Assessing the value of acoustic indices to distinguish species and quantify activity: A case study using frogs

• Published in: Freshwater biology 2020-01, Vol.65 (1), p.142-152
• Main Authors: Indraswari, Karlina, Bower, Deborah S., Tucker, David, Schwarzkopf, Lin, Towsey, Michael, Roe, Paul
• Format: Article
• Language: English
• Subjects: Acoustic noise; Acoustics; Amphibians; Case studies; Complexity; Computer applications; Correlation; Duration; Entropy; Exploration; Frequency ranges; Frequency spectra; Frequency spectrum; Frogs; Harmonics; Information processing; Intervals; Loudness; Noise; Species
• ISSN: 0046-5070; 1365-2427
• DOI: 10.1111/fwb.13222

Soundscapes can provide information about a wide range of habitats and species through the recording of vocalisations over long temporal scales. Because of the large volumes of data collected, computational approaches, such as the application of acoustic indices, are required to extract useful information from long‐duration recordings. Acoustic indices summarise various soundscape features into frequency ranges over defined time intervals and can aid in the visual exploration, detection, and analysis of species vocalisation patterns. Here, we examine the performance of combinations of three acoustic indices commonly used in visual exploration, the acoustic complexity index, the temporal entropy spectrum index, and the event spectrum index, and assess their ability to distinguish species and describe acoustic features commonly used to detect species and analyse activity. Our case study focuses on three frog species with distinct call structures from Bickerton Island, Northern Territory, Australia. Call structure was categorised based on the number of pulses and harmonics. We summarised acoustic activity by calculating acoustic indices in 256 equal‐sized bins over the entire the frequency spectrum, for 30‐s intervals, and found that acoustic index values could be used to distinguish species and describe acoustic features. The acoustic complexity index was the most effective index for distinguishing species. To describe acoustic features, we examined correlations between acoustic index values and summarised acoustic features, including call rate, total duration, loudness and signal‐to‐noise ratio. In single‐pulsed species with no harmonics, we found spectral index values were significantly and sometimes strongly correlated with acoustic features. In comparison, species with harmonics were found to be weakly and less frequently correlated with acoustic features even if sampled calls were loud and have high signal‐to‐noise ratio. We suggest that acoustic indices have the potential to describe acoustic features in single‐pulsed species but are limited in those with harmonics. We conclude that acoustic indices can be a useful tool to distinguish some anuran species and to broadly understand specific acoustic features used to analyse calling activity over long periods of time. Further research is required to better understand the relationships between acoustic indices and acoustic features to determine the general utility of indices to detect and distinguish audib