Using citizen science to test for acoustic niche partitioning in frogs

Abstract

The acoustic niche hypothesis proposes that to avoid interference with breeding signals, vocal species should evolve to partition acoustic space, minimising similarity with co-occurring signals. Tests of the acoustic niche hypothesis are typically conducted using a single assemblage, with mixed outcomes, but if the process is evolutionarily important, a pattern of reduced acoustic competition should emerge, on average, over many communities. Using a continental-scale dataset derived from audio recordings collected by citizen scientists, we show that frogs do partition acoustic space. Differences in calls were predominately caused by differences in spectral, rather than temporal, features. Specifically, the 90% frequency bandwidths of observed frog assemblages overlapped less than expected, and there was greater distance between dominant frequencies than expected. To our knowledge, this study is the first to use null models to test for acoustic niche partitioning over a large geographic scale.

Figure 1

(a) Spectrogram, oscillogram and power spectrum of sample frog call (Adelotus brevis) showing the various call parameters measured to determine acoustic similarity among calls of different frog species. (b) Map of records used for spectral overlap, PCA_All, PCA_Spectral and PCA_Temporal (red points, n = 1641), and dominant frequency distance (red and black points, n = 1854) analyses overlayed on Australia’s 7 ecoregions representing the different broad habitat types from which frog assemblages originate (TrFo = Tropical and Subtropical Moist Broaleaf Forests, TeFo = Temperate Broadleaf and Mixed Forests, TrGr = Tropical and Subtropical Grasslands, Savannas and Shrublands, TeGr = Temperatre Grasslands, Savannas and Shrublands, MoGr = Montane Grasslands and Shrublands, MeFo = Mediterranean Forests, Woodlands and Scrub, DeSh = Deserts and Xeric Shrublands). Figures generated using R version 3.6.1 (https://www.r-project.org/). Annotations on a) added with GIMP version 2.10.6 (https://www.gimp.org/).

Figure 2

Standardised effect sizes of mean pairwise differences between observed and null assemblages for each measure of acoustic similarity. PCA_X measures represent the Euclidean distances between calls from the first three principal components of a PCA on either all measured call parameters, spectral call parameters only, or temporal call parameters only. Spectral overlap is the proportion of overlap between species 90% frequency bandwidths. Dominant frequency distance is the difference between species dominant frequencies in log₁₀ Hz. Positive values indicate a trend towards acoustic niche partitioning, while negative values indicate a trend towards acoustic niche aggregation. Note The sign of values for spectral overlap have been reversed so that they are comparable with the other four acoustic similarity measures which are all based on distance. Figure generated using R version 3.6.1 (https://www.r-project.org/).