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Mullerian mimicry and the colouration patterns of sympatric coral snakes

Citation

Bosque, Renan et al. (2021), Mullerian mimicry and the colouration patterns of sympatric coral snakes, Dryad, Dataset, https://doi.org/10.5061/dryad.jh9w0vtc2

Abstract

This dataset cointains data used for the study of Müllerian mimicry in coral snakes. Coral snakes in the genus Micrurus are venomous, aposematic organisms that signal danger to predators through vivid colouration. Previous studies found that they serve as models to several harmless species of Batesian mimics. However, the extent to which Micrurus species engage in Müllerian mimicry remains poorly understood. We integrate detailed morphological and geographical distribution data to investigate if coral snakes are Müllerian mimics. We found that colouration is spatially structured and that Micrurus species tend to be more similar where they co-occur. Though long supposed, we empirically demonstrate Müllerian mimicry for the first time in coral snakes. Additionally, we found that the length of red-coloured rings in Micrurus is conserved, even at large geographic scales. This finding suggests that bright red rings may be under more substantial stabilizing selection than other aspects of colouration, and probably function as a generalized signal for deterring predators.

Methods

We examined museum specimens of Micrurus brasiliensis, M. frontalis, M. ibiboboca, M. lemniscatus, and M. surinamensis by taking high-quality digital photographs from the dorsum of 1528 preserved snakes. We measured the number of red rings, relative length of red rings (length of red ring / total length), relative length of external black rings ((length of black ring I + length of black ring III) / total length) / 2), relative length of white rings ((length of white ring I + length of white ring II / total length) / 2), and relative length of internal black rings (length of black ring II / total length). We calculated the colour variation through the geographic distribution of each species coupled with a multivariate spatial analysis approach.