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.
Using machine learning to analyze more than 16,000 butterfly specimens, the researchers found that both sexes contribute to species diversity: Males tend to be more variable, supporting Darwin’s theory of sexual selection, while females’ more subtle variations are consistent with Wallace’s idea of natural selection.
These findings extend classical theory by showing how both mechanisms work together to drive biodiversity.
Key Facts:
- AI analyzed the evolutionary patterns of more than 16,000 male and female birdwing butterflies.
- There was greater diversity in males, supporting Darwin’s theory of sexual selection.
- The subtle changes in females are consistent with Wallace’s theory of natural selection.
sauce: University of Essex
A pioneering AI-powered study of butterflies has shed light on a little-studied aspect of female evolution, adding a new chapter to a debate between the founding fathers of evolutionary theory.
University of Essex study – published in 2010 Communication Biology – Explores the debate between Victorian scientists Charles Darwin and Alfred Russel Wallace.
Darwin believed that there was more diversity in males because females often chose their mates based on the male’s appearance.
Wallace, on the other hand, thought that natural selection on the sexes was the biggest factor in the differences.
For more than a century, scientists have primarily studied males, because the differences between males and females are more obvious, while females have been less studied because their evolutionary changes are more subtle.
Dr Jennifer Hoyal-Cuthill, working with collaborators at the Natural History Museum and AI research institutes Cross Labs and Cross Compass, used high-tech machine learning to survey more than 16,000 male and female birdwing butterflies.
This is the first time that visual differences between the sexes have been investigated in this species, which lives in southeast Asia and Australia.
The Ornithoptera was chosen for this study because of its striking wing color patterns and the differences between males and females.
Dr Hoyal Kathir, from the School of Life Sciences, said: “This is an exciting time, as machine learning is enabling new, large-scale tests of long-standing questions in evolutionary science.
“For the first time, we can measure the visible extent of evolution and test how much variation exists between different biological groups and between males and females.
“Machine learning is bringing new information about the evolutionary processes that create and maintain biodiversity, including groups that have been historically ignored.”
The study looked at photographs of butterflies from the Natural History Museum’s collection, which showed a variety of characteristics, including wing shape, color and pattern, across several butterfly species.
The study found that while males often have more distinctive shapes and patterns, both males and females contribute to overall diversity.
The study found that butterflies exhibit the evolutionary patterns predicted by both Darwin and Wallace.
This shows that both males and females contribute to species diversity.
Males show considerable variation in appearance, which is consistent with Darwin’s idea that females choose mates on the basis of these characteristics.
But deep learning found subtle variations in females as well, consistent with Wallace’s prediction that natural selection allows for phenotypic variation in females.
Dr Hoyal Kathiru said: “The Birdwing butterfly is said to be one of the most beautiful butterflies in the world and this study gives us new insight into the evolution of this amazing but endangered species’ diversity.”
“In this case study of birdwing photography, it appears that sex is what has driven the greatest evolutionary changes, including the extreme male shapes, colors and patterns.”
“However, within the birdwing group, we found contrasting examples where female birdwings have greater visible phenotypic diversity than males, and vice versa.
“The high visible diversity among male butterflies confirms the real importance of sexual selection through female mate choice to male diversity, as Darwin first suggested.
“These instances in which female butterflies are visibly more diverse than males of the same species support the even more important role of naturally selected female variation in interspecific diversity, as Wallace suggested.
“Large-scale evolutionary studies using machine learning offer new opportunities to resolve debates that have remained unresolved since the founding of evolutionary science.”
More on this evolution and AI research news
author: Ben Hall
sauce: University of Essex
contact: Ben Hall – University of Essex
image: Image courtesy of Neuroscience News
Original Research: Open access.
“Contribution of males and females to diversity in birdwing images” by Jennifer Hoyal Cathill et al. Communication Biology
Abstract
Contribution of males and females to diversity in birdwing images
Machine learning (ML) has made it newly possible to test the high interspecific diversity in visible phenotypes (differences) between males and females predicted by Darwin’s sexual selection and Wallace’s natural selection.
Here, we use ML to quantify variation across a sample of over 16,000 photographs of dorsal and ventral views of the sexually dimorphic birdwing swallowtail butterfly (Lepidoptera: Papilionidae).
Validation of image embedding distances learned by triplet-trained deep convolutional neural networks showed that ML can be used to automatically reconstruct phenotypic evolution while achieving a measure of phylogenetic congruence to gene-species trees within the range sampled from the gene trees themselves.
Quantifying sex-specific differences (male and female embedding distances) indicates differences between the sexes and between phylogenetically distinct species.
Bird eyes We provide illustrative examples of highly embedded male image inconsistency, diversification of selection optima in fitted multi-peak OU models, accelerated divergence, and extreme divergence in heterotopy and empathy.
However, Troides Although they show inverted patterns, including relatively static male embedding phenotypes and greater variance in females than in males, this is within the range of the putative selection regime common to these females.The shape and colour patterns of birdwing butterflies that are phenotypically most distinctive in ML similarity are typically those of males.
However, both sexes can contribute significantly to the phenotypic diversity observed among species.