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An integrated analysis of hyperspectral and morphological data of cicada ovipositors revealed unexplored links to specific oviposition hosts

文献类型： 外文期刊

作者： Hou, Zehai 1 ; Zhong, Haiying 2 ; Nansen, Christian 2 ; Wei, Cong 1 ;

作者机构： 1.Northwest A&F Univ, Coll Plant Protect, Minist Educ, Key Lab Plant Protect Resources & Pest Management, Yangling, Shaanxi, Peoples R China

2.Zhejiang Acad Agr Sci, Hangzhou, Zhejiang, Peoples R China

3.Univ Calif Davis, Dept Entomol & Nematol, Davis, CA 95616 USA

关键词： Cicadidae; Oviposition host selection; Adaptive trait; Hyperspectral imaging; Morphometrics; Ultrastructure

期刊名称：ZOOMORPHOLOGY （ 影响因子：1.326； 五年影响因子：1.668 ）

ISSN： 0720-213X

年卷期： 2019 年 138 卷 2 期

页码：

收录情况： SCI

摘要： Oviposition host selection by females greatly influences the survival of insect offspring. Based on data collected from 11 cicada species, we propose a new analytical approach to examine associations between oviposition host selection (live or dead wood) and three types of quantitative data (reflectance data acquired from ovipositors, morphometric data, and types and distribution of various sensilla). The study hypothesis was that a combination of these quantitative data would provide accurate characterization of species with known oviposition hosts and also enable prediction of a species with unknown oviposition hosts. Using cluster analysis based on morphometric and types and distribution of various sensilla as explanatory variables, the 11 cicada species were clearly categorized into two groups, i.e., one group ovipositing in live twigs, and the other group ovipositing in dead twigs. Although host selection of two species with unknown ovipositional preference awaits to be confirmed by future field investigation, we used the proposed integrated functional morphology approach to predict that these two species oviposit in dead twigs. Animal ecologists and evolutionary biologists frequently face the challenge of having incomplete information about function and behavior of animals, and therefore, seek to perform functional morphological studies. The combination of cluster analysis of morphometric and reflectance data as explanatory variables described in this study may be considered of considerable relevance to this broad audience.

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