贵州剑河寒武系苗岭统凯里组太阳女神螺类几何形态学研究*

太阳女神螺类(helcionellids)是寒武纪常见的一类软体动物,广布全球,多见于碳酸盐岩沉积地层中,而布尔吉斯页岩型生物群中却少有报道。贵州剑河凯里生物群是典型的特异埋藏化石库,产有700余件太阳女神螺类标本,这在世界各地同时期的布尔吉斯页岩型生物群中是很少见的。本文对贵州剑河八郎寒武系凯里组太阳女神螺类化石标本进行了系统研究,采用几何形态测量学的典型变量分析进行量化分析。几何形态测量学(Geometric morphometrics)是用界标点或轮廓线等来描绘生物的形态或者标记特征部位及器官,将生物形态特征归纳为数据变化的定量学方法,其中的典型变量分析(Canonical Variate Analysis)是多变量分析中进行判别分析的一个重要方法,可以用于多组数据之间的判别。CVA判别结果显示:利用壳体侧视轮廓线判别Dorispira属中三个种的正确率为92%,验证了Dorispira accordinonata、D.taijiangensis和D.cf.pearylandica化石种分类合理性。本文研究表明即使壳体形态较为相似的类群,也可以较为准确地使用CVA量化其中的差别,...     

Shape disparity of bovid (Mammalia,Artiodactyla) horn sheaths and horn cores allows discrimination by species in 3D geometric morphometric analyses

The bony cranial structures of even‐toed hoofed mammals are important for understanding ecology and behavior of ruminants. Horns, the cranial appendages of the family Bovidae, are covered in a layer of keratin that is often not preserved in the fossil record; however, this keratin sheath is intimately involved in the processes that influence horn shape evolution. To understand the relationship between these two components of horns, we quantified both core and sheath shape for four extant species using three‐dimensional geometric morphometric analyses in separate, core‐ and sheath‐specific morphospaces as well as a combined morphospace. We assessed correlations between the horn and sheath morphospaces using two‐block partial least squares regression, a Mantel test of pairwise distances between species, and Procrustes ANOVA. We measured disparity in the combined morphospace as Procrustes distances between mean shapes of cores and sheaths within and between species and as Procrustes variance. We also tested whether core and sheath shapes could be discriminated by taxon with a canonical variate analysis. Results show that horn core and sheath morphospaces are strongly correlated. The differences in shape between a species' core and sheath were statistically significant, but not as great as those between the cores and sheaths of different species when close relatives were not considered, and core and sheath Procrustes variances are not significantly different within species. Cores and sheath shapes were highly identifiable and were assigned to the correct clade 93% of the time in the canonical variate analysis. Based on these tests, horn cores are distinguishable in geometric morphometric analyses, extending the possibility of using geometric morphometrics to study the ecology and evolution of bovid horns to the fossil record.     

Multivariate Approach for Studying Interactions between Environmental Variables and Microbial Communities

To understand the role of human microbiota in health and disease, we need to study effects of environmental and other epidemiological variables on the composition of microbial communities. The composition of a microbial community may depend on multiple factors simultaneously. Therefore we need multivariate methods for detecting, analyzing and visualizing the interactions between environmental variables and microbial communities. We provide two different approaches for multivariate analysis of these complex combined datasets: (i) We select variables that correlate with overall microbiota composition and microbiota members that correlate with the metadata using canonical correlation analysis, determine independency of the observed correlations in a multivariate regression analysis, and visualize the effect size and direction of the observed correlations using heatmaps; (ii) We select variables and microbiota members using univariate or bivariate regression analysis, followed by multivariate regression analysis, and visualize the effect size and direction of the observed correlations using heatmaps. We illustrate the results of both approaches using a dataset containing respiratory microbiota composition and accompanying metadata. The two different approaches provide slightly different results; with approach (i) using canonical correlation analysis to select determinants and microbiota members detecting fewer and stronger correlations only and approach (ii) using univariate or bivariate analyses to select determinants and microbiota members detecting a similar but broader pattern of correlations. The proposed approaches both detect and visualize independent correlations between multiple environmental variables and members of the microbial community. Depending on the size of the datasets and the hypothesis tested one can select the method of preference.     

Spatial analysis of two-species interactions

Summary In this paper, I present and discuss some methods for the analysis of univariate and bivariate spatial point pattern data. Examples of such data in ecology include x-y coordinates of organisms in mapped field plots. I illustrate the methods with analyses of data from mapped field plots on Mount St. Helens, Washington state, USA. The statistical methods I emphasize are graphical methods that rely on analysis of distances between organisms. Hypothesis testing for methods like these is easily done using Monte Carlo methods, which I also discuss. For both univariate and bivariate analyses, I find that second-order methods such as K-function plots are often preferable to first-order methods (i.e., QQ-plots). However, for multivariate analyses, these second-order methods are more sensitive to small sample sizes than first-order analyses.     

Wing morphometric analysis of Australian Sarcophaginae (Diptera: Sarcophagidae)

Phenetic affinities of thirty-two species of Australian Sarcophaginae are described. A set of wing morphometric characters was analysed using canonical variate analysis and clustering of generalized distances. The results were compared to classifications of Roback (1954) and to that of Souza Lopes (1954, 1958a, b, 1959). There was substantially more agreement with the classification of Roback than with that of Souza Lopes. Thus the subfamily appears to consist of a reduced number of minor genera (Heteronychia, Blaesoxipha, Tricharaea and possibly Sarcosolomonia/Fergusonimyia) and a large complex consisting of species of Sarcophaga sensu lato.     

A multivariate analysis of geographic variation in morphology inPersoonia mollis (Proteaceae)

This study highlights the utility and limitations of multivariate procedures for the analysis and taxonomic interpretation of geographic variation within a complex species. Morphological data from herbarium specimens ofPersoonia mollis (Proteceae) were analyzed by two ordination procedures, multidimensional scaling (MDS) and canonical variate analysis (CVA). Support for the earlier recognition of nine infraspecific taxa was found. However, plots of canonical variate scores against latitute or longitude across parapatric subspecies boundaries revealed unexpected phenetic homogeneity within subspecies with sharp transitions between subspecies. The geographic variation in morphology withinP. mollis can be best described as a mosaic of nine recognisably distinct and internally homogeneous allopatric or parapatric taxa, where neighbouring taxa share surprisingly narrow zones of morphological transition at ecotones. The utility of these procedures was highlighted by the recovery of unexpected patterns of variation. However, questions of rank remain unresolved by phenetic analysis alone.     

Nonignorable missingness in matched case-control data analyses

Matched case-control data analysis is often challenged by a missing covariate problem, the mishandling of which could cause bias or inefficiency. Satten and Carroll (2000, Biometrics56, 384-388) and other authors have proposed methods to handle missing covariates when the probability of missingness depends on the observed data, i.e., when data are missing at random. In this article, we propose a conditional likelihood method to handle the case when the probability of missingness depends on the unobserved covariate, i.e., when data are nonignorably missing. When the missing covariate is binary, the proposed method can be implemented using standard software. Using the Northern Manhattan Stroke Study data, we illustrate the method and discuss how sensitivity analysis can be conducted.     

The Neanderthal taxonomic position: models of intra- and inter-specific craniofacial variation

The Neanderthal taxonomic position is a matter of wide disagreement among paleoanthropologists. Some workers consider this fossil human group to represent a different species, Homo neanderthalensis, while others see it as a subspecies of Homo sapiens. This study developed two models of morphological variation to be applied to a comparison between Neanderthals and modern humans: modern human populations provided a measure of intra-specific variation, while the species and subspecies of Pan provided measures of both intra- and inter-specific morphological differences. Although such an approach has been advocated strongly, it has not been systematically undertaken until recently. The techniques of geometric morphometrics were used to collect data in the form of three-dimensional coordinates of craniofacial landmarks. The data were processed using generalized procrustes analysis, and analyzed by an array of multivariate statistical methods, including principal components analysis, canonical variates analysis and Mahalanobis D(2). The morphological distances between Neanderthals and modern humans, and between Neanderthals and Late Paleolithic/early anatomically modern specimens, are consistently greater than the distances among recent human populations, and greater than the distances between the two chimpanzee species. Furthermore, no strong morphological similarities were found between Neanderthals and Late Paleolithic Europeans. This study does not find evidence for Neanderthal contribution to the evolution of modern Europeans. Results are consistent with the recognition of Neanderthals as a distinct species.     

Quantitative analysis of Neanderthal temporal bone morphology using three-dimensional geometric morphometrics

The temporal bone is the location of several traits thought to differentiate Neanderthals from modern humans, including some proposed Neanderthal-derived traits. Most of these, however, are difficult to measure and are usually described qualitatively. This study applied the techniques of geometric morphometrics to the complex morphology of the temporal bone, in order to quantify the differences observed between Neanderthal and modern human anatomy. Two hundred and seventy modern human crania were measured, representing 9 populations of 30 individuals each, and spanning the extremes of the modern human geographical range. Twelve Neanderthal specimens, as well as Reilingen, Kabwe, Skhul 5, Qafzeh 9, and 4 Late Paleolithic European specimens, were included in the fossil sample. The data were collected in the form of three-dimensional (3-D) landmark coordinates, and specimen configurations were superimposed using generalized Procrustes analysis. The fitted coordinates were then analyzed by an array of multivariate statistical methods, including principal components analysis, canonical variates analysis, and Mahalanobis D(2). The temporal bone landmark analysis was very successful in separating Neanderthals from modern humans. Neanderthals were separated from modern humans in both the principal components and canonical variates analyses. They were much further in Mahalanobis distances from all modern human populations than any two modern human groups were from each other. Most of the previously described temporal bone traits contributed to this separation.     

Some African fossil foot bones: a note on the interpolation of fossils into a matrix of extant species

Certain fossil foot bones (a terminal toe phalanx from Olduvai, specimens of tali from Spy, Skhūl, Olduvai, Kromdraai, Songhor and Rusinga) have been investigated by other workers using the multivariate statistical approach. The conclusions of their studies have, in the main, been based upon examination of early canonical variates alone. It is demonstrated here that if the full analyses (generalized distances) are taken into account, then almost exactly opposite conclusions obtain. The terminal toe phalanx from Olduvai is widely different from those of modern men; the Neandertal tali differ more from modern human bones than previously realized; the specimens from Olduvai, Kromdraai, Songhor and Rusinga are all completely dissimilar from both African ape and modern human tali.     

Reexamining Sample Size Requirements for Multivariate,Abundance-Based Community Research: When Resources are Limited,the Research Does Not Have to Be

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.     

Multipoint Genetic Mapping with Trisomy Data

Trisomy is the most common genetic abnormality in humans and is the leading cause of mental retardation. Although molecular studies that use a large number of highly polymorphic markers have been undertaken to understand the recombination patterns for chromosome abnormalities, there is a lack of multilocus approaches to incorporating crossover interference in the analysis of human trisomy data. In the present article, we develop two statistical methods that simultaneously use all genetic information in trisomy data. The first approach relies on a general relationship between multilocus trisomy probabilities and multilocus ordered-tetrad probabilities. Under the assumption that no more than one chiasma exists in each marker interval, we describe how to use the expectation-maximization algorithm to examine the probability distribution of the recombination events underlying meioses that lead to trisomy. One limitation of the first approach is that the amount of computation increases exponentially with the number of markers. The second approach models the crossover process as a chi(2) model. We describe how to use hidden Markov models to evaluate multilocus trisomy probabilities. Our methods are applicable when both parents are available or when only the nondisjoining parent is available. For both methods, genetic distances among a set of markers can be estimated and the pattern of overall chiasma distribution can be inspected for differences in recombination between meioses exhibiting trisomy and normal meioses. We illustrate the proposed approaches through their application to a set of trisomy 21 data.     

Multivariate analysis of hematological and serum biochemical values in female cynomolgus monkeys (Macaca fascicularis) aged less than a year

Hematological and serum biochemical data obtained from 91 laboratory-bred cynomolgus monkeys (Macaca fascicularis) aged 11 to 362 days were analyzed by the discriminant analysis. All animals used had been bred and reared under uniform environmental conditions at Tsukuba Primate Center for Medical Science, N. I. H., Japan. The examination items were as follows: red blood cell count (RBC), hematocrit value (Ht), hemoglobin concentration (Hb), mean corpuscular volume (MCV), white blood cell count (WBC), glutamic oxaloacetic transaminase activity (GOT), glutamic pyruvic transaminase activity (GPT), total protein concentration (TP), albumin concentration (ALB), albumin-globulin ratio (A/G), blood urea nitrogen (BUN), glucose concentration (GLU), total cholesterol concentration (TCHO), free cholesterol concentration (FCHO), triglyceride concentration (TG), alkaline phosphatase activity (ALP) and calcium concentration (Ca). The animals were divided into four groups (A: Suckling infants, less than 176 days old. B, C, D: Weanlings and juveniles, 121 to 220 days old, 221 to 280 days old, and 281 to 362 days old, respectively). Discrimination was possible among these four groups on the basis of the Mahalanobis' generalized distance. Regarding the canonical discriminant analysis (discriminant analysis with reduction of dimensionality), discrimination was possible. The suckling infant group could be discriminated from the juvenile groups by the first canonical variate. Concerning the juvenile groups, age was highly correlated to the value of the second canonical variate.2+ Judging from an approximate relative eigenvector value for the second canonical variate, the effective discriminant variables were WBC, TP, ALB, A/G, FCHO, TG, and ALP. It can be concluded that these eight parameters are important and useful for monitoring the physiologicals conditions of growing juvenile monkeys.     

Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari,Hydrachnidia, Arrenuridae)

Geometric and traditional morphometric approaches are tested to describe and reveal taxonomic characters and character states in variation of shape and size of idiosoma morphology in the Arrenuridae. Patterns of variation of idiosoma and glandularia features of males from 11 Mexican species of Arrenurus (Megaluracarus) and two species of subgenus Dadayella were explored with five landmark configurations and three sets of interlandmark distances. Separate principal component analyses (PCA) and canonical variate analyses (CVA) were performed for each data set. The eight multivariate analyses of variance among 13 a priori groups (species) detected significantly different morphometric variants, which were interpreted as different taxonomic character states. Patterns of character state similarity among species were examined with unweighted‐pair grouping method using averages (UPGMA) cluster analyses on Mahalanobis distances. Analyses of five landmark configurations revealed important taxonomical variation in the anterior idiosoma outline (10 character states), the outline of the posterior region or cauda (13 states), the distribution of postocularia, and the second and third pairs of dorsoglandularia (nine states), the fourth pair of dorsoglandularia (three states), and ventroglandularia on the posterior side of idiosoma (nine character states). Multivariate analyses of three sets of distance measurements also resulted in the detection of potential taxonomic characters related to idiosoma size (12 character states), postocularia and dorsoglandularia (13 states), and ventroglandularia (nine character states). Morphometric analyses of distances and shapes provide a formal basis for the interpretation of taxonomic characters, and for the discovery of character states. These characters should be investigated further in a wider sample of species for the phylogenetic systematics of these water mites. In the meantime, idiosoma regions and structures were tested for congruence in a phylogenetic analysis, and were proposed as homologous among the species sampled.     

The frequency distribution of gene family sizes in complete genomes

We compare the frequency distribution of gene family sizes in the complete genomes of six bacteria (Escherichia coli, Haemophilus influenzae, Helicobacter pylori, Mycoplasma genitalium, Mycoplasma pneumoniae, and Synechocystis sp. PCC6803), two Archaea (Methanococcus jannaschii and Methanobacterium thermoautotrophicum), one eukaryote (Saccharomyces cerevisiae), the vaccinia virus, and the bacteriophage T4. The sizes of the gene families versus their frequencies show power- law distributions that tend to become flatter (have a larger exponent) as the number of genes in the genome increases. Power-law distributions generally occur as the limit distribution of a multiplicative stochastic process with a boundary constraint. We discuss various models that can account for a multiplicative process determining the sizes of gene families in the genome. In particular, we argue that, in order to explain the observed distributions, gene families have to behave in a coherent fashion within the genome; i.e., the probabilities of duplications of genes within a gene family are not independent of each other. Likewise, the probabilities of deletions of genes within a gene family are not independent of each other.      

基于GC-MS的异翅亚目臭腺分泌物化学分类学分析

【目的】探讨异翅亚目(Heteroptera)昆虫不同类群间臭腺分泌物化学组分的差异,为该类昆虫寻找新的分类特征并为各类群间的相互关系提供新的证据。【方法】我们采用固相微萃取(solid phase microextraction, SPME)偶联气相色谱-质谱仪(GC-MS)对采自中国的异翅亚目8个总科32个种的臭腺分泌物进行了测定分析;采用典型判别分析法、非参数多元方差分析法、典型变量分析法进行了高级阶元分泌物的化学分类学分析。【结果】典型判别分析结果表明,异翅亚目,尤其是蝽次目中不同总科间的臭腺分泌物具显著差异性,可作为总科间的分类特征;非参数多元方差分析结果支持臭腺分泌物在总科间的显著差异性;结合典型判别分析结果和典型变量分析的结果找到划分异翅亚目8个总科32个种的主要特征性化合物有6类共30种,包括酸类［己酸(hexanoic acid)、丁酸(butanoic acid)、2-己烯酸(2-hexenoic acid)］,醇类｛2-丁基-1-辛醇(2-butyl-octan-1-ol)、2-己基-1-辛醇(2-hexyl-octan-1-ol)、2-己炔-1-醇(2-hexyn-1-ol)、3,7-二甲基-2-辛烯-1-醇(3,7-dimethyl-2-octen-1-ol)、4,8-二甲基-1-壬醇(4,8-dimethyl-1-nonanol)、2-癸烯-1-醇(2-decen-1-ol)、1-己醇(1-hexanol)、高蒎醇(cis-pinene hydrate)、2-茨醇(borneol)、冰片(2-bornanol)、丙二醇甲醚(1-methoxy-propan-2-ol)、2-乙基1-己醇(2-ethyl-hexan-1-ol)、(6Z, 9Z)-十五烷-1-醇［(6Z, 9Z)-pentadecadien-1-ol］、(E)-9-十六碳烯-1-醇［(E)-9-hexadecen-1-ol］、(S)-3-乙基-4-甲基-1-戊醇［(S)-3-ethyl-4-methyl-pentan-1-ol］、异葑醇(isofenchol)、斯巴醇(spathulenol)｝,醛类｛(E)-2-辛烯醛［(E)-2-octenal］、十二醛(dodecanal)、(Z)-3-己烯醛［(Z)-3-hexenal］、(E)-2-癸烯醛［(E)-2-decenal］、(E, E)-2,4-癸二烯醛［(E, E)-2,4-decadienal］｝,烷类［2-甲基己烷(2-methyl-hexane)、2,21-二甲基二十二烷(2,21-dimethyl-docosane)］,环类［糠醛(furfural)］和萜类［二氢香芹醇(neodihydrocarveol)、二氢松油醇(dihydroterpineol)］。【结论】本研究从异翅亚目8个总科32个物种臭腺分泌物中鉴定的30种特征性化合物在一定程度上可作为异翅亚目总科级阶元的分类特征并为其相互关系提供依据。