Resume: A new AI-powered study examines evolutionary differences between male and female birdwing butterflies, shedding new light on a historic debate between Charles Darwin and Alfred Russel Wallace.
Using machine learning to analyze more than 16,000 butterfly specimens, researchers found that both sexes contribute to species diversity. Males tend to show more variation, supporting Darwin’s theories of sexual selection, while subtle variations in females match Wallace’s ideas about natural selection.
These findings build on classical theories by showing how both mechanisms work together to promote biodiversity.
Key Facts:
- AI analyzed the evolutionary patterns of over 16,000 male and female birdwing butterflies.
- There was more variation in males, supporting Darwin’s theory of sexual selection.
- Subtle variations in females are consistent with Wallace’s theory of natural selection.
Source: University of Essex
Groundbreaking AI research on butterflies has explored the understudied evolution of females and adds to the debate among the founders of evolution.
The University of Essex study – published in Communication Biology – examines a controversy between Victorian scientists Charles Darwin and Alfred Russel Wallace.
Darwin thought there was more variation among males because females often chose a mate based on the male’s appearance.
Wallace, on the other hand, thought that natural selection between the sexes was the major factor in the differences.
For more than a century, scientists have primarily studied males, because their differences are more obvious. Females, on the other hand, with more subtle evolutionary changes, have been less studied.
Using high-tech machine learning, Dr Jennifer Hoyal Cuthill examined more than 16,000 male and female birdwing butterflies, together with collaborators from the Natural History Museum and the AI research institute Cross Labs and Cross Compass.
This is the first time that visual differences between the sexes have been investigated in this species, which lives in Southeast Asia and Australasia.
Birdwing butterflies were chosen for this study because of their spectacular wing color patterns and the differences between males and females.
Dr Hoyal Cuthill from the School of Life Sciences said: “This is an exciting time, with machine learning enabling new, large-scale tests of long-standing questions in evolutionary science.
“For the first time, we are able to measure the apparent extent of evolution to test how much variation exists within different biological groups and between both males and females.
“Machine learning provides us with new information about the evolutionary processes that generate and maintain biodiversity, including in historically neglected groups.”
The study examined photographs of butterflies from the collections of the Natural History Museum. These show a range of characteristics, such as wing shape, colours and patterns, in different species.
The study found that males often have more pronounced shapes and patterns, but that both males and females contribute to the overall diversity.
The research found that the evolutionary patterns predicted by both Darwin and Wallace were also found in the butterflies.
To demonstrate that both males and females contribute to diversity within species.
The males showed more variation in appearance, which fits with Darwin’s idea that females choose a mate based on these characteristics.
However, closer examination also revealed subtle variation among females, consistent with Wallace’s predictions about natural selection allowing for diversity in female phenotypes.
Dr Hoyal Cuthill said: “Birdwings are described as some of the most beautiful butterflies in the world and this study gives us new insights into the evolution of their remarkable but threatened diversity.
“In this case study of birdwing butterfly photographs, it appears that gender has caused the greatest evolutionary change, including extreme male forms, colors, and patterns.
“Within the birdwing moth group, however, we found contrasting examples, with female birdwing moths showing greater diversity in visible phenotype than males, and vice versa.
“The great apparent diversity among male butterflies supports the real importance of sexual selection of female mate choice on male variation, as originally suggested by Darwin.
“Cases in which female butterflies are visibly more diverse than the males of their species support an additional, important role for naturally selected female variation in diversity among species, as suggested by Wallace.
“Large-scale studies of evolution using machine learning offer new opportunities to resolve debates that have been going on since the inception of evolutionary science.”
About this evolution and AI research news
Author: Am Zaal
Source: University of Essex
Contact: Ben Hall – University of Essex
Image: The image is attributed to Neuroscience News
Original research: Open access.
“Male and female contributions to diversity in birdwing butterfly images” by Jennifer Hoyal Cuthill et al. Communication Biology
Abstract
Male and female contributions to diversity in birdwing butterfly images
Thanks to machine learning (ML), it is now possible to test for greater diversity between species in visible phenotypes (differences) between males and females. These predictions are based on Darwinian sexual selection and Wallacean natural selection, respectively.
Here we use ML to quantify variation in a sample of >16,000 dorsal and ventral photographs of the sexually dimorphic birdwing moths (Lepidoptera: Papilionidae).
Validation of the image embedding distances learned by a triplet-trained deep convolutional neural network shows that ML can be used for the automated reconstruction of phenotypic evolution, taking measures of phylogenetic similarity from genetic species trees within a range sampled between genetic trees themselves.
Quantification of differences in sexual disparity (embedding distance between males and females) reveals sexually and phylogenetically variable differences between species.
Ornithoptera illustrate high embedded male image disparity, diversification of selective optima in adjusted multi-peak OU models, and accelerated divergence, with cases of extreme divergence in allopatry and sympatry.
However, gender Troids shows inverse patterns, including a relatively static male-embedded phenotype, and higher female than male disparity – albeit within a derived selective regime common to these females. Bird wing shapes and color patterns that are most phenotypically distinctive in ML similarity are generally those of males.
However, both sexes can contribute greatly to the observed phenotypic diversity between species.