Length-based morphometric study of the morphologically resembling butterfly species within the genus graphium (Lepidoptera: Papilionidae)

• Main Authors: Wahid, Noor Azrizal, Mohd Noor, Nurinatasya, Mamat, Noorhidayah, Mohd Zainudin, Nur Ain Izzati
• Format: Article
• Published: Lembaga Penelitian dan Pengabdian Masyarakat (LPPM) Universitas Andalas 2023
• Online Access: http://psasir.upm.edu.my/id/eprint/110043/; http://aijent.lppm.unand.ac.id/index.php/aijent/article/view/2

The genus Graphium within the family Papilionidae comprises several species that exhibit morphological resemblance. Due to this criterion, their identification and discrimination through morphology is notably challenging. Therefore, in this study, we employed a length-based morphometric approach to reveal the ability of the characters to discriminate the five Graphium species that demonstrates the morphological resemblance; Graphium sarpedon, Graphium bathycles, Graphium doson, Graphium eurypylus, and Graphium evemon. The morphometric measurement of the total of 50 specimens was carried out by using seven characters measured from the wing and body regions. Multivariate statistical analyses such as Discriminant Function Analysis (DFA) and Cluster Analysis (CA) were utilized to assess the discriminatory ability of the morphometric data. While comparing between species, all morphometric characters were significantly different (p < 0.05). The results of DFA showed that two out of seven characters utilized have the lowest values of Partial’s Wilks Lambda; body length (1.165), and forewing length (1.183), therefore are suggested as the two most significant characters for the discrimination of the Graphium species. There are great overlapping patterns between the five species when plotting a scatter plot graph except for G. bathycles that formed nearly distinct group. In Cluster Analysis, G. sarpedon tends to be closer to G. evemon by having the lowest value of agglomeration (0.061). Our findings underscore the potential of length-based morphometric analysis as a supporting quantitative tool for resolving taxonomic ambiguities and enhancing species identification particularly within complex genera such as Graphium.