Is There a Minimum Number of Landmarks That Optimizes the Geometric Morphometric Analysis of Mosquito (Diptera, Culicidae) Wings?

Culicids are the most significant arthropods affecting human health. Thus, their correct identification is critical. The use of Geometric Morphometrics (GM) has been recently incorporated into mosquito taxonomy and has begun to complement classic diagnostic techniques. Since sampling size depends on...

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Veröffentlicht in:Journal of medical entomology 2021-03, Vol.58 (2), p.576-587
Hauptverfasser: Beriotto, Agustina C., Garzón, Maximiliano J., Schweigmann, Nicolás
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Sprache:eng
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Zusammenfassung:Culicids are the most significant arthropods affecting human health. Thus, their correct identification is critical. The use of Geometric Morphometrics (GM) has been recently incorporated into mosquito taxonomy and has begun to complement classic diagnostic techniques. Since sampling size depends on the number of Landmarks (LMs) used, this study aimed to establish the minimum number of wing LMs needed to optimize GM analysis of mosquito species and/or genera from urban and peri-urban areas of Argentina. Female left wings were used for the optimization phase, in which 17 LMs were reduced to four by iterative LM exclusion. To verify its efficiency, Principal Component Analysis (PCA), Discriminant Analysis (DA), and Canonical Variate Analysis (CVA) were performed. Additionally, a phenogram was constructed to visualize the results. We observed that five LMs for the PCA, CVA, and phenogram and nine for the DA enabled discrimination and/or clustering of almost all species and genera. Therefore, we tested the LM selection by using nine LMs and adding new species. The resulting PCA showed little overlap between species and almost all species clustered as expected, which was also reflected in the phenogram. Significant differences were found between wing shape among all species, together with a low total error rate in the DA. In conclusion, the number of LMs can be reduced and still be used to effectively differentiate and cluster culicids. This is helpful for better exploitation of available material and optimization of data processing time when classic taxonomy methods are inadequate or the material is scarce.
ISSN:0022-2585
1938-2928
DOI:10.1093/jme/tjaa187