Data for 'Translocated wild birds are predisposed to learn songs of their ancestral population'

Published: 9 May 2024| Version 1 | DOI: 10.17632/h6mn2jp3d9.1
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Description

Data and code to reproduce results and figures from 'Translocated wild birds are predisposed to learn songs of their ancestral population'. Abstract: Population differences in socially learned mating signals like oscine birdsong are particularly vulnerable to breakdown through dispersal. Despite this challenge, geographic variation in learned signals is ubiquitous. A proposed explanation for this pattern is that birds express predispositions to selectively learn and produce population typical songs. While experimental studies on lab-reared birds have shown the existence of within-species learning predispositions, it remains unclear whether and how learning predispositions influence song acquisition in the wild. Here, we investigated innate song learning predispositions in wild pied flycatchers (Ficedula hypoleuca) by measuring the songs of individuals translocated as eggs from a Dutch population to a breeding population in Sweden. We compared the songs of the adult males hatched from these translocated eggs with those from the ancestral and receiving populations. Songs of translocated males closely resemble the local Swedish songs to which they were exposed during development, supporting the importance of social learning. However, translocated males selectively learned those local Swedish song elements that sound the most ‘Dutch-like’. As a result, their songs are significantly shifted towards those of the ancestral Dutch population. This suggests that innate learning predispositions track ongoing song evolution in wild populations of pied flycatchers. We propose that as songs continue to diverge over time, this coevolutionary relationship between song and learning predispositions may contribute to the emergence of incipient pre-mating barriers.

Files

Steps to reproduce

R v4.2.0. See READme file for more information about datasets, relationship between data and code files and variable specific information.

Institutions

Stockholms Universitet Zoologiska Institutionen

Categories

Behavioral Ecology, Speciation, Song Learning, Dual Inheritance Theory

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