Can vocalizations predict mating pairs in a society of songbirds? A maximum-entropy Ising model approach

During mating season, most species of songbird engage in a societal evolution wherein monogamous pairs “freeze out”. Presumably, these bonds are a recipe for successful procreation. The means by which all individuals “agree” on this structure is unknown. The role of song is significant¹, but its mechanism of orchestrating bonding is obscure. Moreover, a dynamical systems modeling approach would be premature, as it is not clear how to define the variables.

We tackle this problem with a maximum-entropy Ising model. This approach has been applied to an eclectic set of contexts^2,3,4, but – to our knowledge – not to acoustic signaling. Our inferred model, trained on instances of song, is a stronger predictor of mating pairs than are the statistical correlations: it finds monogamous pairs and also instances of polygamy. Minima on the energy landscape align with particular pairs. The Ising model fails to capture all of the structure in the data, suggesting that triadic interactions matter. Moreover, the language of statistical physics offers a framework for examining the biological motivations for songbird social structure. Refs: 1) Perkes et al., Behavioural processes 2018; 2) Schneidman et al., Nature 2006; 3) Lee, Broedersz, Bialek, J Stat Phys 2015; 4) Louie et al. PNAS 2018.