Back

Courtship choreography is stabilised among genetically isolated populations

Butterworth, N. J.; White, T. E.; Dawson, B. M.; Appleton, J.; McDonald, C.; McGaughran, A.; Markowsky, G.; Bayless, K. M.

2025-09-11 evolutionary biology
10.1101/2025.09.08.675024 bioRxiv
Show abstract

Sexual selection has sculpted diverse and intricate courtship displays throughout the animal kingdom, where failure to achieve the choreographic standards of a potential partner can be highly costly for reproductive success. Yet this raises a paradox: if there is such strong selection for optimal display choreography within species, how do courtship displays diversify so extensively between species? To address this, we measure how the choreography of courtship changes among allopatric populations of the dancing dune fly - Apotropina ornatipennis Malloch (Diptera: Chloropidae) - a species in which males and females spend their days cavorting on Australias hot sandy beaches. Merging population genetics with detailed quantification of the courtship display we explore which elements of the display are the first to diverge between isolated populations, whether new behaviours arise rapidly, and whether sequence rearrangements occur in the modular structure of the display. We find that these tiny flies express courtship repertoires approaching the levels of visual complexity seen in birds of paradise. Yet despite clear genetic and geographic isolation, the complex choreography of courtship displays is stable among populations. In contrast to the notion that courtship behaviour should be highly evolvable and rapidly diverge among allopatric populations, our findings suggests that the complex choreography of courtship can instead act as a stabilising feature that limits divergence over short evolutionary timescales.

Published in Behavioral Ecology (predicted rank #5) · training set

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.