1. The study of the diversity of animal signals on within‐ and among‐species levels is the key to uncover mechanisms that shape the evolution of communication systems. However, the methods used to quantify acoustic diversity (like repertoire size) lack to grasp several aspects of acoustic diversity. Here, we propose a new framework for the study of animal communication, in which we decompose the acoustic diversity with the methodological toolbox from community ecology.
2. We explore how different diversity estimates reflecting different aspects of acoustic diversity can be applied to characterise the complexity of acoustic signals. We propose that this approach can be used in a wide range of animal taxa to derive further insights about the function and evolution of communication systems besides the traditional methods.
3. To illustrate the use of our approach in a case study, we used the song of the collared flycatcher Ficedula albicollis as model system. Based on three frequency and time variables, we calculated three functional diversity indices (FRic, FEve and FDiv) to characterise the distribution of song elements (syllables) in the acoustic parameter space. We aimed to uncover the interrelations of diversity indices, reveal the degree of among‐individual consistency and investigate their relationships with certain aspects of individual quality (body condition, age and arrival date).
4. We found that the diversity indices were largely independent of each other and showed different consistency patterns that were time‐scale dependent, indicating different signalling potential of individual‐specific attributes. We also found that FEve strongly related to the age of males. Our case study showed that decomposing the diversity into different components can reveal additional biologically meaningful aspects of birdsong.

中文翻译：

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一种通过社区生态学方法测量声多样性的实用方法

1. 在种内和种间水平上研究动物信号的多样性是发现影响通信系统发展的机制的关键。但是，用于量化声学分集（如曲目大小）的方法缺少掌握声学分集的几个方面的方法。在这里，我们提出了一个动物交流研究的新框架，在该框架中，我们使用了来自社区生态学的方法学工具箱来分解声学多样性。
2. 我们探索如何将反映声学分集不同方面的不同分集估计值应用于表征声学信号的复杂性。我们建议，这种方法可以用于广泛的动物分类中，以获取除传统方法之外的有关通信系统功能和演进的更多见解。
3. 为了说明我们的方法在案例研究中的使用，我们使用了衣领fly蝇Ficedula albicollis的歌曲作为模型系统。基于三个频率和时间变量，我们计算了三个功能多样性指数（FRic，FEve和FDiv）来表征声学参数空间中歌曲元素（音节）的分布。我们旨在揭示多样性指数的相互关系，揭示个体之间的一致性程度，并研究它们与个体素质的某些方面（身体状况，年龄和到达日期）之间的关系。
4. 我们发现多样性指数在很大程度上彼此独立，并显示出不同的一致性模式，这些模式随时间的变化而变化，表明个体特有属性具有不同的发信号潜力。我们还发现，FEve与男性年龄密切相关。我们的案例研究表明，将多样性分解为不同的组成部分可以揭示鸟鸣的其他生物学意义。