Abstract
Passive acoustic monitoring is emerging as a promising non-invasive proxy for ecological complexity with potential as a tool for remote assessment and monitoring (Sueur & Farina, 2015). Rather than attempting to recognise species-specific calls, either manually or automatically, there is a growing interest in evaluating the global acoustic environment. Positioned within the conceptual framework of ecoacoustics, a growing number of indices have been proposed which aim to capture community-level dynamics by (e.g., Pieretti, Farina & Morri, 2011; Farina, 2014; Sueur et al., 2008b) by providing statistical summaries of the frequency or time domain signal. Although promising, the ecological relevance and efficacy as a monitoring tool of these indices is still unclear. In this paper we suggest that by virtue of operating in the time or frequency domain, existing indices are limited in their ability to access key structural information in the spectro-temporal domain. Alternative methods in which time-frequency dynamics are preserved are considered. Sparse-coding and source separation algorithms (specifically, shift-invariant probabilistic latent component analysis in 2D) are proposed as a means to access and summarise time-frequency dynamics which may be more ecologically-meaningful.
Highlights
Biodiversity assessment is a central and urgent task, for research in the biological sciences, and in applied conservation biology, including major multi-lateral initiatives for promoting and protecting biodiversity
The main contribution of this paper is to highlight a disjunct between a founding premise of ecoacoustics and the fact that community level indices to date are derived from representations of the acoustic signal in the time or frequency domain and limited in accessing and evaluating structures across spectro-temporal dimensions
Monitoring subtle changes in complex ecosystems is crucial for ecological research and conservation but far from straight forward
Summary
Biodiversity assessment is a central and urgent task, for research in the biological sciences, and in applied conservation biology, including major multi-lateral initiatives for promoting and protecting biodiversity. Toward the extraction and evaluation of ecologicallymeaningful soundscape components using sparse coding methods. The main contribution of this paper is to highlight a disjunct between a founding premise of ecoacoustics (that the acoustic environment is structured through spectro-temporal partitioning) and the fact that community level indices to date are derived from representations of the acoustic signal in the time or frequency domain and limited in accessing and evaluating structures across spectro-temporal dimensions. We consider approaches to decomposition which preserve time-frequency structure and propose sparse-coding as a possible solution. Ecoacoustic applications are illustrated with example analyses from a recent acoustic survey. Results are illustrative rather than conclusive but point to possibilities for analyses of community level acoustic structures which are impervious to investigation with current tools
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