Data and code for Immigrant birds use payoff biased social learning in spatially variable environments

The repository contains the data and code to reproduce the study "Immigrant birds use payoff biased social learning in spatially variable environments". Please consult the readme file for file descriptions and locations, and descriptions of variable names. We simulated immigration events between captive experimental populations of great tits (Parus major) to test whether spatial variability in environmental cues or payoffs affected the degree to which immigrant birds used social information. We analyzed birds' preferences before and after immigration, and used Bayesian learning models to understand the mechanisms behind change (or lack-thereof) in preferences. Behavioral data was collected using automated puzzle boxes in an experiment using captive wild-caught great tits (Parus major). The experiment took place over 2 periods: Jan-March 2021, and Jan-March 2022. All work was conducted by under a nature conservation permit and animal ethics permit from the Regierungsprasidium Freiburg, no.35-9185.81/G-20/100.

本存储库包含了再现研究《移民鸟类在空间可变环境中利用收益偏好的社会学习》所需的数据和代码。请参阅readme文件以获取文件描述、位置信息以及变量名称的说明。我们模拟了实验种群中金翅雀（Parus major）的移民事件，以检验环境线索或收益的空间变异性是否影响了移民鸟类利用社会信息的程度。我们分析了移民前后鸟类的偏好，并采用贝叶斯学习模型来理解偏好变化（或缺乏变化）背后的机制。行为数据是通过使用自动谜题箱在捕捉的野生金翅雀（Parus major）的实验中收集的。实验分为两个阶段：2021年1月至3月，以及2022年1月至3月。所有工作均在Regierungsprasidium Freiburg颁发的自然保护许可证和动物伦理许可证（编号35-9185.81/G-20/100）的指导下进行。