Toward Objective, Morphology-Based Taxonomy: A Case Study on the Malagasy Nesomyrmex sikorai Species Group (Hymenoptera: Formicidae).
Madagascar is one of the world's greatest biodiversity hotspots, meriting special attention from biodiversity scientists. It is an excellent testing ground for novel techniques in taxonomy that aim to increase classification objectivity and yield greater taxonomic resolving power. Here we reveal the diversity of a unique and largely unexplored fragment of the Malagasy ant fauna using an advanced combination of exploratory analyses on quantitative morphological data allowing for increased objectivity in taxonomic workflow. The diversity of the Nesomyrmex sikorai species-group was assessed via hypothesis-free nest-centroid-clustering combined with recursive partitioning to estimate the number of morphological clusters and determine the most probable boundaries between them. This combination of methods provides a highly automated and objective species delineation protocol based on continuous morphometric data. Delimitations of clusters recognized by these exploratory analyses were tested via confirmatory Linear Discriminant Analysis (LDA) and Multivariate Ratio Analysis (MRA). The final species hypotheses are corroborated by many qualitative characters, and the recognized species exhibit different spatial distributions and occupy different ecological regions. We describe and redescribe eight morphologically distinct species including six new species: Nesomyrmex excelsior sp. n., N. modestus sp. n., N. reticulatus sp. n., N. retusispinosus (Forel, 1892), N. rugosus sp. n., N. sikorai (Emery, 1896), N. striatus sp. n., and N. tamatavensis sp. n. An identification key for their worker castes using morphometric data is provided.
Department of Entomology, California Academy of Sciences, 55 Music Concourse Drive, San Francisco, CA 94118, United States of America.
Sándor
S
Csősz
Department of Entomology, California Academy of Sciences, 55 Music Concourse Drive, San Francisco, CA 94118, United States of America.
Brian L
BL
Fisher
D000465:Algorithms; D000818:Animals; D044822:Biodiversity; D002965:Classification / Q000379:methods*; D016000:Cluster Analysis; D016002:Discriminant Analysis; D006927:Hymenoptera / Q000145:classification*