Principal components method and nonmetric two-dimensional scaling method for quantitative dermatoglyphic traits of the taimir aborigines

The quantitative dermatoglyphic traits of the Taimir aborigines have been studied in this paper. The correlation matrix of the traits was analyzed by a nonmetric two-dimensional scaling method and by a principal components method. Comparative contribution of palmar and digital traits variation to the principal components is under discussion.     

Extended dissimilarity: a method of robust estimation of ecological distances from high beta diversity data

It is widely accepted that reliable ordination of ecological data requires a strong linear or ordinal relationship between the dissimilarity of sites, based on species composition, and the ecological distance between them. Certain dissimilarity measures, having the property that they take a fixed maximum value when sites have no species in common, have been shown to be strongly correlated with ecological distance. For ecological gradients of moderate length (moderate beta diversity), such measures, in conjunction with non-metric multidimensional scaling, will reliably yield successful ordinations. However, as beta diversity increases, more sites have no species in common, and such measures invariably under-estimate ecological distance for such sites. Thus ordinations of data with high species turnover (high beta diversity) may fail.Extended dissimilarities are defined using an iterative adaptation of flexible shortest path adjustment applied to the matrix of dissimilarities with fixed maximum values. By means of theoretical argument and simulations, this is shown to lead to far stronger correlations between the adjusted site dissimilarity and ecological distance for ecological gradients of greater length than previously considered. Hence ordinations of extended dissimilarities, by means of either metric or non-metric scaling techniques, are shown to outperform corresponding ordinations of unadjusted dissimilarities, with the difference increasing with increasing beta diversity.     

Pluralism and diversity: trends in the use and application of ordination methods 1990‐2007

Question: What are the trends and patterns in the application of ordination techniques in vegetation science since 1990? Location: Worldwide literature analysis. Methods: Evaluation of five major journals of vegetation science; search of all ISI‐listed ecological journals. Data were analysed with ANCOVAs, Spearman rank correlations, GLMs, biodiversity indices and simple graphs. Results: The ISI search retrieved fewer papers that used ordinations than the manual evaluation of five selected journals. Both retrieval methods revealed a clear trend in increasing frequency of ordination applications from 1990 to the present. Canonical Correspondence Analysis was far more frequently detected by the ISI search than any other method. Applications such as Correspondence Analysis/Reciprocal Averaging and Detrended Correspondence Analysis have increasingly been used in studies published in “applied” journals, while Canonical Correspondence Analysis, Redundancy Analysis and Non‐Metric Multidimensional Scaling were more frequently used in journals focusing on more “basic” research. Overall, Detrended Correspondence Analysis was the most commonly applied method within the five major journals, although the number of publications slightly decreased over time. Use of Non‐Metric Multidimensional Scaling has increased over the last 10 years. Conclusion: The availability of suitable software packages has facilitated the application of certain techniques such as Non‐Metric Multidimensional Scaling. However, choices of ordination techniques are currently less driven by the constraints imposed by the software; there is also limited evidence that the choice of methods follows social considerations such as the need to use fashionable methods. Methodological diversity has been maintained or has even increased over time and reflects the researcher's need for diverse analytical tools suitable to address a wide range of questions.     

Scaling of metabolic rate in the lesser wax moth Achroia grisella does not fit the 3/4‐power law and shows significant sex differences

Allometric scaling of metabolic rates is commonly described as a power function and 0.75 is a widely accepted exponent. The universality of this exponent is in doubt and, particularly for insects, contradictory results have been obtained. Furthermore, sexual differences in scaling exponents are observed for several species that could lead to artefacts when they are not considered in intra‐ and interspecific scaling. Whether the metabolic scaling exponent in the lesser wax moth Achroia grisella differs significantly from 0.75 is tested, as well as whether it differs between the sexes. Adults of this moth neither feed nor drink, rendering them as suitable subjects for a study of metabolic rates. Neglecting sex differences, a metabolic scaling exponent of 0.8 is recorded. However, there are significant differences in metabolic scaling between the sexes. When considered separately, males scale with 0.96 and females with 0.67. Thus, in this species, a scaling exponent of 0.75 does not appear to exist either for males or females. The body size optimization model offers a potential explanation for the sex differences in metabolic scaling, although it remains to be tested in wax moths. With insects in particular, there is the need for more detailed studies on the scaling of metabolic rates that also take sexual differences into account.     

The bootstrapped ordination re-examined

Abstract. A method is described to determine the number of significant dimensions in metric ordination of a sample. The method is probabilistic, based on bootstrap resampling. An iterative algorithm takes bootstrap samples with replacement from the sample. It finds in each bootstrap sample ordination coordinates and computes, after Procrustean adjustments, the correlation between observed and bootstrap ordination scores. It compares this correlation to the same parameter generated in a parallel bootstrapped ordination of randomly permuted data, which upon many iterations will generate a probability. The method is assessed in principal coordinates analysis of simulated data sets that have varying number of variables and correlation levels, uniform or patterned correlation structure. The results suggest the method is more reliable than other available methods in recovering the true intrinsic dimensionality. Examples with grassland data illustrate utility.     

生态学中的尺度问题——尺度上推

尺度推绎是生态学理论和应用的核心。如何在一个异质景观中进行尺度推绎仍然是一个悬而未决的科学难题,是对当今生态学家在全球变化背景下研究环境问题的重大挑战。就目前的研究,一般可分为四大类尺度推绎途径:空间分析法(如分维分析法和小波分析法)、基于相似性的尺度上推方法、基于局域动态模型的尺度上推方法、随机(模型)法。基于相似性的尺度上推方法来源于生物学上的异量关联,可将其思想延伸至空间上,研究物种丰富度、自然河网、地形特征、生态学格局或过程变量和景观指数等。基于局域动态模型的尺度上推方法需要首先确定是否进行跨尺度推绎,以及是否考虑空间单元之间的水平相互作用和反馈,然后再应用具体的方法或途径,如简单聚合法、有效值外推法、直接外推法、期望值外推、显式积分法和空间相互作用模拟法等。随机(模型)法以其它尺度上推方法为基础,根据研究的是单个景观,还是多个景观,采用不同的途径。理解、定量和降低尺度推绎结果的不确定性已经变得越来越重要,但相关研究仍然极少。以上所有有关尺度推绎的方法、途径和结果分析共同构成了尺度推绎的概念框架。