Using Approximate Bayesian Computation to infer sex ratios from acoustic data

PLoS One. 2018 Jun 21;13(6):e0199428. doi: 10.1371/journal.pone.0199428. eCollection 2018.

Abstract

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acoustics*
  • Animals
  • Bayes Theorem
  • Chiroptera / physiology*
  • Computer Simulation*
  • Databases as Topic
  • Female
  • Male
  • Sex Ratio*
  • Vocalization, Animal / physiology

Grants and funding

LL was funded by a PhD position in the framework of the RTG 2010 Research Training Programme (Deutsche Forschungsgemeinschaft, German Science Foundation DFG; http://www.dfg.de/; grant awarded to SJP, GK). Additional financial support was provided by the Deutsche Bundesstiftung Umwelt DBU (https://www.dbu.de/; German Federal Environmental Foundation, AZ3186-45) and the Bundesinstitut für Bau-, Stadtund Raumforschung BBSR (http://www.bbsr.bund.de/; Federal Institute for Research on Building, Urban Affairs, and Spatial Development, AZ WD-10.08.18.7-14.23), both awarded to IK, WS, MB. Three of the authors are employees of NACHTaktiv, an environmental consultancy involved in bat monitoring and impact assessment studies for bats. NACHTaktiv provided support in the form of salaries for authors WS, IK, MB, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.