Morphometric Analysis and Interrelationship of Seven Indonesian Hornbill Species (Aves, Bucerotidae) Utilizing Principal Component and Cluster Analyses

Abstract

In this comprehensive study, we examined 15 distinct morphometric characteristics within seven Indonesian hornbill species. Precise measurements of these morphometric traits were obtained using 0.1 mm calipers and a 1000 mm measuring tape. Our analysis encompassed a total of 85 individuals representing seven hornbill species: Anthracoceros albirostris (18 individuals), A. malayanus (4 individuals), Aceros cassidix (3 individuals), Rhyticeros plicatus (7 individuals), R. undulatus (36 individuals), Buceros bicornis (1 individual), and B. rhinoceros (16 individuals). To elucidate the morphometric ratio data, we employed a robust analytical approach involving the Principal Component Analysis (PCA), Discriminant Analysis, and Cluster Analysis. Our findings underscored a clear separation between hornbill genera, primarily attributed to a combination of PC1 (pertaining to body length) and PC3 (associated with beak morphology). Key morphometric traits that delineated these genera on PC1 included tail length, beak length, horn length, total length, and wing length. Meanwhile, on PC3 (characterizing beak morphology), the distinguishing features encompassed beak width, horn width, and tarsus length. Additionally, our analysis unveiled the characteristics that distinguish species within the genera Anthracoceros and Rhyticeros to be a composite of tail length and head length. This discerning morphometric data facilitated the clustering of seven hornbill species into two distinct groups: Group I comprised A. albirostris and A. malayanus, while Group II included R. plicatus, R. undulatus, A. cassidix, B. rhinoceros, and B. bicornis. Notably, these groups exhibited a 31.93% degree of similarity. This dataset holds immense potential for facilitating genetic classification and comparative studies of Indonesian hornbills.

Keywords

• classification
• hornbills
• morphometric
• principal component analysis
• similarity