Effectiveness of acoustic indices as indicators of vertebrate biodiversity
Open accessAbstract
Effective monitoring tools are key for tracking biodiversity loss and informing management intervention strategies. Passive acoustic monitoring promises to provide a cheap and effective way to monitor biodiversity across large spatial and temporal scales, however, extracting useful information from long-duration audio recordings still proves challenging. Recently, a range of acoustic indices have been developed, which capture different aspects of the soundscape, and may provide a way to estimate traditional biodiversity measures. Here we investigated the relationship between 13 acoustic indices obtained from passive acoustic monitoring and biodiversity estimates of various vertebrate taxonomic groupings obtained from manual surveys at six sites spanning over 20 degrees of latitude along the Australian east coast. We found a number of individual acoustic indices that correlated well with species richness, Shannon’s diversity index, and total individual count estimates obtained from traditional survey methods. Correlations were typically greater for avian and total vertebrate biodiversity than for anuran and non-avian vertebrate biodiversity. Acoustic indices also correlated better with species richness and total individual count than with Shannon’s diversity index. Random forest models incorporating multiple acoustic indices provided more accurate predictions than single indices alone. Out of the acoustic indices tested, cluster count, mid-frequency cover and spectral density contributed the greatest predictive ability to models. Our results suggest that models incorporating multiple acoustic indices could be a useful tool for monitoring certain vertebrate groups. Further work is required to understand how site-specific variables can be incorporated into models to improve predictive capabilities and how to improve the monitoring of taxa besides avians, particularly anurans.
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Using a set of acoustic indices instead of single ones is better for estimating biodiversity.
“Our findings add to the growing literature that shows that using a set of acoustic indices instead of single ones is better for estimating biodiversity50.”
From Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests (2023) · cites this paper as [50]
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- Authors
- Allen-Ankins, S., McKnight, D. T., Nordberg, E. J., Hoefer, S., Roe, P., Watson, D. M., McDonald, P. G., Fuller, R. A., & Schwarzkopf, L.
- Affiliations
- La Trobe University (AU)
- James Cook University (AU)
- Queensland University of Technology (AU)
- Charles Sturt University (AU)
- University of New England (AU)
- The University of Queensland (AU)
- ORCID
- Venue
- Ecological Indicators
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 147
- Pages
- 109937
- ISSN
- 1470-160X (ISSN-L)
- OpenAlex
- W4320341365
- Cited by
- 55
- References
- 54
- Citations by year
- 2026: 13 · 2025: 21 · 2024: 12 · 2023: 9
- FWCI
- 13.54
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Ecological Indicators (publishedVersion, cc-by-nc-nd)
- ResearchOnline - JCU (James Cook University) (submittedVersion)
- RUNE (Research UNE) (submittedVersion, cc-by-nc-nd)
- Charles Sturt University Research Output (CRO) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Funders
- Winifred Violet Scott Charitable Trust
- Australian Research Council (200101365)
- James Cook University (A2727)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Developmental Biology › Animal Vocal Communication and Behavior
- Physical Sciences › Environmental Science › Ecology › Wildlife Ecology and Conservation
- Physical Sciences › Environmental Science › Ecology › Avian ecology and behavior
- Keywords
- acoustic indices, passive acoustic monitoring, vertebrate diversity, biodiversity monitoring, soundscape, species richness, Shannon diversity index, bird diversity, random forest, eastern Australian coast
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