Evolutionary biology was defined by Charles Darwin, but he had his critics, similar to Alfred Russel Wallace, who added the idea of evolution as we comprehend it today.
Now, AI has contributed its own research to this debate because of a recent study from the University of Essex published in Communications Biology.
Darwin and Wallace debated what drives the remarkable diversity we observe in nature, particularly the striking differences between women and men of the identical species.
Strong sexual dimorphism and dichromatism is usually most distinguished in insects and birds.
Darwin proposed that the usually flamboyant appearance of male members from the identical species resulted from sexual selection, with females selecting their mates based on aesthetic preferences.
Wallace, nevertheless, countered that natural selection, acting on each sexes, was the first force shaping these differences.
Dr. Jennifer Hoyal Cuthill from the University of Essex and her team launched into a mission to unravel the evolutionary secrets of stunning birdwing group butterflies
As Dr. Hoyal Cuthill explained in a blog post, “For the primary time, we’re capable of measure the visible extents of evolution to check how much variation is present in numerous biological groups and amongst each women and men.”
Male birdwings (left) are often more colourful than females (right) but not necessarily more diverse. Source: Wikimedia Commons.
How the study worked
The researchers used AI to research a powerful 16,000 photographs of birdwing butterflies, representing 35 species and 131 subspecies, from the Natural History Museum in London.
Here’s the method:
- Curation and digitization: The museum’s extensive birdwing butterfly collection was rigorously curated and digitized, providing high-quality photographs of each female and male specimens.
- AI training: The researchers trained an AI algorithm called ButterflyNet to acknowledge and group images based on their visual similarities, enabling the AI to discover patterns and variations among the many butterflies.
- Embedding and evaluation: ButterflyNet generated a multidimensional “butterfly space” where similar images were clustered together, allowing the researchers to look at evolutionary relationships and differences between species and sexes.
- Genetic validation: To confirm the biological significance of the AI’s findings, the machine-learned embeddings were compared with genetic data, ensuring alignment with the evolutionary history of the birdwing butterflies.
- Quantifying sexual variation: The team developed a brand new measure called the “sexual disparity difference” to quantify the extent of variation between women and men, providing insights into the contributions of every sex to overall diversity.
The study’s findings supported each Darwin’s and Wallace’s theories.
Male birdwing butterflies generally exhibited more distinct shapes and patterns in comparison with females, aligning with Darwin’s idea of sexual selection.
However, the research also revealed substantial variation amongst females, particularly within the genus Troides.
Particularly, some female butterflies displayed greater diversity than their male counterparts, supporting Wallace’s hypothesis that natural selection can drive divergence in female phenotypes.
Heatmaps showing differences in sexual disparity between women and men from a model trained on 16,734 images. Blue indicates males are more different, and red indicates females are more different. Source: Nature (open access).
Dr. Hoyal Cuthill explained the findings: “Birdwings have been described as amongst probably the most beautiful butterflies on the planet. This study gives us latest insights into the evolution of their remarkable but endangered diversity.”
She adds, “High visible diversity amongst male butterflies supports the real-world importance of sexual selection from female mate selection on male variation, as originally suggested by Darwin. Cases where female butterflies are more visibly diverse than the males of their species, support an extra, essential role for naturally chosen female variation in inter-species diversity, as suggested by Wallace.”
This isn’t the primary time AI has been applied to evolutionary biology. Not way back, researchers from Colorado State University developed an AI system to explore how elephants communicate.
Researchers found that elephants call one another by name, just like humans.
One of the cornerstones of Darwin’s theory of evolution was that animals, like humans, evolved skills like language for similar advantages to their survival.
The study’s authors described that elephants likely developed similar communication methods as humans because of their must socialize and work together in groups.
As Dr. Hoyal Cuthill, from the School of Life Sciences, described: “This is an exciting time, when machine learning is enabling latest, large-scale tests of longstanding questions in evolutionary science.”
