Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

Spatio-temporal variation of trace elements distributed over surface water of Upper Ganga River Basin in Western Himalayan Region

The rivers draining from the Himalayan range distribute enormous amount of fresh water to the people living in downstream regions.Trace metals flowed with river water can lead to serious impact on ecological system and human health.Nevertheless,the documentation on trace elements of Himalayan rivers is inadequately documented.The current study deals with the spatial and temporal variability of the major and trace elements of Ganga river water in epirhithron,metarhithron and hyporhithron zone belonging to Himalayan segment.Water samples from nineteen monitoring locations were collected in pre-monsoon(May-June),monsoon(AugustSeptember)and post-monsoon(December)seasons and subjected to be assessed for 20 elements(Ag,Al,Ba,Cd,Ca,Cr,Cu,Fe,Ga,K,Mn,Mg,Na,Ni,Pb,Sr,Th,U,Zn,and Zr)using ICP-OES(Inductively Coupled Plasma-Optical Emission Spectrometer).Different water pollution indexes such as HPI(Heavy Metal Pollution Index),MI(Metal Index)and PI(Pollution Index)were used to describe current water quality status at each monitoring station under particular classified ecological zone.The studied stations in hyporhithron zone had the value of Metal Index(MI>1),indicating threshold of warning.Further,the highest values of HPI in hyporhithron zone correspond to poor water quality status.Sites with poor water quality were also found to be contaminated as per the Pollution Index(PI),exhibiting high concentrations for element(Fe).However,the epirhithron and metarhithron zone in Himalayan segment showed excellent water quality mainly contributed from natural sources.Cluster Analysis(CA)and Principal Component Analysis(PCA)were applied to identify the main influential sources for Ganga river water pollution.The Kriging interpolation method was also applied to prepare spatial distribution map of computed indexes(HPI,MI,and PI).With the help of index of local Moran’s I(LMI),identified spatial clusters and spatial outliers revealed the elevated concentration of most elements in hyporhithron zone.The dataset presented in this study would be convenient for government officials in developing more effective management policies and necessary steps to check and monitor the Ganga river water quality.It was also suggested that further investigations in terms of trace elemental sources and their role in self-purification properties of Ganga water can be addressed in future.

Spatio-temporal variation and propagation direction of coal fire in Jharia Coalfield,India by satellite-based multi-temporal night-time land surface temperature imaging

In this paper,the spatio-temporal variation and propagation direction of coal fire were studied in the Jharia Coalfield(JCF),India during 2006–2015 through satellite-based night-time land surface temperature(LST)imaging.The LST was retrieved from Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER)night-time thermal-infrared data by a robust split-window algorithm based on scene-specific regression coefficients,band-specific hybrid emissivity,and night-time atmospheric transmittance.The LST-profile-based coal fire detection algorithm was formulated through statistical analysis of the LST values along multiple transects across diverse coal fire locations in the JCF in order to compute date-specific threshold temperatures for separating thermally-anomalous and background pixels.This algorithm efficiently separates surface fire,subsurface fire,and thermally-anomalous transitional pixels.During the observation period,it was noticed that the coal fire area increased significantly,which resulted from new coal fire at many places owing to extensive opencast-mining operations.It was observed that the fire propagation occurred primarily along the dip direction of the coal seams.At places,lateral-propagation of limited spatial extent was also observed along the strike direction possibly due to spatial continuity of the coal seams along strike.Moreover,the opencast-mining activities carried out during 2009–2015 and the structurally weak planes facilitated the fire propagation.

Spatio-temporal Variations of Temperature and Precipitation During 1951–2019 in Arid and Semiarid Region, China

Understanding the spatio-temporal variations of temperature and precipitation in the arid and semiarid region of China(ASRC)is of great significance for promoting regional eco-environmental protection and policy-making.In this study,the annual and seasonal spatio-temporal patterns of change in average temperature and precipitation and their influencing factors in the ASRC were analyzed using the Mann-Kendall test,linear tendency estimation,accumulative anomaly and the Pearson’s correlation coefficient.The results showed that both annual average temperature and average annual precipitation increased in the ASRC during 1951–2019.The temperature rose by about 1.93℃and precipitation increased by about 24 mm.The seasonal average temperature presented a significant increase trend,and the seasonal precipitation was conspicuous ascension in spring and winter.The spatio-temporal patterns of change in temperature and precipitation differed,with the southwest area showing the most obvious variation in each season.Abrupt changes in annual and seasonal average temperature and precipitation occurred mainly around the 1990 s and after 2000,respectively.Atmospheric circulation had an important effect on the trends and abrupt changes in temperature and precipitation.The East Asian summer monsoon had the largest impact on the trend of average annual temperature,as well as on the abrupt changes of annual average temperature and precipitation.Temperature and precipitation changes in the ASRC were influenced by long-term and short-term as well as direct and indirect anthropogenic and natural factors.This study identifies the characteristics of spatio-temporal variations in temperature and precipitation in the ASRC and provides a scientific reference for the formulation of climate change responses.

SPATIO-TEMPORAL VARIATION OF ACTUAL EVAPOTRANSPIRATION AND ITS RELATION WITH CLIMATE PARAMETERS IN THE PEARL RIVER BASIN,CHINA

Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity model(AA model) in the current study, and Mann-Kendall test(MK) and Inverse Distance Weighted interpolation method(IDW)were applied to detect the trends and spatial variation pattern. The relations of ETa with climate parameters and radiation/dynamic terms are analyzed by Person correlation method. Our findings are shown as follows: 1) Mean annual ETa in the Pearl River basin is about 665.6 mm/a. It has significantly decreased in 1961-2010 at a rate of-24.3mm/10 a. Seasonally, negative trends of summer and autumn ETa are higher than that of spring and winter. 2) The value of ETa is higher in the southeast coastal area than in the northwest region of the Pearl River basin, while the latter has shown the strongest negative trend. 3) Negative trends of ETa in the Pearl River basin are most probably due to decreasing radiation term and increasing dynamic term. The decrease of the radiation term is related with declining diurnal temperature range and sunshine duration, and rising atmospheric pressure as well. The contribution of dynamic term comes from increasing average temperature, maximum and minimum temperatures in the basin. Meanwhile, the decreasing average wind speed weakens dynamic term and finally, to a certain extent, it slows down the negative trend of the ETa.

Spatio-temporal variations in organic carbon density and carbon sequestration potential in the topsoil of Hebei Province, China

Reliable prediction of soil organic carbon(SOC) density and carbon sequestration potential(CSP) plays an important role in the atmospheric carbon dioxide budget. This study evaluated temporal and spatial variation of topsoil SOC density and CSP of 21 soil groups across Hebei Province, China, using data collected during the second national soil survey in the 1980 s and during the recent soil inventory in 2010. The CSP can be estimated by the method that the saturated SOC content subtracts the actual SOC associated with clay and silt. Overall, the SOC density and CSP of most soil groups increased from the 1980 s to 2010 and varied between different soil groups. Among all soil groups, Haplic phaeozems had the highest SOC density and Endogleyic solonchaks had the largest CSP. Areas of soil groups with the highest SOC density(90 to 120 t C ha^(–1)) and carbon sequestration(120 to 160 t C ha^(–1)) also increased over time. With regard to spatial distribution, the north of the province had higher SOC density but lower CSP than the south. With respect to land-use type, cultivated soils had lower SOC density but higher CSP than uncultivated soils. In addition, SOC density and CSP were influenced by soil physicochemical properties, climate and terrain and were most strongly correlated with soil humic acid concentration. The results suggest that soil groups(uncultivated soils) of higher SOC density have greater risk of carbon dioxide emission and that management should be aimed at maximizing carbon sequestration in soil groups(cultivated soils) with greater CSP. Furthermore, soils should be managed according to their spatial distributions of SOC density and carbon sequestration potential under different soil groups.

Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p < 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon;precipitation induced surface runoff in monsoon;and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand, monitor and manage the quality of the water resources.

SPATIO-TEMPORAL VARIATION OF SENSIBLE HEAT FLUX OVER SOUTHERN CHINA

The spatio-temporal variation of surface sensible heat flux(SHF) in southern China(SC) is studied based on the data evaluated from conventional observational meteorological data.There exist prominent increasing trends in all seasonal surface sensible heat fluxes in the western SC and decreasing trends in the central-eastern part of southern China.The variations of surface sensible heat flux in all seasons are dominant on interannual time-scales.The land-air temperature difference and the near-surface wind speed are two key factors for the interannual variations of SHF,but the former is more important.The first two major anomalous patterns of SHF are presented as the region-wide in-phase anomalies and the east-west dipole anomalies,respectively,based on the EOF analysis results.

Spatio-Temporal Variation of HIV Infection in Kenya

Disease mapping is the study of the distribution of disease relative risks or rates in space and time, and normally uses generalized linear mixed models (GLMMs) which includes fixed effects and spatial, temporal, and spatio-temporal random effects. Model fitting and statistical inference are commonly accomplished through the empirical Bayes (EB) and fully Bayes (FB) approaches. The EB approach usually relies on the penalized quasi-likelihood (PQL), while the FB approach, which has increasingly become more popular in the recent past, usually uses Markov chain Monte Carlo (McMC) techniques. However, there are many challenges in conventional use of posterior sampling via McMC for inference. This includes the need to evaluate convergence of posterior samples, which often requires extensive simulation and can be very time consuming. Spatio-temporal models used in disease mapping are often very complex and McMC methods may lead to large Monte Carlo errors if the dimension of the data at hand is large. To address these challenges, a new strategy based on integrated nested Laplace approximations (INLA) has recently been recently developed as a promising alternative to the McMC. This technique is now becoming more popular in disease mapping because of its ability to fit fairly complex space-time models much more quickly than the McMC. In this paper, we show how to fit different spatio-temporal models for disease mapping with INLA using the Leroux CAR prior for the spatial component, and we compare it with McMC using Kenya HIV incidence data during the period 2013-2016.

Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

Precise information on indoor positioning provides a foundation for position-related customer services.Despite the emergence of several indoor positioning technologies such as ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,Wi-Fi is one of the most widely used technologies.Predominantly,Wi-Fi fingerprinting is the most popular method and has been researched over the past two decades.Wi-Fi positioning faces three core problems:device heterogeneity,robustness to signal changes caused by human mobility,and device attitude,i.e.,varying orientations.The existing methods do not cover these aspects owing to the unavailability of publicly available datasets.This study introduces a dataset that includes the Wi-Fi received signal strength(RSS)gathered using four different devices,namely Samsung Galaxy S8,S9,A8,LG G6,and LG G7,operated by three surveyors,including a female and two males.In addition,three orientations of the smartphones are used for the data collection and include multiple buildings with a multifloor environment.Various levels of human mobility have been considered in dynamic environments.To analyze the time-related impact on Wi-Fi RSS,data over 3 years have been considered.

Spatio-temporal variation and focal mechanism of the Wenchuan M_S8.0 earthquake sequence

Based on abundant aftershock sequence data of the Wenchuan MS8.0 earthquake on May 12, 2008, we studied the spatio-temporal variation process and segmentation rupture characteristic.Dense aftershocks distribute along Longmenshan central fault zone of NE direction and form a narrow strip with the length of 325 km and the depth between several and 40 km.The depth profile(section of NW direction) vertical to the strike of aftershock zone(NE direction) shows anisomer-ous wedgy distribution characteristic of aftershock concentrated regions;it is related to the force form of the Longmenshan nappe tectonic belt.The stronger aftershocks could be divided into northern segment and southern segment apparently and the focal depths of strong aftershocks in the 50 km area between northern segment and southern segment are shallower.It seems like ‘to be going to rupture' segment.We also study focal mechanisms and segmentation of strong aftershocks.The principal compressive stress azimuth of aftershock area is WNW direction and the faulting types of aftershocks at southern and northern segment have the same proportion.Because aftershocks distribute on different secondary faults, their focal mechanisms present complex local tectonic stress field.The faulting of seven strong earthquakes on the Longmenshan cen-tral fault is mainly characterized by thrust with the component of right-lateral strike-slip.Meantime six strong aftershocks on the Longmenshan back-range fault and Qingchuan fault present strike-slip faulting.At last we discuss the complex segmen-tation rupture mechanism of the Wenchuan earthquake.

Spatio-temporal variation of spring phenology in Tibetan Plateau and its linkage to climate change from 1982 to 2012

The influence of climate change on vegetation phenology is a heated issue in current climate change study.We used GIMMS-3g NDVI data to detect the spatio-temporal dynamics of the start of the growing season(SGS) over the Tibetan Plateau(TP) from 1982 to 2012 and to analyze its relationship with temperature and precipitation.No significant trend was observed in the SGS at the regional scale during the study period(R^2 = 0.03,P = 0.352).However,there were three time periods(1982-1999,1999-2008 and 2008-2012) with identifiable,distinctly different trends.Regions with a significant advancing trend were mainly scattered throughout the humid and semi-humid areas,whereas the regions with a significant delaying trend were mostly distributed throughout the semi-arid areas.Statistical analysis showed that the response of the SGS to climate change varies spatially.The SGS was significantly correlated with the spring temperature and the start of the thermal growth season(STGS) in the relatively humid area.With increasing aridity,theimportance of the spring temperature for the SGS gradually decreased.However,the influences of precipitation and winter temperature on the SGS were complicated across the plateau.

Estimation of ocean primary productivity and its spatio-temporal variation mechanism for East China Sea based on VGPM model

According to calculation results of ocean chlorophyll concentration based on SeaWiFS data by SeaBAM model and synchronous ship-measured data, this research set up an improved model for CaseⅠand CaseⅡwater bodies respectively. The monthly chlorophyll distribution in the East China Sea in 1998 was obtained from this improved model on calculation results of SeaBAM. The euphotic depth distribution in 1998 in the East China Sea is calculated by using remote sensing data of K 490 from SeaWiFS according to the relation between the euphotic depth and the oceanic diffuse attenuation coefficient. With data of ocean chlorophyll concentration, euphotic depth, ocean surface photosynthetic available radiation (PAR), daily photoperiod and optimal rate of daily carbon fixation within a water column, the monthly and annual primary productivity spatio-temporal distributions in the East China Sea in 1998 were obtained based on VGPM model. Based on analysis of those distributions, the conclusion can be drawn that there is a clear bimodality character of primary productivity in the monthly distribution in the East China Sea. In detail, the monthly distribution of primary productivity stays the lowest level in winter and rises rapidly to the peak in spring. It gets down a little in summer, and gets up a little in autumn. The daily average of primary productivity in the whole East China Sea is 560.03 mg/m 2 /d, which is far higher than the average of subtropical ocean areas. The annual average of primary productivity is 236.95 g/m 2 /a. The research on the seasonal variety mechanism of primary productivity shows that several factors that affect the spatio-temporal distribution may include the chlorophyll concentration distribution, temperature condition, the Yangtze River diluted water variety, the euphotic depth, ocean current variety, etc. But the main influencing factors may be different in each local sea area.

Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

Soil respiration(SR) is the second-largest flux in ecosystem carbon cycling. Due to the large spatio-temporal variability of environmental factors, SR varied among different vegetation types, thereby impeding accurate estimation of CO_2 emissions via SR. However, studies on spatio-temporal variation of SR are still scarce for semi-arid regions of North China. In this study, we conducted 12-month SR measurements in six land-use types, including two secondary forests(Populus tomentosa(PT) and Robinia pseudoacacia(RP)), three artificial plantations(Armeniaca sibirica(AS), Punica granatum(PG) and Ziziphus jujuba(ZJ)) and one natural grassland(GR), to quantify spatio-temporal variation of SR and distinguish its controlling factors. Results indicated that SR exhibited distinct seasonal patterns for the six sites. Soil respiration peaked in August 2012 and bottomed in April 2013. The temporal coefficient of variation(CV) of SR for the six sites ranged from 76.98% to 94.08%, while the spatial CV of SR ranged from 20.28% to 72.97% across the 12-month measurement. Soil temperature and soil moisture were the major controlling factors of temporal variation of SR in the six sites, while spatial variation in SR was mainly caused by the differences in soil total nitrogen(STN), soil organic carbon(SOC), net photosynthesis rate, and fine root biomass. Our results show that the annual average SR and Q_(10)(temperature sensitivity of soil respiration) values tended to decrease from secondary forests and grassland to plantations, indicating that the conversion of natural ecosystems to man-made ecosystems may reduce CO_2 emissions and SR temperature sensitivity. Due to the high spatio-temporal variation of SR in our study area, care should be taken when converting secondary forests and grassland to plantations from the point view of accurately quantifying CO_2 emissions via SR at regional scales.

Spatio-temporal variation in China's climatic seasons from 1951 to 2017

In this paper,meteorological industry standard,daily mean temperature,and an improved multiple regression model are used to calculate China's climatic seasons,not only to help understand their spatio-temporal distribution,but also to provide a reference for China's climatic regionalization and crop production.It is found that the improved multiple regression model can accurately show the spatial distribution of climatic seasons.The main results are as follows.There are four climatic seasonal regions in China,namely,the perennial-winter,no-winter,no-summer and discernible regions,and their ranges basically remained stable from 1951 to 2017.The cumulative anomaly curve of the four climatic seasonal regions clarifies that the trend of China's climatic seasonal regions turned in 1994,after which the area of the perennial-winter and no-summer regions narrowed and the no-winter and discernible regions expanded.The number of sites with significantly reduced winter duration is the largest,followed by the number of sites with increased summer duration,and the number of sites with large changes in spring and autumn is the least.Spring advances and autumn is postponed due to the shortened winter and lengthened summer durations.Sites with significant change in seasonal duration are mainly distributed in Northwest China,the Sichuan Basin,the Huanghe-Huaihe-Haihe(Huang-Huai-Hai) Plain,the Northeast China Plain,and the Southeast Coast.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

Associations of genome-wide structural variations with phenotypic differences in cross-bred Eurasian pigs

Background During approximately 10,000 years of domestication and selection,a large number of structural variations(SVs)have emerged in the genome of pig breeds,profoundly influencing their phenotypes and the ability to adapt to the local environment.SVs(≥50 bp)are widely distributed in the genome,mainly in the form of insertion(INS),mobile element insertion(MEI),deletion(DEL),duplication(DUP),inversion(INV),and translocation(TRA).While studies have investigated the SVs in pig genomes,genome-wide association studies(GWAS)-based on SVs have been rarely conducted.Results Here,we obtained a high-quality SV map containing 123,151 SVs from 15 Large White and 15 Min pigs through integrating the power of several SV tools,with 53.95%of the SVs being reported for the first time.These high-quality SVs were used to recover the population genetic structure,confirming the accuracy of genotyping.Potential functional SV loci were then identified based on positional effects and breed stratification.Finally,GWAS were performed for 36 traits by genotyping the screened potential causal loci in the F2 population according to their corresponding genomic positions.We identified a large number of loci involved in 8 carcass traits and 6 skeletal traits on chromosome 7,with FKBP5 containing the most significant SV locus for almost all traits.In addition,we found several significant loci in intramuscular fat,abdominal circumference,heart weight,and liver weight,etc.Conclusions We constructed a high-quality SV map using high-coverage sequencing data and then analyzed them by performing GWAS for 25 carcass traits,7 skeletal traits,and 4 meat quality traits to determine that SVs may affect body size between European and Chinese pig breeds.

The Variation of Plankton Community Structure in Artificial Reef Area and Adjacent Waters in Haizhou Bay

Plankton are an important component of marine protected areas(MPAs),and its communities would require much smaller interpatch distances to ensure connection among MPAs.According to the survey from MPAs dominated by artificial reefs and adjacent waters(estuary area(EA),aquaculture area(AA),artificial reef area(ARA),natural area(NA)and comprehensive effect area(CEA))in Haizhou Bay in spring and autumn,we analyzed phyto-zooplankton composition,abundance and biomass,and correlation with hydrologic variables to gain information about the forces that structure the plankton.The results showed that the dominant zooplankton were copepods(spring,98.9%;autumn,94.2%),while the phytoplankton were mainly composed of Bacillariophyta(spring,61.8%;autumn,95.6%).The RDA results showed that temperature,salinity and depth highly associated with the distribution and composition of plankton species among the habitats than other factors in spring;temperature,Chla and DO had the strongest influence in autumn.The zooplankton in the ARA and AA ecosystems basically contained the same species as those in other habitats,and each habitat also exhibited a relatively unique combination of plankton species.The structures of the EA zooplankton in spring and the EA phytoplankton in both seasons were much different than other habitats,which may have been caused by factors such as currents and tides.We concluded that there exists similarity of the plankton community between artificial reef area and adjacent waters,whereas the EAs may be relatively independent systems.Therefore,these interaction between plankton community should be considered when designing MPA networks,and ocean circulations should be considered more than the environmental factors.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.