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
To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau,CO_(2)flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons.CO_(2)flu...To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau,CO_(2)flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons.CO_(2)flux dynamics was distinct between the two seasons.During the growing season from May to September,the ecosystem exhibited net CO_(2)uptake from 08:00 to 19:00(Beijing Standard Time),but net CO_(2)emission from 19:00 to 08:00.Maximum CO_(2)uptake appeared around 12:00 with values of 0.71,1.19,1.46 and 0.67 g CO_(2)m-2 h-1 for June,July,August and September,respectively.Diurnal fluctuation of CO_(2)flux showed higher correlation with photosynthetic photon flux density than temperature.The maximum net CO_(2)influx occurred in August with a value of 247 g CO_(2)m-2.The total CO_(2)uptake by the ecosystem was up to 583 g CO_(2)m-2 for the growing season.During the non-growing season from January to April and from October to December,CO_(2)flux showed small fluctuation with the largest net CO_(2)efflux of 0.30 g CO_(2)m-2 h-1 in April.The diurnal CO_(2)flux was close to zero during most time of the day,but showed a small net CO_(2)efflux from 11:00 to 18:00.Diurnal CO_(2)flux,is significantly correlated to diurnal temperature in the non-growing season.The maximum monthly net CO_(2)efflux appeared in April,with a value of 105 g CO_(2)m-2.The total net CO_(2)efflux for the whole non-growing season was 356 g CO_(2)m-2.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 explored in ...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 CO_(2)m-2 d-1,and the lowest occurred in late November.The average Rs of non-growing season was 456.06±20.01 g CO_(2)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
Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio ac...Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.展开更多
Effective conservation relies on robust assessments;however,the lack of waterbird data in the Yellow River Basin(YRB)has led to an underestimation of key habitat significance.This study addressed this gap by evaluatin...Effective conservation relies on robust assessments;however,the lack of waterbird data in the Yellow River Basin(YRB)has led to an underestimation of key habitat significance.This study addressed this gap by evaluating YRB wetland conservation importance using waterbirds as indicators and applying Ramsar,Important Bird Areas(IBA),and East Asian-Australasian Flyway(EAAF)criteria.We integrated coordinated surveys with citizen science data,creating a framework that tackles data deficiencies along the under-monitored Central Asian Flyway(CAF).Our analysis identified 75 priority wetlands,supporting 15 threatened species and 49 exceeding global/flyway 1%thresholds,highlighting the basin's biodiversity.We observed strong seasonal habitat use,with high-altitude wetlands vital for breeding and migration,and the Yellow River Delta providing year-round refuge.This research also provided data to refine Baer's Pochard population estimates.Alarmingly,one-third of the identified priority areas,primarily rivers and lakes,remain unprotected.To address this,we recommend systematic surveys,enhanced protected areas,OECMs,and targeted wetland restoration.This study underscores the YRB's role in regional conservation and provides essential data for adaptive management,particularly emphasizing the CAF's importance.展开更多
Urbanization has profoundly reshaped biodiversity,yet its impacts on community seasonal changes remain poorly understood.Here,we used citizen science data from 839 bird species in 37 cities and their corresponding rur...Urbanization has profoundly reshaped biodiversity,yet its impacts on community seasonal changes remain poorly understood.Here,we used citizen science data from 839 bird species in 37 cities and their corresponding rural areas in China to assess how urbanization alters seasonal changes in bird communities.We calculated S??rensen beta dissimilarity indices(β_(sor))between seasons to compare the seasonality of communities in urban and rural areas and decomposed these indices into turnover(β_(sim))and nestedness(β_(nes))components.We evaluated whether there are differences in the latitudinal clines in community seasonality between urban and rural areas,and explored whether environmental and socio-economic factors affect the urbanization-driven changes in community seasonality.Our results show that the overall seasonalβ_(sor)in urban communities was 16.2%higher than in rural areas,due to a 49.5%increase inβ_(nes)(urban:0.22±0.12 vs.rural:0.15±0.08),but there was no significant difference inβ_(sim).In rural areas,β_(sor)increased with latitude,butβ_(sor)showed no latitudinal trend in urban communities.Human population emerges as a key predictor of urbanization-driven changes in the species turnover and nestedness components,with larger cities showing lower species turnover but higher nestedness components.We conclude that urbanization alters the seasonality of bird communities through nestedness components,decouples the relationship between community seasonality and latitude,and concentrates its impacts in densely populated cities.Future research must employ long-term monitoring to track how urbanization changes bird communities in space and time.展开更多
The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain....The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain.In this study,we analyze how global warming levels(GWLs)of 1.5℃ and 2℃ could affect the timing of rainfall onset(RODs),rainfall cessation(RCDs),and the overall duration of the rainy season(LRS)over global land monsoon(GLM)regions using simulations from CMIP6 under the SSP2-4.5 and SSP5-8.5 scenarios.With high model consensus,our results reveal that RODs are projected to occur later over Southern Africa,North Africa,and South America,but earlier over South Asia and Australia,in a warmer climate.The projected early RODs in Australia are more pronounced at the 2℃ GWL under SSP5-8.5.On the other hand,early RCDs are projected over South America and East Asia,while late RCDs are projected over North Africa,with high inter-model agreement.These changes are associated with a future decrease in LRS in most GLM regions.Additionally,we found that continuous warming over 1.5℃ will further reduce the length of the rainy season,especially over the South America,North Africa,and Southern Africa monsoon regions.The findings underscore the urgent need to mitigate global warming.展开更多
Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,bu...Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,but the regional sources of halocarbons in China are not yet well comprehended.To investigate the characteristics,emissions,and source profiles,this study conducted a field campaign in Xiamen,a coastal city in southeastern China.Higher enhancements were found in the unregulated halocarbons(CH_(3)Cl,CH_(2)Cl_(2),CHCl_(3))than in the MP eliminated species(CCl_(4),CH_(3)Br)and theMP controlled species(HCFCs,HFCs).Many of the measured halocarbons varied seasonally and regionally,depending on the anthropogenic sources and atmospheric transport.Backward trajectory analysis showed that the air masses from inland were polluted over Shandong,Hebei,and northern Fujian in the cold season,while the air masses fromthe sea in the warm season were clean.Different air masses in two seasons were associated with the halocarbon patterns in the study area.Industrial activities,especially solvent usage,were the primary sources of halocarbons.The emission hot spots in Fujian Province were concentrated in Sanming,Fuzhou,and Xiamen,and the unregulated halocarbons made the largest contribution.This study provides an insight for a deep understanding of the characteristics and potential sources of halocarbons,and for strengthened management of halocarbons in China.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
The Himalayan monal(Lophophorus impejanus),Nepal’s national bird,is a protected species facing significant conservation challenges.Understanding the distribution and habitat preferences of the Himalayan monal(HM)is c...The Himalayan monal(Lophophorus impejanus),Nepal’s national bird,is a protected species facing significant conservation challenges.Understanding the distribution and habitat preferences of the Himalayan monal(HM)is crucial for its conservation.This study was conducted in the Langtang National Park(LNP),Nepal using the route census method during both winter(November/December 2022)and summer(June 2023)seasons to examine the seasonal variation in HM’s elevational distribution and habitat preference.Further,we assessed their conservation threats by conducting a semi-structured questionnaire survey with the local residents.During the winter period,the HMs preferred grassland habitats,while in the summer,their preference shifted to shrubland and barren area.HM abundance was negatively associated with the Normalized Differential Vegetation Index(NDVI)and the shortest distance from the survey trails in the winter.The HMs actively avoided areas with high anthropogenic pressure.In the summer,they showed a wider elevational range up to 4400 m above sea level(a.s.l.),with a higher sighting frequency between 3600 and 3900 m a.s.l.The questionnaire survey of the local residents revealed that anthropogenic pressure such as poaching and free-ranging livestock grazing are the major threats to the species in the study area.This study provides valuable insight into the complex habitat preferences and critical threats faced by the HMs in LNP and underscores the urgent need for targeted conservation action.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
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
The building construction industry,recognized as one of the eight high-risk sectors,also serves as a crucial pillar of the national economy and a key source of employment.Major project advancements typically concentra...The building construction industry,recognized as one of the eight high-risk sectors,also serves as a crucial pillar of the national economy and a key source of employment.Major project advancements typically concentrate between April to June and September to November each year.However,construction progress tends to slow down during July and August due to increased rainfall associated with the flood season.The impact of the flood season on construction projects is primarily reflected in areas such as civil works,machinery and equipment,and temporary power supply.By establishing a dual-control emergency management system for the flood season,construction enterprises can enhance their emergency response capabilities,effectively reduce management challenges,and improve the overall efficiency of emergency handling.展开更多
The symbiotic association between reef-building corals and Symbiodiniaceae is pivotal for coral reef ecosystems,yet remains susceptible to environmental factors.Currently,there is a dearth of research examining season...The symbiotic association between reef-building corals and Symbiodiniaceae is pivotal for coral reef ecosystems,yet remains susceptible to environmental factors.Currently,there is a dearth of research examining seasonal fluctuations in coral-associated Symbiodiniaceae communities.In this study,we investigated the seasonal dynamics of Symbiodiniaceae communities associated with coral species in the Luhuitou coral reef using high-throughput sequencing techniques and SymPortal analytical framework.The results indicated that the genus Cladocopium exhibited dominance(averaging 82%),followed by Durusdinium(18%)and Breviolum(0.01%)within the examined coral species.Among the 521 Symbiodiniaceae ITS2 sequence types,C15 emerged as the prevalent type(13.24%),trailed by C3u(9.51%)and D1(8.57%).Interestingly,Symbiodiniaceae communities varied among different coral species.Pocillopora damicornis displayed a predominant association with Durusdinium,while Porites lutea,Goniastrea retiformis,Montipora truncata,Montipora aequituberculata,and Acropora divaricata were entirely dominated by the genus Cladocopium(100%),showcasing distinct host specificity.In the cases of Hydnophora exesa,Acropora latistella,Acropora digitifera,and seawater,both Cladocopium and Durusdinium were concurrently detected.Moreover,the diversity of Symbiodiniaceae associated with P.damicornis,P.lutea,G.retiformis,M.truncata,M.aequituberculata,and A.digitifera exhibited significant variations across different seasons.Notably,the results revealed that the alterations in Symbiodiniaceae community compositions were primarily driven by nutrient concentrations and seawater temperature.The network analysis of Symbiodiniaceae revealed the dominant Symbiodiniaceae types C15,C17f,C3u,C3,and D4 were exclusive.This study provided the seasonal variation characteristics of Symbiodiniaceae communities among different coral species,which may be a potential adaptive mechanism to environmental conditions.展开更多
Antarctic krill(Euphausia superba)is a keystone species in the Southern Ocean;however,seasonal variations in reproductive development for krill are complex and remains unknown.A histological investigation with observa...Antarctic krill(Euphausia superba)is a keystone species in the Southern Ocean;however,seasonal variations in reproductive development for krill are complex and remains unknown.A histological investigation with observations of external secondary sex features of krill in the south Scotia Sea region was carried out using a multi-seasonal dataset for detail reproductive descriptions for this commercially important species.The monthly development of secondary sexual characteristics,the thelycum,as well as of oocytes over a period of two years were described.It was observed that krill have diverse reproductive development characteristics within the ovary,and that this function differently between the juvenile,sub-adult,and adult stages.During the summer,adult krill ovaries are large and ripe with oocytes rich in yolk ready for release in late summer.Post spawning,the ovaries resorb,fragment,and regress throughout the autumn and winter.During reproductive diapause period,krill focus on absorbing nutrients.Un-released eggs are reabsorbed by the ovary,the permanent germinal zone is active,and early oocytes begin to develop in preparation for the egg production phase.Krill that are about to spawn have an ovary that fills the space between the digestive gland and muscle.The ovarian development of krill is divided into 10 sexual developmental stages.As a part of this study,data on the carapace thickness with similar development patterns in krill size and carapace width,was investigated for the first time to help understand krill growth and development.展开更多
Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the au...Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the authors utilize two mainstream reanalysis datasets for the period 1979-2013 and propose an effective statistical seasonal forecasting model-namely,the Sun Yat-sen University(SYSU)Model-for predicting the number of TC landfalls on TW based on the environmental factors in the preseason.The comprehensive predictor sampling and multiple linear regression show that the 850-hPa meridional wind over the west of the Antarctic Peninsula in January,the 300-hPa specific humidity over the open ocean southwest of Australia in January,the 300-hPa relative vorticity over the west of the Sea of Okhotsk in March,and the sea surface temperature in the South Indian Ocean in April,are the most significant predictors.The correlation coefficient between the modeled results and observations reaches 0.87.The model is validated by the leave-one-out and nine-fold cross-validation methods,and recent 9-yr observations(2014-2022).The Antarctic Oscillation,variabilities of the western Pacific subtropical high,Asian summer monsoon,and oceanic tunnel are the possible physical linkages or mechanisms behind the model result.The SYSU Model exhibits a 98%hit rate in 1979-2022(43 out of 44),suggesting an operational potential in the seasonal forecasting of TC landfalls on TW.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
Fire season affects the dynamic changes of post-fire vegetation communities and carbon emissions.Analyzing its global patterns supports understanding of the ecological impacts of fires and responses of fires to climat...Fire season affects the dynamic changes of post-fire vegetation communities and carbon emissions.Analyzing its global patterns supports understanding of the ecological impacts of fires and responses of fires to climate change.Meteorological variables have been widely used to quantify fire season in current studies.However,their results can not be used to assess climate impacts on the seasonality of fire activities.Here we utilized satellite-based Moderate Resolution Imaging Spectroradiometer(MODIS)burned area data from 2001 to 2022 to identify global fire season types based on the number of peaks within a year.Using satellite data and innovatively processing the data to obtain a more accurate length of the fire season.We divided fire season types and examined the spatial distribution of fire season types across the Koppen-Geiger climate(KGC)zones.At a global scale,we identified three major fire season types,including unimodal(31.25%),bimodal(52.07%),and random(16.69%).The unimodal fire season primarily occurs in boreal and tropical regions lasting about 2.7 mon.In comparison,temperate ecosystems tend to have a longer fire season(3 mon)with two peaks throughout the year.The KGC zones show divergent contributions from the fire season types,indicating potential impacts of the climatic conditions on fire seasonality in these regions.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 Knowledge Innovation Project of the Chinese Academy of Sci-ences(Grant Nos.KZCX1-SW-01-01A5and KZCX1-09-01)the State Key Basic Research Plan of China(GrantNo.2002CB412501)+2 种基金and partly by the joint research projects between National Institute for En-vironmental Studies,Japan and Northwest Plateau Institute of BiologyChinese Academy of Sciences(Grant Nos.13575035 and B13)as well as partly by the project of Asia-PacificEnvironmental Innovation Strategy(APEIS).
文摘To assess carbon budget for shrub ecosystems on the Qinghai-Tibet Plateau,CO_(2)flux was measured with an open-path eddy covariance system for an alpine shrub ecosystem during growing and non-growing seasons.CO_(2)flux dynamics was distinct between the two seasons.During the growing season from May to September,the ecosystem exhibited net CO_(2)uptake from 08:00 to 19:00(Beijing Standard Time),but net CO_(2)emission from 19:00 to 08:00.Maximum CO_(2)uptake appeared around 12:00 with values of 0.71,1.19,1.46 and 0.67 g CO_(2)m-2 h-1 for June,July,August and September,respectively.Diurnal fluctuation of CO_(2)flux showed higher correlation with photosynthetic photon flux density than temperature.The maximum net CO_(2)influx occurred in August with a value of 247 g CO_(2)m-2.The total CO_(2)uptake by the ecosystem was up to 583 g CO_(2)m-2 for the growing season.During the non-growing season from January to April and from October to December,CO_(2)flux showed small fluctuation with the largest net CO_(2)efflux of 0.30 g CO_(2)m-2 h-1 in April.The diurnal CO_(2)flux was close to zero during most time of the day,but showed a small net CO_(2)efflux from 11:00 to 18:00.Diurnal CO_(2)flux,is significantly correlated to diurnal temperature in the non-growing season.The maximum monthly net CO_(2)efflux appeared in April,with a value of 105 g CO_(2)m-2.The total net CO_(2)efflux for the whole non-growing season was 356 g CO_(2)m-2.
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 CO_(2)m-2 d-1,and the lowest occurred in late November.The average Rs of non-growing season was 456.06±20.01 g CO_(2)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.
基金supported by the Key Research and Development Plan Project of Heilongjiang Province (2022ZX02C13)。
文摘Xishui National Forest Park in Heilongjiang Province hosts China's most pristine temperate forests and serves as a key site for ecotourism and forest therapy.However,the emission patterns of phytoncides(key bio active compounds) remain poorly understood,limiting their therapeutic application.This study provides the first comprehensive characterization of spatiotemporal dynamics in airborne phytoncides and their synergistic interactions with environmental factors throughout the autumn-early spring seasonal transition in a temperate forest ecosystem.We analyzed the compositional dynamics of phytoncides and terpenoid content variations using thermal desorption-gas chromatography-mass spectrometry(TD-GC-MS) from September 2024 to March 2025.This period encompassed seasonal transitions from autumn to early spring,including diurnal variations in September and snowfall events in November.The method demonstrated detection limits(LODs) ranging from 1.35 to 5.33 ng m-3 and quantification limits(LOQs) from 4.09 to 16.15 ng m-3.Our results revealed pronounced seasonal fluctuations in phytoncide composition.In September,terpenoids,esters,alcohols,and alkanes displayed a diurnal "decrease-increase" trend,whereas aldehydes and ketones peaked at midday.Notably,esters and alcohols were undetectable in November and January.By January,terpenoids reached their lowest proportion(0.17±0.02%) at noon.Five terpenoids(α-pinene,myrcene,D-limonene,camphene,p-cymene) were detected in September,four(α-pinene,D-limonene,camphene,p-cymene) in November,two(D-limonene,p-cymene) in January,and only p-cymene in March.The total concentration and emission rate of the five terpenoids peaked in September afternoons at 1961.58±106.67 ng m^(-3) and653.86±35.56 ng m^(-3) h^(-1),respectively.Nocturnal emissions(32131.95±2522.21 ng m^(-3)) significantly surpassed daytime levels(14473.04±958.49 ng m^(-3)),with emission rates escalating from 1447.30±95.85 ng m^(-3) h^(-1)(day) to 5355.33±420.37 ng m^(-3) h^(-1)(night),marking a3.7-fold increase.Snowfall dramatically elevated terpenoid concentrations(pre-snowfall:158.58±14.12 ng m^(-3);post-snowfall:1080.57±57.76 ng m^(-3)) and emission rates(pre-snowfall:52.86±4.71 ng m^(-3) h^(-1);post-snowfall:360.19±19.25 ng m^(-3) h^(-1)),reflecting a 6.8-fold surge.This study underscores the profound influence of light intensity,seasonal shifts,and climatic conditions on airborne phytoncide levels,offering a scientific foundation for optimizing forest therapy and ecotourism strategies.
基金The Science and Technology Basic Resources Survey Project,No.2021FY101002Wetland Protection and Restoration in China Funded by the Palson Institute and Laoniu Foundation,UNDP-GEF Flyway Project,No.PIMS ID:6110。
文摘Effective conservation relies on robust assessments;however,the lack of waterbird data in the Yellow River Basin(YRB)has led to an underestimation of key habitat significance.This study addressed this gap by evaluating YRB wetland conservation importance using waterbirds as indicators and applying Ramsar,Important Bird Areas(IBA),and East Asian-Australasian Flyway(EAAF)criteria.We integrated coordinated surveys with citizen science data,creating a framework that tackles data deficiencies along the under-monitored Central Asian Flyway(CAF).Our analysis identified 75 priority wetlands,supporting 15 threatened species and 49 exceeding global/flyway 1%thresholds,highlighting the basin's biodiversity.We observed strong seasonal habitat use,with high-altitude wetlands vital for breeding and migration,and the Yellow River Delta providing year-round refuge.This research also provided data to refine Baer's Pochard population estimates.Alarmingly,one-third of the identified priority areas,primarily rivers and lakes,remain unprotected.To address this,we recommend systematic surveys,enhanced protected areas,OECMs,and targeted wetland restoration.This study underscores the YRB's role in regional conservation and provides essential data for adaptive management,particularly emphasizing the CAF's importance.
基金supported by the National Natural Science Foundation of China(Grant No.32271733)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2023A1515011045)。
文摘Urbanization has profoundly reshaped biodiversity,yet its impacts on community seasonal changes remain poorly understood.Here,we used citizen science data from 839 bird species in 37 cities and their corresponding rural areas in China to assess how urbanization alters seasonal changes in bird communities.We calculated S??rensen beta dissimilarity indices(β_(sor))between seasons to compare the seasonality of communities in urban and rural areas and decomposed these indices into turnover(β_(sim))and nestedness(β_(nes))components.We evaluated whether there are differences in the latitudinal clines in community seasonality between urban and rural areas,and explored whether environmental and socio-economic factors affect the urbanization-driven changes in community seasonality.Our results show that the overall seasonalβ_(sor)in urban communities was 16.2%higher than in rural areas,due to a 49.5%increase inβ_(nes)(urban:0.22±0.12 vs.rural:0.15±0.08),but there was no significant difference inβ_(sim).In rural areas,β_(sor)increased with latitude,butβ_(sor)showed no latitudinal trend in urban communities.Human population emerges as a key predictor of urbanization-driven changes in the species turnover and nestedness components,with larger cities showing lower species turnover but higher nestedness components.We conclude that urbanization alters the seasonality of bird communities through nestedness components,decouples the relationship between community seasonality and latitude,and concentrates its impacts in densely populated cities.Future research must employ long-term monitoring to track how urbanization changes bird communities in space and time.
基金supported by the Australian Research Council(Grant No.CE230100012)。
文摘The onset,cessation,and length of the rainy season are crucial for global water resources,agricultural practices,and food security.However,the response of precipitation seasonality to global warming remains uncertain.In this study,we analyze how global warming levels(GWLs)of 1.5℃ and 2℃ could affect the timing of rainfall onset(RODs),rainfall cessation(RCDs),and the overall duration of the rainy season(LRS)over global land monsoon(GLM)regions using simulations from CMIP6 under the SSP2-4.5 and SSP5-8.5 scenarios.With high model consensus,our results reveal that RODs are projected to occur later over Southern Africa,North Africa,and South America,but earlier over South Asia and Australia,in a warmer climate.The projected early RODs in Australia are more pronounced at the 2℃ GWL under SSP5-8.5.On the other hand,early RCDs are projected over South America and East Asia,while late RCDs are projected over North Africa,with high inter-model agreement.These changes are associated with a future decrease in LRS in most GLM regions.Additionally,we found that continuous warming over 1.5℃ will further reduce the length of the rainy season,especially over the South America,North Africa,and Southern Africa monsoon regions.The findings underscore the urgent need to mitigate global warming.
基金supported by the National Natural Science Foundation of China(Nos.42030707,72394404)the International Partnership Program of the Chinese Academy of Sciences(No.121311KYSB20190029)the Fundamental Research Fund for the Central Universities(Nos.20720210083,20720210082).
文摘Halocarbons play a vital role in ozone depletion and global warming,and are regulated by the Montreal Protocol(MP)and its amendments.China has been identified as an important contributor to the halocarbon emissions,but the regional sources of halocarbons in China are not yet well comprehended.To investigate the characteristics,emissions,and source profiles,this study conducted a field campaign in Xiamen,a coastal city in southeastern China.Higher enhancements were found in the unregulated halocarbons(CH_(3)Cl,CH_(2)Cl_(2),CHCl_(3))than in the MP eliminated species(CCl_(4),CH_(3)Br)and theMP controlled species(HCFCs,HFCs).Many of the measured halocarbons varied seasonally and regionally,depending on the anthropogenic sources and atmospheric transport.Backward trajectory analysis showed that the air masses from inland were polluted over Shandong,Hebei,and northern Fujian in the cold season,while the air masses fromthe sea in the warm season were clean.Different air masses in two seasons were associated with the halocarbon patterns in the study area.Industrial activities,especially solvent usage,were the primary sources of halocarbons.The emission hot spots in Fujian Province were concentrated in Sanming,Fuzhou,and Xiamen,and the unregulated halocarbons made the largest contribution.This study provides an insight for a deep understanding of the characteristics and potential sources of halocarbons,and for strengthened management of halocarbons in China.
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an MSc thesis research grant from the Zoological Society of London(ZSL)Nepal.RCK’s effort was supported in part by the Office of Research Infrastructure Programs(ORIP)of the National Institutes of Health through grant number P51OD010425 to the Washington National Primate Research Center,USA。
文摘The Himalayan monal(Lophophorus impejanus),Nepal’s national bird,is a protected species facing significant conservation challenges.Understanding the distribution and habitat preferences of the Himalayan monal(HM)is crucial for its conservation.This study was conducted in the Langtang National Park(LNP),Nepal using the route census method during both winter(November/December 2022)and summer(June 2023)seasons to examine the seasonal variation in HM’s elevational distribution and habitat preference.Further,we assessed their conservation threats by conducting a semi-structured questionnaire survey with the local residents.During the winter period,the HMs preferred grassland habitats,while in the summer,their preference shifted to shrubland and barren area.HM abundance was negatively associated with the Normalized Differential Vegetation Index(NDVI)and the shortest distance from the survey trails in the winter.The HMs actively avoided areas with high anthropogenic pressure.In the summer,they showed a wider elevational range up to 4400 m above sea level(a.s.l.),with a higher sighting frequency between 3600 and 3900 m a.s.l.The questionnaire survey of the local residents revealed that anthropogenic pressure such as poaching and free-ranging livestock grazing are the major threats to the species in the study area.This study provides valuable insight into the complex habitat preferences and critical threats faced by the HMs in LNP and underscores the urgent need for targeted conservation action.
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The building construction industry,recognized as one of the eight high-risk sectors,also serves as a crucial pillar of the national economy and a key source of employment.Major project advancements typically concentrate between April to June and September to November each year.However,construction progress tends to slow down during July and August due to increased rainfall associated with the flood season.The impact of the flood season on construction projects is primarily reflected in areas such as civil works,machinery and equipment,and temporary power supply.By establishing a dual-control emergency management system for the flood season,construction enterprises can enhance their emergency response capabilities,effectively reduce management challenges,and improve the overall efficiency of emergency handling.
文摘The symbiotic association between reef-building corals and Symbiodiniaceae is pivotal for coral reef ecosystems,yet remains susceptible to environmental factors.Currently,there is a dearth of research examining seasonal fluctuations in coral-associated Symbiodiniaceae communities.In this study,we investigated the seasonal dynamics of Symbiodiniaceae communities associated with coral species in the Luhuitou coral reef using high-throughput sequencing techniques and SymPortal analytical framework.The results indicated that the genus Cladocopium exhibited dominance(averaging 82%),followed by Durusdinium(18%)and Breviolum(0.01%)within the examined coral species.Among the 521 Symbiodiniaceae ITS2 sequence types,C15 emerged as the prevalent type(13.24%),trailed by C3u(9.51%)and D1(8.57%).Interestingly,Symbiodiniaceae communities varied among different coral species.Pocillopora damicornis displayed a predominant association with Durusdinium,while Porites lutea,Goniastrea retiformis,Montipora truncata,Montipora aequituberculata,and Acropora divaricata were entirely dominated by the genus Cladocopium(100%),showcasing distinct host specificity.In the cases of Hydnophora exesa,Acropora latistella,Acropora digitifera,and seawater,both Cladocopium and Durusdinium were concurrently detected.Moreover,the diversity of Symbiodiniaceae associated with P.damicornis,P.lutea,G.retiformis,M.truncata,M.aequituberculata,and A.digitifera exhibited significant variations across different seasons.Notably,the results revealed that the alterations in Symbiodiniaceae community compositions were primarily driven by nutrient concentrations and seawater temperature.The network analysis of Symbiodiniaceae revealed the dominant Symbiodiniaceae types C15,C17f,C3u,C3,and D4 were exclusive.This study provided the seasonal variation characteristics of Symbiodiniaceae communities among different coral species,which may be a potential adaptive mechanism to environmental conditions.
基金Supported by the Inter-governmental Science and Technology Innovation(STI)Cooperation Special Program of the National Key Research and Development Program of China(No.2023YFE0104500)the NIWA-SHOU-Otago Joint Research Center on Antarctic Marine Science。
文摘Antarctic krill(Euphausia superba)is a keystone species in the Southern Ocean;however,seasonal variations in reproductive development for krill are complex and remains unknown.A histological investigation with observations of external secondary sex features of krill in the south Scotia Sea region was carried out using a multi-seasonal dataset for detail reproductive descriptions for this commercially important species.The monthly development of secondary sexual characteristics,the thelycum,as well as of oocytes over a period of two years were described.It was observed that krill have diverse reproductive development characteristics within the ovary,and that this function differently between the juvenile,sub-adult,and adult stages.During the summer,adult krill ovaries are large and ripe with oocytes rich in yolk ready for release in late summer.Post spawning,the ovaries resorb,fragment,and regress throughout the autumn and winter.During reproductive diapause period,krill focus on absorbing nutrients.Un-released eggs are reabsorbed by the ovary,the permanent germinal zone is active,and early oocytes begin to develop in preparation for the egg production phase.Krill that are about to spawn have an ovary that fills the space between the digestive gland and muscle.The ovarian development of krill is divided into 10 sexual developmental stages.As a part of this study,data on the carapace thickness with similar development patterns in krill size and carapace width,was investigated for the first time to help understand krill growth and development.
基金jointly supported by the Innovation Group Project of the Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)[grant number 316323005]the Guangdong Basic and Applied Basic Research Foundation[grant numbers 2023A1515010741 and 2024B1515020035]the Science and Technology Planning Project of Guangdong Province[grant number 2023B1212060019]。
文摘Forecasting tropical cyclone(TC)activities has been a topic of great interest and research.Taiwan Island(TW)is one of the key regions that is highly exposed to TCs originated from the western North Pacific.Here,the authors utilize two mainstream reanalysis datasets for the period 1979-2013 and propose an effective statistical seasonal forecasting model-namely,the Sun Yat-sen University(SYSU)Model-for predicting the number of TC landfalls on TW based on the environmental factors in the preseason.The comprehensive predictor sampling and multiple linear regression show that the 850-hPa meridional wind over the west of the Antarctic Peninsula in January,the 300-hPa specific humidity over the open ocean southwest of Australia in January,the 300-hPa relative vorticity over the west of the Sea of Okhotsk in March,and the sea surface temperature in the South Indian Ocean in April,are the most significant predictors.The correlation coefficient between the modeled results and observations reaches 0.87.The model is validated by the leave-one-out and nine-fold cross-validation methods,and recent 9-yr observations(2014-2022).The Antarctic Oscillation,variabilities of the western Pacific subtropical high,Asian summer monsoon,and oceanic tunnel are the possible physical linkages or mechanisms behind the model result.The SYSU Model exhibits a 98%hit rate in 1979-2022(43 out of 44),suggesting an operational potential in the seasonal forecasting of TC landfalls on TW.
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Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Fire season affects the dynamic changes of post-fire vegetation communities and carbon emissions.Analyzing its global patterns supports understanding of the ecological impacts of fires and responses of fires to climate change.Meteorological variables have been widely used to quantify fire season in current studies.However,their results can not be used to assess climate impacts on the seasonality of fire activities.Here we utilized satellite-based Moderate Resolution Imaging Spectroradiometer(MODIS)burned area data from 2001 to 2022 to identify global fire season types based on the number of peaks within a year.Using satellite data and innovatively processing the data to obtain a more accurate length of the fire season.We divided fire season types and examined the spatial distribution of fire season types across the Koppen-Geiger climate(KGC)zones.At a global scale,we identified three major fire season types,including unimodal(31.25%),bimodal(52.07%),and random(16.69%).The unimodal fire season primarily occurs in boreal and tropical regions lasting about 2.7 mon.In comparison,temperate ecosystems tend to have a longer fire season(3 mon)with two peaks throughout the year.The KGC zones show divergent contributions from the fire season types,indicating potential impacts of the climatic conditions on fire seasonality in these regions.
