University of Greifswald, Zoological Institute and Museum, Applied Zoology and Nature Conservation, Greifswald, Germany.
NACHTaktiv - Biologists for Bat research GbR, Erfurt, Germany.
PLoS One. 2018 Jun 21;13(6):e0199428. doi: 10.1371/journal.pone.0199428. eCollection 2018.
Population sex ratios are of high ecological relevance, but are challenging to determine in species lacking conspicuous external cues indicating their sex. Acoustic sexing is an option if vocalizations differ between sexes, but is precluded by overlapping distributions of the values of male and female vocalizations in many species. A method allowing the inference of sex ratios despite such an overlap will therefore greatly increase the information extractable from acoustic data. To meet this demand, we developed a novel approach using Approximate Bayesian Computation (ABC) to infer the sex ratio of populations from acoustic data. Additionally, parameters characterizing the male and female distribution of acoustic values (mean and standard deviation) are inferred. This information is then used to probabilistically assign a sex to a single acoustic signal. We furthermore develop a simpler means of sex ratio estimation based on the exclusion of calls from the overlap zone. Applying our methods to simulated data demonstrates that sex ratio and acoustic parameter characteristics of males and females are reliably inferred by the ABC approach. Applying both the ABC and the exclusion method to empirical datasets (echolocation calls recorded in colonies of lesser horseshoe bats, Rhinolophus hipposideros) provides similar sex ratios as molecular sexing. Our methods aim to facilitate evidence-based conservation, and to benefit scientists investigating ecological or conservation questions related to sex- or group specific behaviour across a wide range of organisms emitting acoustic signals. The developed methodology is non-invasive, low-cost and time-efficient, thus allowing the study of many sites and individuals. We provide an R-script for the easy application of the method and discuss potential future extensions and fields of applications. The script can be easily adapted to account for numerous biological systems by adjusting the type and number of groups to be distinguished (e.g. age, social rank, cryptic species) and the acoustic parameters investigated.
人口性别比例具有很高的生态相关性，但在缺乏明显外部线索表明其性别的物种中，确定性别比例具有挑战性。如果雌雄个体的发声存在差异，那么可以通过声学性别鉴定来确定性别，但在许多物种中，雄性和雌性发声值的分布存在重叠，这种方法就不适用了。因此，即使存在这种重叠，也有一种方法可以推断出性别比例，这将大大增加从声学数据中提取的信息量。为了满足这一需求，我们开发了一种使用近似贝叶斯计算 (ABC) 的新方法，从声学数据中推断出种群的性别比例。此外，还推断出了描述雄性和雌性发声值（均值和标准差）分布的参数。然后，将这些信息用于概率性地为单个声学信号分配性别。我们还开发了一种更简单的性别比例估计方法，基于排除重叠区域的叫声。应用我们的方法对模拟数据进行演示，表明 ABC 方法可以可靠地推断出雄性和雌性的性别比例和声学参数特征。将 ABC 方法和排除方法应用于实证数据集（在小马蹄蝠，Rhinolophus hipposideros 的群体中记录的回声定位叫声），提供了与分子性别鉴定相似的性别比例。我们的方法旨在促进基于证据的保护，并为研究与各种生物体发出声学信号有关的生态或保护问题的科学家提供帮助，这些生物体包括与性别或群体特定行为有关的问题。所开发的方法是非侵入性的、低成本的和高效的，因此允许对许多地点和个体进行研究。我们提供了一个 R 脚本，用于轻松应用该方法，并讨论了潜在的未来扩展和应用领域。该脚本可以通过调整要区分的群体类型和数量（例如年龄、社会等级、隐存物种）以及研究的声学参数，轻松适应许多生物系统。
