Garland Ellen C, Rendell Luke, Lilley Matthew S, Poole M Michael, Allen Jenny, Noad Michael J
School of Biology, University of St. Andrews, St. Andrews, Fife, KY16 9TH, United Kingdom.
SecuritEase International, Level 8, IBM Tower, 25 Victoria Street, Petone, 5012, New Zealand.
J Acoust Soc Am. 2017 Jul;142(1):460. doi: 10.1121/1.4991320.
Identifying and quantifying variation in vocalizations is fundamental to advancing our understanding of processes such as speciation, sexual selection, and cultural evolution. The song of the humpback whale (Megaptera novaeangliae) presents an extreme example of complexity and cultural evolution. It is a long, hierarchically structured vocal display that undergoes constant evolutionary change. Obtaining robust metrics to quantify song variation at multiple scales (from a sound through to population variation across the seascape) is a substantial challenge. Here, the authors present a method to quantify song similarity at multiple levels within the hierarchy. To incorporate the complexity of these multiple levels, the calculation of similarity is weighted by measurements of sound units (lower levels within the display) to bridge the gap in information between upper and lower levels. Results demonstrate that the inclusion of weighting provides a more realistic and robust representation of song similarity at multiple levels within the display. This method permits robust quantification of cultural patterns and processes that will also contribute to the conservation management of endangered humpback whale populations, and is applicable to any hierarchically structured signal sequence.
识别和量化发声的变化对于推进我们对物种形成、性选择和文化进化等过程的理解至关重要。座头鲸(Megaptera novaeangliae)的歌声展现了复杂性和文化进化的极端例子。它是一种长的、层次结构的发声展示,不断经历进化变化。获得可靠的指标以在多个尺度上(从声音到跨海洋景观的种群变化)量化歌声变化是一项重大挑战。在此,作者提出了一种在层次结构内多个层面量化歌声相似度的方法。为了纳入这些多个层面的复杂性,相似度的计算通过声音单元(展示中的较低层面)的测量进行加权,以弥合上下层面之间的信息差距。结果表明,加权的纳入在展示内的多个层面提供了更现实和可靠的歌声相似度表示。这种方法允许对文化模式和过程进行可靠量化,这也将有助于濒危座头鲸种群的保护管理,并且适用于任何层次结构信号序列。