The paradox of learned song in a semi‐solitary mammal

Abstract

AbstractLearning can occur via trial and error; however, learning from conspecifics is faster and more efficient. Social animals can easily learn from conspecifics, but how do less social species learn? In particular, birds provide astonishing examples of social learning of vocalizations, while vocal learning from conspecifics is much less understood in mammals. We present a hypothesis aimed at solving an apparent paradox: how can harbor seals (Phoca vitulina) learn their song when their whole lives are marked by loose conspecific social contact? Harbor seal pups are raised individually by their mostly silent mothers. Pups' first few weeks of life show developed vocal plasticity; these weeks are followed by relatively silent years until sexually mature individuals start singing. How can this rather solitary life lead to a learned song? Why do pups display vocal plasticity at a few weeks of age, when this is apparently not needed? Our hypothesis addresses these questions and tries to explain how vocal learning fits into the natural history of harbor seals, and potentially other less social mammals. We suggest that harbor seals learn during a sensitive period within puppyhood, where they are exposed to adult males singing. In particular, we hypothesize that, to make this learning possible, the following happens concurrently: (1) mothers give birth right before male singing starts, (2) pups enter a sensitive learning phase around weaning time, which (3) coincides with their foraging expeditions at sea which, (4) in turn, coincide with the peak singing activity of adult males. In other words, harbor seals show vocal learning as pups so they can acquire elements of their future song from adults, and solitary adults can sing because they have acquired these elements as pups. We review the available evidence and suggest that pups learn adult vocalizations because they are born exactly at the right time to eavesdrop on singing adults. We conclude by advancing empirical predictions and testable hypotheses for future work.