Geographic patterns of song variation reveal timing of song acquisition in a wild avian population

Geographic patterns of song variation are common in passerines and can develop as a consequence of the mechanisms of song acquisition and dispersal. In particular, the timing of dispersal relative to the sensory learning phase and the time of song crystallization is important. For example, when the sensory phase continues after dispersal or when males learn new songs every breeding season, i.e. open-ended learner, neighborhoods can develop where males share their songs. In this study, we utilize a unique, comprehensive dispersal and song recording dataset to investigate the existence and development of micro-geographic song variation in a wild passerine population. Machine learning song analysis methods allow us to overcome perceptual bias in the classification of the songs of New Zealand hihi (Notiomystis cincta). We show that males share more song elements of their repertoire with their neighbors than with more distant males or with males from the same natal area, implying that repert...鸣唱变异的地理格局在雀形目鸟类（Passerines）中极为常见，其形成往往源于鸣唱习得与扩散的相关作用机制。尤为关键的是，扩散时机相对于感觉学习阶段（sensory learning phase）与鸣唱定型期（song crystallization）的先后关系。例如，若感觉学习阶段在扩散后仍持续，或是雄性个体每个繁殖季都会学习新鸣唱（即开放式鸣唱学习者（open-ended learner）），则会形成雄性间共享鸣唱的邻里集群。本研究依托一套独特且全面的扩散与鸣唱录音数据集，旨在探究野生雀形目种群中微地理尺度鸣唱变异的存在性与形成过程。机器学习鸣唱分析方法帮助我们克服了新西兰吸蜜鸟（hihi，Notiomystis cincta）鸣唱分类中的感知偏差。研究结果表明，雄性个体与其邻近个体共享的鸣唱曲目元素，远多于与较远雄性或同出生地雄性共享的元素，这暗示鸣唱曲目……