Summary: A new AI-powered study explores the evolutionary differences between male and female birdwing butterflies, shedding new light on a historic debate between Charles Darwin and Alfred Russel Wallace.
By analyzing more than 16,000 butterfly specimens using machine learning, the researchers found that both sexes contribute to species diversity. Males often show more variation, supporting Darwin’s theories of sexual selection, while subtle variations in females fit Wallace’s ideas about natural selection.
These results expand on classical theories by showing how the two mechanisms work together to promote biodiversity.
Highlights:
- The AI analyzed more than 16,000 male and female birdwing butterflies to determine their evolutionary patterns.
- Males showed more variation, supporting Darwin’s theory of sexual selection.
- Subtle variations in females fit Wallace’s theory of natural selection.
Source: University of Essex
Pioneering AI-powered butterfly research has probed the understudied evolution of females and contributed to a debate among the founding fathers of evolution.
The University of Essex study – published in Biology of communications – explores a controversy between Victorian scientists Charles Darwin and Alfred Russel Wallace.
Darwin thought that males showed more variation because females often chose mates based on the male’s appearance.
While Wallace believed that natural selection between the sexes was the most important factor in difference.
For more than a century, scientists have primarily studied males because their differences are more obvious, while females, 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, with collaborators from the Natural History Museum and AI research institute Cross Labs, Cross Compass.
This is the first time that visual differences between the sexes have been explored 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, 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 visible extent of evolution to test the degree of variation present in different biological groups and among males and females.
“Machine learning gives us new insights into the evolutionary processes that generate and maintain biodiversity, including in historically neglected groups.”
The study looked at photographs of butterflies from the Natural History Museum’s collections, which show a range of characteristics, such as wing shapes, colours and patterns, across several species.
It found that while males often have more distinct shapes and patterns, both males and females contribute to overall diversity.
Research has shown that the evolutionary patterns predicted by Darwin and Wallace have been found in butterflies.
Demonstrate that both males and females contribute to species diversity.
Males showed more variation in appearance, consistent with Darwin’s idea that females choose mates based on these traits.
However, deep learning also revealed subtle variation among females, consistent with Wallace’s predictions that natural selection enables diversity in female phenotypes.
Dr Hoyal Cuthill said: “Birdwings have been described as some of the most beautiful butterflies in the world. This study gives us new insights into the evolution of their remarkable but threatened diversity.
“In this case study of birdwing butterfly photographs, it is sex that appears to have driven the greatest evolutionary change, including extreme male shapes, colors and patterns.
“However, within the birdwing butterfly group, we found contrasting examples where female birdwing butterflies are more diverse in visible phenotype than males, and vice versa.
“The great diversity visible among male butterflies confirms the real importance of sexual selection from female mate choice on male variation, as originally suggested by Darwin.
“Cases where female butterflies are visibly more diverse than males of their species support an important additional role for naturally selected female variation in inter-species diversity, as Wallace suggests.
“Large-scale studies of evolution using machine learning offer new opportunities to resolve debates that have persisted since the founding of evolutionary science.”
About this development and current AI research
Author: Ben Hall
Source: University of Essex
Contact: Ben Hall – University of Essex
Picture: Image credited to Neuroscience News
Original research: Free access.
“Male and Female Contributions to Diversity Among Birdwing Butterfly Images” by Jennifer Hoyal Cuthill et al. Biology of communications
Abstract
Contributions of men and women to the diversity of ornithological butterfly images
Machine learning (ML) now allows testing for greater inter-species diversity in visible phenotype (disparity) between males and females, predictions made from 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 sexually dimorphic birdwing butterflies (Lepidoptera: Papilionidae).
Validation of image embedding distances, learned by a triplet-trained deep convolutional neural network, shows that ML can be used for automated reconstruction of phenotypic evolution by obtaining measures of phylogenetic congruence with genetic species trees within a range sampled among the gene trees themselves.
Quantification of the difference in sexual disparity (male versus female integration distance) shows variable inter-species disparity on the sexual and phylogenetically level.
Ornithopters illustrate strong integrated male image disparity, diversification of selective optima in fitted multi-peak OR models, and accelerated divergence, with cases of extreme divergence in allopatry and likability.
However, the genre Troides exhibits reversed patterns, including a relatively static integrated male phenotype and greater disparity between females and males – albeit within an inferred selective regime common to these females. The most phenotypically distinctive bird wing shapes and color patterns in terms of ML similarity are generally those of males.
However, either sex may contribute predominantly to the phenotypic diversity observed among species.