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      Nebria (Pseudonebriola) tsambagarav sp. nov., a new alpine species from the Mongolian Altai (Coleoptera, Carabidae)

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      Alpine Entomology
      Pensoft Publishers

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          Abstract

          Nebria (Pseudonebriola) tsambagarav sp. nov. is described from an alpine altitude in the Mongolian Altai. The new species is separated from other two Pseudonebriola species from the Mongolian Altai Mountain range, N. kerzhneri and N. medvedevi, by morphometric and morphological analyses. The new species and its habitat are illustrated, the subgeneric key is amended, and a distribution map is given.

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          Analysis of Ratios in Multivariate Morphometry

          The analysis of ratios of body measurements is deeply ingrained in the taxonomic literature. Whether for plants or animals, certain ratios are commonly indicated in identification keys, diagnoses, and descriptions. They often provide the only means for separation of cryptic species that mostly lack distinguishing qualitative characters. Additionally, they provide an obvious way to study differences in body proportions, as ratios reflect geometric shape differences. However, when it comes to multivariate analysis of body measurements, for instance, with linear discriminant analysis (LDA) or principal component analysis (PCA), interpretation using body ratios is difficult. Both techniques are commonly applied for separating similar taxa or for exploring the structure of variation, respectively, and require standardized raw or log-transformed variables as input. Here, we develop statistical procedures for the analysis of body ratios in a consistent multivariate statistical framework. In particular, we present algorithms adapted to LDA and PCA that allow the interpretation of numerical results in terms of body proportions. We first introduce a method called the “LDA ratio extractor,” which reveals the best ratios for separation of two or more groups with the help of discriminant analysis. We also provide measures for deciding how much of the total differences between individuals or groups of individuals is due to size and how much is due to shape. The second method, a graphical tool called the “PCA ratio spectrum,” aims at the interpretation of principal components in terms of body ratios. Based on a similar idea, the “allometry ratio spectrum” is developed which can be used for studying the allometric behavior of ratios. Because size can be defined in different ways, we discuss several concepts of size. Central to this discussion is Jolicoeur's multivariate generalization of the allometry equation, a concept that was derived only with a heuristic argument. Here we present a statistical derivation of the allometric size vector using the method of least squares. The application of the above methods is extensively demonstrated using published data sets from parasitic wasps and rock crabs.
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            A revision of theEncarsia pergandiellaspecies complex (Hymenoptera: Aphelinidae) shows cryptic diversity in parasitoids of whitefly pests

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              Climate change impact on high-altitude geomorphological systems

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                Author and article information

                Journal
                Alpine Entomology
                AlpEnt
                Pensoft Publishers
                2535-0889
                April 15 2020
                April 15 2020
                : 4
                : 29-38
                Article
                10.3897/alpento.4.50408
                aa0a304e-8d8f-486c-ab87-b74f596d8c93
                © 2020

                http://creativecommons.org/licenses/by/4.0/

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