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      Two new species of Ooencyrtus (Hymenoptera, Encyrtidae), egg parasitoids of the bagrada bug Bagrada hilaris (Hemiptera, Pentatomidae), with taxonomic notes on Ooencyrtus telenomicida

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          Abstract

          In support of a biological control program in California, USA, against the bagrada bug, Bagrada hilaris (Burmeister) (Hemiptera, Pentatomidae), an invasive pest of Asian origin, colonies of two species of Ooencyrtus Ashmead (Hymenoptera, Encyrtidae) are maintained using B. hilaris eggs as host. One of them, Ooencyrtus mirus Triapitsyn & Power, sp. nov., is of Pakistani origin. It displays natural preference for bagrada bug eggs and is being evaluated in quarantine as a candidate for classical biological control. The other, Ooencyrtus lucidus Triapitsyn & Ganjisaffar, sp. nov., appears to be native to California, and we believe it switched to B. hilaris from native pentatomid hosts. Both new species are described and illustrated, as is the Old World species Ooencyrtus telenomicida (Vassiliev), for which a neotype is designated. The presented morphometric evidence as well as mitochondrial and nuclear ribosomal DNA sequence data separate Ooencyrtus mirus from O. telenomicida. A lectotype is designated for Ooencyrtus californicus Girault from California, which is morphologically similar to O. lucidus.

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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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            Phylogeny of the Nasonia species complex (Hymenoptera: Pteromalidae) inferred from an internal transcribed spacer (ITS2) and 28S rDNA sequences

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              Species-diagnostic differences in a ribosomal DNA internal transcribed spacer from the sibling species Anopheles freeborni and Anopheles hermsi (Diptera:Culicidae).

              Approximately 460 base pairs (bp) of DNA sequence that included the second internal transcribed spacer (ITS2) and some flanking 5.8S and 28S ribosomal RNA coding regions were compared between the two closely related and morphologically indistinguishable mosquito species Anopheles freeborni and A. hermsi and a third related species, A. occidentalis. Sequences were determined from 14 clones of polymerase chain reaction (PCR)-amplified DNA obtained from four colonies of A. freeborni, two colonies of A. hermsi, and one individual A. occidentalis. Four clones showed independent single bp differences from the consensus for the relevant species. Eleven sites differed between the consensus sequences of A. hermsi and A. freeborni; 28 sites differed between A. hermsi and A. occidentalis. With the exception of a single bp mismatch in the 5.8S and two single bp mismatches near the undetermined junction of the ITS2 and 28S regions, all differences were confined to the ITS2 region. A PCR-based species-diagnostic assay for the cryptic species A. hermsi and A. freeborni was developed; it uses four synthetic oligonucleotides, two derived from areas of interspecies sequence difference in the ITS2, and two derived from highly conserved regions in the flanking coding sequences. Small amounts of mosquito DNA amplified in the presence of these four primers produce fragments of diagnostic size for each species: 900 bp for A. freeborni, 350 bp for A. hermsi, and approximately 1.2-1.4 kb for various other Anopheles species tested. We believe that this general approach to the development of species-diagnostic assays can be extended easily to other complexes of closely related, morphologically indistinguishable species.
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                Author and article information

                Journal
                Journal of Hymenoptera Research
                JHR
                Pensoft Publishers
                1314-2607
                1070-9428
                April 27 2020
                April 27 2020
                : 76
                : 57-98
                Article
                10.3897/jhr.76.48004
                ff74a655-74b1-47f8-a50e-0d5a5f1d0c13
                © 2020

                https://creativecommons.org/share-your-work/public-domain/cc0/

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