Tempo and mode of diapause evolution in butterflies

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Sridhar Halali, Etka Yapar, Christopher Wheat , Niklas Wahlberg, Karl Gotthard, Nicolas Chazot, Sören Nylin, Philipp Lehmann


Quantifying the tempo and mode via modern phylogenetic comparative methods can provide insights into how selection and constraints shape trait evolution. Here we elucidate the evolution of diapause, a complex and key trait that allows temporal escape from unfavorable conditions in many insects, including our model system, butterflies. Using a thorough literature survey, we first scored the developmental stage of diapause (egg, larva, pupa, adult) vs. absence of winter diapause. We find that larval diapause is most common in temperate areas while pupal, egg, and adult diapause are relatively rare. Next, we determined that the loss of diapause occurred at a much higher rate, and its gain primarily occurred from the non-diapause state. While ancestral state estimation at deeper nodes remained uncertain, we found consistent patterns for some families and strong evidence for extensive convergent evolution of diapause. Contrary to expectations, we find no support for increased diapause gain during the Eocene-Oligocene glaciation (~35 MYA). Overall, the evolution of diapause in butterflies has a complex history, has evolved convergently, and has likely pre-dated major glaciation event consistent with the deep history of diapause evolution in insects. These findings fill an important gap in much-needed studies for future comparative research.




Ecology and Evolutionary Biology, Entomology, Life Sciences


Eocene-Oligocene glacial maximum, Life-history trait, Mk models, Phylogenetic comparative methods, seasonality, Convergent evolution, Eocene-Oligocene glacial maximum, Life-history trait, Mk models, Phylogenetic comparative methods, seasonality


Published: 2024-02-19 23:48

Last Updated: 2024-03-11 20:17

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CC-BY Attribution-No Derivatives 4.0 International

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Data and Code Availability Statement:
Open data/code are not available. We will make the the raw data, full R scripts and all the log files (as .RDS files) to reproduce the analyses (e.g. on Dryad) after acceptance of the manuscript in the journal.