Winter Time Research Articles

Stock identification of sympatric Atlantic cod populations in the Gulf of Maine and mixed stock fishery analysis using otolith-based techniques

Sympatric populations of Atlantic cod with distinct spawning times in winter and spring have been identified within the Gulf of Maine. A new western Gulf of Maine stock assessment unit in U.S. waters lumps winter and spring spawning populations into a single stock unit and future monitoring and assessment of their abundance will require mixed stock analysis. The goal of this study was to evaluate the utility of otolith-based stock identification techniques to discriminate spawning populations. Significant differences in otolith structure and microchemistry were identified between winter and spring spawners with the highest degree of classification accuracy based on both features. Mixed stock analysis applied to fishery samples of unknown origin indicated the contemporary (2015-2016) commercial fishery is dominated by winter spawners. Exploratory classification of historical fishery samples suggested a change over time with spring and winter spawners present in near equal proportion in the early 1990s and winter spawners dominating in the early 1980s. Otolith-based stock composition analysis has the potential to support monitoring and assessment of cod populations in the Gulf of Maine.

Long-term geomagnetic activities and stratospheric winter temperature

In this research, impact of long term solar forcing on stratospheric winter temperature is checked. The 11- year sunspot activity and geomagnetic indices (AE, Kp, Dst) are used as an indicator for solar forcing, as geomagnetic activity indices show good correlation with solar variability. To understand the impact of solar forcing through high latitude, stratospheric winter (November to March) time North Polar Region (60N–90N) temperature anomalies are considered. The findings showed that temperature changes in the stratosphere are significantly correlated with solar activity, as evidenced by a significant positive correlation between the 11-year moving mean of stratospheric (10 hPa) temperature anomalies and sunspot number. Approximately from 1970 to 2000, the North Polar Region saw positive anomalous stratospheric winter temperatures. During the same time, the geomagnetic activity also showed a substantial increase. The year-to-year correlation between stratospheric pole temperature and geomagnetic activity is significant (about 0.5). The Empirical Mode Decomposition analysis reveals a highly significant correlation (around 0.9) between the long-term component of stratospheric winter temperature (IMF-4) and the long-term component of geomagnetic activity (IMF-3 and IMF-4). One of the reasons for the increase in lower stratospheric temperature is an increase in ozone concentration during the same period when geomagnetic activity is higher. Empirical orthogonal function (EOF) and correlation analysis of stratospheric winter temperature with large-scale circulation patterns are also carried out. The spatial correlation is checked for stratospheric winter temperature at North Pole and lower atmospheric levels (250 hPa and 850 hPa) followed by pre-monsoon and monsoon season. This study includes statistical analysis, however, also highlights the necessity of in-depth dynamical analysis to improve our understanding of how solar activity impacts Earth's atmospheric layers, which may be helpful in predicting the weather and climate.

Seasonal forecasting of the European North-West shelf seas: limits of winter and summer sea surface temperature predictability

The European North-West shelf seas (NWS) support economic interests and provide environmental services to adjacent countries. Expansion of offshore activities, such as renewable energy infrastructure, aquaculture, and growth of international shipping, will place increasingly complex demands on the marine environment over the coming decades. Skilful forecasting of NWS properties on seasonal timescales will help to effectively manage these activities. Here we quantify the skill of an operational large-ensemble ocean-atmosphere coupled global forecasting system (GloSea), as well as benchmark persistence forecasts, for predictions of NWS sea surface temperature (SST) at 2–4 months lead time in winter and summer. We identify sources of and limits to SST predictability, considering what additional skill may be available in the future. We find that GloSea NWS SST skill is generally high in winter and low in summer. GloSea outperforms simple persistence forecasts by adding information about atmospheric variability, but only to a modest extent as persistence of anomalies in the initial conditions contributes substantially to predictability. Where persistence is low – for example in seasonally stratified regions – GloSea forecasts show lower skill. GloSea skill can be degraded by model deficiencies in the relatively coarse global ocean component, which lacks dynamic tides and subsequently fails to robustly represent local circulation and mixing. However, “atmospheric mode matched” tests show potential for improving prediction skill of currently low performing regions if atmospheric circulation forecasts can be improved. This underlines the importance of coupled atmosphere-ocean model development for NWS seasonal forecasting applications.

The impact of solid fuel use on major depression and the buffering effect of outdoor time in the UK adults: A 12-year cohort study

BackgroundThis study aims to investigate age- and gender-specific effects of household solid fuels for heating on major depression and buffering effects of outdoor time in a high-income country. MethodsData were obtained from the UK Biobank. Participants with complete information on our studied variables and no prior diagnosis of major depression at baseline were included. Cox proportional hazards regression models were used to examine the effects of household solid fuels for heating on major depression. Subgroup analyses were conducted to investigate the buffering effects of outdoor time in summer and winter. Sensitivity analyses were performed to test the robustness of the main findings. ResultsOf 255,505 participants (50.2 % women), the 12-year cumulative incidence of major depression was 4.4 %. Household solid fuels for heating increased the risk of major depression only in women aged <45 years (HR (95%CI) = 1.30 (1.04, 1.63)). In this group, the solid fuel effect was moderated by outdoor time spending both in summer (HR (95%CI), ≤2 h/day: 1.61 (1.13, 2.28); >2 h/day: 1.13 (0.84, 1.52)) and winter (≤1 h/day: 1.35 (1.01, 1.08); >1 h/day: 1.24 (0.86, 1.77)). LimitationsSelf-reported measures might lead to recall bias and some potential confounders, such as ventilation efficiency, were not measured and controlled in data analyses. ConclusionsYounger women are more vulnerable to the impact of domestic air pollution on major depression. Promoting outdoor activities is a cost-effective and efficient approach to mitigating the risk of major depression caused by household solid fuels.

Time series of alpine snow surface radiative-temperature maps from high-precision thermal-infrared imaging

Abstract. The surface temperature of snow cover is a key variable, as it provides information about the current state of the snowpack, helps predict its future evolution, and enhances estimations of the snow water equivalent. Although satellites are often used to measure the surface temperature despite the difficulty of retrieving accurate surface temperatures from space, calibration–validation datasets over snow-covered areas are scarce. We present a dataset of extensive measurements of the surface radiative temperature of snow acquired with an uncooled thermal-infrared (TIR) camera. The set accuracy goal is 0.7 K, which is the radiometric accuracy of the TIR sensor of the future CNES/ISRO TRISHNA mission. TIR images have been acquired over two winter seasons, November 2021 to May 2022 and February to May 2023, at the Col du Lautaret, 2057 m a.s.l. in the French Alps. During the first season, the camera operated in the off-the-shelf configuration with rough thermal regulation (7–39 °C). An improved setup with a stabilized internal temperature was developed for the second campaign, and comprehensive laboratory experiments were carried out in order to characterize the physical properties of the components of the TIR camera and its calibration. Thorough processing, including radiometric processing, orthorectification, and a filter for poor-visibility conditions due to fog or snowfall, was performed. The result is two winter season time series of 130 019 maps of the surface radiative temperature of snow with meter-scale resolution over an area of 0.5 km2. The validation was performed against precision TIR radiometers. We found an absolute accuracy (mean absolute error, MAE) of 1.28 K during winter 2021–2022 and 0.67 K for spring 2023. The efforts to stabilize the internal temperature of the TIR camera therefore led to a notable improvement of the accuracy. Although some uncertainties persist, particularly the temperature overestimation during melt, this dataset represents a major advance in the capacity to monitor and map surface temperature in mountainous areas and to calibrate–validate satellite measurements over snow-covered areas of complex topography. The complete dataset is provided at https://doi.org/10.57932/8ed8f0b2-e6ae-4d64-97e5-1ae23e8b97b1 (Arioli et al., 2024a) and https://doi.org/10.57932/1e9ff61f-1f06-48ae-92d9-6e1f7df8ad8c (Arioli et al., 2024b).

Spatial source, simulating improvement, and short-term health effect of high PM2.5 exposure during mutation event in the key urban agglomeration regions in China

Air quality in China has significantly improved owing to the effective implementation of pollution control measures. However, mutation events caused by short-term spikes in PM2.5 in urban agglomeration regions continue to occur frequently. Identifying the spatial sources and influencing factors, as well as improving the prediction accuracy of high PM2.5 during mutation events, are crucial for public health. In this study, we firstly introduced discrete wavelet transform (DWT) to identify the mutation events with high PM2.5 concentration in the four key urban agglomerations, and evaluated the spatial sources for the polluted scenario using Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. Additionally, DWT was combined with a widely used artificial neural network (ANN) to improve the prediction accuracy of PM2.5 concentration seven days in advance (seven-day forecast). Results indicated that mutation events commonly occurred in the northern regions during winter time, which were under the control of both short-range transportation of dirty airmass as well as negative meteorology conditions. Compared with the ANN model alone, the average band errors decreased by 9% when using DWT-ANN model. The average correlation coefficient (R) and root mean square error (RMSE) obtained using the DWT-ANN improved by 10% and 12% compared to those obtained using the ANN, indicating the efficiency and accuracy of simulating PM2.5, by combining the DWT and ANN. The short-term mortality during mutation events was then calculated, with the total averted all-cause, cardiovascular, and respiratory deaths in the four regions, being 4751, 2554, and 582 persons, respectively. A declining trend in prevented deaths from 2018 to 2020 demonstrated that the pollution intensity during mutation events gradually decreased owing to the implementation of the Three-Year Action Plan to Win the Blue Sky Defense War. The method proposed in this study can be used by policymakers to take preventive measures in response to a sudden increase in PM2.5, thereby ensuring public health.

Efficient utilization of winter nitrogen sources by soil microorganisms and plants in a temperate grassland

In seasonal snow-covered regions, the soil microbial community remains highly active, enabling nitrogen (N) mineralization processes to occur even during the winter. Therefore, winter N accumulation is likely to be a primary N source for plant growth in the subsequent spring. However, the availability of winter N resources (i.e., ammonium and nitrate N) to soil microorganisms and plants in temperate grasslands remains unclear. Here, we applied 15NH4Cl and K15NO3 tracers before autumn-winter freezing, and then investigated the retention of both 15N tracers in soil microorganisms and different plants during the winter and spring period in a typical steppe. The results showed that approximately 33 % and 27 % of 15NH4Cl and K15NO3 tracers were immobilized by soil microorganisms, while little had been uptake by plants during winter. In the subsequent spring, soil retained 32 % and 34 %, microorganisms immobilized 5.1 % and 5.2 %, plant acquired 40 % and 28 % of the 15NH4Cl and K15NO3 tracers, respectively. At a temporal scale, perennial bunch grasses first acquired 15N in the winter-spring transition, followed by perennial rhizome grasses and forbs in early spring, while legumes utilized little 15N. In contrast, the 15N absorption capacity of perennial rhizome grasses and perennial forbs was similar to that of bunch grasses. Additionally, only dominant bunch grasses showed a preference for ammonium N over nitrate N, while other plant species did not exhibit a clear preference for different forms of N. Our results suggest that the temporal differentiation of N utilization between plants and microorganisms enhances the availability of winter N sources. Importantly, the differences among plant species in the timing and quantity of winter N resource utilization contribute to species coexistence in temperate grasslands. This study highlights the crucial role of winter N accumulation as a primary N source for plant growth in temperate grasslands. Understanding the availability of winter N sources for plant and microbial growth is essential for predicting plant community dynamics and species coexistence in these ecosystems.

Results from the InSight atmospheric imaging campaign

NASA's InSight lander monitored the Martian atmosphere while conducting its primarily geophysical investigation. Atmospheric imaging was used to study dust and ice at the site for over two Mars years in 2018–2022. An optical depth record, including dust and ice, was derived from systematic sky imaging in the mornings (for the first part of the mission) and evenings. Optical depths ranged from 0.5 to 1.9 but were typically under 1. Dust storms were seen at expected times in late northern autumn and early winter, including one shortly after landing, along with one late summer storm in January 2022. The optical depth record closely matched that of Curiosity, 600 km to the south, except for the expected additional water ice content during the aphelion cloud belt (ACB, spring to early summer). In addition to ice hazes, the ACB included discrete clouds, whose motion was tracked to show northeasterly to southeasterly daytime winds. While InSight recorded many meteorological vortices, no dust devils were seen, requiring that dust-devil occurrence was <10−3 times as common as during Spirit rover dust devil seasons.

Study of the Strain Law and Model of an Open-Air Steel Column under Daily Temperature Changes in Winter

Steel structures with light weight, high rigidity, and easy assembly have become the first choice for large-span complex building materials. At the same time, transparent materials are widely used for the sake of practicality and aesthetics. However, steel structures will be deformed due to changes in temperature, which will affect the accuracy of closure. The components are restricted from free deformation as a result of multiple statically indeterminate structures. A safety hazard will occur if the residual temperature stress is not released. At present, the strain law of open-air steel structures caused by temperature change is still unclear, and the corresponding temperature–strain model has not been established. This paper is based on the third-phase reconstruction and expansion project of Taiyuan Wusu Airport in Xiaodian District, Taiyuan City, Shanxi Province (37°45′ N, 112°38′ E, average altitude of 774 m), winter long time series temperature measured data, deduced daily temperature change laws, and the established relationship model between air temperature and steel surface temperature. Based on the measured data of long-term stress and strain in winter, the strain law of open-air steel columns under temperature change is discussed. According to the results, the air temperature can be utilized to determine the strain of the open-air steel column during winter. The determination coefficient of the temperature–stress model can reach 0.868, and the radial bending stress caused by the change in daily temperature cannot be ignored, accounting for 15.7% of the radial stress at the same time, which can provide a reference for stress calculations of similar structures.

Winter Time Ichthyoplankton Assemblages Following Dense Mucilage Event in the Sea Of Marmara, Türkiye

The community structure of ichthyoplankton after mucilage was investigated. For this purpose, three ichthyoplankton survey were conducted from 34 stations between December 2021 and March 2022. A total of 19 fish egg and 16 fish larvae species were identified. It was detected that the biodiversity of winter time ichthyoplankton was higher than previous studies. European Sprat, Sprattus sprattus had the highest mean biomass for both fish eggs and fish larvae, whereas Sardine, Sardina pilchardus had relatively low biomass. Karacabey Floodplain area, Büyükçekmece estuarine area and Erdek Bay were the most important spawning areas for winter spawners. It was found that ecosystem health of the Marmara Sea was suitable for fertilization, hatching and larval growth soon after the mucilage and hydrological regime recover itself immidiatelly.

Assessment of universal thermal climate index (UTCI) using the WRF-UCM model over a metropolitan city in India.

Rapid urbanization increases urban air temperature, considerably affecting health, comfort, and the quality of life in urban spaces. The accurate assessment of outdoor thermal comfort is crucial for urban health. In the present study, a high-resolution mesoscale model coupled with a layer Urban Canopy Model (WRF-UCM) is implemented over the city of Hyderabad (17.3850° N, 78.4867° E) to simulate urban meteorological conditions during the summer and winter period of 2009 and 2019. The universal thermal climate index (UTCI) has been estimated using the model-derived atmospheric variables and a human biometeorology parameter to assess the linkages between the outdoor environment and thermal comfort. Results revealed that during summer, the city experiences nearly 50h of very strong thermal stress, whereas about 120h of slight cold stress are experienced during winter. The urban area in Hyderabad expanded from 5 to 15% during the study period, leading to a 2.5℃ (2.8 ℃) increase in land surface temperature, and a 1.2 (1.9 ℃) rise in air temperature at 2m height and 1.5 (2.5 ℃) UTCI during summer (winter) time. The analysis reveals that the maximum UTCI values were noticed over built-up areas compared to other land classes during daytime and nighttime. The results derived from the present study have shown that the performance of WRF-UCM-derived UTCI reasonably portrayed the significant impact of urbanization on thermal comfort over the city and provided useful insights with regard to urban comfort and welfare.

Factors affecting the number of influenza patients before and during COVID-19 pandemic, Thailand.

This study was aimed to explore the association between potential factors including public health and social measures and the number of influenza patients in Thailand between 2014-2021. Secondary data from relevant agencies were collected. Generalized Estimating Equation (GEE) and regression coefficient (β) were performed at a significance level of 0.05. We found factors associated with number of influenza patients during the time prior to COVID-19 pandemic were monthly income per household (Adjusted β = -0.02; 95% CI: -0.03, -0.01), population density (Adjusted β = 1.00; 95% CI: 0.82, 1.18), rainy season (Adjusted β = 137.15; 95% CI: 86.17, 188.13) and winter time (Adjusted β = 56.46; 95% CI: 3.21, 109.71). During the time of COVID-19 pandemic, population density (Adjusted β = 0.20; 95% CI: 0.15, 0.26), rainy season (Adjusted β = -164.23; 95% CI: -229.93, -98.52), winter time (Adjusted β = 61.06; 95% CI: 0.71, 121.41), public health control measures (prohibition of entering to into an area with high number of COVID-19 infections (Adjusted β = -169.34; 95% CI: -233.52, -105.16), and restriction of travelling also reduced the number of influenza patients (Adjusted β = -66.88; 95% CI: -125.15, -8.62) were associated with number of influenza patients. This study commends strategies in monitoring influenza patients to focus on the areas with low income, high population density, and in specific seasons. Public health and social measures which can be implemented are prohibition of entering to risk-areas (lock down), and restriction of travelling across provinces which their effectiveness in reducing influenza infections.

Genetics of phenological development and implications for seed yield in lentil.

Understanding phenology, its genetics and agronomic consequences, is critical for crop adaptation. Here we aim to (i) characterize lentil response to photoperiod with a focus on five loci: the lentil ELF3 orthologue Sn, two loci linked to clusters of lentil FT orthologues, and two loci without candidates in chromosomes 2 and 5 (Experiment 1: 36 lines, short and long days in a phytotron), and (ii) establish the phenology-yield relationship (Experiment 2: 25 lines, 11 field environments). A vintage perspective, where we quantify time trends in phenotype over three decades of breeding, links both experiments. Yield increased linearly from older to newer varieties at 29 kg ha-1 year-1 or 1.5% year-1, correlated negatively with flowering time in both winter- and summer-rainfall regimes, and decoupled from biomass in favourable environments. Time to flowering shortened from older to newer varieties at -0.56% year-1 in the field, and -0.42% year-1 (short days) and -0.99% year-1 (long days) in the phytotron. Early-flowering lines of diverse origin carried multiple early alleles for the five loci, indicating that at least some of these loci affect phenology additively. Current germplasm primarily features the early-flowering haplotype for an FTb cluster region, hence the potential to increase phenological diversity with yield implications.

New data on the ecology of the fossil don hare (&lt;i&gt;Lepus tanaiticus&lt;/i&gt; [Gureev, 1964

A spore-pollen research of the contents of the gastrointestinal tracts and sediments containing frozen mummies of the fossil Don hare, discovered in the sediments of the Upper Pleistocene ice complex in the Verkhoyansk region of Yakutia, was carried out for the first time. Radiocarbon dating (C14) revealed that the found hares lived during the Karginian Interstadial of the Late Pleistocene, 32.5 thousand years ago (calibrated date). As a result, the understanding of the extinct Lepus tanaiticus ecology has been expanded: this species lived in cold steppes dominated by xerophytic communities, as well as in grass-forb and sedge-forb meadows; unlike the modern mountain hare L. timidus, which feeds during winter time mainly on branches and bark of woody plants and shrubs, the diet of Don hares in winter previously consisted of herbaceous plants.

Study on Sunlight Temperature Field of Steel Box Arch Ribs in Irregular Arch Bridges

Due to their excellent thermal conductivity and sensitivity to temperature changes, special attention should be paid to the influence of temperature on steel-structure bridges. The temperature effect is complex, especially for unstable steel arch bridges with complex structural forms. This paper proposes an approximate method that measures the three-dimensional temperature field of the symmetrical arch rib with the two-dimensional temperature field of multiple sections. In addition, it converts the complex radiant intensity calculation of the special-shaped steel box arch rib into the calculation of numerous planar radiant intensities. It uses the ANSYS Workbench to establish the three-dimensional transient thermal analysis finite element model of the No. 2 steel box arch rib. The influence of seasons and arch rib direction on the temperature field of steel box arch ribs and the stress and deformation of steel box arch ribs under non-linear temperature effects were analyzed. The results show that the temperature changes in different seasons significantly impact the temperature changes in the arch ribs. The change in the azimuth angle of the arch rib has a significant impact on the temperature difference between the web plates on both sides of the arch rib; under the influence of the temperature field at the most unfavorable time in summer and winter, symmetrical stress concentration occurs in the arch foot area. Furthermore, the maximum vertical displacement is 13.9 mm and 10.8 mm, respectively. Finally, when the angle is 40°, the maximum temperature difference between the web plates on both sides is 6.9 °C.

Optimum Control Wind Power Installations Being Subjected to Ice Formation on Wind Wheel Blades Within Wind Electrc Station Structure

On the basis of the analysis of wind electric unit control with preliminary installation of blades at a required angle according to an estimation of the drive pitch engine start timesubjected toice formation on wind wheel blades to minimize the wind turbine rotor angular speedtransient time, that promotes wind wheel rotation speed stability under the conditions of incomplete wind speed and the electric loadinginformation, that may change significantly with time, the criterion of access time to the of bladeposition control devicefrom the proposed and basic methods of control is established. The program module towind power automation control within thewind electric stationstructure is developed, providing relevantsystem preparation for external actions due to ice formation on blades wind wheel at different operation modes of power unit,that showedangular speed increase of a wind turbine rotor during winter time thus demanding more energy of a wind stream (14m/s) in comparison with the spring and autumn period (11.1m/s).Therefore, ice formation on wind wheel blades slows down wind wheel rotor rotation. Hence, the offered control method efficiency during winter time to avoid control delay is shown byrotation speed increase of a wind turbine rotor towards can be realizedforwind speeds exceeding 13m/s. The improved software control unit of wind power installation within the structure of wind power station based on the power unit operation modes provides: «Summer mode» - electric power generationunder favorable environment conditions; «Winter mode» - electric power generation under ice formation on blades wind wheel.

Research of the Spread of Covid-19 in World Wide and Particular Countries

To understand the spread of COVID-19, the data sets from Google and GitHub are obtained by using Python and R, and ARIMA model is established for prediction. By visualising the data sets, it can be found that the total trend of the COVID-19 is bimodal and reaches its peaks during the winter and spring time in 2022 and 2023, and this may due to the virus activity and government management. When taking into prediction, ARIMA (3,1,3) is the best predict model to forecast the overall spread trend of COVID-19 as the data is not normal distributed since it keeps fluctuating in the P-P plot, and it can be considered as time series, showing a seasonal pattern. This conclusion is drawn by calculating the values of AIC and BIC to see which model has smallest. At the same time, the ACF and PACF index could determine the p and q value in the model. The model can help to predict the spread of similar diseases.

Estimation of spawning stock biomass and spawning areas of sardine, (Sardina pilchardus) with winter time ichthyoplankton sampling in the Sea of Marmara, Türkiye

The spawning areas and spawning stock biomass of sardine were studied with ichthyoplankton sampling in the winter period from the 32 stations, in the Marmara Sea. The mean fish egg and larvae biomass in a unit area were calculated as 18.4 ± 5.3 eggs/10 m2 and 2.5 larvae/10 m2, respectively. Three main spawning areas were detected as Karacabey Floodplain area, Gönen, and Büyükçekmece estuarine area. The larvae are mostly located in the western part. The batch fecundity of sardine was detected between 2415.9 and 16738.3, with a mean of 6899.8 ± 255.7 eggs. The sex ratio (R), spawning fraction (S), mortality rate, and daily egg production (Po) were calculated as 0.53, 0.098, 0.62, and 9.25 eggs/m2 in the Marmara Sea. The spawning stock biomass (B) is estimated at 2998 tonnes in the Marmara Sea. Both ichthyoplankton biomass and spawning stock biomass were found relatively lower. It is recommended to apply stricter management sanctions for the sustainability of sardine stocks.

Seasonal changes of prokaryotic microbial community structure in Zhangjiayan Reservoir and its response to environmental factors

As a typical sub-deep reservoir in the upper reaches of the Yangtze River in the southwest region, Zhangjiayan Reservoir is also an important source of drinking water. Exploring the role of microorganisms in the material cycle of water bodies is of great significance for preventing the exacerbation of eutrophication in the reservoir. In this study, water samples from the overlying water of five points in the reservoir were collected four times in spring (April), summer (July), autumn (November), and winter (January) of 2022–2023 using a gas-tight water sampler. Physicochemical factors were measured, and the microbial community structure was analyzed by high-throughput MiSeq sequencing of the V3–V4 hypervariable region of 16S rRNA gene in order to explore the relationship between physicochemical factors and microbial community structure and the dominant microbial populations that affect eutrophication of the reservoir. The following results were obtained through analysis. Among the 20 overlying water samples from Zhangjiayan Reservoir, a total of 66 phyla, 202 classes, 499 orders, 835 families, 1716 genera, and 27,904 ASVs of the bacterial domain were detected. The phyla Proteobacteria and Actinobacteria were dominant in the microbial community of the overlying water in Zhangjiayan Reservoir. At the genus level, hgcI_clade and Actinobacteria had the highest abundance and was the dominant population. The microbial community in the water of Zhangjiayan Reservoir has a high level of diversity. The diversity index ranked by numerical order was winter > autumn > summer > spring. Significant differences were found in the composition and structure of the microbial community between the spring/summer and autumn/winter seasons (p < 0.05). Total phosphorus, dissolved total phosphorus, soluble reactive phosphorus, and dissolved oxygen have a significant impact on the composition and structure of the microbial community (p < 0.01). The bacterial community in the overlying water of Zhangjiayan Reservoir showed a mainly positive correlation. Sphingomonas, Brevundimonas, and Blastomonas were the central populations of the bacterial community in the overlying water of Zhangjiayan Reservoir. This study indicates that environmental factors, such as phosphorus and other nutrients, have a significant impact on the formation of the microbial community structure in different seasons. Sphingomonas, Brevundimonas, and Blastomonas are key populations that may have a significant impact on eutrophication in Zhangjiayan Reservoir.

Temporal variation of chemical profiles and insecticidal properties of Cinnamomum glanduliferum (Wall.) Nees leaf essential oil

Chinese traditional medicine has been faced with pest attacks in storage units for decades thus causing grave waste of resource and misfortunes. Essential oils are rich in different organs of Cinnamomum glanduliferum (Wall.) Nees which often exploited for insecticidal purpose. Contact toxicity and repellency rate of essential oils, derived from C. glanduliferum leaves monthly from 2021 to 2022, were investigated targeting storage pests Tribolium castaneum and Liposcelis bostrychophila for the first time. Gas chromatography-mass spectrometry (GC/MS) and principal component analysis (PCA) revealed L-camphor, cineole, nerolidol, linalool and caryophyllene were the main components. Dominant ingredients showed seasonal difference, as L-camphor was presented in majority of oils from September to November 2021 (72.60%−84.01%) but cineole was abundant in 2202–2208 specimens (66.58%−78.75%). It was confirmed by partial correlation analysis that the content of L-camphor positively related to average temperature but showed inverse relationship with month precipitation. Moreover, there was a significant positive correlation (p <0.01) between cineole percentage and month precipitation. The most powerful contact effect against T. castaneum and L. bostrychophila, was both found in L2109, indicating a low LD50/LC50 value (12.13 μg/adult and 104.67 μg/cm2 respectively). Winter time (December and January) had best repellent performance against two insect species with relative correlations higher than 0.5. The work intends to optimize ideal collection period of C. glanduliferum leaves by insecticidal properties, and also explore the relationship between climate and oil feature compounds, relieving the stress of pesticide dilemma and promoting further exploitation of bio-pesticides.