Modelling Birdsong Evolution

在许多鸟类中，年轻的雄性从他们的父亲那里学习他们的歌声。但学习是在错误中发生的，所以歌曲可以代代相传。这种文化传播的行为吸引了公众，并对保护具有重要意义。鸟类用歌声来选择配偶，因此，如果部分孤立的种群之间的歌声出现分歧，这可能会阻止这些种群交换基因，减少遗传多样性，威胁物种的生存能力。鸟鸣进化的数据驱动机制模型可以帮助我们理解鸟鸣进化，但这样的模型很少存在。鸟鸣进化在某些方面类似于基因组进化。音符扮演着核苷酸的角色，突变(即复制错误)可以将一种音符改变为另一种音符。可以插入、删除或复制音符或歌曲片段。因此，来自分子系统发育学的工具可能会为模拟鸟类鸣叫的代际变化提供基础。然而，基因组和鸟鸣之间有重要的区别。例如，个体只有一个基因组，但一只鸟可能会唱许多不同的歌。基因组只由四个核苷酸组成，但鸟鸣通常不止有四个不同的音符，而且--至少在原则上--完全可以出现新的音符。此外，由于相关鸟鸣之间的变化比遗传变化更常见，为了研究而对鸟鸣进行比对是困难的，可能需要从多个可能的比对中得出推断。需要新的数学和统计方法来克服这些挑战。本专业的学生将开发新的数学模型来描述和预测鸟鸣的进化。这些模型将有助于解释动物文化是如何进化的，并将应用于就地和迁地保护。该项目将由一个团队提供建议，其中包括曼彻斯特大学的一名应用数学家、数学生态学家和语言学家，以及北海道大学的一名动物行为学家和鸟鸣专家。

In many bird species, young males learn their songs from their fathers. But learning occurs with error, so songs can change over generations. This culturally transmitted behaviour fascinates the public and has important implications for conservation. Birds use songs to choose mates, so if songs diverge between partly isolated populations, this may prevent those populations from exchanging genes, diminishing genetic diversity and threatening the species viability. Data-driven mechanistic models of the evolution of birdsong could help us understand birdsong evolution, but few such models exist.Birdsong evolution is in some ways analogous to genome evolution. Notes play the role of nucleotides, and mutations (i.e., errors in copying) can change one note to another. Notes or song segments can be inserted, deleted, or duplicated. Tools from molecular phylogenetics may thus provide a foundation for modelling the generation-to-generation change in birds' songs. There are, however, important differences between genomes and birdsongs. For example, individuals have a single genome, but a bird may sing many different songs. Genomes are comprised of only four nucleotides, but birdsongs typically have many more than four different notes and - at least in principle - entirely new notes can arise. Furthermore, because changes between related birdsongs are more common than genetic changes, aligning birdsongs for study is difficult, and inferences may need to be drawn from multiple possible alignments. Novel mathematical and statistical approaches are needed to overcome these challenges.The student in this will develop novel mathematical models to describe and predict the evolution of birdsong. These models will help explain how animal cultures evolve and will have applications for in situ and ex situ conservation. The project will be advised by a team including an applied mathematician, a mathematical ecologist and a linguist at the University fo Manchester as well as an animal behaviourist who is a birdsong expert at the University of Hokkaido.