Insect morphometry is reproducible under average investigation standards.

Abstract

Morphometric research is being applied to a growing number and variety of organisms. Discoveries achieved via morphometric approaches are often considered highly transferable, in contrast to the tacit and idiosyncratic interpretation of discrete character states. The reliability of morphometric workflows in insect systematics has never been a subject of focused research, but such studies are sorely needed. In this paper, we assess the reproducibility of morphometric studies of ants where the mode of data collection is a shared routine.We compared datasets generated by eleven independent gaugers, that is, collaborators, who measured 21 continuous morphometric traits on the same pool of individuals according to the same protocol. The gaugers possessed a wide range of morphometric skills, had varying expertise among insect groups, and differed in their facility with measuring equipment. We used intraclass correlation coefficients (ICC) to calculate repeatability and reproducibility values (i.e., intra‐ and intergauger agreements), and we performed a multivariate permutational multivariate analysis of variance (PERMANOVA) using the Morosita index of dissimilarity with 9,999 iterations.The calculated average measure of intraclass correlation coefficients of different gaugers ranged from R = 0.784 to R = 0.9897 and a significant correlation was found between the repeatability and the morphometric skills of gaugers (p = 0.016). There was no significant association with the magnification of the equipment in the case of these rather small ants. The intergauger agreement, that is the reproducibility, varied between R = 0.872 and R = 0.471 (mean R = 0.690), but all gaugers arrived at the same two‐species conclusion. A PERMANOVA test revealed no significant gauger effect on species identity (R 2 = 0.69, p = 0.58).Our findings show that morphometric studies are reproducible when observers follow the standard protocol; hence, morphometric findings are widely transferable and will remain a valuable data source for alpha taxonomy.