自我重复取样技术与多项式定理在年龄-龄期两性生命表研究中的应用

年龄-龄期两性生命表(age-stage, two-sex life table)简称两性生命表,是种群生态学研究与害虫治理中常用的重要理论与分析工具。根据两性生命表理论而设计的方便用户的软件TWOSEX-MSChart近年来被越来越多国内外学者用于昆虫种群研究的数据分析。两性生命表软件的分析功能是由许多的统计技术与计算机模拟方法作为数据分析的支撑,其中自我重复取样(bootstrap)是其重要技术之一。本文详述了bootstrap技术的基本原理、方法、优缺点及其在两性生命表分析中的应用,并介绍了其理论基础多项式定理(multinomial theorem)在生命表研究中的应用。与常用统计方法相比,bootstrap不需要数据分布假设就可以对数据总体的分布特性进行统计和推断。在两性生命表分析中,bootstrap不仅可以估算种群参数或一般统计值的方差和标准误,同时利用paired bootstrap test还可以比较不同处理间的差异,准确显示种群的变异性。利用相同的自我重复取样样本(same bootstrap samples)可以正确计算昆虫的孵化率与不同繁殖型对种群参数的贡献,并...     

Misconceptions about the comparison of intrinsic rates of natural increase

The intrinsic rate of natural increase (r_m) is a common measurement in entomology to describe and evaluate the growth and adaptation of a population of arthropods to certain environmental conditions. Following the method of Birch, the r_m is the solution of an exponential equation, which depends on the whole life cycle of each female and her survival time. A simplification of this equation was provided by Wyatt and White, which allows the study to be shortened as it does not depend on any survival times and only a part of the life cycle of the females. Therefore, this method has become quite popular among entomologists. As the r_m is a population parameter, it lacks any variance and thus a valid statistical comparison of r_ms for different populations is not straightforward. Hence, many approaches include statistical misconceptions. We discuss those approaches, apply them to real data and demonstrate some drawbacks of them. Furthermore, we present an easy to implement and consistent method for the comparison of r_ms.     

USING PARTITIONED MAHALANOBIS D2(K) TO FORMULATE A GIS-BASED MODEL OF TIMBER RATTLESNAKE HIBERNACULA

Abstract: Mahalanobis Distance (D²) Statistic is a multivariate statistical method that has been used to model habitats occupied by wildlife and plant species. The output, whether standardized squared distance or probability values, represents the similarity of a given set of values with those of an optimum habitat configuration defined exclusively by sites where the species of interest is known to occur. Typically, all principal components with nonzero eigenvalues are used to calculate D² values. We partitioned D² into contributions from individual principal components (PCs) and selected PCs corresponding to relatively invariant aspects of the environment across all use sites to formulate D²(k). Partitioned Mahalanobis D²(k) represents the similarity of a given set of values with those of “minimum” habitat requirements of the species as defined by occupied sites using the k subset of principal components. We created a GIS-based model of the habitat surrounding 39 confirmed timber rattlesnake hibernacula on the Madison County Wildlife Management Area in northwest Arkansas, USA, using slope, aspect, elevation, and 11 physical soil attributes. We retained 4 of 15 principal components in D²(k = 4) calculations, and minimum habitat requirements corresponded to a combination of moderate slope, south to southwest facing slopes, and medium to high elevations. We used bootstrap and cross-validation techniques to examine the stability of the correlation matrix and the effect of each site on overall D²(k) values. The D²(k = 4) model specifically highlighted habitats similar to known rattlesnake hibernacula. We present a method to translate the probability surface into a qualitative data layer useful in making management decisions by examining the cumulative distributions of the percentages of (1) hibernacula correctly classified and (2) the study area predicted. We selected the probability threshold that maximized the predictive gain by including the greatest number of hibernacula in the smallest area. The probability threshold 0.2 captured 82% of the known hibernacula in 25% of the 5,666-ha study area. Partitioned Mahalanobis D²(k) requires only data for where species are known to occur, thus circumventing costly errors in misclassifying habitat use with commonly used classification algorithms that require dichotomous data sets.     

Influence of nucleotide identity on ribose 2′-hydroxyl reactivity in RNA

Hydroxyl-selective electrophiles, including N-methylisatoic anhydride (NMIA) and 1-methyl-7-nitroisatoic anhydride (1M7), are broadly useful for RNA structure analysis because they react preferentially with the ribose 2′-OH group at conformationally unconstrained or flexible nucleotides. Each nucleotide in an RNA has the potential to form an adduct with these reagents to yield a comprehensive, nucleotide-resolution, view of RNA structure. However, it is possible that factors other than local structure modulate reactivity. To evaluate the influence of base identity on the intrinsic reactivity of each nucleotide, we analyze NMIA and 1M7 reactivity using four distinct RNAs, under both native and denaturing conditions. We show that guanosine and adenosine residues have identical intrinsic 2′-hydroxyl reactivities at pH 8.0 and are 1.4 and 1.7 times more reactive than uridine and cytidine, respectively. These subtle, but statistically significant, differences do not impact the ability of selective 2′-hydroxyl acylation analyzed by primer extension-based (SHAPE) methods to establish an RNA secondary structure or monitor RNA folding in solution because base-specific influences are much smaller than the reactivity differences between paired and unpaired nucleotides.