PCA coordinates describing dorsal colour pattern variation in 723 Morpho butterflies
Cite this dataset
Llaurens, Violaine et al. (2020). PCA coordinates describing dorsal colour pattern variation in 723 Morpho butterflies [Dataset]. Dryad. https://doi.org/10.5061/dryad.6q573n5xb
Species interactions such as mimicry can promote trait convergence but disentangling this effect from those of shared ecology, evolutionary history and niche conservatism is often challenging. Here by focusing on wing color pattern variation within and between three butterfly species living in sympatry in a large proportion of their range, we tested the effect of species interactions on trait diversification. These butterflies display a conspicuous iridescent blue coloration on the dorsal side of their wings and a cryptic brownish colour on the ventral side. Combined with an erratic and fast flight, these color patterns increase the difficulty of capture by predators and contribute to the high escape abilities of these butterflies. We hypothesize that, beyond their direct contribution to predator escape, these wing patterns can be used as signals of escape abilities by predators, resulting in positive frequency-dependent selection favouring convergence in wing pattern in sympatry. To test this hypothesis, we quantified dorsal wing pattern variations of 723 butterflies from the three species sampled throughout their distribution, including sympatric and allopatric situations and compared the phenotypic distances between species, sex and localities. We detected a significant effect of localities on colour pattern, and higher inter-specific resemblance in sympatry as compared to allopatry, consistent with the hypothesis of local convergence of wing patterns. Our results provide support to the existence of escape mimicry in the wild and stress the importance of estimating trait variation within species to understand trait variation between species, and to a larger extent, trait diversification at the macro-evolutionary scale.
We used the collections of National Natural History Museum of Paris to study the variation of colour pattern in the butterfly species Morpho helenor, M. achilles and M. deidamia throughout their geographical range. Pictures of collection specimens were taken in controlled standard white light conditions. The four wings were first manually separated using Adobe Photoshop Element. Wing images were then analysed following the Colour Pattern Modelling approach (Le Poul et al. 2014) implemented in Matlab. This method allows precise comparison of colour pattern while accounting for wing shape and venation that might differ between species. It has been shown to be especially relevant to quantify similarity and differences in color pattern within and across species (Le Poul et al. 2014; Huber et al. 2015; McClure et al. 2019). Briefly, the algorithm detects the four wings on the white background and segments the colour pattern in different categories based on pixel densities of the RGB values. The number of colours is then set manually: here we chose to consider three colours, namely black, blue and white. Some individuals (as for instance M. deidamia samples from French Guiana), display a gradient of blue that is often detected as a different colour category by CPM. Dark blue was nevertheless treated as blue in our analyses. This is probably a conservative assumption regarding convergence in colour patterns, because the dark blue area of M. deidamia has a similar location to the basal black area in M. helenor and M. achilles, and look very dark from far-distance. After segmentation, wings were aligned by adjusting translation, rotation and scale in order to maximize similarity, allowing the colour value for each pixel of the wings to be compared.
The dataset provides the PCA coordinates for each of the 723 Morpho butterflies used in this study, together with information on their species, sub-species, sex, sampling zones (using codes defined in the associated article), sampling country and exact sampling locality with latitudinal and longitudinal localisation.
Mairie de Paris (France)
Mairie de Paris (France)