Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obt...Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obtain drinking water,it is necessary to clarify the causes and control factors of groundwater mineralization in Gao region,northern Mali.Based on the analysis of the hydrochemical composition of groundwater in 24 boreholes,Piper and Sch?eller diagrams,principal component analysis(PCA)and hierarchical cluster analysis(HCA)are used to carry out multivariate statistical analysis on the main ions.The results show that the groundwater samples are weakly alkaline,with pH values ranging from 5.83 to 8.40,and the average values of boreholes are 7.50,respectively.The average electrical conductivity(EC)value is 354.4(μS/cm),and the extreme value is between 124.0 and 1247(μS/cm).Water is usually mineralized and presents nine types of water phase.The three principal components explain 84.42%of the total variance for 13 parameters.The factor F1(58.85%),the factor F2(16.88%)and the factor F3(8.69%)present for the majority of the total data set.In addition,multivariate statistical analysis confirmed the genetic relationship among aquifers and identified three main clusters.Clustering related to groundwater mineralization(F1),clustering related to oxide reduction and iron enrichment(F2),and clustering of groundwater pollution caused by nitrate and magnesium(F3).We found that agriculture,weathering activities and dissolution of geological materials promote the mineralization of groundwater.Groundwater quality in the Gao region is becoming less and less potable because of increasing salinity.展开更多
Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were ...Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were introduced in this work. The results indicate that the canonical discriminant function with 7 parameters was established using the discriminant analysis（DA） method, which can afford 100% correct assignation according to the 3 different clusters（good water（GW）, poor water（PW）, and very poor water（VPW）） obtained from cluster analysis（CA）. According to factor analysis（FA）, 8 factors were extracted from 25 hydrochemical elements and account for 80.897% of the total data variance, suggesting that groundwater with higher concentrations of sodium, calcium, magnesium, chloride, and sulfate in southeastern study area are mainly affected by the natural process; the higher level of arsenic and chromium in groundwater extracted from northwestern part of study area are derived by industrial activities; domestic and agriculture sewage have important contribution to copper, iron, iodine, and phosphate in the northern study area. Therefore, this work can help identify the main controlling factor of groundwater quality in North China plain so as to make better and more informed decisions about how to achieve groundwater resources sustainable development.展开更多
Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental...Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, the elemental contents of M. concha from five sampling points in Rushan Bay have been determined by means of inductively coupled plasma optical emission spectrometry(ICP-OES). Based on the contents of 14 inorganic elements(Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, and Zn), the inorganic elemental fingerprint which well reflects the elemental characteristics was constructed. All the data from the five sampling points were discriminated with accuracy through hierarchical cluster analysis(HCA) and principle component analysis(PCA), indicating that a four-factor model which could explain approximately 80% of the detection data was established, and the elements Al, As, Cd, Cu, Ni and Pb could be viewed as the characteristic elements. This investigation suggests that the inorganic elemental fingerprint combined with multivariate statistical analysis is a promising method for verifying the geographical origin of M. concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.展开更多
Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for ...Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for Jinhongtang is not available.In present study,we developed a UFLC-MS/MS method to determine 16 analytes in 20 batches of home-made and commercial Jinhongtang.Multivariate statistical analysis revealed the significant differences in the quality of home-made and commercial Jinhongtang and the difference in the quality of home-made samples was more significant.The integrated strategy based on UFLC-MS/MS and multivariate statistical analysis provided a new basis for the overall quality assessment of Jinhongtang.展开更多
[Objective] The study aimed to study the relationship between soil and environment on the basis of multivariate statistical analysis. [ Method] Through field investigation, sampling and laboratory analysis, we discuss...[Objective] The study aimed to study the relationship between soil and environment on the basis of multivariate statistical analysis. [ Method] Through field investigation, sampling and laboratory analysis, we discussed the relationship between soil properties and environmental factors in Mizhi County, North Shaanxi by using Canoco multivariate statistical analysis. [ Result]According to the effects of various environmental factors on soil properties, the influencing order of environmental factors was land use way 〉 vegetation type 〉 vegetation restoration years 〉 vegeta- tion coverage 〉 slope aspect 〉 gradient 〉 elevation. In a word, soil properties were significantly affected by land use way and vegetation type which were the most important environmental factors of soil properties in spatial variation, while vegetation restoration years were closely related to the ac- cumulation of soil nutrients. [ Condusion]The research could provide theoretical references for the construction of ecological environment in Loess Plateau of China.展开更多
Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and re...Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and revealing its underlying general rules. Among the most powerful mathematical tools for organizing and helping to structure complex, heterogeneous and noisy data are the tools provided by multivariate statistical analysis (MSA) approaches. These eigenvector/eigenvalue data-compression approaches were first introduced to electron microscopy (EM) in 1980 to help sort out different views of macromolecules in a micrograph. After 35 years of continuous use and developments, new MSA applications are still being proposed regularly. The speed of computing has increased dramatically in the decades since their first use in electron microscopy. However, we have also seen a possibly even more rapid increase in the size and complexity of the EM data sets to be studied. MSA computations had thus become a very serious bottleneck limiting its general use. The parallelization of our programs—speeding up the process by orders of magnitude—has opened whole new avenues of research. The speed of the automatic classification in the compressed eigenvector space had also become a bottleneck which needed to be removed. In this paper we explain the basic principles of multivariate statistical eigenvector-eigenvalue data compression;we provide practical tips and application examples for those working in structural biology, and we provide the more experienced researcher in this and other fields with the formulas associated with these powerful MSA approaches.展开更多
Objective To establish an effective approach for rapid and comprehensive analysis on the absorbed and metabolic components in rats after ig administration of Yuanhu Zhitong Dropping Pill（YHZT）. Methods Based on the ...Objective To establish an effective approach for rapid and comprehensive analysis on the absorbed and metabolic components in rats after ig administration of Yuanhu Zhitong Dropping Pill（YHZT）. Methods Based on the combination of UPLC-Q-TOF/MS and multivariate statistical analysis, the absorbed prototype constituents and their metabolites in rat plasma were rapidly analyzed and identified, and the components absorbed into brain were further identified by comparing the extracted ion chromatograms（EICs） of control and brain tissue samples of dosed rats. Results A total of 38 YHZT-related xenobiotic compounds were detected and identified as the potential bioactive constituents in rat plasma, including 24 absorbed prototype constituents and 14 metabolites. In particular, of all prototype constituents, 14 were also detected in rat brain tissue, indicating that they could penetrate the blood-brain barrier and enter into brain. Conclusion An effective method is established and applied to analyze the potential bioactive constituents in YHZT, which provides a pathway to further investigate the pharmacological pattern and mechanism of YHZT.展开更多
To identify the chemical differences which lead to the different therapeutic effects of dried rehmannia root(DRR)and prepared rehmannia root(PRR),we compared the chemical composition of decoctions of randomly purchase...To identify the chemical differences which lead to the different therapeutic effects of dried rehmannia root(DRR)and prepared rehmannia root(PRR),we compared the chemical composition of decoctions of randomly purchased DRR and PRR using ultra performance liquid chromatography(UPLC)coupled with time-of-fight mass spectrometry and high performance liquid chromatography(HPLC)coupled with evaporative light scattering detection(ELSD)with the aid of multivariate statistical analysis.Both approaches clearly revealed compositional and quantitative differences between DRR and PRR.UPLC-MS data indicated stachyose,rehmaiono-side A(or rehmaionoside B),acteoside(or forsythiaside,or isoacteoside),6-O-coumaroylajugol(or 6-O-E-feruloylajugol,or 6-O-Z-feruloylajugol)as important discriminators between DRR and PRR decoctions.HPLC-ELSD analysis showed that the content of fructose in the decoctions of PRR was about four times greater than that of DRR(P<10^(-5)),while sucrose content in the decoctions of PRR was only about one seventh of that in DRR(P<0.01).Our results suggest that some compounds,such as fructose,stachyose and rehmaionoside,may be responsible for the differing therapeutic effects of DRR and PRR.Furthermore,improvements in quality control for PRR,which is currently lacking in the Chinese Pharmacopoeia,are recommended.展开更多
A new multivariate statistical strategy for analyzing large datasets that are produced by imaging mass spectrometry（IMS） techniques is reported.The strategy divides the whole datacube of the sample into several subs...A new multivariate statistical strategy for analyzing large datasets that are produced by imaging mass spectrometry（IMS） techniques is reported.The strategy divides the whole datacube of the sample into several subsets and analyses them one by one to obtain the results.Instead of analyzing the whole datacube at one time,the strategy makes the analysis easier and decreases the computation time greatly.In this report,the IMS data are produced by the air flow-assisted ionization IMS（AFAI-IMS）.The strategy can be used in combination with most multivariate statistical analysis methods.In this paper,the strategy was combined with the principal component analysis（PCA） and partial least square analysis（PLS）.It was proven to be effective by analyzing the handwriting sample.By using the strategy,the m/z corresponding to the specific lipids in rat brain tissue were distinguished successfully.Moreover the analysis time grew linearly instead of exponentially as the size of sample increased.The strategy developed in this study has enormous potential for searching for the mjz of potential biomarkers quickly and effectively.展开更多
The application of multivariate data analysis, a method for coping with multi-colinearity among independent variables in analyzing coastal water quality data, is presented. This study investigates the statistical regr...The application of multivariate data analysis, a method for coping with multi-colinearity among independent variables in analyzing coastal water quality data, is presented. This study investigates the statistical regression modeling of FIB （fecal indicator bacteria） concentrations at the outlet of Talbert Marsh in Orange County, California. The multivariate data modeling utilized FIB and physical variables measurements （n = 5,580） collected during a series of longitudinal study of the Talbert Marsh. For the statistical prediction modeling in predicting the FIB concentrations at the outlet of the Talbert Marsh, multivariate analysis techniques such as PCR （principal components regression）, PLS （partial least-squares） regression and SVM （support vector machine） regression were adopted. Statistical modeling results suggest that the statistical modeling predictions are all fell within the reasonable range of actual measurement data. In addition, it is indicated that the accuracy of SVM regression for predicting FIB concentrations at the Talbert Marsh outlet is better than that of other models.展开更多
Water quality of Mexican tropical lake Chapala was assessed through multivariate statistical techniques, cluster analysis (CA) and principal component analysis (PCA) at ten different monitoring sites for ten physicoch...Water quality of Mexican tropical lake Chapala was assessed through multivariate statistical techniques, cluster analysis (CA) and principal component analysis (PCA) at ten different monitoring sites for ten physicochemical variables and six metals. This study evaluated and interpreted complex water quality data sets and apportioned of pollution sources to get better information about water quality. From descriptive statistics results, the highest concentrations of metals occurred during the dry season, and this trend was explained by the fact that an unusual rainy event occurred during the month of February 2009 and brought metals into the lake by runoffs from nearby mountains. According to international criteria for water consumption by aquatic organisms [USEPA], only Zn concentration values were below these criteria whereas the values of Ni, Pb, Cd and Fe were above the corresponding values set in these criteria (Ni: 52 μg·L-1, Pb: 2.5 μg·L-1, Cd: 0.25 μg·L-1, and Fe: 1000 μg·L-1). The correlations were observed by PCA, which were used to classify the samples by CA, based on the PCA scores. Seven significant cluster groups of sampling locations—(sites 4 and 5), (sites 3 and 9), (site 7), (site 10), (sites 2 and 6), (site 8) and (site 1)— were detected on the basis of similarity of their water quality. The results revealed that the stress exerted on the lake caused by waste sources follows the order: domestic > agricultural > industrial.展开更多
Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements ...Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.展开更多
The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide dist...The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide distribution and the lithotectonic regime of Darma Valley,Kumaun Himalaya.A landslide inventory comprising 295 landslides in the area has been prepared and several morphotectonic proxies such as valley floor width to height ratio(Vf),stream length gradient index(SL),and hypsometric integral(HI)have been used to infer tectonic regime.Morphometric analysis,including basic,linear,aerial,and relief aspects,of 59 fourth-order sub-basins,has been carried out to estimate erosion potential in the study area.The result demonstrates that 46.77%of the landslides lie in very high,20.32%in high,21.29%in medium,and 11.61%in low erosion potential zones respectively.In order to determine the key parameters controlling erosion potential,two multivariate statistical methods namely Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC)were utilized.PCA reveals that the Higher Himalayan Zone(HHZ)has the highest erosion potential due to the presence of elongated sub-basins characterized by steep slopes and high relief.The clusters created through AHC exhibit positive PCA values,indicating a robust correlation between PCA and AHC.Furthermore,the landslide density map shows two major landslide hotspots.One of these hotspots lies in the vicinity of highly active Munsiyari Thrust(MT),while the other is in the Pandukeshwar formation within the MT's hanging wall,characterized by a high exhumation rate.High SL and low Vf values along these hotspots further corroborate that the occurrence of landslides in the study area is influenced by tectonic activity.This study,by identifying erosionprone areas and elucidating the implications of tectonic activity on landslide distribution,empowers policymakers and government agencies to develop strategies for hazard assessment and effective landslide risk mitigation,consequently safeguarding lives and communities.展开更多
Water quality is a pressing issue affecting the sustainable development of lakes.To elucidate the spatial and temporal characteristics of water quality in Bos ten Lake,China,this study constructed a comprehensive wate...Water quality is a pressing issue affecting the sustainable development of lakes.To elucidate the spatial and temporal characteristics of water quality in Bos ten Lake,China,this study constructed a comprehensive water quality index(CWQI) based on key water quality indicators,utilizing water quality data collected from 17 sampling sites spaning from 2011 to 2019.Key water quality indicators were determined using factor analysis,and the spatial and temporal characteristics of key water quality indicators and the CWQI were examined using multivariate statistical analysis.The key water quality indicators included pH,chemical oxygen demand(COD),water transparency(SD),NO3-,total dissolved solids(TDS),Cl-,SO42-,and electrical conductivity(EC).Furthermore,the contribution rates of all water quality indicators to the water quality were quantitatively elucidated using the SHapley Additive explanations(SHAP) values,thereby validating the factor analysis outcomes.Among the eight key water quality indicators,the COD had the most significant influence on the water quality of Bos ten Lake.The water quality condition of Bosten Lake has remained at Class Ⅲ from 2011 to 2019(CWQI ranging from3.19 to 3.90).The water quality of Bos ten Lake was characterized by distinct regional differences that arose from hydrodynamic processes within the lake and upstream water quality.The southwestern region exhibited the best water quality(mean CWQI of 3.47),whereas the northwestern region exhibited the worst(mean CWQI of 3.58).It is crucial to acknowledge that alongside the increase in industrial and agricultural effluent discharge monitoring,a series of ecological restoration projects for the lake basin have been initiated.Over time,the water quality of Bosten Lake showed gradual improvement(improvement rate of CWQI at 0.05/a).This study provides a critical scientific basis for enhancing the understanding and effective management of water quality in the Bosten Lake Basin through a comprehensive analysis of its spatial and temporal evolution and driving mechanisms.展开更多
Viscum coloratum(Kom.)Nakai is a well-known medicinal hemiparasite widely distributed in Asia.The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants,while the ...Viscum coloratum(Kom.)Nakai is a well-known medicinal hemiparasite widely distributed in Asia.The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants,while the latter of which is usually overlooked.The purpose of this study was to comprehensively evaluate the effects of host and habitat on the metabolites in V.coloratum through multiple chemical and biological approaches.The metabolite profile of V.coloratum harvested from three different host plants in two habitats were determined by multiple chemical methods including high-performance liquid chromatography-ultraviolet(HPLC-UV),gas chromatography-flame ionization detector(GC-FID)and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry(UPLC-QTOF/MS).The differences in antioxidant efficacy of V.coloratum were determined based on multiple in vitro models.The multivariate statistical analysis and data fusion strategy were applied to analyze the differences in metabolite profile and antioxidant activity of V.coloratum.Results indicated that the metabolite profile obtained by various chemical approaches was simultaneously affected by host and environment factors,and the environment plays a key role.Meanwhile,three main differential metabolites between two environment groups were identified.The results of antioxidant assay indicated that the environment has greater effects on the biological activity of V.coloratum than the host.Therefore,we conclude that the integration of various chemical and biological approaches combined with multivariate statistical and data fusion analysis,which can determine the influences of host plant and habitat on the metabolites,is a powerful strategy to control the quality of semi-parasitic herbal medicine.展开更多
This study investigates the suitability of statistical techniques for evaluating the fluoride content and the groundwater quality from Robles Department(RD)and Banda Department(BD)in Santiago del Estero(Argentina).For...This study investigates the suitability of statistical techniques for evaluating the fluoride content and the groundwater quality from Robles Department(RD)and Banda Department(BD)in Santiago del Estero(Argentina).For the original statistical study,evaluation of nine parameters(fluoride,pH,conductivity,atmospheric and water temperature,total dissolved solids,chloride,hardness,and alkalinity)of 110 collected underground water samples from 23 dispersed rural areas was proposed.Groundwater samples were obtained by sampling taken from wells at different depths.Fluoride levels were determined by a standard colorimetric method in two seasonal periods,the dry(from April to September)and rainy(from October to March)period.The analytical results obtained for physicochemical parameters such as pH,total dissolved solids(TDS),and temperature does not reveal any notable difference between the rainy and dry seasons studied.In both seasons,the atmospheric temperature average was 22℃.With respect to fluoride content,approximately 50%of the analysed groundwater samples exceeded the limit established by current legislation(1.0 mg/L),obtaining concentration levels in the range of 0.01-2.80 mg/L.This study demonstrates the usefulness of the univariate statistical method(quartiles calculation,interquartile range IQR),multivariate principal component analysis(PCA),and cluster analysis to establish a better understanding of the state of the contamination of the waters in the region studied.展开更多
The effect of Radix Scutellariae treated on type 2 diabetic rats has been investigated by a liquid chromatography coupled with tandem mass spectrometry（LC-MS/MS） based urinary quantitative approach.In this research,...The effect of Radix Scutellariae treated on type 2 diabetic rats has been investigated by a liquid chromatography coupled with tandem mass spectrometry（LC-MS/MS） based urinary quantitative approach.In this research,multiple reactions monitoring mode of MS/MS in LC-MS/MS analysis was used to quantitatively analyze the concentrations of 7 endogenous compounds in urine of normal control group,type 2 diabetic model group and Radix Scutellariae-treated group,and multivariate statistical analysis was utilized for MS data processing.The above-mentioned three groups can be distinguished via pattern recognition.The obtained results indicated that Radix Scutellariae affect the urinary metabolic profiling of type 2 diabetic rats on the polyol pathway,protein glycation reaction and amino acids metabolism pathway.According to these results,Radix Scutellariae should have the pharmacological effect on preventing or delaying the onset and progression of diabetes and its complications.展开更多
Compared with traditional chemical analysis methods,reflectance spectroscopy has the advantages of speed,minimal or no sample preparation,non-destruction,and low cost.The present study explored the application of the ...Compared with traditional chemical analysis methods,reflectance spectroscopy has the advantages of speed,minimal or no sample preparation,non-destruction,and low cost.The present study explored the application of the reflectance spectroscopy within near ultraviolet-visible-near infrared region to predict bio-element compositions in the ornithogenic sediments from the maritime Antarctic.A total of 106 samples were taken from four ornithogenic sediment cores on the Ardley Island of Antarctica,68 samples were used for building calibration equation,and 38 for prediction of nine bio-elements including P,Ca,Cu,Zn,Se, Sr,Ba,F and S.Three multivariate statistical analysis techniques,including stepwise multiple linear regression（Stepwise-MLR）,principal component regression（PCR） and partial least squares regression（PLS） were used to develop mathematical relationships between the spectral data and the chemical reference data.The results showed that the regression models constructed by PCR and PLS models have no significant differences,and obviously supervisor to Stepwise-MLR.The correlations between spectra-predicted and chemically analyzed concentrations of nine bio-elements are statistically significant,and the concentration-versusdepth profiles predicted from reflectance spectra using PLS calibration model are consistent with those from actual chemical analysis.These results demonstrated the feasibility of using reflectance spectroscopy to infer bio-element concentrations in the ornithogenic sediments,and thus it is suggested that the reflectance spectroscopy could provide a rapid and valuable technique to indirectly identify whether the sediments were influenced by penguin droppings in the Antarctic region.展开更多
Owing to the significant differences in environmental characteristics and explanatory factors among estuarine and coastal regions,research on diatom transfer functions and database establishment remains incomplete.Thi...Owing to the significant differences in environmental characteristics and explanatory factors among estuarine and coastal regions,research on diatom transfer functions and database establishment remains incomplete.This study analysed diatoms in surface sediment samples and a sediment core from the Lianjiang coast of the East China Sea,together with environmental variables.Principal component analysis of the environmental variables showed that sea surface salinity(SSS)and sea surface temperature were the most important factors controlling hydrological conditions in the Lianjiang coastal area,whereas canonical correspondence analysis indicated that SSS and pH were the main environmental factors affecting diatom distribution.Based on the modern diatom species–environmental variable database,we developed a diatom-based SSS transfer function to quantitatively reconstruct the variability in SSS between 1984 and 2021 for sediment core HK3 from the Lianjiang coastal area.The agreement between the reconstructed SSS and instrument SSS data from 1984 to 2021 suggests that diatombased SSS reconstruction is reliable for studying past SSS variability in the Lianjiang coastal area.Three low SSS events in AD 2019,2013,and 1999,together with an increased relative concentration of freshwater diatom species and coarser sediment grain sizes,corresponded to two super-typhoon events and a catastrophic flooding event in Lianjiang County.Thus,a diatom-based SSS transfer function for reconstructing past SSS variability in the estuarine and coastal areas of the East China Sea can be further used to reflect the paleoenvironmental events in this region.展开更多
基金funded by the China's National Natural Science Foundation(No.41440027)。
文摘Population growth and expanding urbanization have caused persistent shortages and contamination of groundwater resources in Mali,Africa.The increase in groundwater salinity makes it more difficult for residents to obtain drinking water,it is necessary to clarify the causes and control factors of groundwater mineralization in Gao region,northern Mali.Based on the analysis of the hydrochemical composition of groundwater in 24 boreholes,Piper and Sch?eller diagrams,principal component analysis(PCA)and hierarchical cluster analysis(HCA)are used to carry out multivariate statistical analysis on the main ions.The results show that the groundwater samples are weakly alkaline,with pH values ranging from 5.83 to 8.40,and the average values of boreholes are 7.50,respectively.The average electrical conductivity(EC)value is 354.4(μS/cm),and the extreme value is between 124.0 and 1247(μS/cm).Water is usually mineralized and presents nine types of water phase.The three principal components explain 84.42%of the total variance for 13 parameters.The factor F1(58.85%),the factor F2(16.88%)and the factor F3(8.69%)present for the majority of the total data set.In addition,multivariate statistical analysis confirmed the genetic relationship among aquifers and identified three main clusters.Clustering related to groundwater mineralization(F1),clustering related to oxide reduction and iron enrichment(F2),and clustering of groundwater pollution caused by nitrate and magnesium(F3).We found that agriculture,weathering activities and dissolution of geological materials promote the mineralization of groundwater.Groundwater quality in the Gao region is becoming less and less potable because of increasing salinity.
基金supported by the Major State Basic Research Development Program (No. 2010CB428800)the Geological Survey Projects Foundation of Institute of Hydrogeology and Environmental Geology (No. SK201308)
文摘Understanding the controlling factor of groundwater quality can enhance promoting sustainable development of groundwater resources. To this end, multivariate statistical analysis（MA） and hydrochemical analysis were introduced in this work. The results indicate that the canonical discriminant function with 7 parameters was established using the discriminant analysis（DA） method, which can afford 100% correct assignation according to the 3 different clusters（good water（GW）, poor water（PW）, and very poor water（VPW）） obtained from cluster analysis（CA）. According to factor analysis（FA）, 8 factors were extracted from 25 hydrochemical elements and account for 80.897% of the total data variance, suggesting that groundwater with higher concentrations of sodium, calcium, magnesium, chloride, and sulfate in southeastern study area are mainly affected by the natural process; the higher level of arsenic and chromium in groundwater extracted from northwestern part of study area are derived by industrial activities; domestic and agriculture sewage have important contribution to copper, iron, iodine, and phosphate in the northern study area. Therefore, this work can help identify the main controlling factor of groundwater quality in North China plain so as to make better and more informed decisions about how to achieve groundwater resources sustainable development.
基金supposed by the Program for Science and Technology of Shandong Province (2011GHY11521)the Department of Education of Shandong Province (No. J11LB07)the Natural Science Foundation of Qingdao City (Nos. 12-1-3-52-(1)-nsh and 12-1-4-16-(7)-jch)
文摘Meretricis concha is a kind of marine traditional Chinese medicine(TCM), and has been commonly used for the treatment of asthma and scald burns. In order to investigate the relationship between the inorganic elemental fingerprint and the geographical origin identification of Meretricis concha, the elemental contents of M. concha from five sampling points in Rushan Bay have been determined by means of inductively coupled plasma optical emission spectrometry(ICP-OES). Based on the contents of 14 inorganic elements(Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Se, and Zn), the inorganic elemental fingerprint which well reflects the elemental characteristics was constructed. All the data from the five sampling points were discriminated with accuracy through hierarchical cluster analysis(HCA) and principle component analysis(PCA), indicating that a four-factor model which could explain approximately 80% of the detection data was established, and the elements Al, As, Cd, Cu, Ni and Pb could be viewed as the characteristic elements. This investigation suggests that the inorganic elemental fingerprint combined with multivariate statistical analysis is a promising method for verifying the geographical origin of M. concha, and this strategy should be valuable for the authenticity discrimination of some marine TCM.
基金The authors thank National Key Research and Development Program of China(2018YFC1705900)National Natural Science Foundation of China(No.81903706)+1 种基金Distinguished professor of Liaoning Province(XLYC2002008)Science Foundation of Department of Education of Liaoning Province(LZ2020054)for financial support.
文摘Jinhongtang is a traditional Chinese medicine formula composed of Rheum palmatum L.stem,Sargentodoxa cuneata stem,and Taraxacum mongolicum and is used for the treatment of sepsis.However,quality assessment method for Jinhongtang is not available.In present study,we developed a UFLC-MS/MS method to determine 16 analytes in 20 batches of home-made and commercial Jinhongtang.Multivariate statistical analysis revealed the significant differences in the quality of home-made and commercial Jinhongtang and the difference in the quality of home-made samples was more significant.The integrated strategy based on UFLC-MS/MS and multivariate statistical analysis provided a new basis for the overall quality assessment of Jinhongtang.
基金Supported by the Scientific Research Foundation of Xianyang Normal University for Bringing in Talents(10XSYK104)
文摘[Objective] The study aimed to study the relationship between soil and environment on the basis of multivariate statistical analysis. [ Method] Through field investigation, sampling and laboratory analysis, we discussed the relationship between soil properties and environmental factors in Mizhi County, North Shaanxi by using Canoco multivariate statistical analysis. [ Result]According to the effects of various environmental factors on soil properties, the influencing order of environmental factors was land use way 〉 vegetation type 〉 vegetation restoration years 〉 vegeta- tion coverage 〉 slope aspect 〉 gradient 〉 elevation. In a word, soil properties were significantly affected by land use way and vegetation type which were the most important environmental factors of soil properties in spatial variation, while vegetation restoration years were closely related to the ac- cumulation of soil nutrients. [ Condusion]The research could provide theoretical references for the construction of ecological environment in Loess Plateau of China.
文摘Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and revealing its underlying general rules. Among the most powerful mathematical tools for organizing and helping to structure complex, heterogeneous and noisy data are the tools provided by multivariate statistical analysis (MSA) approaches. These eigenvector/eigenvalue data-compression approaches were first introduced to electron microscopy (EM) in 1980 to help sort out different views of macromolecules in a micrograph. After 35 years of continuous use and developments, new MSA applications are still being proposed regularly. The speed of computing has increased dramatically in the decades since their first use in electron microscopy. However, we have also seen a possibly even more rapid increase in the size and complexity of the EM data sets to be studied. MSA computations had thus become a very serious bottleneck limiting its general use. The parallelization of our programs—speeding up the process by orders of magnitude—has opened whole new avenues of research. The speed of the automatic classification in the compressed eigenvector space had also become a bottleneck which needed to be removed. In this paper we explain the basic principles of multivariate statistical eigenvector-eigenvalue data compression;we provide practical tips and application examples for those working in structural biology, and we provide the more experienced researcher in this and other fields with the formulas associated with these powerful MSA approaches.
基金National Natural Science Foundation of China(No.81430096)
文摘Objective To establish an effective approach for rapid and comprehensive analysis on the absorbed and metabolic components in rats after ig administration of Yuanhu Zhitong Dropping Pill（YHZT）. Methods Based on the combination of UPLC-Q-TOF/MS and multivariate statistical analysis, the absorbed prototype constituents and their metabolites in rat plasma were rapidly analyzed and identified, and the components absorbed into brain were further identified by comparing the extracted ion chromatograms（EICs） of control and brain tissue samples of dosed rats. Results A total of 38 YHZT-related xenobiotic compounds were detected and identified as the potential bioactive constituents in rat plasma, including 24 absorbed prototype constituents and 14 metabolites. In particular, of all prototype constituents, 14 were also detected in rat brain tissue, indicating that they could penetrate the blood-brain barrier and enter into brain. Conclusion An effective method is established and applied to analyze the potential bioactive constituents in YHZT, which provides a pathway to further investigate the pharmacological pattern and mechanism of YHZT.
基金The authors are grateful for financial support from the National Nature Science Foundation of China(Grant Nos.81073161,81130067 and 30730112)the National Basic Research Program of China(Grant No.2011CB505304)+1 种基金the Natural Science Foundation of Beijing(Grant No.7112110)for technical support from Mr.Yong Wang and other technologists of Waters China Ltd.
文摘To identify the chemical differences which lead to the different therapeutic effects of dried rehmannia root(DRR)and prepared rehmannia root(PRR),we compared the chemical composition of decoctions of randomly purchased DRR and PRR using ultra performance liquid chromatography(UPLC)coupled with time-of-fight mass spectrometry and high performance liquid chromatography(HPLC)coupled with evaporative light scattering detection(ELSD)with the aid of multivariate statistical analysis.Both approaches clearly revealed compositional and quantitative differences between DRR and PRR.UPLC-MS data indicated stachyose,rehmaiono-side A(or rehmaionoside B),acteoside(or forsythiaside,or isoacteoside),6-O-coumaroylajugol(or 6-O-E-feruloylajugol,or 6-O-Z-feruloylajugol)as important discriminators between DRR and PRR decoctions.HPLC-ELSD analysis showed that the content of fructose in the decoctions of PRR was about four times greater than that of DRR(P<10^(-5)),while sucrose content in the decoctions of PRR was only about one seventh of that in DRR(P<0.01).Our results suggest that some compounds,such as fructose,stachyose and rehmaionoside,may be responsible for the differing therapeutic effects of DRR and PRR.Furthermore,improvements in quality control for PRR,which is currently lacking in the Chinese Pharmacopoeia,are recommended.
基金supported by the National Instrumentation Programmme(Nos.2011YQ17006702 and 2011YQ14015010)the National Natural Science Foundation of China(Nos.81102413 and 21175121)Fundamental Research Program of Shenzhen (No.JC201005280634A).
文摘A new multivariate statistical strategy for analyzing large datasets that are produced by imaging mass spectrometry（IMS） techniques is reported.The strategy divides the whole datacube of the sample into several subsets and analyses them one by one to obtain the results.Instead of analyzing the whole datacube at one time,the strategy makes the analysis easier and decreases the computation time greatly.In this report,the IMS data are produced by the air flow-assisted ionization IMS（AFAI-IMS）.The strategy can be used in combination with most multivariate statistical analysis methods.In this paper,the strategy was combined with the principal component analysis（PCA） and partial least square analysis（PLS）.It was proven to be effective by analyzing the handwriting sample.By using the strategy,the m/z corresponding to the specific lipids in rat brain tissue were distinguished successfully.Moreover the analysis time grew linearly instead of exponentially as the size of sample increased.The strategy developed in this study has enormous potential for searching for the mjz of potential biomarkers quickly and effectively.
文摘The application of multivariate data analysis, a method for coping with multi-colinearity among independent variables in analyzing coastal water quality data, is presented. This study investigates the statistical regression modeling of FIB （fecal indicator bacteria） concentrations at the outlet of Talbert Marsh in Orange County, California. The multivariate data modeling utilized FIB and physical variables measurements （n = 5,580） collected during a series of longitudinal study of the Talbert Marsh. For the statistical prediction modeling in predicting the FIB concentrations at the outlet of the Talbert Marsh, multivariate analysis techniques such as PCR （principal components regression）, PLS （partial least-squares） regression and SVM （support vector machine） regression were adopted. Statistical modeling results suggest that the statistical modeling predictions are all fell within the reasonable range of actual measurement data. In addition, it is indicated that the accuracy of SVM regression for predicting FIB concentrations at the Talbert Marsh outlet is better than that of other models.
基金the National Council of Science and Technoloy(CONACyT)and the Ministry of Public Education-PROMEP for their support through grants No.84252 and 103.5/13/9346,respectively,and for the scholarship of Jessica Badillo-Camacho from CONACyT.
文摘Water quality of Mexican tropical lake Chapala was assessed through multivariate statistical techniques, cluster analysis (CA) and principal component analysis (PCA) at ten different monitoring sites for ten physicochemical variables and six metals. This study evaluated and interpreted complex water quality data sets and apportioned of pollution sources to get better information about water quality. From descriptive statistics results, the highest concentrations of metals occurred during the dry season, and this trend was explained by the fact that an unusual rainy event occurred during the month of February 2009 and brought metals into the lake by runoffs from nearby mountains. According to international criteria for water consumption by aquatic organisms [USEPA], only Zn concentration values were below these criteria whereas the values of Ni, Pb, Cd and Fe were above the corresponding values set in these criteria (Ni: 52 μg·L-1, Pb: 2.5 μg·L-1, Cd: 0.25 μg·L-1, and Fe: 1000 μg·L-1). The correlations were observed by PCA, which were used to classify the samples by CA, based on the PCA scores. Seven significant cluster groups of sampling locations—(sites 4 and 5), (sites 3 and 9), (site 7), (site 10), (sites 2 and 6), (site 8) and (site 1)— were detected on the basis of similarity of their water quality. The results revealed that the stress exerted on the lake caused by waste sources follows the order: domestic > agricultural > industrial.
基金supported by the Doctoral Research Start-up Fund,East China University of Technology(DHBK2019313)the Open Research Fund Program of Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring(Central South University),the Ministry of Education(2020YSJS10)+1 种基金the Open Research Fund Program of Shandong Provincial Engineering Laboratory of Application and Development of Big Data for Deep Gold Exploration(SDK202224)the Basic Scientific Research Fund of the Institute of Geophysical and Geochemical Exploration,Chinese Academy of Geological Sciences(AS2022P03).
文摘Geochemical surveys are essential for understanding the spatial distribution of ore-forming elements.However,these surveys often involve compositional data,the weight concentrations,which do not meet the requirements of statistical methods due to the closure effect.In this study,we applied an integrated approach combining compositional data,multifractal,and multivariate statistical analyses to identify the nonlinear complexity of the spatial distributions of elemental concentrations in the Er’renshan ore field.Initially,the raw concentrations were transformed into log-ratios following the principles of composition data theory to alleviate the impact of the closure effect.Multifractal analysis was then conducted to characterise the nonlinear complexity of the concentration distributions.Furthermore,principal component analysis(PCA)and factor analysis(FA)were applied to identify spurious correlations and the potential factors controlling the distribution patterns.The results demonstrate that:a)the raw data are biased,while the log-ratio data are unbiased and more reliable;b)the spatial distributions of elemental concentrations exhibit nonlinear complexity;and c)the elemental distribution in the study area is largely controlled by structural factors.
基金CSIR for providing financial assistance(09/0420(11800)/2021EMR-I)。
文摘The Kumaun Himalaya is well-known as a geologically and tectonically complex region that amplifies mass wasting processes,particularly landslides.This study attempts to investigate the interplay between landslide distribution and the lithotectonic regime of Darma Valley,Kumaun Himalaya.A landslide inventory comprising 295 landslides in the area has been prepared and several morphotectonic proxies such as valley floor width to height ratio(Vf),stream length gradient index(SL),and hypsometric integral(HI)have been used to infer tectonic regime.Morphometric analysis,including basic,linear,aerial,and relief aspects,of 59 fourth-order sub-basins,has been carried out to estimate erosion potential in the study area.The result demonstrates that 46.77%of the landslides lie in very high,20.32%in high,21.29%in medium,and 11.61%in low erosion potential zones respectively.In order to determine the key parameters controlling erosion potential,two multivariate statistical methods namely Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC)were utilized.PCA reveals that the Higher Himalayan Zone(HHZ)has the highest erosion potential due to the presence of elongated sub-basins characterized by steep slopes and high relief.The clusters created through AHC exhibit positive PCA values,indicating a robust correlation between PCA and AHC.Furthermore,the landslide density map shows two major landslide hotspots.One of these hotspots lies in the vicinity of highly active Munsiyari Thrust(MT),while the other is in the Pandukeshwar formation within the MT's hanging wall,characterized by a high exhumation rate.High SL and low Vf values along these hotspots further corroborate that the occurrence of landslides in the study area is influenced by tectonic activity.This study,by identifying erosionprone areas and elucidating the implications of tectonic activity on landslide distribution,empowers policymakers and government agencies to develop strategies for hazard assessment and effective landslide risk mitigation,consequently safeguarding lives and communities.
基金supported by the National Natural Science Foundation of China(42377072,52409105).
文摘Water quality is a pressing issue affecting the sustainable development of lakes.To elucidate the spatial and temporal characteristics of water quality in Bos ten Lake,China,this study constructed a comprehensive water quality index(CWQI) based on key water quality indicators,utilizing water quality data collected from 17 sampling sites spaning from 2011 to 2019.Key water quality indicators were determined using factor analysis,and the spatial and temporal characteristics of key water quality indicators and the CWQI were examined using multivariate statistical analysis.The key water quality indicators included pH,chemical oxygen demand(COD),water transparency(SD),NO3-,total dissolved solids(TDS),Cl-,SO42-,and electrical conductivity(EC).Furthermore,the contribution rates of all water quality indicators to the water quality were quantitatively elucidated using the SHapley Additive explanations(SHAP) values,thereby validating the factor analysis outcomes.Among the eight key water quality indicators,the COD had the most significant influence on the water quality of Bos ten Lake.The water quality condition of Bosten Lake has remained at Class Ⅲ from 2011 to 2019(CWQI ranging from3.19 to 3.90).The water quality of Bos ten Lake was characterized by distinct regional differences that arose from hydrodynamic processes within the lake and upstream water quality.The southwestern region exhibited the best water quality(mean CWQI of 3.47),whereas the northwestern region exhibited the worst(mean CWQI of 3.58).It is crucial to acknowledge that alongside the increase in industrial and agricultural effluent discharge monitoring,a series of ecological restoration projects for the lake basin have been initiated.Over time,the water quality of Bosten Lake showed gradual improvement(improvement rate of CWQI at 0.05/a).This study provides a critical scientific basis for enhancing the understanding and effective management of water quality in the Bosten Lake Basin through a comprehensive analysis of its spatial and temporal evolution and driving mechanisms.
基金funded by the National Natural Science Foundation of China(Grant No.:30901967)the Natural Science Foundation of Liaoning Province(Grant No.:2013020223)Shenyang Pharmaceutical University Student Science and Technology Innovation Project(Grant No.:12)。
文摘Viscum coloratum(Kom.)Nakai is a well-known medicinal hemiparasite widely distributed in Asia.The synthesis and accumulation of its metabolites are affected by both environmental factors and the host plants,while the latter of which is usually overlooked.The purpose of this study was to comprehensively evaluate the effects of host and habitat on the metabolites in V.coloratum through multiple chemical and biological approaches.The metabolite profile of V.coloratum harvested from three different host plants in two habitats were determined by multiple chemical methods including high-performance liquid chromatography-ultraviolet(HPLC-UV),gas chromatography-flame ionization detector(GC-FID)and ultra-performance liquid chromatography quadrupole time of flight mass spectrometry(UPLC-QTOF/MS).The differences in antioxidant efficacy of V.coloratum were determined based on multiple in vitro models.The multivariate statistical analysis and data fusion strategy were applied to analyze the differences in metabolite profile and antioxidant activity of V.coloratum.Results indicated that the metabolite profile obtained by various chemical approaches was simultaneously affected by host and environment factors,and the environment plays a key role.Meanwhile,three main differential metabolites between two environment groups were identified.The results of antioxidant assay indicated that the environment has greater effects on the biological activity of V.coloratum than the host.Therefore,we conclude that the integration of various chemical and biological approaches combined with multivariate statistical and data fusion analysis,which can determine the influences of host plant and habitat on the metabolites,is a powerful strategy to control the quality of semi-parasitic herbal medicine.
基金partially supported by the research project"Water and Environment"by the Secretary of Science and Technology of the University National of Santiago del Estero,Argentina(UNSE)+1 种基金National University of Distance Education(UNED)(project reference:2017/CTINV-0024)by the Comunidad of Madrid and European funding from FSE and FEDER programs(project S2018/BAA-4393,AVANSECALII-CM)。
文摘This study investigates the suitability of statistical techniques for evaluating the fluoride content and the groundwater quality from Robles Department(RD)and Banda Department(BD)in Santiago del Estero(Argentina).For the original statistical study,evaluation of nine parameters(fluoride,pH,conductivity,atmospheric and water temperature,total dissolved solids,chloride,hardness,and alkalinity)of 110 collected underground water samples from 23 dispersed rural areas was proposed.Groundwater samples were obtained by sampling taken from wells at different depths.Fluoride levels were determined by a standard colorimetric method in two seasonal periods,the dry(from April to September)and rainy(from October to March)period.The analytical results obtained for physicochemical parameters such as pH,total dissolved solids(TDS),and temperature does not reveal any notable difference between the rainy and dry seasons studied.In both seasons,the atmospheric temperature average was 22℃.With respect to fluoride content,approximately 50%of the analysed groundwater samples exceeded the limit established by current legislation(1.0 mg/L),obtaining concentration levels in the range of 0.01-2.80 mg/L.This study demonstrates the usefulness of the univariate statistical method(quartiles calculation,interquartile range IQR),multivariate principal component analysis(PCA),and cluster analysis to establish a better understanding of the state of the contamination of the waters in the region studied.
基金supported by the National Natural Science Foundation of China(No.81373952,81473537)the Jilin province science and technology development projects(No.20150311039YY)
文摘The effect of Radix Scutellariae treated on type 2 diabetic rats has been investigated by a liquid chromatography coupled with tandem mass spectrometry（LC-MS/MS） based urinary quantitative approach.In this research,multiple reactions monitoring mode of MS/MS in LC-MS/MS analysis was used to quantitatively analyze the concentrations of 7 endogenous compounds in urine of normal control group,type 2 diabetic model group and Radix Scutellariae-treated group,and multivariate statistical analysis was utilized for MS data processing.The above-mentioned three groups can be distinguished via pattern recognition.The obtained results indicated that Radix Scutellariae affect the urinary metabolic profiling of type 2 diabetic rats on the polyol pathway,protein glycation reaction and amino acids metabolism pathway.According to these results,Radix Scutellariae should have the pharmacological effect on preventing or delaying the onset and progression of diabetes and its complications.
基金supported by the National Natural Science Foundation(Grant Nos.40876096,40606003 and40730107)the young fund for strategetic research of Chinese polar sciences from CAAA(No.20070202)+1 种基金open research fund from SOA Key Laboratory for Polar Science(KP2007002)special fund for excellent PhD thesis of CAS.
文摘Compared with traditional chemical analysis methods,reflectance spectroscopy has the advantages of speed,minimal or no sample preparation,non-destruction,and low cost.The present study explored the application of the reflectance spectroscopy within near ultraviolet-visible-near infrared region to predict bio-element compositions in the ornithogenic sediments from the maritime Antarctic.A total of 106 samples were taken from four ornithogenic sediment cores on the Ardley Island of Antarctica,68 samples were used for building calibration equation,and 38 for prediction of nine bio-elements including P,Ca,Cu,Zn,Se, Sr,Ba,F and S.Three multivariate statistical analysis techniques,including stepwise multiple linear regression（Stepwise-MLR）,principal component regression（PCR） and partial least squares regression（PLS） were used to develop mathematical relationships between the spectral data and the chemical reference data.The results showed that the regression models constructed by PCR and PLS models have no significant differences,and obviously supervisor to Stepwise-MLR.The correlations between spectra-predicted and chemically analyzed concentrations of nine bio-elements are statistically significant,and the concentration-versusdepth profiles predicted from reflectance spectra using PLS calibration model are consistent with those from actual chemical analysis.These results demonstrated the feasibility of using reflectance spectroscopy to infer bio-element concentrations in the ornithogenic sediments,and thus it is suggested that the reflectance spectroscopy could provide a rapid and valuable technique to indirectly identify whether the sediments were influenced by penguin droppings in the Antarctic region.
基金The National Natural Science Foundation of China under contract Nos 42376236 and 42176226.
文摘Owing to the significant differences in environmental characteristics and explanatory factors among estuarine and coastal regions,research on diatom transfer functions and database establishment remains incomplete.This study analysed diatoms in surface sediment samples and a sediment core from the Lianjiang coast of the East China Sea,together with environmental variables.Principal component analysis of the environmental variables showed that sea surface salinity(SSS)and sea surface temperature were the most important factors controlling hydrological conditions in the Lianjiang coastal area,whereas canonical correspondence analysis indicated that SSS and pH were the main environmental factors affecting diatom distribution.Based on the modern diatom species–environmental variable database,we developed a diatom-based SSS transfer function to quantitatively reconstruct the variability in SSS between 1984 and 2021 for sediment core HK3 from the Lianjiang coastal area.The agreement between the reconstructed SSS and instrument SSS data from 1984 to 2021 suggests that diatombased SSS reconstruction is reliable for studying past SSS variability in the Lianjiang coastal area.Three low SSS events in AD 2019,2013,and 1999,together with an increased relative concentration of freshwater diatom species and coarser sediment grain sizes,corresponded to two super-typhoon events and a catastrophic flooding event in Lianjiang County.Thus,a diatom-based SSS transfer function for reconstructing past SSS variability in the estuarine and coastal areas of the East China Sea can be further used to reflect the paleoenvironmental events in this region.
