Substituting missing data in compositional analysis

Multivariate analysis of environmental data sets requires the absence of missing values or their substitution by small values. However, if the data is transformed logarithmically prior to the analysis, this solution cannot be applied because the logarithm of a small value might become an outlier. Several methods for substituting the missing values can be found in the literature although none of them guarantees that no distortion of the structure of the data set is produced. We propose a method for the assessment of these distortions which can be used for deciding whether to retain or not the samples or variables containing missing values and for the investigation of the performance of different substitution techniques. The method analyzes the structure of the distances among samples using Mantel tests. We present an application of the method to PCDD/F data measured in samples of terrestrial moss as part of a biomonitoring study.     

Estimation of Similarity in the Qualitative Composition of Humic Substance in Marine Sediments By Means of an Uv-Spectroscopic Library

In this paper a method for the study of the qualitative similarity of extractable humic substance (EHS) in marine sediments based on the realisation of UV spectral library of EHS is described. the spectral library was built including the digitised spectra of humic substance extracted from several marine sediments (46 samples) and two samples of standard materials (lignin sulphonate and humic substance) in a Statistica data file. the data matrix was elaborated by means of different multivariate statistic techniques such as Cluster Analysis (CA), Principal Components Analysis (PCA) and the univariate technique Spectral Correlation Analysis (SCA). This approach allows us to show the contribution of different organic compounds (aromatic, lipid and acid) to the composition of EHS and moreover it evidences also the structural characteristics of EHS in terms of similarities in the qualitative composition of samples such as presence of terrestrial and/or vegetal contributions. the UV library is an objective tool to study the qualitative composition of EHS and it represents a complementary approach to the most common methods based on the application of spectroscopic (IR, ¹³CNMR), potentiometric and chromatographic techniques.     

Einsatz der Hasse-Diagrammtechnik zur vergleichenden Datenanalyse von Biomarkerantworten und ?kotoxikologischen Tests

Die ?kotoxikologie mu? sich mit biologischen Systemen und ihren Antworten auf schadstoffinduzierten Stre? auseinandersetzen. Die hierzu verwendete experimentelle Technik eilt dabei den M?glichkeiten dynamischer, proze?orientierter mathematischer Modellierung weit voraus. In dieser methodisch orientierten Arbeit werden Techniken aus der mathematischen Disziplin der Verbandstheorie vorgestellt, die eine Datenanalyse unter den Aspekten vergleichender Bewertung erlauben. Wichtige Ergebnisse sind dabei

废黄河水质的多元统计分析

用主成分分析的方法,找出影响废黄河2007年水质的主成分,计算各样本的主成分得分,用聚类分析的方法将样本水质分类,结合分类结果及水质综合评分对各样本水质进行评价。     

我国部分商品粮基地土壤重金属污染的差异分析与综合评价探讨

根据1988年全国农业环境质量状况调查资料,选取我国部分商品粮基地县土壤重金属污染数据(污染指数),通过多元统计分析,揭示了各商品粮基地土壤重金属污染的差异与分类.建立模糊综合评判模型对各商品粮基地土壤污染状况进行了综合评价,得到了各商品粮基地土壤污染程度的相对排序.      

泸州市降水监测布点优化研究

在泸州市2016—2020年大气降水监测数据的基础上,借助聚类分析、多元方差分析等统计分析手段,对原有降水监测点位进行优化研究,并验证优化结果。在遵循《酸沉降监测技术规范》(HJ/T 165—2004)点位布设要求的前提下,建立了降水监测点位评价体系,从原有7个降水监测点位中优化筛选出3个。优化后的点位对监测结果的影响显著性均>0.05,表明优化前后全市降水数据无显著性差异,该优化方案不会影响区域整体代表性。     

Estimation of Similarity in the Qualitative Composition of Humic Substance in Marine Sediments By Means of an Uv-Spectroscopic Library

In this paper a method for the study of the qualitative similarity of extractable humic substance (EHS) in marine sediments based on the realisation of UV spectral library of EHS is described. the spectral library was built including the digitised spectra of humic substance extracted from several marine sediments (46 samples) and two samples of standard materials (lignin sulphonate and humic substance) in a Statistica data file. the data matrix was elaborated by means of different multivariate statistic techniques such as Cluster Analysis (CA), Principal Components Analysis (PCA) and the univariate technique Spectral Correlation Analysis (SCA). This approach allows us to show the contribution of different organic compounds (aromatic, lipid and acid) to the composition of EHS and moreover it evidences also the structural characteristics of EHS in terms of similarities in the qualitative composition of samples such as presence of terrestrial and/or vegetal contributions. the UV library is an objective tool to study the qualitative composition of EHS and it represents a complementary approach to the most common methods based on the application of spectroscopic (IR, ¹³CNMR), potentiometric and chromatographic techniques.     

Ecosystem states: Creating a data-derived, ecosystem-scale ecological response model that is explicit in space and time

Increasing difficulties associated with balancing consumptive demands for water and achieving ecological benefits in aquatic ecosystems provide opportunities for new ecosystem-scale ecological response models to assist managers. Using an Australian estuary as a case study, we developed a novel approach to create a data-derived state-and-transition model. The model identifies suites of co-occurring birds, fish, benthic invertebrates and aquatic macrophytes (as ‘states’) and the changing physico-chemical conditions that are associated with each (‘transitions’). The approach first used cluster analysis to identify sets of co-occurring biota. Differences in the physico-chemical data associated with each state were identified using classification trees, with the biotic distinctness of the resultant statistical model tested using analysis of similarities. The predictive capacity of the model was tested using new cases. Two models were created using different time-steps (annual and quarterly) and then combined to capture both longer-term trends and more-recent declines in ecological condition. We identified eight ecosystem states that were differentiated by a mix of water-quantity and water-quality variables. Each ecosystem state represented a distinct biotic assemblage under well-defined physico-chemical conditions. Two ‘basins of attraction’ were identified, with four tidally-influenced states, and another four independent of tidal influence. Within each basin, states described a continuum of relative health, manifest through declining taxonomic diversity and abundances. The main threshold determining relative health was whether freshwater flows had occurred in the region during the previous 339 days. Canonical analyses of principal coordinates tested the predictive capacity of the model and demonstrated that the variance in the environmental data set was well captured (87%) with 52% of the variance in the biological data set also captured. The latter increased to >80% when long- and short-term biological data were analysed separately, indicating that the model described the available data for the Coorong well. This approach thus created a data-derived, multivariate model, where neither states nor transitions were determined a priori. The approach did not over-fit the data, was robust to patchy or missing data, the choice of initial clustering technique and random errors in the biological data set, and was well-received by local natural resource managers. However, the model did not capture causal relationships and requires additional testing, particularly during future episodes of ecological recovery. The approach shows significant promise for simplifying management definitions of ecological condition and, via scenario analyses, can be used to assist in manager decision-making of large, complex aquatic ecosystems in the future.     

Multivariate Analysis of Interactions Between Phytoplankton Biomass and Environmental Variables in Taihu Lake, China

Phytoplankton variation in large shallow eutrophic lakes is characterized by high spatial and temporal heterogenity. Understanding the pattern of phytoplankton variation and the relationships between it and environmental variables can contribute to eutrophic lakes management. In this study Taihu Lake, one of the largest eutrophic fresh water lake in China, was taken as study area. The water body of Taihu Lake was divided into five regions viz. Wuli bay (WB), Meilian Bay (MB), West Taihu Lake (WTL), Main Body of Taihu Lake (MBTL) and East Taihu Lake (ETL). Concentrations of chlorophyll-a and the related environmental variables were determined in each region in the period 2000–2003. Factor analysis and multivariate analysis were applied to evaluate the interactions between phytoplankton variation and environmental variables. Results showed that the highest average concentrations of TN, TP and Chl-a were observed in WB, followed in a descending order by MB and WTL, and the lowest concentrations of TN, TP and Chl-a were observed in MBTL and ETL. Chl-a and TP concentrations in most regions (except ETL) declined during the study period. It suggested that to some extent the lake was recovering from eutrophication. However, persistent ascending of TN and NH₄–N in all five regions indicated the deteriorating of water quality in the study period. Results of multivariate showed that the relationships between phytoplankton biomass and environmental variables varied among regions. TP illustrated itself a controlling role on phytoplankton in WB, MB, WTL and MBTL according to the significant positive relations to phytoplankton biomass in these regions. Nitrogen could be identified as a limiting factor to phytoplankton biomass in ETL in view of the positive correlations between TN and phytoplankton and between NH₄–N and phytoplankton. Spatial variation of interactions between phytoplankton and environmental parameters suggested proper eutrophication control measures were needed to restore ecological system in each region of Taihu Lake.     

Potentially toxic metal contamination of urban soils and roadside dust in Shanghai, China

A detailed investigation was conducted to understand the contamination characteristics of a selected set of potentially toxic metals in Shanghai. The amount of Pb, Zn, Cu, Cr, Cd and Ni were determined from 273 soil/dust samples collected within urban area. The results indicated that concentration of all metals except Ni in soils was significant, and metal pollution was even severer in roadside dust. A series of metal spatial distribution maps were created through geostatistical analysis, and the pollution hotspots tended to associate with city core area, major road junctions, and the regions close to industrial zones. In attempt of identifying the source of metals through geostatistical and multivariate statistical analyses, it was concluded as follows: Pb, Zn and Cu mainly originated from traffic contaminants; soil Ni was associated with natural concentration; Cd largely came from point-sourced industrial pollution; and Cr, Ni in dust were mainly related to atmospheric deposition.