Global warming may reshape seasonal changes in microbial community diversity and co-occurrence network patterns, with significant implications for terrestrial ecosystem function. We conducted a 2-year in situ field simulation of the effects of warming on the seasonal dynamics of soil microbial communities in a northern subtropical Quercus acutissima forest. Our study revealed that warming had no significant effect on the richness or diversity of soil bacteria or fungi in the growing season, whereas different warming gradients had different effects on their diversity in the nongrowing season. Warming also changed the microbial community structure, increasing the abundance of some thermophilic microbial species and decreasing the abundance of some symbiotrophic microorganisms. The co-occurrence network analysis of the microbial community showed that warming decreased the complexity of the intradomain network in the soil bacterial community in the growing and nongrowing seasons but increased it in the fungal community. Moreover, increasing warming temperatures increased the complexity of the interdomain network between bacteria and fungi in the growing season but decreased it in the nongrowing season, and the keystone species in the interdomain network changed with warming. Warming also reduced the proportion of positive microbial community interactions, indicating that warming reduced the mutualism, commensalism, and neutralism of microorganisms as they adapted to soil environmental stress. The factors affecting the fungal community varied considerably across warming gradients, with the bacterial community being significantly affected by soil temperature, MBC, NO3--N and NH4+-N, moreover, SOC and TN significantly affected fungal communities in the 4 °C warming treatment.. These results suggest that warming increases seasonal differences in the diversity and complexity of soil microbial communities in the northern subtropical region, significantly influencing soil dynamic processes regulating forest ecosystems under global warming.

This study delves into the environmental impact of inland aquaculture on estuarine ecosystems by examining the water quality of four estuarine streams within the key inland aquaculture zone of South India. In this region, extensive and intensive aquaculture practices are common, posing potential challenges to estuarine health. The research explores the predictive capabilities of the Gaussian elimination method (GEM) and machine learning techniques, specifically multi-linear regression (MLR) and support vector regressor (SVR), in forecasting the water quality index of these streams. Through comprehensive evaluation using performance metrics such as coefficient of determination (R2) and average mean absolute percentage error (MAPE), MLR and SVR demonstrate higher prediction efficiency. Notably, employing key water parameters as inputs in machine learning models is also more effective. Biochemical oxygen demand (BOD) emerges as a critical water parameter, identified by both MLR and SVR, exhibiting high specificity in predicting water quality. This suggests that MLR and SVR, incorporating key water parameters, should be prioritized for future water quality monitoring in intensive aquaculture zones, facilitating timely warnings and interventions to safeguard water quality.

Exploring the effects of seasonal variation on the gut microbiota of cold-water fish plays an important role in understanding the relationship between seasonal variation and cold-water fish. Gut samples of cold-water fish and environmental samples were collected during summer and winter from the lower reaches of the Yalong River. The results of the 16S rRNA sequencing showed that significant differences were identified in the composition and diversity of gut bacteria of cold-water fish. Co-occurrence network complexity of the gut bacteria of cold-water fish was higher in summer compared to winter (Sum: nodes: 256; edges: 20,450; Win: nodes: 580; edges: 16,725). Furthermore, from summer to winter, the contribution of sediment bacteria (Sum: 5.3%; Win: 23.7%) decreased in the gut bacteria of cold-water fish, while the contribution of water bacteria (Sum: 0%; Win: 27.7%) increased. The normalized stochastic ratio (NST) and infer community assembly mechanisms by phylogenetic bin-based null model analysis (iCAMP) showed that deterministic processes played a more important role than stochastic processes in the microbial assembly mechanism of gut bacteria of cold-water fish. From summer to winter, the contribution of deterministic processes to gut bacteria community assembly mechanisms decreased, while the contribution of stochastic processes increased. Overall, these results demonstrated that seasonal variation influenced the gut bacteria of cold-water fish and served as a potential reference for future research to understand the adaptation of fish to varying environments.

Background/Objectives: Recent studies provide the first indications of the impact of climate factors on human health, especially with individuals already grappling with internal and neurological conditions being particularly vulnerable. In the face of escalating climate change, our research delves into the specific influence of a spectrum of climatic factors and seasonal variations on the hospital admissions of patients receiving treatment for epileptic seizures at our clinic in Kaiserslautern. Methods: Our study encompassed data from 9366 epilepsy patients who were admitted to hospital due to epileptic seizures. We considered seven climate parameters that Germany\'s National Meteorological Service made available. We employed the Kruskal-Wallis test to examine the correlation between the frequency of admittance to our hospital in the mentioned patient group and seasons. Furthermore, we used conditional Poisson regression and distributed lag linear models (DLMs) to scrutinize the coherence of the frequency of patient admittance and the investigated climate parameters. The mentioned parameters were also analyzed in a subgroup analysis regarding the gender and age of patients and the classification of seizures according to ILAE 2017. Results: Our results demonstrate that climatic factors, such as precipitation and air pressure, can increase the frequency of hospital admissions for seizures in patients with general-onset epilepsy. In contrast, patients with focal seizures are less prone to climatic changes. Consequently, admittance to the hospital for seizures is less affected by climatic factors in the latter patient group. Conclusions: The present study demonstrated that climatic factors are possible trigger factors for the provocation of seizures, particularly in patients with generalized seizures. This was determined indirectly by analyzing the frequency of seizure-related emergency admissions and their relation to prevailing climate factors. Our study is consistent with other studies showing that climate factors, such as cerebral infarcts or cerebral hemorrhages, influence patients\' health.

Blueberry leaves (BBL) are a natural source with strong antioxidant activity, but bioactive compounds and their seasonal variation remain vague. Here, two major classes of compounds including four caffeoylquinic acids and eight flavonoids were identified in two southern highbush cultivars (\"Lanmei\" #1 and \"Jewel\") grown in China. Major bioactive compounds were discovered using an online HPLC post-column derivatization system and determined as neochlorogenic acid (NeoCA), chlorogenic acid (CA), rutin, hyperoside, and isoquercitrin. CA contributed the most to the BBL antioxidant activity. \"Lanmei\" showed significant advantages in terms of rutin content and antioxidant activity over \"Jewel\" (P < 0.05). The highest CA content (CAC) of juvenile \"Jewel\" leaves reached 17.9%. July was the optimum harvest time for both cultivars after fruiting stage. Total phenolic content (TPC) and Trolox equivalent antioxidant capacity (TEAC) of fresh BBL were accurately predicted by a portable near-infrared (NIR) device in a rapid, low-cost, and non-destructive way in situ.

BACKGROUND: Most studies infer increasing incidence of proximal humeral fractures (PHF) from the 1950´s until the 1990´s. Recent time trends are less clear.
OBJECTIVE: Our primary objective was to identify time trends in the age- and sex-adjusted adult incidence of PHF in Malmö, Sweden, from year 1944 until 2020. Our secondary objectives were to describe the variation in incidence according to age, the monthly distribution, and to compare data from the two most recent decades with earlier.
METHODS: Malmö has one emergency hospital where acute fractures are treated. We identified PHF in adult patients (≥ 18 years) by reviewing relevant radiology examinations during 17 sample years from year 1944 to 2020. We used jointpoint analyses to estimate time trends.
RESULTS: We identified 3 031 PHF during the study period (3 231 161 person years), 73% were sustained by women with mean age of 69 years (mean age in men 59). Joinpoint analyses indicated an increase in the age- and sex-adjusted incidence of PHF from year 1944 (52 per 100 000 person years) until 1977 (120 per 100 000) and thereafter a decrease until 2020 (85 per 100 000). A seasonal variation with more fractures during winter months, was apparent in earlier but not recent decades.
CONCLUSIONS: The age- and sex-adjusted incidence of PHF increased in Malmö, Sweden, from the 1940´s until year 1977 and thereafter decreased until 2020. More fractures were seen during winter months in earlier but not recent decades.

This paper investigated the MP presence and removal in the urban WWTP in Astana, the capital city of Kazakhstan. MP concentrations in the 100-5000 μm size were analyzed across treatment stages with a modified treatment process scheme, and their removal efficiencies were evaluated. The WWTP effluent displayed a low MP concentration (4.06 ± 3.06 MP/L to 5.44 ± 3.51 MP/L), but considering the daily wastewater discharge (253,900,000 L/day), it can significantly contribute to the MP pollution of aquatic systems. Seasonal variation was observed in the influent, with higher abundance during summer, while no significant trend was observed in the effluent. The WWTP achieved an 88.6-93.0 % removal efficiency, with mechanical treatment and granular filtration being the most effective, followed by biological treatment and UV disinfection. Fragments were the most abundant among the observed shapes (53.9-59.9 %) and black MPs dominated (44.7-67.5 %). Polyethylene (PE) emerged as the most prevalent polymer type among the MPs analyzed (31.6-35.7 %).

The stress resistance of medicinal plants is essential to the accumulation of pharmacological active ingredients, but the regulation mechanism of biological factors and abiotic factors on medicinal plants is still unclear. To investigate the mechanism of soil nutrient and microecology on the stress resistance of C. pilosula, rhizosphere soil and roots were collected across the four seasons in Minxian, Gansu, and their physicochemical properties, as well as root-associated microorganisms, were examined. The results showed that the bacterial α-diversity indexes increased in the endosphere and rhizosphere from summer to autumn. At the same time, the community composition and function changed considerably. The stability of the endophytic bacterial community was higher than that rhizospheric bacteria, and the complexity of the endophytic bacterial community was lower than rhizospheric bacteria. Soil organic matter (OM), water content (WC), total potassium (TK), and total nitrogen (TN) have been identified as the key factors affecting bacterial community diversity and stress resistance of C. pilosula. WC, TN, and OM showed significant differences from summer to autumn (P < 0.5). Four key soil physiochemical factors changed significantly between seasons (P < 0.01). TN and OM change the stress resistance of C. pilosula mainly by changing the activity of antioxidant enzymes. Changes of OM and endophytic bacterial diversity affect the accumulation of soluble sugars to alter stress resistance. These four key soil physicochemical factors significantly influenced the diversity of endophytic bacteria. WC and OM were identified as the most important factors for endophytic and rhizospheric bacteria, respectively. This study provided the research basis for the scientific planting of C. pilosula.

Water use efficiency (WUE) is a key indicator for predicting the impacts of climate change on ecosystem carbon and water cycles. Most studies have explored the changes in the response environment of WUE at a particular scale. Few studies have examined how WUE responds to environments at multiple scales, thus limiting our in-depth understanding of the cross-scale carbon and water cycles. In this study, we measured photosynthesis and transpiration in situ periodically and continuously from June to October 2022 in a community dominated by Artemisia ordosica in Mu Us Sandy Land, and analyzed the seasonal variations in WUE at leaf, canopy, and ecosystem scales. The results showed there were significant seasonal variations in leaf water use efficiency (WUEL), canopy water use efficiency (WUET), and ecosystem water use efficiency (WUEE). WUEL was large in June and small in both August and September, ranging from 0.73-2.98 μmol·mmol-1. Both WUET and WUEE were lowest in June and highest in July and August, ranging from 0.10-7.00 and 0.06-6.25 μmol·mmol-1. WUEL was significantly negatively correlated with stomatal conductance. WUET was significantly positively correlated with canopy conduc-tance and soil water content, and negatively correlated with vapor pressure deficit (VPD). There was a significant positive correlation between WUEE and soil water content (SWC10) in 10 cm soil depth. The structural equation model showed that SWC10 and air temperature affected net photosynthetic rate and transpiration rate by modifying stomatal conductance, and thus affecting WUEL. VPD and SWC10 affected WUET by altering transpiration. SWC10, air temperature, and VPD affected WUEE by regulating ecosystem gross primary productivity. The modelling of carbon and water cycles should thoroughly consider the path and intensity of the effect of environmental factors on WUE at multiple scales.
水分利用效率(WUE)是预测气候变化对生态系统碳、水循环过程的关键指标。以往研究多从单一观测尺度对WUE响应环境的变化进行探究,鲜有研究对不同观测尺度WUE如何响应环境进行论述,这限制了对跨尺度碳水循环的深入理解。本研究选取毛乌素沙地优势种黑沙蒿群落,于2022年6—10月,利用固定样地测定与原位连续监测方法对黑沙蒿的光合与蒸腾特征进行观测,分析黑沙蒿叶片、冠层和生态系统水分利用效率季节特征及其环境影响因素。结果表明: 叶片水分利用效率(WUEL)与冠层水分利用效率(WUET)和生态系统水分利用效率(WUEE)的季节变化差异明显。WUEL在6月较大,在8、9月较小,波动范围为0.73～2.98 μmol·mmol-1;WUET和WUEE在6月最小,在7、8月最大,波动范围分别为0.10～7.00和0.06～6.25 μmol·mmol-1。WUEL与气孔导度呈显著负相关;WUET与冠层导度和土壤含水量呈显著正相关,与饱和水汽压差呈显著负相关;WUEE与10 cm土层土壤含水量(SWC10)呈显著正相关。结构方程模型表明,SWC10和空气温度通过调节气孔导度影响净光合速率和蒸腾速率,进而影响WUEL;饱和蒸气压差和SWC10通过调节蒸腾速率对WUET产生影响;土壤含水量、空气温度和饱和蒸气压差通过调节生态系统总初级生产力对WUEE产生影响。未来碳水循环的模型拟合应充分考虑环境因子对不同观测尺度WUE的影响路径与强度。.