Procedures for outlier detection in circular time series models

It is known that the occurrence of outliers in linear or non-linear time series models may have adverse effects on the modelling and statistical inference of the data. Consequently, extensive research has been conducted on developing outlier detection procedures so that outliers may be properly managed. However, no work has been done on the problem of outliers in circular time series data. This problem is the focus of this paper. The main objective is to develop novel numerical and graphical procedures for detecting these outliers in circular time series data.A number of circular time series models have been proposed including the circular autoregressive model. We extend the iterative outlier detection procedure which has been successfully used in linear time series models to the circular autoregressive model. The proposed procedure shows a good performance when investigated via simulation for the circular autoregressive model of order one. At the same time, several statistical techniques have been used to detect the change of preferred trend in time series data using SLIME and CUSUM plots. While the methods fail to indicate directly the outliers in circular time series data, we use the ideas employed to develop three novel graphical procedures for identifying the outliers. For illustration, we apply the procedures to a particular set of wind direction data. An agreement between the results of the graphical and iterative detection procedures is observed. These procedures could be very useful in improving the modelling and inferential processes for circular time series data.     

Bewertungsansatz von Umweltmonitoring-Informationssystemen in Ballungsräumen

Comprehensive data on environmental monitoring programs concerned with air pollutants like ozone (O₃), nitrogen dioxide (NO₂), nitrogen oxide (NO), carbon dioxide (CO₂) und carbon monoxide (CO), and occassionally suspended dust, benzene and other environmental chemicals, are available on the free Internet. As different monitoring information systems exist in most states or big cities of the Federal Republic of Germany, a comparison of these systems with their pros and cons is of great interest to the public. Environmental air pollutant monitoring systems in 16 states of Germany are listed and evaluated by applying 5 evaluation criteria for the differentiation of these systems. Different data-analysis methods will be applied, the Hasse diagram technique, a method derived from discrete mathematics and the partially Ordered Scalogram Analysis with Coordinates (POSAC) method, a multivariate statistical approach. The important objects, the so-called maximal or minimal objects, are detected in both methods. The Internet-based environmental monitoring systems of the states of Berlin, Bremen, Saxony-Anhalt, Baden-Wurttemberg are rated good in the evaluation approaches, whereas the information systems of the states of Brandenburg, North Rhine-Westphalia, Saxony received a rather poor ranking. The attributes of DA, way of data presentation on the Internet, and ME, type and length of measurements, were pointed out in the data-analysis methods. Multivariate explorative statistical methods offer a comprehensive tool for the graphical analysis of data-matrices. The ranking of objects is given in an effective and graphically comprehensible manner using the Hasse diagram technique. The choice and preference of the methods is problem-driven. A combination of these different methods is envisaged in the authors’ future research.     

Application of standard statistical methods in the analysis of complex data generated from soil bioassays to assess the impacts of agrochemical-containing sludge amendments

The use of sludge as soil amendment is widely encouraged by its high contents in organic matter and plant nutrients. Nevertheless, agrochemicals potentially present in sludge could be harmful to terrestrial ecosystems. The present work aimed to apply standard statistical methods for suitable assessment of the ecotoxicological impacts of sludge amendments on soil, involving the following factors: the type of treated sludge, their application dose, and their contents in agrochemicals. Terrestrial Model Ecosystems were used to assess the effects of sludge amendments on endpoints from different trophic levels of the soil ecosystem, including an in vitro estrogenic bioassay on soil leachates. Here, we show the significant negative effects of the highest dose of sludge in most of the soil bioassays. Thermally dried sludge increased significantly the microbial activity leading to lower contamination of leachates with endocrine disrupting molecules. Agrochemicals contents of sludge have only significant impacts on increasing the delay of germination of plant seeds. Soil bioassays are thus complementary to sludge chemical analysis when the impacts of its application on soil should be assessed: significant negative impacts were related to the intrinsic composition of sludge rather than its agrochemicals contents. We conclude that standard statistical methods are relevant tools for the analysis of complex data generated from this type of experiment.     

Interaction structures analysed from water-quality data

Fortnightly observations of water quality parameters, discharge and water temperature along the River Elbe have been subjected to a multivariate data analysis. In a previous study [Petersen, W., Bertino, L., Callies, U., Zorita, E., 2001. Process identification by principal component analysis of river-quality data. Ecol. Model. 138, 193–213] applied principal component analysis (PCA) to show that 60% of variability in the data set can be explained through just two linear combinations of eight original variables. In the present paper more advanced multivariate methods are applied to the same data set, which are supposed to suit better interpretations in terms of the underlying system dynamics.The first method, graphical modelling, represents interaction structures in terms of a set of conditional independence constraints between pairs of variables given the values of all other variables. Assuming data from a multinormal distribution conditional independence constraints are expressed by zero partial correlations. Different graphical structures with nodes for each variable and connecting edges between them can be assessed with regard to their likelihood. The second method, canonical correlation analysis (CCA), is applied for studying the correlation structures of external forcing and water quality parameters.Results of CCA turn out to be consistent with the dominant patterns of variability obtained from PCA. The percentages of variability explained by external forcing, however, are estimated to be smaller. Fitting graphical models allows a more detailed representation of interaction structures. For instance, for given discharge and temperature correlated variations of the concentrations of oxygen and nitrate, respectively, can be modelled as being mediated by variations of pH, which is a representer for algal activity. Considerably simplified graphical models do not much affect the outcomes of both PCA and CCA, and hence it is concluded that these graphical models successfully represent the main interaction structures represented by the covariance matrix of the data. The analysed conditional independence patterns provide constraints to be satisfied by directed probabilistic networks, for instance.     

Effects of cotton straw amendment on soil fertility and microbial communities

Maintaining soil fertility, while controlling pollution from excessive chemical fertilizer application is important for keeping soil productivity of sustainable agriculture. Variety of straws have been used and proven to be good soil amendments for increasing soil organic matter (OM) and a range of additional soil nutrients. However, little is known about the utilization of cotton straw for soil amendment. To better understand the mechanism behind cotton straw soil amendments, investigations were performed upon cucumber seedlings, where changes to soil nutrients and microbial communities were investigated. The results revealed that the cotton straw application promoted the cucumber seedling growth by significantly increasing the soil OM, available nitrogen, available phosphorus, and available potassium. The concentration of cotton straw was positively correlated to both the number of the culturable microorganisms and also the total microbial biomass within soil. Furthermore, assessment of cotton straw application using Biolog metabolic profiling and phospholipid fatty acid analysis revealed that such application increased the microbial community metabolic activity, and markedly changed the structure of microbial community. 16S rRNA gene clone library construction and phylogenetic analysis of soil bacteria revealed γ- Proteobacteria sequences dominated the cotton straw amendment soil, comprising 27.8% of the total number of analyzed sequences, while they were less represented in control soil (13.4%). On the contrary, the Sphingobacteria (7.8%) and Verrucomicrobia (2.4%) in the cotton straw amendment soil decreased after application when compared to the control soil 15.2% and 15.2%.     

Probability distributions of arsenic in soil from brownfield sites in Beijing (China): statistical characterization of the background populations and implications for site assessment studies

A probabilistic analysis was performed on soil arsenic concentration data from 4 brownfield sites at Beijing (Chaoyang and Haidian Districts), involved in environmental assessment studies. The available data sets were processed to provide a statistical characterization of the background populations and differentiate “anomalous data” from the natural range of variation of arsenic concentrations in soil. The site-specific background distributions and the existing wide-scale background values defined for the Beijing area were compared, discussing related implications for the definition of metal contamination soil screening levels (SSLs) in site assessment studies. The statistical analysis of As data sets discriminated site-specific background populations, encompassing 88% to 94% of the sample data, from outliers values, associated with either subsoil natural enrichments or possible anthropogenic releases. Upper Baseline Concentration (UBC) limits (+ 2σ level), including most of the site-specific metal background variability, were derived based on the statistical characterization of the background populations. Sites in the Chaoyang South District area had UBC values in the range 10.4–12.6 mg·kg^-1. These ranges provide meaningful SSL values to be adopted for As in local site assessment studies. Using the wide-scale background value for the Beijing area would have erroneously classified most of the areas in the subject sites as potentially contaminated.     

Bewertung heterogener Altlasten durch Probenahme, statistische und geostatistische Modellierung

A slack heap in Saxony serves as an example for the model procedure of evaluation heterogeneous waste sites via sampling as well as statistical and geostatistical data analysis. This paper demonstrates the usefulness of the known regulations for sampling and of the tried and proven geostatistical methods developed for assessing homogeneous wastes and the concornitantly contaminated soil. Emphasized here are the contents of iron and sulfur. Considered in addition are the concentrations of arsenic and the heat loss. To establish a conclusion, the variograms of the original data are used to evaluate the waste site in different directions and at determined depths. With the aid of a spot interpolation, further data can be calculated for additional sites which have not been sampled and can be used consequently for displaying the spatial variability. Finally, the statistical data analysis is applied using the standard methods of random sampling as an alternative to the geostatistical modeling. In this manner, the consequences for the sampling strategy can be demonstrated.     

Multiple source spatial cluster detection via multi-criteria analysis

Multiple data sources are essential to provide reliable information regarding the emergence of potential health threats, compared to single source methods. Spatial Scan Statistics have been adapted to analyze multivariate data sources, but only ad hoc procedures have been devised to address the problem of selecting the most likely cluster and computing its significance. In this work, information from multiple data sources of disease surveillance is incorporated to achieve more coherent spatial cluster detection using tools from multi-criteria analysis. The best cluster solutions are found by maximizing two objective functions simultaneously, based on the concept of dominance. To evaluate the statistical significance of solutions, a statistical approach based on the concept of attainment function is used. The multi-criteria approach has several advantages: the representation of the evaluation function for each data source is clear, and does not suffer from an artificial, and possibly confusing mixture with the other data source evaluations; it is possible to attribute, in a rigorous way, the statistical significance of each candidate cluster; and it is possible to analyze and pick-up the best cluster solutions, as given naturally by the non-dominated set. The methodology is illustrated with real datasets.     

宁夏引黄灌区不同土地利用方式土壤微生物群落多样性研究

以宁夏引黄灌区6种典型利用方式(12年果园田、稻旱轮作田、盐化旱田、枸杞田、常年旱田、常年稻田)灌淤土为研究对象,通过同期野外多点采样和室内培养分析相结合,运用磷脂脂肪酸谱图分析方法,探讨了不同土地利用与管理方式下灌淤土理化性质、微生物生物量、微生物区系及微生物群落多样性差异及相关关系,以期为宁夏引黄灌区土壤可持续利用提供数据支撑。结果表明,(1)不同土地利用方式中,长期秸秆还田的盐化旱田、长期有机无机配施的12年果园以及常年旱田3种利用方式下,土壤地力水平较高,相应土壤微生物生物量炭、氮水平最高,有利于土壤微生物数量的保持,而常年淹水条件下的常年稻田土壤肥力水平低下,微生物生物量最低。(2)不同土地利用方式磷脂脂肪酸PLFA总量变幅为81.1-94.8 nmol·g^?1,其中盐化旱田>12年果园>稻旱轮作>常年旱田>枸杞园>常年稻田;好氧细菌14:0、16:0和18:0比例最大,革兰氏阳性细菌16:0iso在12年果园、稻旱轮作田中含量显著提高,放线菌次之,而真菌18:3ω6c在12年果园、盐化旱田、稻旱轮作3种利用方式下含量升高。(3)相关分析表明,引黄灌区土壤磷酸脂肪酸与土壤pH、微生物量碳及微生物量磷之间呈极显著正相关,与土壤有机质呈显著正相关;主成分分析表明,盐化旱田和12年果园具有相近的微生物群落结构。(4)综上所述,有机无机配施常年果园和秸秆还田常年旱田是适用于该地区的土地利用与管理方式。     

Multivariate analysis of the mud crab Scylla serrata (Brachyura: Portunidae) from four locations in Southeast Asia

The large, edible mud crab Scylla serrata (Forskål) exhibits different phenotypes which are recognised by the fishermen of Southeast Asia and are given local names such as “white”, “green”, “red” or “black” crabs on the basis of their colouration. A preliminary study using multivariate techniques was undertaken in order to examine the degree of dissimilarity between the different morphs of commercially fished stocks of S. serrata. Twenty-two morphometric and 20 meristic characters were measured on male crabs from four locations in three countries in Southeast Asia, including Surat Thani in Thailand where “black” and “white” morphs exist sympatrically. Canonical variate analysis (CVA) on the morphometric data discriminated three groups with no chain-linking. Surat Thani “white” crabs and those from south Vietnam were phenotypically similar and formed one distinct group; a second group contained crabs from Ranong (Thailand) and Sarawak which were phenotypically “black”; the third group contained “black” crabs from Surat Thani. CVA on meristic data confirmed two groupings, but implied that the Surat Thani “black” morph may only be a variant of the Surat Thani/Vietnam “white” form, rather than a third species. These findings are discussed in relation to the ecology, fishery management and aquaculture potenial of S. serrata.     

Multivariate analysis of spatial patterns: a unified approach to local and global structures

We propose a new approach to the multivariate analysis of data sets with known sampling site spatial positions. A between-sites neighbouring relationship must be derived from site positions and this relationship is introduced into the multivariate analyses through neighbouring weights (number of neighbours at each site) and through the matrix of the neighbouring graph. Eigenvector analysis methods (e.g. principal component analysis, correspondence analysis) can then be used to detect total, local and global structures. The introduction of the D-centring (centring with respect to the neighbouring weights) allows us to write a total variance decomposition into local and global components, and to propose a unified view of several methods. After a brief review of the matrix approach to this problem, we present the results obtained on both simulated and real data sets, showing how spatial structure can be detected and analysed. Freely available computer programs to perform computations and graphical displays are proposed.     

土壤微生物生物量及多样性测定方法评述

土壤微生物作为土壤中重要的分解者,在养分的循环与转化中起着重要的作用。另外,由于其与土壤理化性质相比,对外界环境的变化更为敏感,因此,土壤微生物性质常被用作表征土壤质量的灵敏性指标,而土壤微生物生物量与微生物多样性是土壤微生物学研究中应用最广泛的指标。土壤环境复杂,微生物种类丰富多样,需要合适的研究方法才能真正打开土壤系统这个黑箱,自19世纪60年代以后,土壤微生物学在研究方法上取得了重要的进展,本文综述了微生物生物量及多样性的概念及微生物生物量和多样性研究方法的发展状况,重点就已有应用比较多的研究方法如测定微生物生物量的熏蒸法,测定微生物多样性的平板计数法、Biolog微平板计数法、磷脂脂肪酸法及分子生物学等研究方法进行了详细介绍及优缺点分析。结合现有微生物生物量及多样性的测定方法,在未来的研究中,一方面应该引入更多的新技术,发展新方法,以期探索更多的未知微生物种群;其次应该根据实验要求,完善和改进现有研究方法,使其更为统一和准确;再者,在微生物数据的分析上应该探索和借鉴更多的分析方法和手段,从而更深入更全面的解读实验当中所得到的微生物的信息。     

Direct determination of dichlorvos in water by partial least square-discriminant analysis

This report describes a rapid, onsite method to analyze the dichlorvos pesticide in water. Dichlorvos is a broad-spectrum pesticide that has been used worldwide. As an organophosphorus pesticide, dichlorvos disrupts the nervous system by inhibiting the activity of acetyl cholinesterase. Traditional analysis of dichlorvos by chromatography is time-consuming and environmentally unfriendly. Therefore, rapid, on-site methods to analyze dichlorvos are needed. Here, we used for the first time Fourier transform near infrared spectroscopy combined with partial least square-discriminant analysis to determine the dichlorvos directly in water samples. Results were compared with traditional high-performance liquid chromatography data as reference. We found that over 9,000–8,333?cm^?1, the new method had a good performance with a classification accuracy of 100?% and a correlation coefficient of 0.92 between measured and reference data. The new method can also be used as a “concentration sieve” by setting up different levels of boundary, a parameter of partial least square-discriminant analysis, thus allowing rapid on-site screening.     

土壤变暖对土壤微生物活性的影响

讨论了土壤变暖对土壤微生物活性的影响及其后果。许多研究表明,土壤呼吸与土壤温度呈正相关关系。描述这种关系所用的模式有线性回归分析、Q10关系式、幂关系式、Arrhenius关系式及其它关系式,但这些模式通常都不能准确地估计呼吸率。尽管如此,几乎所有的研究都显示土壤温度强烈地影响土壤微生物活性及呼吸。在一定温度范围内,土壤变暖提高土壤微生物活性及呼吸率。解释这种现象的一种机制是微生物群体组成随温度升高而改变。文章最后指出,为了得出更加明确的结论及更加准确地预测全球变暖对土壤的影响,必须进行更深入地研究。     

Environmetrical interpretation of analytical data of marine organisms from the black sea

The environmetrical analysis of the benthic organisms data set from a Black sea region has revealed new information concerning the chemical content and the bioindicating abilities of polychaeta (Melina palmata), Crustacea (Aspendopsis ostroumovi) and molluscs (Mytilus gallo‐provincialis). The application of various multivariate statistical approaches like cluster and principal component analysis, linear regression and partial least square modeling, source apportioning makes it possible to understand in a better way the properties of the benthic organism as collectors of pollutants in a total and a more specific mode. It is shown that heavily polluted coastal zones are indicated in the same way by all benthic species but some specificity could be detected when moderately polluted zones are considered. In this case polychaeta accumulated preferably Co, Cr, Cu and Pb Crustacea ‐ As, Cd and Ni and molluscs ‐ Zn to a limited extent.

PCA identified three latent factors (“anthropogenic flotation”;, “anthropogenic galvanic”; and “naturally occurring") which explain about 65% of the total variance of the system and determine the data set structure. The source apportioning on the absolute principal component scores proved that none of the metals is quantitatively linked with only one anthropogenic or natural source.

The linear regression and PLS models have indicated that a reliable prognosis of the pollution on some naturally occurring chemical components (e.g. linear regression on Zn for Cr and Ni) or combination of them (PLS modeling on Mn/Zn or on Mn/Zn/Fe for the rest of the pollutants) could be achieved.     

宁夏引黄灌区农田土壤酶活性及其空间变异

采集了同一地点不同土地利用方式,及不同地点不同典型土地利用类型下银川平原的灌淤土样品,在分析了土壤基本理化性质的基础上,用奈氏比色法、苯磷酸二钠比色法和高锰酸钾滴定法,分别测定了宁夏引黄灌区农田不同利用方式下土壤的磷酸酶、脲酶、过氧化氢酶的活性状况,并对土壤酶活性与土壤的基本理化性质的相关性进行了相关分析。结果表明,土地利用方式对三种酶活性有很大的影响。12年果园磷酸酶活性最高,常年旱田脲酶和过氧化氢酶活性最高,而盐化旱田及常年淹水的稻田,三种酶活性都很低。脲酶活性与土壤全氮之间显著正相关,全磷与三种酶活性都极显著相关,三种酶之间达到显著或极显著正相关关系。表明磷酸酶、脲酶和过氧化氢酶活性的大小可以敏感地表征宁夏引黄灌区土壤肥力和生产力的高低。     

Ecotoxicological testing of soil by four bacterial biotests

The objective of this work was threefold. Firstly, this paper intends to introduce four microbial toxicity screening methods (Bacillus subtilis agar diffusion method, Azotobacter agile and Pseudomonas fluorescens dehydrogenase enzyme inhibition tube test, and Photobacterium phosphoreum contact toxicity test) for the investigation of contaminated solid samples such as soil and sediment. Secondly, this work was carried out to prove that both soil characteristics and chemical form of contaminants influence the bioavailability of contaminants and alter the toxicity of soil sample considerably. Thirdly, the sensitivity of the above mentioned four biotests to different contaminants of the soil (heavy metals, organic compounds) was determined and compared. The data evaluation was processed by computer aided statistical methods such as cluster, correlation and principal components analysis by the use of Statgraphics^R.

According to cluster analysis carried out separately for chemical data and biological data, we observed that those samples that have similar chemical composition do not show similar toxicity, which is probably due to different bioavailability of contaminants, the impacts of soil characteristics as well as interaction of contaminants. According to the investigation of sensitivity of the examined four biotests the following conclusion could be drawn: P. phosphoreum and A. agile tests are similar in the sense that they are sensitive to Cu to a large extent and also to PAHs and hydrocarbons (CH) to a lesser extent. B. subtilis test corresponds well with P. fluorescens test method since both tests give good correlation with heavy metals. Neither B. subtilis nor P.fluorescens biotests are sensitive to organic soil contaminants such as PAH and CH.     

Ableitung ökotoxikologisch begründeter Bodenqualitätskriterien am Beispiel Arsen

Background

A vast amount of data on the concentration of substances in soils is being generated in environmental monitoring programmes. This data has to be assessed in terms of effects on terrestrial biota. Benchmarks for such an assessment have been missing up to now. This gap has been filled by the development of a concept for the derivation of ecotoxicologically based soil quality criteria (SQC) and the application of this concept to environmentally relevant substances.

Objectives

The derivation method was applied to arsenic. The derivation process was described in detail from the compilation of data regarding effects on microbial processes, plants, and soil invertebrates to the formulation of a recommendation for an SQC.

Methods

The conceptual framework for the derivation of ecotoxicologically based SQC was developed after reviewing national and international concepts for the assessment of the effects of substances on terrestrial communities. For the assessment of arsenic effects, all relevant biotic processes and trophic levels have been taken into account. Moreover, soil characteristics that may affect the toxicity to biota have been reviewed.

Results

Effects of arsenic on biota may occur at soil background concentrations or slightly above. There are only a few studies in which the influence of soil characteristics, such as soil pH, soil texture, and soil organic carbon, on the effects of arsenic has been investigated systematically. That is why the SQC was oriented on soil background concentrations for sandy soils (5 mg As/kg soil dw). A comparison of the SQC derived in this work with ecotoxicologically based soilquality values from Canada, Denmark, the Netherlands, and the United States shows an average value of 16 mg As/kg, with a range between 5 and 34 mg/kg. The variations in the soil quality values are mainly due to differences in the derivation approaches.

Conclusions and Outlook

The concept applied is considered suitable for the derivation of SQC designed to protect terrestrial communities against direct effects of substances in soils. Therefore, its use is planned to derive SQC for other environmentally relevant substances. In addition to compensation factors, statistical methods should be taken into account to compensate for risks which cannot be quantified. Furthermore, there is the need for an assessment of indirect effects of soil contaminants on birds and mammals.     

Isolation,identification, and the degradation characteristics of a thiobencarb-degrading bacterium Bacillus sp. T2北大核心CSCD

Thiobencarb, a thiocarbamate herbicide, is widely used to control weeds in rice paddies. Screening for highly efficient thiobencarb-degrading bacteria is important for the bioremediation of thiobencarb-contaminated environments. The aim of this study was to isolate and identify highly efficient thiobencarb-degrading bacteria and to identify the degradation pathway and the degrading properties. The thiobencarb-degrading strain was isolated using methods of microbiological acclimation and enrichment and was then identified using a 16S rRNA phylogenetic analysis. The degrading properties of the isolated bacterium were determined by single-factor experiments, and the degradation products were identified using gas chromatography-mass spectrometry (GC-MS). A thiobencarb-degrading strain T2, which can utilize thiobencarb as the sole source of carbon for energy and growth, was isolated from paddy soil. Strain T2 degraded more than 98.3% of 0.4 mmol/L of thiobencarb within 36 h. It was preliminarily identified as Bacillus sp. T2 according to the 16S rRNA gene analysis and from its morphological, physiological, and biochemical characteristics. The metabolic products of the thiobencarb degradation for strain T2 were identified as 4-chlorobenzyl mercaptan, 4-chlorobenzaldehyde, and 4-chlorobenzoic acid by the GC-MS. Based on metabolite identification, it was speculated that thiobencarb degradation in strain T2 was initiated by the hydrolysis of the thioester bond to produce 4-chlorobenzyl mercaptan, which was further oxidized to 4-chlorobenzaldehyde and 4-chlorobenzoic acid. The thiobencarb degradation that was initiated by the hydrolysis of the thioester bond by strain T2 is a new metabolic pathway, which provides valuable research material and reliable experimental data for revealing the metabolic process and mechanism of thiobencarb microbial degradation in soil. The strain Bacillus sp. T2 has a very high degradation efficiency, suggesting it is a good prospect for microbial remediation in thiobencarb-polluted environments. © 2018 Science Press. All rights reserved.