Morphometric Wing Characters as a Tool for Mosquito Identification

Abstract

Mosquitoes are responsible for the transmission of important infectious diseases, causing millions of deaths every year and endangering approximately 3 billion people around the world. As such, precise identification of mosquito species is crucial for an understanding of epidemiological patterns of disease transmission. Currently, the most common method of mosquito identification relies on morphological taxonomic keys, which do not always distinguish cryptic species. However, wing geometric morphometrics is a promising tool for the identification of vector mosquitoes, sibling and cryptic species included. This study therefore sought to accurately identify mosquito species from the three most epidemiologically important mosquito genera using wing morphometrics. Twelve mosquito species from three epidemiologically important genera (Aedes, Anopheles and Culex) were collected and identified by taxonomic keys. Next, the right wing of each adult female mosquito was removed and photographed, and the coordinates of eighteen digitized landmarks at the intersections of wing veins were collected. The allometric influence was assessed, and canonical variate analysis and thin-plate splines were used for species identification. Cross-validated reclassification tests were performed for each individual, and a Neighbor Joining tree was constructed to illustrate species segregation patterns. The analyses were carried out and the graphs plotted with TpsUtil 1.29, TpsRelw 1.39, MorphoJ 1.02 and Past 2.17c. Canonical variate analysis for Aedes, Anopheles and Culex genera showed three clear clusters in morphospace, correctly distinguishing the three mosquito genera, and pairwise cross-validated reclassification resulted in at least 99% accuracy; subgenera were also identified correctly with a mean accuracy of 96%, and in 88 of the 132 possible comparisons, species were identified with 100% accuracy after the data was subjected to reclassification. Our results showed that Aedes, Culex and Anopheles were correctly distinguished by wing shape. For the lower hierarchical levels (subgenera and species), wing geometric morphometrics was also efficient, resulting in high reclassification scores.

Wing Metric Variation inAedes aegyptiEffect of Altitude on Wing Metric Variation ofAedes aegypti(Diptera: Culicidae) in a Region of the Colombian Central Andes

“…The geometric morphometry permits detecting information patterns on the type, ecological relationships, and environmental factors associated to populations present in the area [25–27]. In A. aegypti , morphometric analyses on wings have been widely studied to investigate heterogeneity and structuring in natural populations [28–31].…”

Inspecting Morphological Features of Mosquito Wings for Identification with Image Recognition Tools

“…Because mosquito identification based on morphology is difficult, it generally requires specialist entomological and taxonomic knowledge and hard to come by identification keys. DNA barcoding may prove to be an effective alternative, but this method requires expensive equipment and specifically designed labs [35,36,37]. A method that would require none of these to identify mosquito species would greatly benefit scientific research.…”

Morphological variation and strain identification of insects using wings and I3S

“…The wings of insects have long been known to be a reliable diagnostic feature for a given species (Woodward 1926, Wooton 1992, Wilke et al 2016. The use of algorithms and software to capture wing shape and the pattern and proportions of the vein structure on insect wings to differentiate species, means that even the smallest change in this shape, pattern and/or proportion can be detected quickly and easily.…”

“…He-Ping Yang's (2015) account of different geometric morphometric methods to identify insects using wing images currently provides the most encompassing review. Wilke et al (2016) dealt entirely with methods using wing morphometrics for the identification of different mosquito species. This comprehensive study is amongst the few to describe the use of software and image recognition for the identification of species and strains.…”