Ecoacoustic indices in marine ecosystems: a review on recent developments, challenges, and future directions

Abstract

Soundscape ecology has gained prominence in the monitoring of marine ecosystems due to its non-invasive characteristics and spatiotemporal efficiency. However, the development of ecoacoustic indices is a recent field that needs to address many challenges to fulfill its great potential, especially in the context of marine ecology. Here, we reviewed the most recent studies that used ecoacoustic indices in marine ecosystems. The literature search was conducted in the Scopus (Elsevier) database and used the chain referral sampling in the list of references of each publication. In total, we identified 27 publications that used ecoacoustic indices in marine environments such as coral reefs, rocky shores, coastal regions, and offshore regions. A total of four major limitations were identified and addressed, including: the challenge to find adequate acoustic bioindicators; the lack of a universal index or standardized protocol; the issue that most acoustic indices applied to marine environments have been developed to be used in terrestrial environments; and the lack of studies that have tested ecoacoustic indices under different environmental conditions. Once these challenges are addressed, the analysis of marine sound based on the interpretation of ecoacoustic indices has a great potential to become one of the most cost-effective tools for monitoring environments.

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

“…Our results suggest a dynamic relationship between underwater sounds and acoustic indices, and one that is not driven by any one sound characteristic. Minello et al (2021) suggested that soniferous species may not all have equal footing as acoustic bioindicator species for ecosystem health monitoring. Our results certainly reflect this sentiment, as was seen in the relationship between sperm whales and delphinids with ACI and BI.…”

“…The Acoustic Complexity Index (ACI) is an algorithm developed by Farina (2019) to provide a fast and direct quantification of biological sounds based on intensity. It is the most commonly assessed acoustic index in marine environments (Pieretti and Danovaro, 2020;Minello et al, 2021). ACI calculates the differences in amplitude in adjacent time samples for each frequency bin, then adds together the difference, thus representing a measure of complexity of the acoustic environment.…”

“…ACI was first applied to an underwater environment by McWilliam and Hawkins (2013) who identified a strong association with biological sounds. Subsequent marine-based studies report that ACI is a promising biodiversity metric as summarized most recently by Minello et al (2021). However, other studies have reported that this metric varies greatly in association with underwater sounds (Kaplan et al, 2015;Bohnenstiehl et al, 2018;Bolgan et al, 2018).…”

Make the CPUs do the hard work - Automated acoustic feature extraction and visualization for marine ecoacoustics applications illustrated using marine mammal Passive Acoustic Monitoring datasets

“…More than 60 different ecoacoustic indices are being employed as descriptors of terrestrial soundscapes (Bradfer-Lawrence et al, 2019), making the search for indices that are successfully measuring biodiversity across widely variable environments very challenging (Minello et al, 2021). So far, ecoacoustic indices have been applied to marine environments with little success (Bohnenstiehl et al, 2018).…”

“…Due to higher sound propagation efficiency, marine acoustic environments can receive acoustic energy from many sources with some that are hundreds of kilometres distant, making them more complex to study than terrestrial environments. Accordingly, the biases shown by acoustic indices measuring terrestrial species diversity (Eldridge et al, 2018;Fairbrass et al, 2017;Heath et al, 2021) are amplified when transferred to the study of marine environments (Bohnenstiehl et al, 2018;Dimoff et al, 2021;Minello et al, 2021).…”