Seasonal Variation Research Articles

Antibiotic resistance and resistome risks of inhalable bioaerosols at aeration tank of a full-scale wastewater treatment plant

Antibiotic resistome could be aerosolized under wastewater aeration processes, however, their seasonal variation, mobility, hosts, aerosolization behavior, and risk, are largely unknown. Herein, the antibiotic resistant pollution associated with fine particulate matter (PM2.5) from the actual aeration tank (AerT), was analyzed using metagenomic assembly. The antibiotic resistance of AerT-PM2.5 was characterized by significant seasonality. Antibiotic resistance genes (ARGs) in AerT-PM2.5, exhibited higher enrichment and mobility and were harbored more by pathogens than those in upwind-PM2.5, regardless of sampling season. Mobile ARGs were mainly flanked by transposase. Totally, 18 pathogenic antibiotic-resistant bacteria (PARB) carried more than one ARG, including 9 PARB with multiple ARG types. Although wastewater exerted a dominant source contribution for the airborne ARGs (47.31–55.56 %) and PARB (46.18–64.32 %), aeration endowed differential aerosolization capacity for various ARGs and PARB from wastewater. Airborne antibiotic resistome was mainly determined by bacterial community and indirectly influenced by meteorological conditions (i.e., relative humidity). Higher PM2.5-borne resistome risk was observed in AerT than upwind, and the most serious resistome risk of AerT-PM2.5 was found in winter. This study emphasizes the importance of wastewater aeration processes in emission of airborne antibiotic resistome and offers referenced information for mitigating air pollution in wastewater treatment plants.

Numerical Investigation of Solar Collector Performance with Encapsulated PCM: A Transient, 3D Approach

This study presents a comprehensive numerical investigation into the thermal performance of solar collectors integrated with encapsulated phase change materials (PCMs) using a transient three-dimensional (3D) approach. The performance of two distinct PCMs—paraffin wax and RT60—was evaluated under varying operational conditions, including seasonal variations, inlet pipe velocities, and inlet temperatures. The results indicate that paraffin wax exhibits a higher peak temperature, reaching approximately 360 K, compared to RT60’s peak of 345 K, making paraffin wax more effective for consistent thermal energy storage. Paraffin wax also maintained higher fluid fractions, with a maximum of 0.9 in summer, indicating superior heat absorption and retention capabilities. In contrast, RT60 demonstrated a quicker phase transition, fully liquefying at a lower fluid fraction, which is advantageous for rapid heat release. Seasonal variations significantly impacted system efficiency, with the highest efficiency observed in June at 365 K and the lowest in December at 340 K. The study also found that lower inlet velocities (e.g., 0.25 L/s) significantly improved heat retention, resulting in higher outlet temperatures, while increasing the inlet temperature from 290 K to 310 K led to a marked increase in outlet temperatures throughout the day. These findings underscore the importance of optimizing PCM selection, inlet velocity, and temperature in enhancing the performance of solar thermal systems, offering quantitative insights that contribute to the development of more efficient and reliable renewable energy solutions.

Epibionts of mediterranean green crab, Carcinus aestuarii Nardo, 1847 in Çanakkale Strait: Based on seasonal, sexual and color variation

Epibionts of mediterranean green crab, Carcinus aestuarii Nardo, 1847 in Çanakkale Strait: Based on seasonal, sexual and color variation

Modeling tuberculosis transmission dynamics in Kazakhstan using SARIMA and SIR models

Tuberculosis (TB) is a highly contagious disease that remains a global concern affecting numerous countries. Kazakhstan has been facing considerable challenges in TB prevention and treatment for decades. This study aims to understand TB transmission dynamics by developing and comparing statistical and deterministic models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and the basic Susceptible-Infected-Recovered (SIR). TB data from 2014 to 2019 were collected from the Unified National Electronic Health System (UNEHS) using retrospective quantitative analysis. SARIMA models were able to capture seasonal variations, with Model 2 exhibiting superior predictive accuracy. Both models showed declining TB incidence and revealed a notable predictive performance evaluated by statistical metrics. In addition, the SIR model calculated the basic reproduction number (\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R_0}$$\\end{document}) below 1, indicating a receding epidemic. Models proved the capability of each to accurately capture trends (SARIMA) and provide mathematical insights (SIR) into TB transmission dynamics. This study contributes to the general knowledge of TB transmission dynamics in Kazakhstan thus laying the foundation for more comprehensive studies on TB and control strategies.

Spatial–Temporal Variation and the Influencing Factors of NO2 Column Concentration in the Plateau Mountains of Southwest China

Given the complex terrain and economic development status of Guizhou Province, research on tropospheric NO2 column concentration using satellite remote sensing is still insufficient. Observing the spatial–temporal evolution characteristics of tropospheric NO2 column concentration can ensure the stable development of air quality. Based on the Google Earth Engine (GEE) platform, NO2 column concentration data retrieved from Sentinel-5P TROPOMI were analyzed using spatial autocorrelation, hotspot analysis, and geographic detector methods (Geodetector). The results show that NO2 column concentration in Guizhou Province exhibits seasonal variation, characterized by higher levels in winter and lower levels in summer, with transitional values in spring and autumn. The annual average concentration was highest in 2021 at 3.47 × 10−5 mol/m2 and lowest in 2022 at 2.85 × 10−5 mol/m2. Spatially, NO2 column concentration displays a distribution pattern of “high in the west, low in the east; high in the north, low in the south”, with significant spatial clustering. The distribution of cold and hot spots aligns with areas of high and low values. NO2 column concentration is primarily influenced by socio-economic factors, with the interaction between any two factors enhancing the explanatory power of individual factors on NO2 column concentration.

Combining SWAT with Machine Learning to Identify Primary Controlling Factors and Their Impacts on Non-Point Source Pollution

Non-point source (NPS) pollution has a complex formation mechanism, and identifying its primary controlling factors is crucial for effective pollution treatment. In this study, the Baixi Reservoir Watershed, characterized by low-intensity development, was selected as the study area. A new methodology combining the Soil and Water Assessment Tool (SWAT) with the Random Forest (RF) algorithm was proposed to comprehensively identify the primary controlling factors of NPS pollution and analyze the interaction between factors. The results of the validated SWAT model showed that the annual intensity of total nitrogen (TN) load range was 0.677–11.014 kg ha−1 yr−1, and the total phosphorus (TP) load per unit area range was 0.020–0.110 kg ha−1 yr−1. Loads of sediment, TP, and TN exhibited significant seasonal variations, particularly in the Baixi basin, where sediment yield had the highest absolute change rate, with a value of up to 232.26. Random Forest models for TN and TP displayed high accuracy (R2 > 0.99) and robust generalization ability. Fertilization, sediment yield, and terrain slope were identified through RF models as the primary factors affecting TN and TP. By graphing partial dependency plots (PDPs) based on the results of the RF models to analyze the interaction between factors, the findings suggest a strong synergistic effect of two combined factors: fertilization and sediment yield. When fertilizer application exceeds 15 kg ha−1 yr−1 and sediment yield exceeds 3 kg ha−1 yr−1, there is a sharp increase in nitrogen and phosphorus load. Through the identification and analysis of the primary controlling factors of NPS pollution, this study provides a solid scientific foundation for developing effective watershed management strategies.

Spatial and seasonal fluctuations in fresh submarine groundwater discharge revealed by marine continuous resistivity profiling

Submarine Groundwater Discharge (SGD) is a major pathway for the discharge of fresh and saline groundwater and associated dissolved compounds into marine environments. However, assessing SGD processes in coastal aquifers is challenging due to inaccessibility, dynamic conditions, complex subsurface geology, and the need for long-term monitoring to capture temporal and spatial variations in SGD rates accurately. This study employs marine continuous resistivity profiling (MCRP) as a main method to assess the presence of freshwater or brackish SGD offshore and to examine its potential seasonal variations. The method has been applied in the coastal alluvial aquifer of Maresme (Spain) and validated with other methods to trace SGD, including salinity profiles, Ra isotopes, and piezometric levels. Several MCRP transects of 700 m long, perpendicular to the coastline, were performed in a coastal marine area to obtain electrical resistivity data of the seabed covering an area of 3 km2. The data was acquired in two field campaigns with contrasting hydrological conditions (dry and wet seasons). The MCRP results allow the identification of areas of fresh SGD in marine sediments, with a clear seasonal variability that indicates a higher discharge of fresh groundwater in the wet season.

Hidden Archaeological Remains in Heterogeneous Vegetation: A Crop Marks Study in Fortified Settlements of Northwestern Iberian Peninsula

This study evaluates the effectiveness of multispectral imaging via Unmanned Aerial Systems (UAS), in combination with advanced digital image processing techniques, for the detection and mapping of archaeological sites within diverse landscapes. The research focuses on six case studies located in the northwest of the Iberian Peninsula, a region marked by complex vegetation patterns and varying topography. The primary objective is to assess the potential of these non-invasive remote sensing techniques in identifying crop marks associated with buried structures from ancient, fortified settlements. By means of Principal Component Analysis (PCA) and vegetation indices, the study aims to pinpoint areas of interest that may indicate the presence of archaeological features, while effectively distinguishing them from modern disturbances or natural terrain variations. The research encountered several challenges, including seasonal variations in crop conditions and recent land-use changes. The methodology successfully identified distinct archaeological features. In some instances, natural vegetation variability, typically seen as an obstacle, enhanced the visibility of crop marks, aiding in the detection of underlying structures. These results offer a cost-effective and scalable option for preliminary archaeological surveys, particularly in refining survey methodologies and guiding future excavation efforts aimed at uncovering and preserving ancient, fortified settlements in the region.

Diversity and Seasonal Variations of Zooplankton in Dudhiya Talab of Sirohi, India

In this study, the seasonal fluctuations of zooplankton and specific physico-chemical parameters were examined in Dudhiya Talab, a significant artificial reservoir located in Sirohi, Rajasthan. During the research period, a total of 41 zooplankton species were identified, comprising 12 species of Rotifera, 14 species of Cladocera, 5 species of Ostracoda, and 4 species of Copepoda. Among these, Rotifera emerged as the predominant group, with a peak abundance of 689 individuals per liter recorded in the summer, while the lowest numbers were noted during the winter season. Additionally, the zooplankton community exhibited correlations with various physico-chemical parameters. The findings of this research suggest that the distribution and density of zooplankton species are significantly affected by the prevailing physical and chemical conditions of the aquatic environment. Key words: Zooplankton, Physico-chemical factors,P Cladocera, Rotifera.

A Retrospective Analysis of Human Cutaneous Leishmaniasis Epidemiology During 2016 - 2021 in Hoveyzeh County, Khuzestan Province, Iran

Background: Leishmaniasis, a significant neglected tropical disease, is caused by obligate intracellular protozoa of the Leishmania genus. Objectives: This research aimed to investigate the epidemiology of cutaneous leishmaniasis (CL) from 2016 to 2021 in Hoveyzeh county. Methods: This study is a retrospective, cross-sectional, descriptive study based on available data. The study population included all individuals treated and followed up in health care centers who were clinically diagnosed with CL and confirmed by laboratory tests. Results: Among the 628 individuals diagnosed with CL, 324 (51.6%) were male, and 304 (48.4%) were female. The average age of the patients was 16.58 ± 15.17 years. The highest proportion (45.4%) of cases occurred in the 0 - 10-year age group, highlighting the vulnerability of children, while those above 50 years had the lowest incidence (3.7%). Approximately 68.2% of patients resided in urban areas, with the remainder living in rural settings. The hand was the most frequently affected area (44.5%), and the maximum number of lesions reported in a single individual was 25. Most patients (46.82%) were treated with topical glucantime along with cryotherapy. Disease incidence showed seasonal variation, with the highest number of cases reported in autumn (54%) and a significant peak in December (22%). The highest incidence year was 2016 (30.3%). Conclusions: Effective strategies to combat this disease should include comprehensive public awareness campaigns focused on health education, early recognition of symptoms, and transmission methods. Promoting personal protective measures is crucial for disease prevention efforts.

Spatiotemporal variations and driving factors of fine-scale habitat use by the Yangtze finless porpoise population in the Yangtze River.

The Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis) is critically endangered and has suffered from extensive habitat loss and fragmentation. Knowledge of its habitat preference could assist the conservation of the species and associated ecosystem. In the present study, spatiotemporal variations and driving factors of habitat use of a Yangtze finless porpoise population were studied in a 30-km section of the Yangtze mainstream. Seasonal variation in porpoise occurrences was observed based on visual surveys conducted from 2022 to 2023, with five surveys during the dry season and seven surveys during the wet season. Biological and environmental factors were synchronously sampled in both seasons. The maximum entropy model (MaxEnt) was applied to get the effects of biological and environmental variables on porpoise habitat preference. Within the study area, high-suitability habitats of the finless porpoises accounted for 19.0% and 15.4% of the area during the dry and wet seasons, respectively. The high-suitability habitat shifted from the mainstream in the dry season to the sandbar head and tributary area in the wet season. In the dry season, variables influencing the distribution were phytoplankton biomass, water velocity, and zooplankton biomass, which contributed 97.05% variation in the MaxEnt modeling. In the wet season, water depth, surface water temperature, and zooplankton biomass accounted for 97.69% variation of the distribution. Above results highlight that food availability plays an important role in porpoises distribution regardless of seasons, particularly in the dry season. This is because plankton is the primary food source for filter-feeding and omnivorous fish, especially those in the upper-middle layer which are frequently preyed on by finless porpoises. Suitable areas for finless porpoises, particularly those with high suitability, differed significantly across seasons at a fine-scale in the Yangtze mainstream. Seasonal variations in habitat were driven by different factors. But food availability plays an important role in porpoises distribution regardless of seasons, particularly in the dry season. These results suggest prioritizing conservation of the finless porpoise in the dry season when fish resources are relatively scarce. Measures including monitoring and evaluating prey resources should be considered. More attention should also be paid on management of shipping in the dry season given that the high-suitability habitat of the finless porpoises shifts to the mainstream.

Seasonal and Interannual Variations in Sea Ice Thickness in the Weddell Sea, Antarctica (2019–2022) Using ICESat-2

The sea ice extent in the Weddell Sea exhibited a positive trend from the start of satellite observations in 1978 until 2016 but has shown a decreasing trend since then. This study analyzes seasonal and interannual variations in sea ice thickness using ICESat-2 laser altimetry data over the Weddell Sea from 2019 to 2022. Sea ice thickness was calculated from ICESat-2’s ATL10 freeboard product using the Improved Buoyancy Equation. Seasonal variability in ice thickness, characterized by an increase from February to September, is more pronounced in the eastern Weddell sector, while interannual variability is more evident in the western Weddell sector. The results were compared with field data obtained between 2019 and 2022, showing a general agreement in ice thickness distributions around predominantly level ice. A decreasing trend in sea ice thickness was observed when compared to measurements from 2003 to 2017. Notably, the spring of 2021 and summer of 2022 saw significant decreases in Sea Ice Extent (SIE). Although the overall mean sea ice thickness remained unchanged, the northwestern Weddell region experienced a noticeable decrease in ice thickness.

Assessing the Potential Impacts of Contaminants on the Water Quality of Lake Victoria: Two Case Studies in Uganda

Nutrients are essential for the growth of aquatic life; however, in excess, they can result in a decline in water quality, posing serious risks to both human and aquatic organisms. Human activities, such as urbanisation, industry, and farming, can increase the amount of nutrients and other elements that reach receiving waterbodies like Lake Victoria in Uganda, which can be problematic at elevated levels. There is therefore a strong need to evaluate recent changes in pollutant concentrations and their potential negative effects. To contribute to this gap and to explore the pollutant changes in Lake Victoria, a series of water chemistry data (phosphate, nitrate, potassium, ammonium, sodium, sulphate, silica and chlorine) was collected between 2016 and 2023 in Uganda’s Napoleon Gulf (NG) and Murchison Bay (MB), primarily by the Ministry of Water and Environment (MWE). These locations were chosen based on their vicinity to expanding urban centres and agriculture, and they are also areas where fishing frequently occurs. The datasets were collected at different water depths (0.5–24 m). Data were analysed with the use of IBM’s Statistical Package for the Social Sciences (SPSS 28.0) software and confirmed the excessive concentrations of pollutants within MB compared to NG. The analysis identified the different nutrient types that exceeded internationally recognised thresholds relating to acceptable water quality during the data collection period. Seasonal variations were observed, during the dry season; nutrient levels, however, in NG showed higher nutrient concentrations during the wet season. The study’s capacity to inform local authorities and policymakers about such potential major sources of pollution is of crucial importance for beginning to address the potential impacts on human health and aquatic life.

Seasonal variations of microbial communities and viral diversity in fishery-enhanced marine ranching sediments: insights into metabolic potentials and ecological interactions

BackgroundThe ecosystems of marine ranching have enhanced marine biodiversity and ecological balance and have promoted the natural recovery and enhancement of fishery resources. The microbial communities of these ecosystems, including bacteria, fungi, protists, and viruses, are the drivers of biogeochemical cycles. Although seasonal changes in microbial communities are critical for ecosystem functioning, the current understanding of microbial-driven metabolic properties and their viral communities in marine sediments remains limited. Here, we employed amplicon (16S and 18S) and metagenomic approaches aiming to reveal the seasonal patterns of microbial communities, bacterial-eukaryotic interactions, whole metabolic potential, and their coupling mechanisms with carbon (C), nitrogen (N), and sulfur (S) cycling in marine ranching sediments. Additionally, the characterization and diversity of viral communities in different seasons were explored in marine ranching sediments.ResultsThe current study demonstrated that seasonal variations dramatically affected the diversity of microbial communities in marine ranching sediments and the bacterial-eukaryotic interkingdom co-occurrence networks. Metabolic reconstruction of the 113 medium to high-quality metagenome-assembled genomes (MAGs) was conducted, and a total of 8 MAGs involved in key metabolic genes and pathways (methane oxidation - denitrification - S oxidation), suggesting a possible coupling effect between the C, N, and S cycles. In total, 338 viral operational taxonomic units (vOTUs) were identified, all possessing specific ecological characteristics in different seasons and primarily belonging to Caudoviricetes, revealing their widespread distribution and variety in marine sediment ecosystems. In addition, predicted virus-host linkages showed that high host specificity was observed, with few viruses associated with specific hosts.ConclusionsThis finding deepens our knowledge of element cycling and viral diversity in fisheries enrichment ecosystems, providing insights into microbial-virus interactions in marine sediments and their effects on biogeochemical cycling. These findings have potential applications in marine ranching management and ecological conservation.DRyDF7ykR-XALqAtu34uZtVideo

Seasonal Variations in Seed Viability and Vigor of Hancornia speciosa Under Osmoprotective Storage Conditions

Seasonal Variations in Seed Viability and Vigor of Hancornia speciosa Under Osmoprotective Storage Conditions

The role of nitrogen and iron biogeochemical cycles in the production and export of dissolved organic matter in agricultural headwater catchments

Abstract. To better understand the seasonal variations in environmental conditions regulating dissolved organic matter (DOM) export in agricultural headwater catchments, we combined the monitoring of nitrate, iron, soluble phosphorus, and DOM concentration (as dissolved organic carbon; DOC) and composition (3D fluorescence) in soil and stream waters at regular intervals during 1 hydrological year. We installed 17 zero-tension lysimeters in organic-rich top soil horizons (15 cm below the surface) in the riparian area of a well-monitored agricultural catchment in French Brittany and collected them at a fortnightly frequency from October 2022 to June 2023. We observed a large increase in DOC concentrations in soil waters during the high-flow period linked to the establishment of Fe-reducing conditions and the subsequent release of DOM. We also noted that the timing and the spatial variability in Fe(II) biodissolution in soils was regulated by nitrate from agricultural origin and the heterogeneity of water flow paths at the hillslope scale. Contrary to our current understanding of DOM export in headwater catchments, these results lead us to consider the winter high-flow period as an active phase of both DOM production and export.

Application of time series and multivariate statistical models for water quality assessment and pollution source apportionment in an Urban River, New Jersey, USA

Water quality monitoring reveals changing trends in the environmental condition of aquatic systems, elucidates the prevailing factors impacting a water body, and facilitates science-backed policymaking. A 2020 hiatus in water quality data tracking in the Lower Passaic River (LPR), New Jersey, has created a 5-year information gap. To gain insight into the LPR water quality status during this lag period and ahead, water quality indices computed with 16-year historical data available for 12 physical, chemical, nutrient, and microbiological parameters were used to predict water quality between 2020 and 2025 using seasonal autoregressive moving average (ARIMA) models. Average water quality ranged from good to very poor (34 ≤ µWQI ≤ 95), with noticeable spatial and seasonal variations detected in the historical and predicted data. Pollution source tracking with the positive matrix factorization (PMF) model yielded significant R2 values (0.9 < R2 ≤ 1) for the input parameters and revealed four major LPR pollution factors, i.e., combined sewer systems, surface runoff, tide-influenced sediment resuspension, and industrial wastewater with pollution contribution rates of 23–30.2% in the upstream and downstream study areas. Significant correlation of toxic metals, nutrients, and sewage indicators suggest similarities in their sources.Graphical

Structure and Dynamics of Phytoplankton Populations in the Black Sea from 2014 to 2017

This study investigated the seasonal variations in phytoplankton communities along the Turkish Black Sea coast (2014-2017). Analyzing data from 20 stations revealed high biodiversity (175 species across 14 classes). Phytoplankton abundance showed distinct seasonality, with a peak in summer (2017, 96.6%) and lows in winter, characterized by dinoflagellate dominance. In terms of biomass, diatoms dominated in half of the sampling seasons, while dinoflagellates dominated in the other half at the surface during the study period. The dominance of dinoflagellates corresponded to the winters and summers of 2015 and 2016. The winter conditions of 2015 were harsh. The surface water community composition sometimes varied from that of the water column. Importantly, 44 potentially toxic species were identified, comprising 25% of the community and significantly contributing to both abundance (73.2-98.6%) and biomass (64-90.2%) throughout the year. These results highlight the unique structure of the Black Sea phytoplankton community, characterized by seasonal dominance of diatoms and a significant presence of potentially toxic species. Season, year, and water depth significantly influenced the phytoplankton assemblages. Water temperature was negatively correlated with dissolved oxygen and nitrogen-based nutrients.

Black Carbon Radiative Impacts on Surface Atmospheric Oxidants in China with WRF-Chem Simulation

Black carbon (BC) changes the radiative flux in the atmosphere by absorbing solar radiation, influencing photochemistry in the troposphere. To evaluate the seasonal direct radiative effects (DREs) of BC and its influence on surface atmospheric oxidants in China, the WRF-Chem model was utilized in this study. The simulation results suggested that the average annual mean values of the clear-sky DREs of BC at the top of the atmosphere, in the atmosphere and at the surface over China are +2.61, +6.27 and −3.66 W m−2, respectively. Corresponding to the seasonal variations of BC concentrations, the relative changes of the mean surface photolysis rates (J[O1D], J[NO2] and J[HCHO]) in the four seasons range between −3.47% and −6.18% after turning off the BC absorption, which further leads to relative changes from −4.27% to −6.82%, −2.14% to −4.40% and −0.47% to −2.73% in hydroxyl (OH) radicals, hydroperoxyl (HO2) radicals and ozone (O3), respectively. However, different from the relative changes, the absolute changes in OH and HO2 radicals and O3 after turning off BC absorption show discrepancies among the different seasons. In the North China Plain (NCP) region, O3 concentration decreases by 1.79 ppb in the summer, which is higher than the magnitudes of 0.24–0.88 ppb in the other seasons. In southern China, the concentrations of OH and HO2 radicals reach the maximum decreases in the spring and autumn, followed by those in the summer and winter, which is due to the enhancement of solar radiation and the summer monsoon. Thus, BC inhibits the formation of atmospheric oxidants, which further weakens the atmospheric oxidative capacity.

Warm growing season activates microbial nutrient cycling to promote fertilizer nitrogen uptake by maize

The influence of nitrogen (N) inputs on soil microbial communities and N uptake by plants is well-documented. Seasonal variations further impact these microbial communities and their nutrient-cycling functions, particularly within multiple cropping systems. Nevertheless, the combined effects of N fertilization and growing seasons on soil microbial communities and plant N uptake remain ambiguous, thereby constraining our comprehension of the optimal growing season for maximizing crop production. In this study, we employed 15N isotope labeling, high-throughput sequencing, and quantitative polymerase chain reaction (qPCR) techniques to investigate the effects of two distinct growing seasons on microbial communities and maize 15N uptake ratios (15NUR). Our results showed that the warm growing season (26.6 °C) increased microbial diversity, reduced network complexity but enhanced stability, decreased microbial associations, and increased modularization compared to the cool growing season (23.1 °C). Additionally, the warm growing season favored oligotrophic species and increased the abundance of microbial guilds and functional genes related to N, phosphorus, and sulfur cycling. Furthermore, alterations in the characteristics of soil microbial keystone taxa were closely linked to variations in maize 15NUR. Overall, our findings demonstrate significant seasonal variations in soil microbial diversity and functioning, with maize exhibiting higher 15NUR during the warm growing season of the double cropping system.