A comparison of univariate and multivariate numerical and graphical techniques for determining inter- and intraspecific feeding relationships in estuarine fish

The advantages and disadvantages of various numerical and graphical techniques for the analysis of inter- and intraspecific feeding relationships of fishes were examined. All methods have been cited in the literature since 1988. The index of preponderance, the resultant index and graphical methods proposed by Costello and Tokeshi were used to illustrate the relative importance of prey species to an individual fish species with no differentiation between size classes. Inter- and intraspecific competition and niche overlap were determined from multivariate analysis [the ordination technique, detrended correspondence analysis, cluster analysis by the Bray-Curtis equation, per cent overlap and two-way indicator species analysis (TWINSPAN)]. The identity of the prey organisms are not lost in the comparisons, and the value of this is determined through comparison with techniques such as Shannon-Wiener which obscure these data. The Shannon-Wiener diversity index was combined with an analysis of 'evenness' to refine the technique further to assess niche breadth, as was the Levins index. The study shows that to give an estimate of competition within the community, it is important to assess the data with respect to seasonal and temporal patterns using multivariate analysis.     

合并与不合并：两个相似性聚类分析方法比较

以山西省4638种昆虫在7个地理小区的分布、内蒙古7766种昆虫在14个地理小区的分布和中国16804属昆虫在67个生态区域的分布3组数据为样本,用传统的层层合并的相似性聚类分析法(SCA)和新的不需合并的多元相似性聚类分析法(MSCA)进行运算分析,对比结果表明,不合并法都能得到既符合统计学逻辑,又符合地理学、生物学逻辑的结果;合并法在参与小区较少时,还能够得到与不合并法类似的结果,随着参与小区的增多,聚类结构发生变化,以致聚类功能彻底丧失.无论两种聚类结果差异大小,其性质都迥然不同:不合并法的相似性系数是固有的、互相独立的、同时存在的,聚类结果是所有小区之间关系亲疏、距离远近的状态;合并法的每个相似性系数都是合并的依据或结果,前一个系数是后一个系数产生的条件,后一个系数是前一个系数消亡的结果,严格按照顺序,当最后一个系数产生时,前面所有系数和所有小区都已不复存在,聚类结果只是记录不断合并、不断消亡的过程.因此在肯定合并法历史价值的同时,认为申效诚等创建的多元相似性系数公式及多元相似性聚类分析法摈弃合并降阶这一产生偏差和错误的根源,能够得出相对客观的聚类结果,是生物地理学研究领域有效的聚类分析工具,必将推动生物地理学定量研究迈入一个新阶段.     

功能性脑成像的多维模式分析方法

利用非侵入式的功能性脑成像记录大脑活动极大地提升了我们对人类认知功能的理解.与此同时,分析成像数据的手段也逐渐从传统的一元方式向更加有效的多元分析转变.在本综述中,特别针对在认知神经科学领域占主导地位的功能性磁共振成像技术,介绍其多元数据分析方法的发展以及这种分析方法的生理学基础和未来发展方向.     

Should ecologists prefer model‐ over distance‐based multivariate methods?

Ecological data sets often record the abundance of species, together with a set of explanatory variables. Multivariate statistical methods are optimal to analyze such data and are thus frequently used in ecology for exploration, visualization, and inference. Most approaches are based on pairwise distance matrices instead of the sites‐by‐species matrix, which stands in stark contrast to univariate statistics, where data models, assuming specific distributions, are the norm. However, through advances in statistical theory and computational power, models for multivariate data have gained traction. Systematic simulation‐based performance evaluations of these methods are important as guides for practitioners but still lacking. Here, we compare two model‐based methods, multivariate generalized linear models (MvGLMs) and constrained quadratic ordination (CQO), with two distance‐based methods, distance‐based redundancy analysis (dbRDA) and canonical correspondence analysis (CCA). We studied the performance of the methods to discriminate between causal variables and noise variables for 190 simulated data sets covering different sample sizes and data distributions. MvGLM and dbRDA differentiated accurately between causal and noise variables. The former had the lowest false‐positive rate (0.008), while the latter had the lowest false‐negative rate (0.027). CQO and CCA had the highest false‐negative rate (0.291) and false‐positive rate (0.256), respectively, where these error rates were typically high for data sets with linear responses. Our study shows that both model‐ and distance‐based methods have their place in the ecologist's statistical toolbox. MvGLM and dbRDA are reliable for analyzing species–environment relations, whereas both CQO and CCA exhibited considerable flaws, especially with linear environmental gradients.     

Multivariate analysis of diatoms and water chemistry in Bolivian saline lakes

Diatom assemblages are described from surface sediments in thirteen salt lakes located in the southern Bolivian Altiplano. Factor analysis of correspondences and cluster analysis are used to classify the diatom assemblages. New methods are proposed to establish the qualitative and quantitative relationships between diatom floras and ecological parameters. Diatom assemblages are linked more to the ionic elements than to the salinity, pH, depth, temperature or elevation. Environmental variables are divided into three modalities which allow considerations of many different variables not under the same units.     

Linear Discriminant Functions and Problems of Hybridization

A discriminant analysis method for frequency data for hybridization based on weighted multivariate analysis of variance is given for allotting an individual to one of groups.     

腕足动物数据库及定量古生物地理学研究——以全球二叠纪Roadian-Wordian期为例

随着古生物原始资料的不断积累,通过建立数据库对化石资料进行搜集和管理已成为一种趋势。丰富的原始数据,使我们进行古生物地理研究,特别是大尺度定量古生物地理研究成为可能。文章从化石数据库的建立开始,详细地介绍一种古生物地理学定量研究的方法。通过对二叠纪Roadian-Wordian期全球381个腕足动物属分布数据的聚类分析,区分出4个腕足动物生物域(北方域、冈瓦纳域、泛大洋域、古赤道域)和9个生物区[东北欧区(Northeast European)、维尔科累马区(Verkolyma)、格兰丁区(Grandian)、华夏区(Cathaysian)、基墨里区(Cim-merian)]、中蒙日区(Sino-Mongolian-Japanese)、泛大洋区(Panthalassan)、西澳区(Westralian)和澳纽区(Aus-trazean),这4个域和9个区的生物地理区系特征与它们当时的古地理位置基本吻合。同时,多维尺度分析表明,与纬度相关的温度梯度是控制腕足动物分布的主要因素,古地理屏障和洋流可能在腕足动物空间分布模式的形成中同样扮演着重要角色。     

Comparative bioacoustics: a roadmap for quantifying and comparing animal sounds across diverse taxa

Animals produce a wide array of sounds with highly variable acoustic structures. It is possible to understand the causes and consequences of this variation across taxa with phylogenetic comparative analyses. Acoustic and evolutionary analyses are rapidly increasing in sophistication such that choosing appropriate acoustic and evolutionary approaches is increasingly difficult. However, the correct choice of analysis can have profound effects on output and evolutionary inferences. Here, we identify and address some of the challenges for this growing field by providing a roadmap for quantifying and comparing sound in a phylogenetic context for researchers with a broad range of scientific backgrounds. Sound, as a continuous, multidimensional trait can be particularly challenging to measure because it can be hard to identify variables that can be compared across taxa and it is also no small feat to process and analyse the resulting high-dimensional acoustic data using approaches that are appropriate for subsequent evolutionary analysis. Additionally, terminological inconsistencies and the role of learning in the development of acoustic traits need to be considered. Phylogenetic comparative analyses also have their own sets of caveats to consider. We provide a set of recommendations for delimiting acoustic signals into discrete, comparable acoustic units. We also present a three-stage workflow for extracting relevant acoustic data, including options for multivariate analyses and dimensionality reduction that is compatible with phylogenetic comparative analysis. We then summarize available phylogenetic comparative approaches and how they have been used in comparative bioacoustics, and address the limitations of comparative analyses with behavioural data. Lastly, we recommend how to apply these methods to acoustic data across a range of study systems. In this way, we provide an integrated framework to aid in quantitative analysis of cross-taxa variation in animal sounds for comparative phylogenetic analysis. In addition, we advocate the standardization of acoustic terminology across disciplines and taxa, adoption of automated methods for acoustic feature extraction, and establishment of strong data archival practices for acoustic recordings and data analyses. Combining such practices with our proposed workflow will greatly advance the reproducibility, biological interpretation, and longevity of comparative bioacoustic studies.     

Use of the canonical discriminant analysis to select SNP markers for bovine breed assignment and traceability purposes

Several market research studies have shown that consumers are primarily concerned with the provenance of the food they eat. Among the available identification methods, only DNA‐based techniques appear able to completely prevent frauds. In this study, a new method to discriminate among different bovine breeds and assign new individuals to groups was developed. Bulls of three cattle breeds farmed in Italy – Holstein, Brown, and Simmental – were genotyped using the 50K SNP Illumina BeadChip. Multivariate canonical discriminant analysis was used to discriminate among breeds, and discriminant analysis (DA) was used to assign new observations. This method was able to completely identify the three groups at chromosome level. Moreover, a genome‐wide analysis developed using 340 linearly independent SNPs yielded a significant separation among groups. Using the reduced set of markers, the DA was able to assign 30 independent individuals to the proper breed. Finally, a set of 48 high discriminant SNPs was selected and used to develop a new run of the analysis. Again, the procedure was able to significantly identify the three breeds and to correctly assign new observations. These results suggest that an assay with the selected 48 SNP could be used to routinely track monobreed products.     

Hypothesis testing in comparative and experimental studies of function-valued traits

Many traits of evolutionary interest, when placed in their developmental, physiological, or environmental contexts, are function-valued. For instance, gene expression during development is typically a function of the age of an organism and physiological processes are often a function of environment. In comparative and experimental studies, a fundamental question is whether the function-valued trait of one group is different from another. To address this question, evolutionary biologists have several statistical methods available. These methods can be classified into one of two types: multivariate and functional. Multivariate methods, including univariate repeated-measures analysis of variance (ANOVA), treat each trait as a finite list of data. Functional methods, such as repeated-measures regression, view the data as a sample of points drawn from an underlying function. A key difference between multivariate and functional methods is that functional methods retain information about the ordering and spacing of a set of data values, information that is discarded by multivariate methods. In this study, we evaluated the importance of that discarded information in statistical analyses of function-valued traits. Our results indicate that functional methods tend to have substantially greater statistical power than multivariate approaches to detect differences in a function-valued trait between groups.     

Analysis of volatile fractions of Schisandra chinensis (Turcz.) Baill. using GC-MS and chemometric resolution

The two-dimensional data obtained from GC-MS has been used qualitatively and quantitatively to determine the components of the volatile fractions of Schisandra chinensis obtained by six different extraction methods. Sub-window factor analysis (SFA) was employed to confirm the identities of components determined in different samples. With the help of SFA, and other chemometric techniques, peak purity in the chromatograms was determined, and overlapping peaks were resolved to yield a pure chromatographic profile and mass spectrum for each component. It is demonstrated that the accuracy of qualitative and quantitative analysis may be greatly enhanced using chemometric resolution methods, such methods being particularly valuable with respect to the analysis of complex samples such as traditional Chinese medicines. It is further demonstrated that different extraction methods give rise to volatile fractions of S. chinensis which differ qualitatively and quantitatively in their composition.     

微生物生态研究中基于BIOLOG方法的数据分析

BIOLOG微平板法作为一种方便快速的微生物检验技术,已广泛应用于环境微生物检测,微生物生态研究等方面,发挥着越来越重要的作用。该方法可以获得关于微生物群落碳源利用能力的大量数据,反映出关于微生物活性的丰富信息。然而大量的数据也对解释和分析提出了挑战,分析了应用于BIOLOG产生数据的统计分析方法,对常用的AWCD值计算,多样性指数计算,主成分分析(PCA),聚类分析,相关、回归等方法深入探讨,阐述各自的功能、不足以及在应用中容易出现的问题。另外也对一些不常见的方法,如非参数多元分析(Non-Parametric version of MANOVA/Permutation version of MANOVA)、动力学参数分析、多元回归树、典范对应分析等也进行了讨论。通过对不同方法应用目标和原理的分析论述了各自优缺点,对微生物研究中基于BIOLOG方法数据分析的选择应用提供参考。     

Process analytical technology case study part I: Feasibility studies for quantitative near-infrared method development

This article is the first of a series of articles detailing the development of near-infrared (NIR) methods for solid-dosage form analysis. Experiments were conducted at the Duquesne University Center for Pharmaceutical Technology to qualify the capabilities of instrumentation and sample handling systems, evaluate the potential effect of one source of a process signature on calibration development, and compare the utility of reflection and transmission data collection methods. A database of 572 production-scale sample spectra was used to evaluate the interbatch spectral variability of samples produced under routine manufacturing conditions. A second database of 540 spectra from samples produced under various compression conditions was analyzed to determine the feasibility of pooling spectral data acquired from samples produced at diverse scales. Instrument qualification tests were performed, and appropriate limits for instrument performance were established. To evaluate the repeatability of the sample positioning system, multiple measurements of a single tablet were collected. With the application of appropriate spectral preprocessing techniques, sample repositioning error was found to be insignificant with respect to NIR analyses of product quality attributes. Sample shielding was demonstrated to be unnecessary for transmission analyses. A process signature was identified in the reflection data. Additional tests demonstrated that the process signature was largely orthogonal to spectral variation because of hardness. Principal component analysis of the compression sample set data demonstrated the potential for quantitative model development. For the data sets studied, reflection analysis was demonstrated to be more robust than transmission analysis. Published: October 6, 2005 The views presented in this article do not necessarily reflect those of the Food and Drug Administration.     

Multivariate Extensions of the Mixed Model for Quantitative Traits

The mixed model for complex segregation analysis of quantitative data from three-generational nuclear families is extended to the multivariate case. Likelihood functions for hypothesis testing are derived for two types of conditional analysis of multiple traits: first when entry to the study depends on the index case's values of all the quantitative traits that are of interest, and second when entry depends on only one trait, but other correlated traits are to be studied simultaneously. Using direct products of covariance matrices, these functions are seen to be direct multivariate equivalence of the univariate functions.     

Taxonomic re-evaluation of the jaguar

The purpose of this report is to re-examine jaguar (Panthera onca) subspecies using morphometric skull characters and multivariate statistical methods to analyze differences. Eleven skull characters used historically to define jaguar subspecies were measured on 170 specimens in U.S. natural history museums. Relationships among the eight recognized subspecies of jaguar were examined. using Multigroup Discriminant Analysis (MDA) and univarite statistics. Discriminant analyses of these skull characteristics does not indicate distinct groups, supporting the null hypothesis. This analysis was conducted to add to systematic studies such as DNA analysis to assist the Felid Taxon Advisory Group (Felid TAG) and the American Zoo and Aquarium Association (AZA) establish valid taxonomic differences in the jaguar. Zoo Biol 16:107–120, 1997. © 1997 Wiley-Liss, Inc.     

乌鲁木齐南部山区森林生态系统树生地衣群落结构

为了探明乌鲁木齐南部山区树生地衣种类及其群落结构特征,应用多元分析中的主成分分析及聚类分析方法,对分布在乌鲁木齐南部山区森林生态系统中的树生地衣植物群落进行数量分类,并对其群落结构的物种多样性、相似性和均匀度等群落参数进行了比较系统的研究。结果表明,分布在乌鲁木齐南部山区的树生地衣共有39种,隶属于5目13科26属。根据多元分析结果,将该地区的树生地衣划分为3种类型：（1）小茶渍（Lecanorahageni（Ach．）Ach．）＋蜈蚣衣（肋归ciastellaris（L．）Nyl．）＋柳茶渍（￡-。saligna（Schrad．）Zahlbr．）群落;（2）斑面蜈蚣衣（Physciaaipolia（Humb．）Furm．）＋对开蜈蚣衣（Ph．dimidiata（Arn．）Nyl．）＋喇叭石蕊（Cladoniapyxidata（L．）Hoffm．）群落：（3）拟石黄衣（Xanthoria fallax（Hepp）Arnold．）＋丽石黄衣（xelegans（Link．）Th．Fr．）群落。群落3的多样性指数最大,为1．509,其次为群落2,其多样性指数为1．109,群落1的多样性指数最低,为1．088。同时,研究发现海拔高度和树种是影响乌鲁木齐南部山区森林生态系统树生地衣结构的两个重要因素。     

Q-mode regression analysis applied to predict the antidotal action of bispyridinium oximes in intoxications with organophosphorus poisons

There are some serious pitfalls if the usual multiple and multivariate regression analysis are applied to correlate the biological activity of compounds against parameters describing the chemical molecule structure if the observations consist of an inhomogeneous data set. By contrast to the more known methods of cluster analysis, it must be required that a partition into homogeneous groups is possible and, in addition, that the members inside any group are normally distributed. The principle of the Q-mode regression analysis dealing with that problem is exemplified on the antidotal action of bispyridinium oximes in intoxication with organophosphorus poisons (soman, tabun, sarin, VX).     

Universal biases in protein composition of model prokaryotes

The levels of cellular organization in living organisms are the results of a variety of selection pressures. We have investigated here the final outcome of this integrated selective process in proteins of the best known microbial models Escherichia coli, Bacillus subtilis, and Methanococcus jannaschii, supposed to have undergone separate evolution for more than 1 billion years. Using multivariate analysis methods, including correspondence analysis, we studied the overall amino acid composition of all proteins making a proteome. Starting from and further developing previous results that had pointed out some general forces driving the amino acid composition of the proteomes of these model bacteria, we explored the correlations existing between the structure and functions of the proteins forming a proteome and their amino acid composition. The electric charge of amino acids measured against hydrophobicity creates a highly homogeneous cluster, made exclusively of proteins that are core components of the cytoplasmic membrane of the cell (integral inner membrane proteins). A second bias is imposed by the G+C content of the genome, indicating that protein functions are so robust with respect to amino acid changes that they can accommodate a large shift in the nucleotide content of the genome. A remarkable role of aromatic amino acids was uncovered. Expressed orphan proteins are enriched in these residues, suggesting that they might participate in a process of gain of function during evolution.