spinoso sardo’ artichoke ecotype (Cynara cardunculus var. scolymus L.) by integrating a multiplex force-A (MFA) fluorometer and unmanned aerial systems (UASs) equipped with a multispectral camera capable of analysing the NDVI vegetation index. Using both proximal and remote sensing instruments, physiological and nutritional variations in the growth cycle of artichokes were identified, distinguishing between traditional and two organic management practices. The two-year MFA experiment revealed physiological variability and different trends among the three management practices, indicating that MFA proximal sensing is a valuable tool for detecting physiological differences, particularly in chlorophyll activity and nitrogen content. In contrast, the UAS survey was less effective at distinguishing between management types, likely due to its limited use during the second year and the constrained timeframe of the multitemporal analysis. The analysis of the MFA fluorimetric indices suggested significant differences among the plots monitored due to the ANOVA statistical analysis and Tukey test, showing greater adaptability of the conventional system in managing production inputs, unlike the organic systems, which showed higher variability within the plots and across the survey years, indicating aleatory trends due to differences in crop management. Full article

Volvariella volvacea, a fungal species of Volvariella within the Pluteaceae family, is predominantly cultivated in southern China. Polysaccharides, the primary bioactive constituents of V. volvacea, exhibit diverse pharmacological activities. However, current cultivation practices face challenges due to the genetic heterogeneity of strains, leading to inconsistent content and compositional variability of polysaccharides and other functional components. ARTP, denoting atmospheric and room-temperature plasma, is a technology capable of generating plasma jets at ambient pressure with temperatures ranging from 25 to 40 °C. These jets feature high concentrations of highly reactive species, including but not limited to excited-state helium atoms, oxygen atoms, nitrogen atoms, and OH radicals. This study aims to develop high-yielding exopolysaccharide (EPS) strains through integrated ARTP mutagenesis and genome shuffling, thereby overcoming current cultivation bottlenecks. ARTP mutagenesis and genome shuffling significantly boosted EPS production in V. volvacea. ARTP generated nine stable mutants with >20% higher EPS yields. Subsequent genome shuffling (three rounds of protoplast fusion) produced the hybrid strain SL212, which achieved 46.85 g/L of EPS, an 111.67% increase over that of the parent strain under identical conditions. Metabolomics and transcriptomics analyses revealed that differential metabolites and genes were mainly enriched in galactose metabolism, ABC transporter pathways, and the tricarboxylic acid cycle. These pathways enhance monosaccharide biosynthesis and generate ATP, providing both precursors and energy for polysaccharide polymerization, thereby driving EPS overproduction. Preliminary mechanistic analysis identified the key contributing factors driving the elevated polysaccharide biosynthesis. Full article

Nitrate reduction serves as a pivotal process in the global nitrogen cycle, playing a crucial role in natural ecosystems and industrial applications. Although the genus Alteromonas is not traditionally regarded as a nitrate reducer, several Alteromonas strains have recently been found to be capable of doing so. However, the evolutionary trajectory of this capability remains undiscovered. In this study, 32 bacterial strains were isolated and cultivated from the tidal flat sediment in Hangzhou Bay and classified into the classes Cytophagia (n = 2), Alphaproteobacteria (n = 2), Gammaproteobacteria (n = 17), Flavobacteriia (n = 5), and Bacilli (n = 6). One nitrate-reducing strain, designated as CYL-A6^T, was identified by polyphasic taxonomy and proposed as a novel Alteromonas species. Genomic analysis reveals that seven Alteromonas genomes encode the dissimilatory nitrate reduction genes narGHI. Evolutionary analysis showed that these three nitrate-reducing genes were present in the early common ancestor of the genus Alteromonas, while gene loss events occurred in the subsequent evolution. With the loss of nitrate-reducing genes in the ancestry nodes, a wide variety of genes related to energy production and conversion, as well as carbohydrate, nucleotide, coenzyme, and inorganic ion metabolism, were gained in those nodes, which enabled Alteromonas members to utilize diverse substrates for increased energy production. This study enhances the understanding of microbial diversity in marine tidal flat sediments, proposes a novel nitrate-reducing species of the genus Alteromonas, and highlights the ecological diversification and ecological niche breadth in the evolution of the microbial metabolic network. Full article

Peat soil is a significant global carbon storage pool, accounting for one-third of the global soil carbon pool. Its greenhouse gas emissions have a significant impact on climate change. Seasonal freeze–thaw cycles are common natural phenomena in high-latitude and high-altitude regions. They significantly affect the mineralization of soil organic carbon and greenhouse gas emissions by altering the physical structure, moisture conditions, and microbial communities of the soil. In this study, through the construction of an indoor simulation experiment of the typical freeze–thaw cycle models in spring and autumn in the Greater Xing‘an Range region of China and the Jinchuan peatland of Jilin Longwan National Nature Reserve, the physicochemical properties, greenhouse gas emission fluxes, microbial community structure characteristics, and key metabolic pathways of peat soils in permafrost and seasonally frozen ground areas were determined. The characteristics of greenhouse gas emissions and their influencing mechanisms for peat soil in northern regions under different freeze–thaw conditions were explored. The research found that the freeze–thaw cycle significantly changed the chemical properties of peat soil and significantly affected the emission rates of CO₂, CH₄, and N₂O. It also clarified the interaction relationship between soil’s physicochemical properties (such as dissolved organic carbon (DOC), dissolved organic nitrogen (DON), ammonium nitrogen (NH₄⁺), soil organic carbon (SOC), etc.) and the structure and metabolic function of microbial communities. It is of great significance for accurately assessing the role of peatlands in the global carbon cycle and formulating effective ecological protection and management strategies. Full article

Soil salinity stands among the most critical abiotic stressors, imposing severe limitations on global rice cultivation. Emerging evidence highlights the potential of beneficial microorganisms to enhance crop salt tolerance. In this study, a halotolerant bacterial strain, Rhodobium marinum RH-AZ (Gram-negative) was identified and analyzed. It exhibited exceptional survival at 9% (w/v) NaCl salinity. Whole-genome sequencing revealed a circular chromosome spanning 3,875,470 bp with 63.11% GC content, encoding 5534 protein-coding genes. AntiSMASH analysis predicted eight secondary metabolite biosynthetic gene clusters. Genomic annotation identified functional genes associated with nitrogen cycle coordination, phytohormone biosynthesis, micronutrient management and osmoprotection. Integrating genomic evidence with the existing literature suggests RH-AZ’s potential for enhancing rice salt tolerance and promoting the growth of rice plants. Subsequent physiological investigations revealed that the RH-AZ strain had significant growth-promoting effects on rice under high salinity stress. Compared with a non-inoculated control, RH-AZ-inoculated rice plants exhibited stem elongation and fresh biomass enhancement under salt stress conditions. The RH-AZ strain concurrently affected key stress mitigation biomarkers: it enhanced the activity of antioxidant enzymes including superoxide dismutase, peroxidase, catalase and ascorbate peroxidase, and the contents of proline and chlorophyll in plants, and reduced the content of malondialdehyde. These findings demonstrate that R. marinum RH-AZ, as a multifunctional bioinoculant, enhances rice salt tolerance by enhancing the stress responses of the plants, presenting a promising solution for sustainable agriculture in saline-affected ecosystems. Full article

Dissolved organic carbon (DOC) maintains the ecological balance of inland lake systems and contributes significantly to the global carbon cycle. This study aims to develop a novel deep learning algorithm to predict DOC concentrations and explore its modeling performance in nonlinear relationships. We used hyperspectral imagery (HSI) from the Chinese Ziyuan-1 satellite series alongside in situ water sample data to construct a Convolutional Multi-Head Attention Fusion Network (CMAF-Net) for prediction of DOC in Chaohu Lake, China. For comparison, we tested its performance against support vector regression (SVR), random forest (RF), and convolutional neural network (CNN) models. The spatial distribution patterns of the DOC were analyzed to explore the primary environmental drivers. The results demonstrate that CMAF-Net significantly outperforms the best-performing baseline CNN model, achieving an R² of 0.88, RMSE of 0.29 mg/L, and RPD of 2.79. Furthermore, environmental factor analysis reveals strong correlations between DOC concentrations and water temperature, total nitrogen (TN), and total phosphorus (TP), identifying them as dominant drivers of the spatial variability of DOC. Hyperspectral remote sensing integrated with CMAF-Net, under the synergistic optimization of local band feature extraction and global band-dependency modeling to screen characteristic water spectra, significantly improves DOC prediction accuracy and enhances multidimensional feature learning. The proposed approach establishes a novel pathway for the quantitative monitoring of DOC in inland aquatic lakes. Full article

Gaseous pollutants and aerosols resulting from anthropic activities and natural phenomena require adequate source apportionment methodologies to be fully assessed. Furthermore, it is crucial to differentiate between fresh anthropogenic emissions and the atmospheric background. The proximity method based on the O₃/NO_x (ozone to nitrogen oxides) ratio has been used at the Lamezia Terme (code: LMT) World Meteorological Organization—Global Atmosphere Watch (WMO/GAW) regional station in Italy to determine the variability of CO (carbon monoxide), CO₂ (carbon dioxide), CH₄ (methane), SO₂ (sulfur dioxide), and eBC (equivalent black carbon), thus allowing the differentiation between local and remote sources of emission. Prior to this work, all O₃/NO_x ratios lower than 10 were grouped under the LOC (local) proximity category, thus including very low ratios (≤1), which are generally attributed by the literature to “urban” air masses, particularly enriched in anthropogenic emissions. This study, aimed at nine continuous years of measurements (2015–2023), introduces the URB category in the assessment of CO, CO₂, CH₄, SO₂, and eBC variability at the LMT site, highlighting patterns and peaks in concentrations that were previously neglected. The daily cycle, which is locally influenced by wind circulation and Planetary Boundary Layer (PBL) dynamics, is particularly susceptible to urban-scale emissions and its analysis has allowed the highlighting of notable peaks in concentrations that were previously neglected. Correlations with wind corridors and speeds indicate that most evaluated parameters are linked to northeastern winds at LMT and wind speeds under 5.5 m/s. Weekly cycle analyses, i.e., differences between weekdays (MON-FRI) and weekends (SAT-SUN), have also highlighted tendencies driven by seasonality and wind corridors. The results highlight the potential of the URB category as a tool necessary to access a given area’s anthropogenic output and its impact on air quality and the environment. Full article