Most soil respiration measurements are conducted during the growing season.In tundra and boreal forest ecosystems,cumulative,non-growing season soil CO2 fluxes are reported to be a significant component of these syst...Most soil respiration measurements are conducted during the growing season.In tundra and boreal forest ecosystems,cumulative,non-growing season soil CO2 fluxes are reported to be a significant component of these systems＇ annual carbon budgets.However,little information exists on soil CO2 efflux during the non-growing season from alpine ecosystems.Therefore,comparing measurements of soil respiration taken annually versus during the growing season will improve the accuracy of estimating ecosystem carbon budgets,as well as predicting the response of soil CO2 efflux to climate changes.In this study,we measured soil CO2 efflux and its spatial and temporal changes for different altitudes during the non-growing season in an alpine meadow located in the Qilian Mountains,Northwest China.Field experiments on the soil CO2 efflux of alpine meadow from the Qilian Mountains were conducted along an elevation gradient from October 2010 to April 2011.We measured the soil CO2 efflux,and analyzed the effects of soil water content and soil temperature on this measure.The results show that soil CO2 efflux gradually decreased along the elevation gradient during the non-growing season.The daily variation of soil CO2 efflux appeared as a single-peak curve.The soil CO2 efflux was low at night,with the lowest value occurring between 02：00-06：00.Then,values started to rise rapidly between 07：00-08：30,and then descend again between 16：00-18：30.The peak soil CO2 efflux appeared from 11：00 to 16：00.The soil CO2 efflux values gradually decreased from October to February of the next year and started to increase in March.Non-growing season Q10 （the multiplier to the respiration rate for a 10℃ increase in temperature） was increased with raising altitude and average Q10 of the Qilian Mountains was generally higher than the average growing season Q10 of the Heihe River Basin.Seasonally,non-growing season soil CO2 efflux was relatively high in October and early spring and low in the winter.The soil CO2 efflux was positively correlated with soil temperature and soil water content.Our results indicate that in alpine ecosystems,soil CO2 efflux continues throughout the non-growing season,and soil respiration is an important component of annual soil CO2 efflux.展开更多
Based on continuous three-year measurements (from 2004 to 2007) of eddy covariance and related environmental factors, environmental controls on variation in soil respiration (Rs) during non-growing season were explore...Based on continuous three-year measurements (from 2004 to 2007) of eddy covariance and related environmental factors, environmental controls on variation in soil respiration (Rs) during non-growing season were explored in a maize agroecosystem in Northeast China. Our results indicated that during non-growing seasons, daily Rs was 1.08-4.08 g CO2 m-2 d-1, and the lowest occurred in late November. The average Rs of non-growing season was 456.06 ± 20.01 g CO2 m-2, accounting for 11% of the gross primary production (GPP) of the growing season. Additionally, at monthly scale, the lowest value of Rs appeared in January or February. From the beginning to the end of non-growing season, daily Rs tended to decrease first, and then increase to the highest. There was a significant quadratic curve relationship between Rs and soil temperature at 10 cm depth when soil temperature was more than 0°C (P<0.001), with the explaining ratio of 38%-70%. When soil water content was more than 0.1 m3 m-3, soil moisture at 10 cm depth was significantly parabolically correlated with Rs (P<0.001), explaining the rate of 18%-60%. Based on all the data of soil temperature of more than 0°C, a better model for Rs was established by coupling soil temperature and moisture, which could explain the rate of up to 53%-79%. Meanwhile, the standard error of regression estimation between the values of prediction and observation for Rs could reach 2.7%-11.8%. Rs in non-growing season can account for 22.4% of Rs in growing season, indicating that it plays a critical role in assessing the carbon budget in maize agroecosystem, Northeast China.展开更多
Aims The response pattern of terrestrial soil respiration to warming during non-growing seasons is a poorly understood phenomenon,though many believe that these warming effects are potentially significant.This study w...Aims The response pattern of terrestrial soil respiration to warming during non-growing seasons is a poorly understood phenomenon,though many believe that these warming effects are potentially significant.This study was conducted in a semiarid temperate steppe to examine the effects of warming during the non-growing seasons on soil respiration and the underlying mechanisms associated therewith.Methods This experiment was conducted in a semiarid temperate grassland and included 10 paired control and experimental plots.Experimental warming was achieved with open top chambers(OTCs)in October 2014.Soil respiration,soil temperature and soil moisture were measured several times monthly from November 2014 to April 2015 and from November 2015 to April 2016.Microbial biomass carbon(MBC),microbial biomass nitrogen(MBN)and available nitrogen content of soil were measured from 0 to 20 cm soil depth.Repeated measurement ANOVAs and paired-sample t tests were conducted to document the effect of warming,and the interactions between warming and time on the above variables.Simple regressions were employed to detect the underlying causality for the observed effects.Important Findings Soil respiration rate was 0.24μmol m^(−2) s^(−1) in the control plots during the non-growing seasons,which was roughly 14.4%of total soil carbon flux observed during growing seasons.Across the two non-growing seasons,warming treatment significantly increased soil temperature and soil respiration by 1.48℃(P<0.001)and 42.1%(P<0.01),respectively,when compared with control plots.Warming slightly,but did not significantly decrease soil moisture by 0.66%in the non-growing seasons from 2015 to 2016.In the non-growing seasons 2015–16,experimental warming significantly elevated MBC and MBN by 19.72%and 20.99%(both P<0.05),respectively.In addition,soil respiration responses to warming were regulated by changes in soil temperate,MBC and MBN.These findings indicate that changes in non-growing season soil respiration impact other components in the carbon cycle.Additionally,these findings facilitate projections regarding climate change–terrestrial carbon cycling.展开更多
To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau, CO2flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons. CO2 flux d...To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau, CO2flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons. CO2 flux dynamics was distinct between the two seasons. During the growing season from May to September, the ecosystem exhibited net CO2uptake from 08:00 to 19:00 (Beijing Standard Time), but net CO2 emission from 19:00 to 08:00.Maximum CO2 uptake appeared around 12:00 with values of 0.71, 1.19, 1.46 and 0.67 g CO2m-2 h-1 for June, July, August and September, respectively. Diurnal fluctuation of CO2 flux showed higher correlation with photosynthetic photon flux density than temperature. The maximum net CO2 influx occurred in August with a value of 247 g CO2 m-2. The total CO2 uptake by the ecosystem was up to 583 g CO2 m-2 for the growing season. During the non-growing season from January to April and from October to December, CO2 flux showed small fluctuation with the largest net CO2 efflux of 0.30 g CO2 m-2 h-1 in April. The diurnal CO2 flux was close to zero during most time of the day, but showed a small net CO2 efflux from 11:00 to 18:00. Diurnal CO2 flux, is significantly correlated to diurnal temperature in the non-growing season. The maximum monthly net CO2 efflux appeared in April, with a value of 105 g CO2 m-2. The total net CO2 efflux for the whole non-growing season was 356 g CO2 m-2.展开更多
A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study em...A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.展开更多
Intraseasonal Oscillation (ISO) which is the eastward-propagating disturbance with a period of 10 - 60 days has been the topic of interest since its discovery by Madden-Julian in 1972. Many researchers have published ...Intraseasonal Oscillation (ISO) which is the eastward-propagating disturbance with a period of 10 - 60 days has been the topic of interest since its discovery by Madden-Julian in 1972. Many researchers have published their work on ISO, yet they all agree that there is no clear understanding of this matter. By using daily observed surface temperature (T2m), this study reveals the presence of significant biweekly ISO over Tanzania, a period shorter than the anticipated Madden-Julian Oscillation (MJO) period of 30 to 60 days. It also reveals significant changes in wind direction when comparing the cold phase to the warm phase, highlighting a distinct atmospheric circulation pattern associated with each phase. Furthermore, the analysis reveals the presence of MJO-like eastward movement of pressure systems in the Subtropical High region, which is associated with this variability. This study presents a new analysis by providing a detailed analysis of the intraseasonal variability (ISV) of temperature over Tanzania, focusing on understanding the 2020 spatial-temporal patterns within the October-November-December (OND) season that may play a role in weather forecasting, agricultural planning, climate adaptation, reducing heat-related illnesses and contributing to the international effort to refine climate models and predictability.展开更多
Seasonal prediction of summer rainfall in China plays a crucial role in decision-making,environmental protection,and socio-economic development,while it currently has a low prediction skill.We developed a deep learnin...Seasonal prediction of summer rainfall in China plays a crucial role in decision-making,environmental protection,and socio-economic development,while it currently has a low prediction skill.We developed a deep learning-based seasonal prediction bias correction method for summer rainfall in China.Based on prediction fields from the flexible Global Ocean-Atmosphere-Land System Model finite volume version 2(FGOALS-f2),we optimized the loss function of U-Net,trained with different hyperparameters,and selected the optimum model.U-Net model can extract multi-scale feature information and preserve spatial information,making it suitable for processing meteorological data.With this endto-end model,the precipitation distribution can be obtained directly without using the traditional method of data dimensionality reduction(e.g.,Empirical Orthogonal Function),which could maximize the retention of spatio-temporal information of the input data.Optimization of the loss function enhances the prediction results and mitigates model overfitting.The independent prediction shows a significant skill improvement measured by the anomalous correlation coefficient score.The skill has an average value of 0.679 in China(0°–63°N,73°–133°E)and 0.691 in the region of the Chinese mainland,which significantly improves the dynamical prediction skill by 1357%and 4836%.This study suggests that the deep learning(U-Net)-based seasonal prediction bias correction method is a promising approach for improving rainfall prediction of the dynamical model.展开更多
Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the nume...Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.展开更多
Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of a...Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of associated hazards.Employing year-to-year increment(DY)and multiple linear regression approaches,this study developed a seasonal prediction model for pre-summer(i.e.,May and June)CHP frequency in South China(SC)during 1981–2022.Three robust predictor factors were identified:March sea surface temperature in Southwestern Atlantic,early-winter snow depth in East Europe,and winter soil moisture in Central Asia.Three predictors exert substantial impacts on presummer precipitation in SC via modulation of an anomalous anticyclone(cyclone)over the(subtropical)western North Pacific.In leave-one-out cross-validation test during 1981–2022,the prediction model exhibited reasonable performance in predicting the interannual and interdecadal variations and trends of CHP days.The temporal correlation coefficient(TCC)was 0.66 between the observations and predictions.In the independent hindcast for 2013–2022,the TCC was as high as 0.85.Moreover,coherent covariations were observed between the frequency and the amounts of CHP,with a TCC of 0.99 for 1981–2022.Those three predictors show good performance in forecasting CHP amounts over SC,with a TCC of 0.68 between the predictions and observations in the cross-validation test during 1981–2022 and of 0.86 in the independent hindcasts during 2013–2022.Notably,the predictors also showed good predictive skill for years with high CHP occurrence(e.g.,1998 and 2019).The predicted high-incidence areas of heavy precipitation days were highly consistent with observations,with a pattern correlation coefficient of 0.44(0.55)for 1998(2019).This study provides valuable insights to improve seasonal prediction of pre-summer CHP frequency in SC.展开更多
Wetland degradation is an escalating global challenge with profound impacts on animal diversity,particularly during successional processes.Birds,as highly mobile and environmentally sensitive organisms,serve as effect...Wetland degradation is an escalating global challenge with profound impacts on animal diversity,particularly during successional processes.Birds,as highly mobile and environmentally sensitive organisms,serve as effective indicators of ecological change.While previous studies have primarily focused on local community structures and species diversity during a specific season,there is a need to extend the research timeframe and explore broader spatial variations.Additionally,expanding from simple species diversity indices to more multidimensional diversity indices would provide a more comprehensive understanding of wetland health and resilience.To address these gaps,we investigated the effects of wetland degradation on bird diversity across taxonomic,phylogenetic,and functional dimensions in the Zoige Wetland,a plateau meadow wetland biodiversity hotspot.Surveys were conducted during both breeding(summer)and overwintering(winter)seasons across 20 transects in 5 sampling areas,representing 4 degradation levels(pristine,low,medium,and high).Our study recorded a total of 106 bird species from 32 families and 14 orders,revealing distinct seasonal patterns in bird community composition and diversity.Biodiversity indices were significantly higher in pristine and low-degraded wetlands,particularly benefiting waterfowl(Anseriformes,Ciconiiformes)and wading birds(Charadriiformes)in winter,when these areas provided superior food resources and habitat conditions.In contrast,medium and highly degraded wetlands supported increased numbers of terrestrial birds(Passeriformes)and raptors(Accipitriformes,Falconiformes).Seasonal differences in taxonomic,phylogenetic,and functional diversity indices highlighted the contrasting ecological roles of wetlands during breeding and overwintering periods.Furthermore,indicator species analysis revealed key species associated with specific degradation levels and seasons,providing valuable insights into wetland health.This study underscores the importance of spatiotemporal dynamics in understanding avian responses to wetland degradation.By linking seasonal patterns of bird diversity to habitat conditions,our findings contribute to conservation efforts and provide a framework for assessing wetland degradation and its ecological impacts.展开更多
Background Ovarian follicular fluid(FF)is a dynamic environment that changes with the seasons,affecting follicle development,ovulation,and oocyte quality.Cells in the follicles release tiny particles called extracellu...Background Ovarian follicular fluid(FF)is a dynamic environment that changes with the seasons,affecting follicle development,ovulation,and oocyte quality.Cells in the follicles release tiny particles called extracellular vesicles(EVs)containing vital regulatory molecules,such as microRNAs(miRNAs).These miRNAs are pivotal in facilitating commu-nication within the follicles through diverse signaling and information transfer forms.EV-coupled miRNA signaling is implicated to be associated with ovarian function,follicle and oocyte growth and response to various environmen-tal insults.Herein,we investigated how seasonal variations directly influence the ovulatory and anovulatory states of ovarian follicles and how are they associated with follicular fluid EV-coupled miRNA dynamics in horses.Results Ultrasonographic monitoring and follicular fluid aspiration of preovulatory follicles in horses during the ano-vulatory(spring:non-breeding)and ovulatory(spring,summer,and fall:breeding)seasons and subsequent EV isola-tion and miRNA profiling identified significant variation in EV-miRNA cargo content.We identified 97 miRNAs with dif-ferential expression among the groups and specific clusters of miRNAs involved in the spring transition(miR-149,-200b,-206,-221,-328,and-615)and peak breeding period(including miR-143,-192,-451,-302b,-100,and let-7c).Bioinformatic analyses showed enrichments in various biological functions,e.g.,transcription factor activity,transcrip-tion and transcription regulation,nucleic acid binding,sequence-specific DNA binding,p53 signaling,and post-trans-lational modifications.Cluster analyses revealed distinct sets of significantly up-and down-regulated miRNAs associ-ated with spring anovulatory(Cluster 1)and summer ovulation–the peak breeding season(Clusters 4 and 6).Conclusions The findings from the current study shed light on the dynamics of FF-EV-coupled miRNAs in relation to equine ovulatory and anovulatory seasons,and their roles in understanding the mechanisms involved in seasonal shifts and ovulation during the breeding season warrant further investigation.展开更多
The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum...The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets.These include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time series.The decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method.With SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues.Moreover,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal signals.It could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.展开更多
Approximately 3.44 billion tons of copper mine tailings(MT)were produced globally in 2018 with an increase of 45%from 2010.Significant efforts are being made to manage these tailings through storage facilities,recycli...Approximately 3.44 billion tons of copper mine tailings(MT)were produced globally in 2018 with an increase of 45%from 2010.Significant efforts are being made to manage these tailings through storage facilities,recycling,and reuse in different industries.Currently,a large portion of tailings are managed through the tailing storage facilities(TSF)where these tailings undergo hydro-thermal-mechanical stresses with seasonal cycles which are not comprehensively understood.This study presents an investigative study to evaluate the performance of control and cement-stabilized copper MT under the influence of seasonal cycles,freeze-thaw(F-T)and wet-dry(W-D)conditions,representing the seasonal variability in the cold and arid regions.The control and cement-stabilized MT samples were subjected to a maximum of 12 F-T and 12 W-D cycles and corresponding micro-and-macro behavior was investigated through scanning electron microscope(SEM),volumetric strain(εvT,wet density(r),moisture content loss,and unconfined compressive strength(UCS)tests.The results indicated the vulnerability of Copper MT to 67%and 75%strength loss reaching residual states with 12 F-T and 8 W-D cycles,respectively.Whereas the stabilized MT retained 39%-55%and 16%-34%strength with F-T and W-D cycles,demonstrating increased durability.This research highlights the impact of seasonal cycles and corresponding strength-deformation characteristics of control and stabilized Copper MT in cold and arid regions.展开更多
Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental pro...Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental properties of an eddy.However,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean perspective.In this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data set.The results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern Hemisphere.The seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes sharply.Further analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.展开更多
在当今世界文化交流愈发频繁的背景下,推动中华文明走向世界成为重中之重。翻译作为推动跨文化交流的重要手段之一,是连接不同文化的桥梁。而文化负载词由于其涵盖的大量民族特色词汇,成为翻译过程中的挑战,同时也是文化传播的重要工具...在当今世界文化交流愈发频繁的背景下,推动中华文明走向世界成为重中之重。翻译作为推动跨文化交流的重要手段之一,是连接不同文化的桥梁。而文化负载词由于其涵盖的大量民族特色词汇,成为翻译过程中的挑战,同时也是文化传播的重要工具。文章基于目的论视角,以纪录片Seasons of China中的中文文化负载词英译为例,探讨译者在翻译过程中采取的恰当翻译方法,以期为纪录片的文化负载词翻译研究提供一定的借鉴与参考。展开更多
To the Editor:Influenza viruses are constantly evolving and have the ability to infect a wide range of hosts,leading to recurrent infections and ongoing morbidity.[1]In China,the surveillance for respiratory infectiou...To the Editor:Influenza viruses are constantly evolving and have the ability to infect a wide range of hosts,leading to recurrent infections and ongoing morbidity.[1]In China,the surveillance for respiratory infectious diseases has been specifically performed for influenza and other respiratory infectious diseases.However,the current surveillance system relies heavily on the analysis of clinically confirmed influenza cases,which has lagged behind the times.[2]It is very important to establish a more accurate influenza prediction model,particularly in densely populated megacities.Our research aims to explore and develop more accurate and sensitive models for predicting influenza outbreaks.展开更多
Two-line hybrid rice with excellent quality is preferred in the Chinese market.However,there is a trade-off between reducing costs for hybrid seed production and lowering the outcrossing rate of the sterile line,which...Two-line hybrid rice with excellent quality is preferred in the Chinese market.However,there is a trade-off between reducing costs for hybrid seed production and lowering the outcrossing rate of the sterile line,which is largely determined by the stigma exsertion rate(SER).In this study,we constructed mutants of male sterility lines with improved grain length(GL)and SER in three elite early-season indica rice varieties through targeted manipulation of the TMS5 and GS3 genes using CRISPR/Cas9-mediated multiplex systems.We obtained a series of marker-free gs3 single mutants and gs3tms5 double mutants with significantly higher SER,longer grains,and increased 1000-grain weight compared with the wild type(WT).Importantly,the typically thermo-sensitive genic male sterile(TGMS)trait with a higher SER was observed in gs3tms5 mutants,and their F1 hybrids exhibited remarkable improvements in grain shape and yield-related traits.Our findings provided an efficient method to generate new valuable TGMS germplasm with improved SER through the mutagenesis of GS3 and TMS5 synergistically,and demonstrated that GS3 had pleiotropic effects on grain size,SER,and grain quality in early-season indica rice.展开更多
In many songbird species,birdsong features phonological syntax,meaning that the units within their vocal se-quences are ordered in a non-random way that adheres to a rule.While such syntactical patterns have been rich...In many songbird species,birdsong features phonological syntax,meaning that the units within their vocal se-quences are ordered in a non-random way that adheres to a rule.While such syntactical patterns have been richly described in many species,comparatively little is known about how those patterns contribute to song achieving its important functions.For each of song’s main functions,territorial defense and mate attraction,evidence of a role for syntax is limited.One species for which syntax has been thoroughly described is the Hermit Thrush(Catharus guttatus),which presents song types from their repertoires in a semi-predictable order and,in doing so,rapidly cycle up and down the frequency spectrum.The objective of the present study was to explore the importance of song syntax in the Hermit Thrush through a within-subject examination of how measures of syntax,such as the predictability of song type order within song sequences,shift over the breeding season.We hypothesized that,if such syntactical characteristics are important to breeding behaviour,they would be most prominent at the start of the breeding season when activity associated with territory establishment and mate attraction is most intense.Analysis revealed that,as predicted,the rigidness of song type ordering within se-quences was highest at the start of the season and declined thereafter.That song type sequences were most predictable at the vitally important early part of the breeding season fit our hypothesis that this aspect of song syntax is important to song’s functions related to territory establishment and/or mate attraction.Future work will clarify whether that role relates to one of song’s two main functions or serves song transmission in some broader way.展开更多
Despite a considerable global effort to eradicate malaria in the last few years,the disease burden in 2020 was 241 million,with 627000 deaths.India accounted for 83%of cases reported in the World Health Organization(W...Despite a considerable global effort to eradicate malaria in the last few years,the disease burden in 2020 was 241 million,with 627000 deaths.India accounted for 83%of cases reported in the World Health Organization(WHO)South-East Asia Region(WHO malaria report 2021).Nevertheless,India has shown its commitment to eliminating malaria from the country by framing the National Strategic Plan(NSP),according to which the districts have been stratified into four categories based on the malaria transmission intensity and the indicator used for categorization of the districts was annual parasite incidence(API).In North-East India,many highly endemic districts(API>2)are in the“Intensified Control Phase”and fall under category栿[1].A few pockets in such districts have disproportionate(API>10)due to forest and tribal dominance in those regions.The previous reports demonstrated a high malaria burden(API>10)in the district East Garo Hills[2];however,a few pockets of the district Udalguri are malaria hotspots with the API>5[3].展开更多
As the core of leaf functional traits,the trade-off relationship between the petiole and lamina expresses the plant's adaptability to the environment in terms of support structure and photosynthesis.We investigate...As the core of leaf functional traits,the trade-off relationship between the petiole and lamina expresses the plant's adaptability to the environment in terms of support structure and photosynthesis.We investigated the proportions of allometric growth in the relationship between the petiole and the lamina of broadleaf woody plants in temperate highland Tianshan Mountains montane forests through three dimensions(length,area,and mass),including the length of the lamina(LL)and the length of the petiole(PL),and the area of the lamina(LA)and petiole cross sectional area(PCA)versus the mass of the lamina(LM)and the mass of the petiole(PM),as well as exploring the characteristics of the variance in response to seasonal changes.We found that the functional traits in all three dimensions showed a clear convergent evolution as the seasons progressed,that is,a“seasonal effect”of increasing and then decreasing.The effect of the petioleelamina relationship under spring was minimal in the area dimension;the effects of the threeedimensional relationships of the traits were all highest in summer,and the effect of the petioleelamina relationship was lower in autumn.We also found that petiole traits are simultaneously and multiply affected by lamina traits,with LA and LM having additional effects on the length/mass and area dimensions,respectively.Compared to tree species,shrub species significantly require more light intensity and support capacity.Compound-leaved plants would invest more in photoluminescence,increasing leaf light capture efficiency and static load and dynamic resistance.Our results suggest that plants have rather complex trade-off mechanisms at the leaf level influencing their ability to adapt to the environment,emphasize the need for leaf-level studies on the relationships between functional traits in plants,and illustrate the importance of the season as a distinct time scale for plant trade-off mechanisms.展开更多
基金funded by the National Natural Science Foundation of China(31270482,41101026,91025002)the Natural Science Foundation of Gansu Province(1107RJZA089)+1 种基金the West Light Foundation of the Chinese Academy of Sciencesthe National Key Technology R & D Program(2012BAC08B05)
文摘Most soil respiration measurements are conducted during the growing season.In tundra and boreal forest ecosystems,cumulative,non-growing season soil CO2 fluxes are reported to be a significant component of these systems＇ annual carbon budgets.However,little information exists on soil CO2 efflux during the non-growing season from alpine ecosystems.Therefore,comparing measurements of soil respiration taken annually versus during the growing season will improve the accuracy of estimating ecosystem carbon budgets,as well as predicting the response of soil CO2 efflux to climate changes.In this study,we measured soil CO2 efflux and its spatial and temporal changes for different altitudes during the non-growing season in an alpine meadow located in the Qilian Mountains,Northwest China.Field experiments on the soil CO2 efflux of alpine meadow from the Qilian Mountains were conducted along an elevation gradient from October 2010 to April 2011.We measured the soil CO2 efflux,and analyzed the effects of soil water content and soil temperature on this measure.The results show that soil CO2 efflux gradually decreased along the elevation gradient during the non-growing season.The daily variation of soil CO2 efflux appeared as a single-peak curve.The soil CO2 efflux was low at night,with the lowest value occurring between 02：00-06：00.Then,values started to rise rapidly between 07：00-08：30,and then descend again between 16：00-18：30.The peak soil CO2 efflux appeared from 11：00 to 16：00.The soil CO2 efflux values gradually decreased from October to February of the next year and started to increase in March.Non-growing season Q10 （the multiplier to the respiration rate for a 10℃ increase in temperature） was increased with raising altitude and average Q10 of the Qilian Mountains was generally higher than the average growing season Q10 of the Heihe River Basin.Seasonally,non-growing season soil CO2 efflux was relatively high in October and early spring and low in the winter.The soil CO2 efflux was positively correlated with soil temperature and soil water content.Our results indicate that in alpine ecosystems,soil CO2 efflux continues throughout the non-growing season,and soil respiration is an important component of annual soil CO2 efflux.
基金supported by the National Outstanding Youth Fund Project (40625015)the National Basic Research Program of China (2006CB400502)
文摘Based on continuous three-year measurements (from 2004 to 2007) of eddy covariance and related environmental factors, environmental controls on variation in soil respiration (Rs) during non-growing season were explored in a maize agroecosystem in Northeast China. Our results indicated that during non-growing seasons, daily Rs was 1.08-4.08 g CO2 m-2 d-1, and the lowest occurred in late November. The average Rs of non-growing season was 456.06 ± 20.01 g CO2 m-2, accounting for 11% of the gross primary production (GPP) of the growing season. Additionally, at monthly scale, the lowest value of Rs appeared in January or February. From the beginning to the end of non-growing season, daily Rs tended to decrease first, and then increase to the highest. There was a significant quadratic curve relationship between Rs and soil temperature at 10 cm depth when soil temperature was more than 0°C (P<0.001), with the explaining ratio of 38%-70%. When soil water content was more than 0.1 m3 m-3, soil moisture at 10 cm depth was significantly parabolically correlated with Rs (P<0.001), explaining the rate of 18%-60%. Based on all the data of soil temperature of more than 0°C, a better model for Rs was established by coupling soil temperature and moisture, which could explain the rate of up to 53%-79%. Meanwhile, the standard error of regression estimation between the values of prediction and observation for Rs could reach 2.7%-11.8%. Rs in non-growing season can account for 22.4% of Rs in growing season, indicating that it plays a critical role in assessing the carbon budget in maize agroecosystem, Northeast China.
基金supported by the National Natural Science Foundation of China(31670477,31800399)China Postdoctoral Science Foundation(2018M642738,2018M642739)Henan Province Foundation and Advanced Technology Project(192102110085).
文摘Aims The response pattern of terrestrial soil respiration to warming during non-growing seasons is a poorly understood phenomenon,though many believe that these warming effects are potentially significant.This study was conducted in a semiarid temperate steppe to examine the effects of warming during the non-growing seasons on soil respiration and the underlying mechanisms associated therewith.Methods This experiment was conducted in a semiarid temperate grassland and included 10 paired control and experimental plots.Experimental warming was achieved with open top chambers(OTCs)in October 2014.Soil respiration,soil temperature and soil moisture were measured several times monthly from November 2014 to April 2015 and from November 2015 to April 2016.Microbial biomass carbon(MBC),microbial biomass nitrogen(MBN)and available nitrogen content of soil were measured from 0 to 20 cm soil depth.Repeated measurement ANOVAs and paired-sample t tests were conducted to document the effect of warming,and the interactions between warming and time on the above variables.Simple regressions were employed to detect the underlying causality for the observed effects.Important Findings Soil respiration rate was 0.24μmol m^(−2) s^(−1) in the control plots during the non-growing seasons,which was roughly 14.4%of total soil carbon flux observed during growing seasons.Across the two non-growing seasons,warming treatment significantly increased soil temperature and soil respiration by 1.48℃(P<0.001)and 42.1%(P<0.01),respectively,when compared with control plots.Warming slightly,but did not significantly decrease soil moisture by 0.66%in the non-growing seasons from 2015 to 2016.In the non-growing seasons 2015–16,experimental warming significantly elevated MBC and MBN by 19.72%and 20.99%(both P<0.05),respectively.In addition,soil respiration responses to warming were regulated by changes in soil temperate,MBC and MBN.These findings indicate that changes in non-growing season soil respiration impact other components in the carbon cycle.Additionally,these findings facilitate projections regarding climate change–terrestrial carbon cycling.
文摘To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau, CO2flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons. CO2 flux dynamics was distinct between the two seasons. During the growing season from May to September, the ecosystem exhibited net CO2uptake from 08:00 to 19:00 (Beijing Standard Time), but net CO2 emission from 19:00 to 08:00.Maximum CO2 uptake appeared around 12:00 with values of 0.71, 1.19, 1.46 and 0.67 g CO2m-2 h-1 for June, July, August and September, respectively. Diurnal fluctuation of CO2 flux showed higher correlation with photosynthetic photon flux density than temperature. The maximum net CO2 influx occurred in August with a value of 247 g CO2 m-2. The total CO2 uptake by the ecosystem was up to 583 g CO2 m-2 for the growing season. During the non-growing season from January to April and from October to December, CO2 flux showed small fluctuation with the largest net CO2 efflux of 0.30 g CO2 m-2 h-1 in April. The diurnal CO2 flux was close to zero during most time of the day, but showed a small net CO2 efflux from 11:00 to 18:00. Diurnal CO2 flux, is significantly correlated to diurnal temperature in the non-growing season. The maximum monthly net CO2 efflux appeared in April, with a value of 105 g CO2 m-2. The total net CO2 efflux for the whole non-growing season was 356 g CO2 m-2.
基金supported by the National Natural Science Foundation of China [grant number 42030605]the National Key R&D Program of China [grant number 2020YFA0608004]。
文摘A remarkable marine heatwave,known as the“Blob”,occurred in the Northeast Pacific Ocean from late 2013 to early 2016,which displayed strong warm anomalies extending from the surface to a depth of 300 m.This study employed two assimilation schemes based on the global Climate Forecast System of Nanjing University of Information Science(NUIST-CFS 1.0)to investigate the impact of ocean data assimilation on the seasonal prediction of this extreme marine heatwave.The sea surface temperature(SST)nudging scheme assimilates SST only,while the deterministic ensemble Kalman filter(EnKF)scheme assimilates observations from the surface to the deep ocean.The latter notably improves the forecasting skill for subsurface temperature anomalies,especially at the depth of 100-300 m(the lower layer),outperforming the SST nudging scheme.It excels in predicting both horizontal and vertical heat transport in the lower layer,contributing to improved forecasts of the lower-layer warming during the Blob.These improvements stem from the assimilation of subsurface observational data,which are important in predicting the upper-ocean conditions.The results suggest that assimilating ocean data with the EnKF scheme significantly enhances the accuracy in predicting subsurface temperature anomalies during the Blob and offers better understanding of its underlying mechanisms.
文摘Intraseasonal Oscillation (ISO) which is the eastward-propagating disturbance with a period of 10 - 60 days has been the topic of interest since its discovery by Madden-Julian in 1972. Many researchers have published their work on ISO, yet they all agree that there is no clear understanding of this matter. By using daily observed surface temperature (T2m), this study reveals the presence of significant biweekly ISO over Tanzania, a period shorter than the anticipated Madden-Julian Oscillation (MJO) period of 30 to 60 days. It also reveals significant changes in wind direction when comparing the cold phase to the warm phase, highlighting a distinct atmospheric circulation pattern associated with each phase. Furthermore, the analysis reveals the presence of MJO-like eastward movement of pressure systems in the Subtropical High region, which is associated with this variability. This study presents a new analysis by providing a detailed analysis of the intraseasonal variability (ISV) of temperature over Tanzania, focusing on understanding the 2020 spatial-temporal patterns within the October-November-December (OND) season that may play a role in weather forecasting, agricultural planning, climate adaptation, reducing heat-related illnesses and contributing to the international effort to refine climate models and predictability.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Postdoctoral Fellowship Program of CPSF(GZC20232598)+1 种基金China Postdoctoral Science Foundation(2024M753168)National Key Scientific and Technological Infrastructure Project“Earth System Numerical Simulation Facility”(EarthLab)。
文摘Seasonal prediction of summer rainfall in China plays a crucial role in decision-making,environmental protection,and socio-economic development,while it currently has a low prediction skill.We developed a deep learning-based seasonal prediction bias correction method for summer rainfall in China.Based on prediction fields from the flexible Global Ocean-Atmosphere-Land System Model finite volume version 2(FGOALS-f2),we optimized the loss function of U-Net,trained with different hyperparameters,and selected the optimum model.U-Net model can extract multi-scale feature information and preserve spatial information,making it suitable for processing meteorological data.With this endto-end model,the precipitation distribution can be obtained directly without using the traditional method of data dimensionality reduction(e.g.,Empirical Orthogonal Function),which could maximize the retention of spatio-temporal information of the input data.Optimization of the loss function enhances the prediction results and mitigates model overfitting.The independent prediction shows a significant skill improvement measured by the anomalous correlation coefficient score.The skill has an average value of 0.679 in China(0°–63°N,73°–133°E)and 0.691 in the region of the Chinese mainland,which significantly improves the dynamical prediction skill by 1357%and 4836%.This study suggests that the deep learning(U-Net)-based seasonal prediction bias correction method is a promising approach for improving rainfall prediction of the dynamical model.
基金jointly supported by the National Natural Science Foundation of China(Grant Nos.42122034,42075043,42330609)the Second Tibetan Plateau Scientific Expedition and Research program(2019QZKK0103)+2 种基金Key Talent Project in Gansu and Central Guidance Fund for Local Science and Technology Development Projects in Gansu(No.24ZYQA031)the Youth Innovation Promotion Association of Chinese Academy of Sciences(2021427)West Light Foundation of the Chinese Academy of Sciences(xbzg-zdsys-202215)。
文摘Seasonal precipitation has always been a key focus of climate prediction.As a dynamic-statistical combined method,the existing observational constraint correction establishes a regression relationship between the numerical model outputs and historical observations,which can partly predict seasonal precipitation.However,solving a nonlinear problem through linear regression is significantly biased.This study implements a nonlinear optimization of an existing observational constrained correction model using a Light Gradient Boosting Machine(LightGBM)machine learning algorithm based on output from the Beijing National Climate Center Climate System Model(BCC-CSM)and station observations to improve the prediction of summer precipitation in China.The model was trained using a rolling approach,and LightGBM outperformed Linear Regression(LR),Extreme Gradient Boosting(XGBoost),and Categorical Boosting(CatBoost).Using parameter tuning to optimize the machine learning model and predict future summer precipitation using eight different predictors in BCC-CSM,the mean Anomaly Correlation Coefficient(ACC)score in the 2019–22 summer precipitation predictions was 0.17,and the mean Prediction Score(PS)reached 74.The PS score was improved by 7.87%and 6.63%compared with the BCC-CSM and the linear observational constraint approach,respectively.The observational constraint correction prediction strategy with LightGBM significantly and stably improved the prediction of summer precipitation in China compared to the previous linear observational constraint solution,providing a reference for flood control and drought relief during the flood season(summer)in China.
基金Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)Science and Technology Development Plan in Jilin Province of China(20230203135SF)+1 种基金National Natural Science Foundation of China(41875119)Special Fund for Innovative Development of China Meteorological Administration(CXFZ2022J007)。
文摘Clustered heavy precipitation(CHP)events can severely impact human society,infrastructure,and natural ecosystems.Consequently,short-term climate prediction of CHP events is vital for the prevention and mitigation of associated hazards.Employing year-to-year increment(DY)and multiple linear regression approaches,this study developed a seasonal prediction model for pre-summer(i.e.,May and June)CHP frequency in South China(SC)during 1981–2022.Three robust predictor factors were identified:March sea surface temperature in Southwestern Atlantic,early-winter snow depth in East Europe,and winter soil moisture in Central Asia.Three predictors exert substantial impacts on presummer precipitation in SC via modulation of an anomalous anticyclone(cyclone)over the(subtropical)western North Pacific.In leave-one-out cross-validation test during 1981–2022,the prediction model exhibited reasonable performance in predicting the interannual and interdecadal variations and trends of CHP days.The temporal correlation coefficient(TCC)was 0.66 between the observations and predictions.In the independent hindcast for 2013–2022,the TCC was as high as 0.85.Moreover,coherent covariations were observed between the frequency and the amounts of CHP,with a TCC of 0.99 for 1981–2022.Those three predictors show good performance in forecasting CHP amounts over SC,with a TCC of 0.68 between the predictions and observations in the cross-validation test during 1981–2022 and of 0.86 in the independent hindcasts during 2013–2022.Notably,the predictors also showed good predictive skill for years with high CHP occurrence(e.g.,1998 and 2019).The predicted high-incidence areas of heavy precipitation days were highly consistent with observations,with a pattern correlation coefficient of 0.44(0.55)for 1998(2019).This study provides valuable insights to improve seasonal prediction of pre-summer CHP frequency in SC.
基金supported by the Southwest Minzu University Research Startup Funds (No.16011221038,RQD2022021)Double World-Class Project (No.CX2023010)。
文摘Wetland degradation is an escalating global challenge with profound impacts on animal diversity,particularly during successional processes.Birds,as highly mobile and environmentally sensitive organisms,serve as effective indicators of ecological change.While previous studies have primarily focused on local community structures and species diversity during a specific season,there is a need to extend the research timeframe and explore broader spatial variations.Additionally,expanding from simple species diversity indices to more multidimensional diversity indices would provide a more comprehensive understanding of wetland health and resilience.To address these gaps,we investigated the effects of wetland degradation on bird diversity across taxonomic,phylogenetic,and functional dimensions in the Zoige Wetland,a plateau meadow wetland biodiversity hotspot.Surveys were conducted during both breeding(summer)and overwintering(winter)seasons across 20 transects in 5 sampling areas,representing 4 degradation levels(pristine,low,medium,and high).Our study recorded a total of 106 bird species from 32 families and 14 orders,revealing distinct seasonal patterns in bird community composition and diversity.Biodiversity indices were significantly higher in pristine and low-degraded wetlands,particularly benefiting waterfowl(Anseriformes,Ciconiiformes)and wading birds(Charadriiformes)in winter,when these areas provided superior food resources and habitat conditions.In contrast,medium and highly degraded wetlands supported increased numbers of terrestrial birds(Passeriformes)and raptors(Accipitriformes,Falconiformes).Seasonal differences in taxonomic,phylogenetic,and functional diversity indices highlighted the contrasting ecological roles of wetlands during breeding and overwintering periods.Furthermore,indicator species analysis revealed key species associated with specific degradation levels and seasons,providing valuable insights into wetland health.This study underscores the importance of spatiotemporal dynamics in understanding avian responses to wetland degradation.By linking seasonal patterns of bird diversity to habitat conditions,our findings contribute to conservation efforts and provide a framework for assessing wetland degradation and its ecological impacts.
基金Southern Illinois University,Carbondale,ILMinistry of Higher Education&Scientific Research,Baghdad,Iraq+2 种基金NIFA-USDA Hatch project accession#1016077(Multistate#W4171)USDAARS project 6066-31000-015-00DNIH MS-IDeA network of Biomedical Research Excellence award 5P20GMI03476-19.GMI received a PhD scholarship from the Ministry of Higher Education&Scientific Research,Baghdad,Iraq.
文摘Background Ovarian follicular fluid(FF)is a dynamic environment that changes with the seasons,affecting follicle development,ovulation,and oocyte quality.Cells in the follicles release tiny particles called extracellular vesicles(EVs)containing vital regulatory molecules,such as microRNAs(miRNAs).These miRNAs are pivotal in facilitating commu-nication within the follicles through diverse signaling and information transfer forms.EV-coupled miRNA signaling is implicated to be associated with ovarian function,follicle and oocyte growth and response to various environmen-tal insults.Herein,we investigated how seasonal variations directly influence the ovulatory and anovulatory states of ovarian follicles and how are they associated with follicular fluid EV-coupled miRNA dynamics in horses.Results Ultrasonographic monitoring and follicular fluid aspiration of preovulatory follicles in horses during the ano-vulatory(spring:non-breeding)and ovulatory(spring,summer,and fall:breeding)seasons and subsequent EV isola-tion and miRNA profiling identified significant variation in EV-miRNA cargo content.We identified 97 miRNAs with dif-ferential expression among the groups and specific clusters of miRNAs involved in the spring transition(miR-149,-200b,-206,-221,-328,and-615)and peak breeding period(including miR-143,-192,-451,-302b,-100,and let-7c).Bioinformatic analyses showed enrichments in various biological functions,e.g.,transcription factor activity,transcrip-tion and transcription regulation,nucleic acid binding,sequence-specific DNA binding,p53 signaling,and post-trans-lational modifications.Cluster analyses revealed distinct sets of significantly up-and down-regulated miRNAs associ-ated with spring anovulatory(Cluster 1)and summer ovulation–the peak breeding season(Clusters 4 and 6).Conclusions The findings from the current study shed light on the dynamics of FF-EV-coupled miRNAs in relation to equine ovulatory and anovulatory seasons,and their roles in understanding the mechanisms involved in seasonal shifts and ovulation during the breeding season warrant further investigation.
基金supported by the National Natural Science Foundation of China(NO.42104028,42174030 and 42004017)the Open Fund of Hubei Luojia Laboratory(No.220100048 and 230100021)the Scientific Research Project of Hubei Provincial Department of Education,and Research Foundation of the Department of Natural Resources of Hunan Province(No.20230104CH)。
文摘The time-varying periodic variations in Global Navigation Satellite System(GNSS)stations affect the reliable time series analysis and appropriate geophysical interpretation.In this study,we apply the singular spectrum analysis(SSA)method to characterize and interpret the periodic patterns of GNSS deformations in China using multiple geodetic datasets.These include 23-year observations from the Crustal Movement Observation Network of China(CMONOC),displacements inferred from the Gravity Recovery and Climate Experiment(GRACE),and loadings derived from Geophysical models(GM).The results reveal that all CMONOC time series exhibit seasonal signals characterized by amplitude and phase modulations,and the SSA method outperforms the traditional least squares fitting(LSF)method in extracting and interpreting the time-varying seasonal signals from the original time series.The decrease in the root mean square(RMS)correlates well with the annual cycle variance estimated by the SSA method,and the average reduction in noise amplitudes is nearly twice as much for SSA filtered results compared with those from the LSF method.With SSA analysis,the time-varying seasonal signals for all the selected stations can be identified in the reconstructed components corresponding to the first ten eigenvalues.Moreover,both RMS reduction and correlation analysis imply the advantages of GRACE solutions in explaining the GNSS periodic variations,and the geophysical effects can account for 71%of the GNSS annual amplitudes,and the average RMS reduction is 15%.The SSA method has proved to be useful for investigating the GNSS timevarying seasonal signals.It could be applicable as an auxiliary tool in the improvement of nonlinear variations investigations.
基金the W.M.Keck Center for Nano-Scale Imaging in the Department of Chemistry and Biochemistry at the University of Arizona(Grant No.RRID:SCR_022884),with funding from the W.M.Keck Foundation Grant.
文摘Approximately 3.44 billion tons of copper mine tailings(MT)were produced globally in 2018 with an increase of 45%from 2010.Significant efforts are being made to manage these tailings through storage facilities,recycling,and reuse in different industries.Currently,a large portion of tailings are managed through the tailing storage facilities(TSF)where these tailings undergo hydro-thermal-mechanical stresses with seasonal cycles which are not comprehensively understood.This study presents an investigative study to evaluate the performance of control and cement-stabilized copper MT under the influence of seasonal cycles,freeze-thaw(F-T)and wet-dry(W-D)conditions,representing the seasonal variability in the cold and arid regions.The control and cement-stabilized MT samples were subjected to a maximum of 12 F-T and 12 W-D cycles and corresponding micro-and-macro behavior was investigated through scanning electron microscope(SEM),volumetric strain(εvT,wet density(r),moisture content loss,and unconfined compressive strength(UCS)tests.The results indicated the vulnerability of Copper MT to 67%and 75%strength loss reaching residual states with 12 F-T and 8 W-D cycles,respectively.Whereas the stabilized MT retained 39%-55%and 16%-34%strength with F-T and W-D cycles,demonstrating increased durability.This research highlights the impact of seasonal cycles and corresponding strength-deformation characteristics of control and stabilized Copper MT in cold and arid regions.
基金The National Key R&D Program of China under contract No.2022YFC2807604the Basic Scientific Fund for National Public Research Institutes of China under contract Nos 2022S02,2022Q03 and 2018S02+3 种基金the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)under contract No.2018SDKJ0105-3the National Natural Science Foundation of China under contract Nos 41876030,41976021,41876231,4190060432 and 41706220the program Impact and Response of Antarctic Seas to Climate Change under contract No.IRASCC 01-01-01Athe Taishan Scholars Project Fund under contract No.ts20190963。
文摘Mesoscale eddies are a prominent oceanic phenomenon that plays an important role in oceanic mass transport and energy conversion.Characterizing by rotational speed,the eddy intensity is one of the most fundamental properties of an eddy.However,the seasonal spatiotemporal variation in eddy intensity has not been examined from a global ocean perspective.In this study,we unveil the seasonal spatiotemporal characteristics of eddy intensity in the global ocean by using the latest satellite-altimetry-derived eddy trajectory data set.The results suggest that the eddy intensity has a distinct seasonal variation,reaching a peak in spring while attaining a minimum in autumn in the Northern Hemisphere and the opposite in the Southern Hemisphere.The seasonal variation of eddy intensity is more intense in the tropical-subtropical transition zones within latitudinal bands between 15°and 30°in the western Pacific Ocean,the northwestern Atlantic Ocean,and the eastern Indian Ocean because baroclinic instability in these areas changes sharply.Further analysis found that the seasonal variation of baroclinic instability precedes the eddy intensity by a phase of 2–3 months due to the initial perturbations needing time to grow into mesoscale eddies.
文摘在当今世界文化交流愈发频繁的背景下,推动中华文明走向世界成为重中之重。翻译作为推动跨文化交流的重要手段之一,是连接不同文化的桥梁。而文化负载词由于其涵盖的大量民族特色词汇,成为翻译过程中的挑战,同时也是文化传播的重要工具。文章基于目的论视角,以纪录片Seasons of China中的中文文化负载词英译为例,探讨译者在翻译过程中采取的恰当翻译方法,以期为纪录片的文化负载词翻译研究提供一定的借鉴与参考。
基金supported by grants from the Chinese Academy of Medical Sciences(CAMS)Innovation Fund for Medical Sciences(No.2021-I2M-1-044)the High-level Public Health Talent Development Program of Beijing(Discipline Leader-01-09)the Postdoctoral Fellowship Program of CPSF(No.GZC20231052)
文摘To the Editor:Influenza viruses are constantly evolving and have the ability to infect a wide range of hosts,leading to recurrent infections and ongoing morbidity.[1]In China,the surveillance for respiratory infectious diseases has been specifically performed for influenza and other respiratory infectious diseases.However,the current surveillance system relies heavily on the analysis of clinically confirmed influenza cases,which has lagged behind the times.[2]It is very important to establish a more accurate influenza prediction model,particularly in densely populated megacities.Our research aims to explore and develop more accurate and sensitive models for predicting influenza outbreaks.
基金the Natural Science Foundation of Zhejiang Province,China(Grant Nos.LY24C130004,LY22C135104,and LY23C130002)the National Natural Science Foundation of China(Grant No.31501288)+1 种基金the Open Project Program of State Key Laboratory of Rice Biology and Breeding,China(Grant No.20210207)Central Publicinterest Scientific Institution Basal Research Fund,China(Grant No.CPSIBRF-CNRRI-202203).
文摘Two-line hybrid rice with excellent quality is preferred in the Chinese market.However,there is a trade-off between reducing costs for hybrid seed production and lowering the outcrossing rate of the sterile line,which is largely determined by the stigma exsertion rate(SER).In this study,we constructed mutants of male sterility lines with improved grain length(GL)and SER in three elite early-season indica rice varieties through targeted manipulation of the TMS5 and GS3 genes using CRISPR/Cas9-mediated multiplex systems.We obtained a series of marker-free gs3 single mutants and gs3tms5 double mutants with significantly higher SER,longer grains,and increased 1000-grain weight compared with the wild type(WT).Importantly,the typically thermo-sensitive genic male sterile(TGMS)trait with a higher SER was observed in gs3tms5 mutants,and their F1 hybrids exhibited remarkable improvements in grain shape and yield-related traits.Our findings provided an efficient method to generate new valuable TGMS germplasm with improved SER through the mutagenesis of GS3 and TMS5 synergistically,and demonstrated that GS3 had pleiotropic effects on grain size,SER,and grain quality in early-season indica rice.
基金partly funded by an NSERC Discovery Grant received by LS Phillmorea UNB University Research Fund grant received by SP Roach
文摘In many songbird species,birdsong features phonological syntax,meaning that the units within their vocal se-quences are ordered in a non-random way that adheres to a rule.While such syntactical patterns have been richly described in many species,comparatively little is known about how those patterns contribute to song achieving its important functions.For each of song’s main functions,territorial defense and mate attraction,evidence of a role for syntax is limited.One species for which syntax has been thoroughly described is the Hermit Thrush(Catharus guttatus),which presents song types from their repertoires in a semi-predictable order and,in doing so,rapidly cycle up and down the frequency spectrum.The objective of the present study was to explore the importance of song syntax in the Hermit Thrush through a within-subject examination of how measures of syntax,such as the predictability of song type order within song sequences,shift over the breeding season.We hypothesized that,if such syntactical characteristics are important to breeding behaviour,they would be most prominent at the start of the breeding season when activity associated with territory establishment and mate attraction is most intense.Analysis revealed that,as predicted,the rigidness of song type ordering within se-quences was highest at the start of the season and declined thereafter.That song type sequences were most predictable at the vitally important early part of the breeding season fit our hypothesis that this aspect of song syntax is important to song’s functions related to territory establishment and/or mate attraction.Future work will clarify whether that role relates to one of song’s two main functions or serves song transmission in some broader way.
基金funded by Indian Council of Medical Research India(grant No.NER/55/2015-ECD-I).
文摘Despite a considerable global effort to eradicate malaria in the last few years,the disease burden in 2020 was 241 million,with 627000 deaths.India accounted for 83%of cases reported in the World Health Organization(WHO)South-East Asia Region(WHO malaria report 2021).Nevertheless,India has shown its commitment to eliminating malaria from the country by framing the National Strategic Plan(NSP),according to which the districts have been stratified into four categories based on the malaria transmission intensity and the indicator used for categorization of the districts was annual parasite incidence(API).In North-East India,many highly endemic districts(API>2)are in the“Intensified Control Phase”and fall under category栿[1].A few pockets in such districts have disproportionate(API>10)due to forest and tribal dominance in those regions.The previous reports demonstrated a high malaria burden(API>10)in the district East Garo Hills[2];however,a few pockets of the district Udalguri are malaria hotspots with the API>5[3].
基金supported by The Third Comprehensive Scientific Investigation Project in Xinjiang(2021XJKK0900).
文摘As the core of leaf functional traits,the trade-off relationship between the petiole and lamina expresses the plant's adaptability to the environment in terms of support structure and photosynthesis.We investigated the proportions of allometric growth in the relationship between the petiole and the lamina of broadleaf woody plants in temperate highland Tianshan Mountains montane forests through three dimensions(length,area,and mass),including the length of the lamina(LL)and the length of the petiole(PL),and the area of the lamina(LA)and petiole cross sectional area(PCA)versus the mass of the lamina(LM)and the mass of the petiole(PM),as well as exploring the characteristics of the variance in response to seasonal changes.We found that the functional traits in all three dimensions showed a clear convergent evolution as the seasons progressed,that is,a“seasonal effect”of increasing and then decreasing.The effect of the petioleelamina relationship under spring was minimal in the area dimension;the effects of the threeedimensional relationships of the traits were all highest in summer,and the effect of the petioleelamina relationship was lower in autumn.We also found that petiole traits are simultaneously and multiply affected by lamina traits,with LA and LM having additional effects on the length/mass and area dimensions,respectively.Compared to tree species,shrub species significantly require more light intensity and support capacity.Compound-leaved plants would invest more in photoluminescence,increasing leaf light capture efficiency and static load and dynamic resistance.Our results suggest that plants have rather complex trade-off mechanisms at the leaf level influencing their ability to adapt to the environment,emphasize the need for leaf-level studies on the relationships between functional traits in plants,and illustrate the importance of the season as a distinct time scale for plant trade-off mechanisms.
