A new direction for Soundscape Ecology? Toward the extraction and evaluation of ecologically-meaningful soundscape objects using sparse coding methods (original) (raw)
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PeerJ, 2016
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2015
Efficient methods of biodiversity assessment and monitoring are central to ecological research and crucial in conservation management. Technological advances in remote acoustic sensing inspire new perspectives in ecology: environmental sound monitoring is emerging as a reliable non-invasive proxy for ecological complexity (Sueur and Farina, 2015). Rather than attempting to recognise species-specific calls, either manually or automatically, we are interested in monitoring the global acoustic environment, tackling the problem of diversity assessment at the community (rather than species) level. Preliminary work has attempted to make a case for community-level acoustic indices (e.g.
Acoustic Indices for Biodiversity Assessment and Landscape Investigation
Acta Acustica united with Acustica, 2014
Bioacoustics is historically adiscipline that essentially focuses on individual behaviour in relation to population and species evolutionary levels butr arely in connection with higher levels of ecological complexity likec ommunity,landscape or ecosystem. However, some recent bioacoustic researches have operated ac hange of scale by developing acoustic indices which aim is to characterize animal acoustic communities and soundscapes. We here reviewt hese indices for the first time. The indices can be divided into twoc lasses: the α or within-group indices and the β or between-group indices. Up to 21 α acoustic indices were proposed in less than six years. These indices estimate the amplitude, evenness, richness, heterogeneity of an acoustic community or soundscape. Seven β diversity indices were suggested to compare amplitude envelopes or,more often, frequencyspectral profiles. Both α and β indices reported congruent and expected results buttheymay still suffer some bias due, for instance, to anthropic background noise or variations in the distances between vocalising animals and the sensors. Research is still needed to improve the reliability of these newmathematical tools for biodiversity assessment and monitoring. We recommend the contemporary use of some of these indices to obtain complementary information. Eventually,weforesee that this newfield of research which tries to build bridges between animal behaviour and ecology should meet an important success in the next years for the assessment and monitoring of marine, freshwater and terrestrial biodiversity from individual-based leveltolandscape dimension. scale shedding newl ight on the acoustic behaviour and acoustic ecology of animals.
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Biodiversity and Conservation, 2018
The evolutionary success of a species is linked to its ability to communicate. Auditory, optic and olfactory systems are biological communication channels. Compared to the latter two, auditory systems are less impeded by physical obstructions. Successful species have effectively articulated this to their advantage. Decoding the acoustic dynamics of a landscape can ingeniously be crafted as a rapid tool to assess biological diversity. Here, we present results of the acoustic analysis carried out in three contrasting soundscapes in Kerala, India. Representative sound samples were recorded at Ernakulam, Kerala, India using Marantz PMD 661 III sonic recorder from 6.00 a.m. to 6.00 p.m. (IST) from an urban park [Hill Palace Museum (L1)], a sacred grove [Iringole Kavu (L2)], and a legally protected area Salim Ali Bird Sanctuary (L3). Acoustic characteristics of these sites expressed as Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bioacoustic Index (BI) and Normalized Difference Soundscape Index (NDSI) were related to corresponding avian diversity. The objective finding reveals the distinctiveness of sonic characteristics and the status of diversity in each soundscape. Rapid assessment of biodiversity using acoustic indices is a prospective option that can be adopted as a means to generate biodiversity indicators of Sustainable Develeopment Goals (SDGs).
Monitoring animal diversity using acoustic indices: Implementation in a temperate woodland
Ecological Indicators, 2012
Biodiversity assessment is one of the major challenges for ecology and conservation. With current increase of biodiversity loss during the last decades, there is an urgent need to quickly estimate biodiversity levels. This study aims at testing the validity of new biodiversity indices based on an acoustic analysis of choruses produced by animal communities. The new Acoustic Richness index (AR) and the former dissimilarity index (D) aim at assessing ␣ and  diversity respectively. Both indices were tested in three woodland habitats: a mature forest, a young forest and a forest-cropland ecotone within the Parc Naturel Régional of Haute-Vallée de Chevreuse (France). Three recorders running for 74 days generated 5328 files of 150 s for a total of 222 h of recording. All files were treated with frequency and amplitude filters to try to remove anthropogenic and environmental background noise. The AR index was in agreement with traditional aural identification of bird species. The AR index revealed an expected gradient of diversity with higher diversity values in the young forest that potentially provides a higher number of microhabitats. The D index also indicated expected differences in the acoustic environment across sites with distinct habitat structure. Both indices reveal significant peak during dawn chorus. These results suggest that diversity could be estimated through acoustics at both ␣ and  scales. Our analyses reveal that, even if background noise needs to be considered with great care, the use of acoustic indices has the potential to facilitate animal diversity assessments over seasons or years and landscape scales.
A framework for the quantification of soundscape diversity using Hill numbers
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Soundscape studies are increasingly common to capture landscape-scale ecological patterns. Yet, several aspects of soundscape diversity quantification remain unexplored. Although some processes influencing acoustic niche usage may operate in the 24h domain, most acoustic indices only capture the diversity of sounds co-occurring in sound files at a specific time of day. Moreover, many indices do not consider the relationship between the spectral and temporal traits of sounds simultaneously. To provide novel insights into landscape-scale patterns of acoustic niche usage at broader temporal scales, we present a workflow to quantify soundscape diversity through the lens of functional ecology.Our workflow quantifies the functional diversity of sound in the 24-hour acoustic trait space. We put forward an entity, the Operational Sound Unit (OSU), which groups sounds by their shared functional properties. Using OSUs as our unit of diversity measurement, and building on the framework of Hill...
Connecting soundscape to landscape: Which acoustic index best describes landscape configuration?
Soundscape assessment has been proposed as a remote ecological monitoring tool for measuring biodiversity, but few studies have examined how soundscape patterns vary with landscape configuration and condition. The goal of our study was to examine a suite of published acoustic indices to determine whether they provide comparable results relative to varying levels of landscape fragmentation and ecological condition in nineteen forest sites in eastern Australia. Our comparison of six acoustic indices according to time of day revealed that two indices, the acoustic complexity and the bioacoustic index, presented a similar pattern that was linked to avian song intensity, but was not related to landscape and biodiversity attributes. The diversity indices, acoustic entropy and acoustic diversity, and the normalized difference soundscape index revealed high nighttime sound, as well as a dawn and dusk chorus. These indices appear to be sensitive to nocturnal biodiversity which is abundant at night in warm, subtropical environments. We argue that there is need to better understand temporal partitioning of the soundscape by specific taxonomic groups, and this should involve integrated research on amphibians, insects and birds during a 24 h cycle. The three indices that best connected the soundscape with landscape characteristics, ecological condition and bird species richness were acoustic entropy, acoustic evenness and the normalized difference soundscape index. This study has demonstrated that remote soundscape assessment can be implemented as an ecological monitoring tool in fragmented Australian forest landscapes. However, further investigation should be dedicated to refining and/or combining existing acoustic indices and also to determine if these indices are appropriate in other landscapes and for other survey purposes.
A primer of acoustic analysis for landscape ecologists
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In this paper we present an introduction to the physical characteristics of sound, basic recording principles as well as several ways to analyze digital sound files using spectrogram analysis. This paper is designed to be a “primer” which we hope will encourage landscape ecologists to study soundscapes. This primer uses data from a long-term study that are analyzed using common software tools. The paper presents these analyses as exercises. Spectrogram analyses are presented here introducing indices familiar to ecologists (e.g., Shannon’s diversity, evenness, dominance) and GIS experts (patch analysis). A supplemental online tutorial provides detailed instructions with step by step directions for these exercises. We discuss specific terms when working with digital sound analysis, comment on the state of the art in acoustic analysis and present recommendations for future research.