On the use of the acoustic evenness index to monitor biodiversity: A comment on “Rapid assessment of avian species richness and abundance using acoustic indices” by Bradfer-Lawrence et al. (2020) [Ecological Indicators, 115, 106400]

Mammides, Christos; Goodale, Eben; Dayananda, Salindra K.; Luo, Kun; Jin, Chen

doi:10.1016/j.ecolind.2021.107626

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…Thus, variation in the vocal repertoire size exhibited by signalling species may critically influence the outputs and is an additional issue to be considered when using and interpreting acoustic indices. As a result, a low‐diversity community may give rise to audio recordings characterised by high acoustic diversity, and vice versa (Mammides et al ., 2021 ). Other confounding sources to take into account when relating acoustic indices to biological diversity are the ecological and evolutionary drivers of interspecific differences in acoustic features (among‐species sound diversity; see Section IV.2 ).…”

Section: Discussionmentioning

confidence: 99%

Acoustic indices as proxies for biodiversity: a meta‐analysis

et al. 2022

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As biodiversity decreases worldwide, the development of effective techniques to track changes in ecological communities becomes an urgent challenge. Together with other emerging methods in ecology, acoustic indices are increasingly being used as novel tools for rapid biodiversity assessment. These indices are based on mathematical formulae that summarise the acoustic features of audio samples, with the aim of extracting meaningful ecological information from soundscapes. However, the application of this automated method has revealed conflicting results across the literature, with conceptual and empirical controversies regarding its primary assumption: a correlation between acoustic and biological diversity. After more than a decade of research, we still lack a statistically informed synthesis of the power of acoustic indices that elucidates whether they effectively function as proxies for biological diversity. Here, we reviewed studies testing the relationship between diversity metrics (species abundance, species richness, species diversity, abundance of sounds, and diversity of sounds) and the 11 most commonly used acoustic indices. From 34 studies, we extracted 364 effect sizes that quantified the magnitude of the direct link between acoustic and biological estimates and conducted a meta-analysis. Overall, acoustic indices had a moderate positive relationship with the diversity metrics (r = 0.33, CI [0.23, 0.43]), and showed an inconsistent performance, with highly variable effect sizes both within and among studies. Over time, studies have been increasingly disregarding the validation of the acoustic estimates and those examining this link have been progressively reporting smaller effect sizes. Some of the studied indices [acoustic entropy index (H), normalised difference soundscape index (NDSI), and acoustic complexity index (ACI)] performed better in retrieving biological information, with abundance of sounds (number of sounds from identified or unidentified species) being the best estimated diversity facet of local communities. We found no effect of the type of monitored environment (terrestrial versus aquatic) and the procedure for extracting biological information (acoustic versus non-acoustic) on the performance of acoustic indices, suggesting certain potential to generalise their application across research contexts. We also identified common statistical issues and knowledge gaps that remain to be addressed in future research, such as a high rate of pseudoreplication and multiple unexplored combinations of metrics, taxa, and regions. Our findings confirm the limitations of acoustic indices to efficiently quantify alpha biodiversity and highlight that caution is necessary when using them as surrogates of diversity metrics, especially if employed as single predictors. Although these tools are able partially to capture changes in diversity metrics, endorsing to some extent the rationale behind acoustic indices and suggesting them as promising bases for future developments, they are far from being direct pr...

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Section: Discussionmentioning

confidence: 99%

Acoustic indices as proxies for biodiversity: a meta‐analysis

et al. 2022

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“…This high variation in vocalisations within the same species may critically influence AI values. As a result, a low‐diversity recording containing such species may lead to AI values that normally characterise high acoustic diversity (Mammides et al., 2021).…”

Section: Discussionmentioning

confidence: 99%

Forest edge structure from terrestrial laser scanning to explain bird biophony characteristics from acoustic indices

Verhelst

Vangansbeke

Frenne

et al. 2023

Remote Sens Ecol Conserv

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Forest edges can be important strongholds for biodiversity and play a crucial role in the protection of forest interiors against edge effects. However, their potential to host biodiversity is dependent on the structure of the forest: Abrupt edges often fail to realise this potential. Yet, methods to accurately characterise and quantify forest edge abruptness are currently lacking. Here, we combine three‐dimensional forest structural data with biodiversity monitoring to assess the influence of forest edge structure on habitat suitability. We derived several structural metrics to determine forest edge abruptness using terrestrial laser scanning and applied these to six forest edge transects in Belgium. The local soundscapes were captured using audio recording devices (Audiomoths) and quantified using acoustic indices (AIs) (metrics on the soundscape characteristics). In each transect, the dawn choruses were recorded over a period of a week, both at the edge and the interior of the forest. No correlation between the AIs and bird species richness was found. There were clear differences between transects in the structural metrics and the recorded soundscapes. Some possible relations between both were found. In this proof of concept, we demonstrated innovative techniques to semi‐automatically classify forest structure and rapidly quantify soundscape characteristics and found a weak effect of forest edge structure on bird biophony.

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“…Both ACI and ADI are proxies to quantify acoustic complexity (the higher the number, the more complex), while low values of AEI represent an even sound and higher values represent more uneven sounds. This is not correlated with the ecological concept of evenness, as acoustic evenness refers to an even distribution of sound energy in different frequency bands, and this can be achieved due to a high biodiversity vocalizing at the same time covering all the frequency bands or by constant broadband sounds such as some anthropogenic sounds 40,41 .…”

Section: Playback and Sound Characteristicsmentioning

confidence: 99%

Navigating Soundscapes: Attractant effect of reef sound on oyster settlement may be attenuated by vessel noise

Schmidlin,

Parcerisas,

Hubert

et al. 2024

Preprint

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Settlement is a critical period in the life cycle of benthic species with planktonic larval stages and for reef building invertebrates such as oysters and corals; settlement rates are predictive for reef restoration and long-term survival. Increasing evidence suggests that marine invertebrates use information from ocean soundscapes to inform settlement decisions. Sessile marine invertebrates with a settlement stage are particularly reliant on environmental cues to direct them to ideal habitats as settlement location is permanent. As gregarious settlers, oysters prefer to settle amongst members of the same species. It has been hypothesized that planktonic larvae use distinct oyster reef sounds to navigate to ideal habitats. In controlled laboratory experiments, we show that sounds recorded at conspecific reefs induce higher percentages of settlement in larvae of the Pacific Oyster Magallana gigas. Additionally, we exposed larvae to anthropogenic sounds from several different vessels, combined reef-vessel sounds as well as off-reef and no sound controls. Our results suggest that attractive reef noises may be masked by vessel sounds, however, this observation is substantiated by a nonsignificant trend. Examining the acoustic characteristics of the preferred reef sounds, we hypothesize that spectro-temporal patterns are the driving attractive quality in reef sounds for this species.

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On the use of the acoustic evenness index to monitor biodiversity: A comment on “Rapid assessment of avian species richness and abundance using acoustic indices” by Bradfer-Lawrence et al. (2020) [Ecological Indicators, 115, 106400]

Cited by 14 publications

References 4 publications

Acoustic indices as proxies for biodiversity: a meta‐analysis

Acoustic indices as proxies for biodiversity: a meta‐analysis

Forest edge structure from terrestrial laser scanning to explain bird biophony characteristics from acoustic indices

Navigating Soundscapes: Attractant effect of reef sound on oyster settlement may be attenuated by vessel noise

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