Affordable, autonomous recording devices facilitate large scale acoustic monitoring and Rapid Acoustic Survey is emerging as a cost-effective approach to ecological monitoring; the success of the approach rests on the development of computational methods by which biodiversity metrics can be automatically derived from remotely collected audio data. Dozens of indices have been proposed to date, but systematic validation against classical, in situ diversity measures are lacking. This study conducted the most comprehensive comparative evaluation to date of the relationship between avian species diversity and a suite of acoustic indices. Acoustic surveys were carried out across habitat gradients in temperate and tropical biomes. Baseline avian species richness and subjective multi-taxa biophonic density estimates were established through aural counting by expert ornithologists. 26 acoustic indices were calculated and compared to observed variations in species diversity. Five acoustic diversity indices (Bioacoustic Index, Acoustic Diversity Index, Acoustic Evenness Index, Acoustic Entropy, and the Normalised Difference Sound Index) were assessed as well as three simple acoustic descriptors (Root-mean-square, Spectral centroid and Zero-crossing rate). Highly significant correlations, of up to 65%, between acoustic indices and avian species richness were observed across temperate habitats, supporting the use of automated acoustic indices in biodiversity monitoring where a single vocal taxon dominates. Significant, weaker correlations were observed in neotropical habitats which host multiple non-avian vocalizing species. Multivariate classification analyses demonstrated that each habitat has a very distinct soundscape and that AIs track observed differences in habitat-dependent community composition. Multivariate analyses of the relative predictive power of AIs show that compound indices are more powerful predictors of avian species richness than any single index and simple descriptors are significant contributors to avian diversity prediction in multi-taxa tropical environments. Our results support the use of community level acoustic indices as a proxy for species richness and point to the potential for tracking subtler habitat-dependent changes in community composition. Recommendations for the design of compound indices for multi-taxa community composition appraisal are put forward, with consideration for the requirements of next generation, low power remote monitoring networks.

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.

In line with the development of socio-ecological perspectives in conservation science, there is increasing interest in the role of soundscape perception in understanding human-environment interactions; the impact of natural soundscapes on human wellbeing is also increasingly recognized. However, research to date has focused on preferences and attitudes to western, urban locations. This study investigated individual emotional associations with local soundscape for three social groups living in areas with distinct degrees of urbanization, from pristine forest and pre-urban landscapes in Ecuador, to urban environments in UK and USA. Participants described sounds that they associated with a range of emotions, both positive and negative, which were categorized according to an adapted version of Schafer’s sound classification scheme. Analyses included a description of the sound types occurring in each environment, an evaluation of the associations between sound types and emotions across social groups, and the elaboration of a soundscape perception map. Statistical analyses revealed that the distribution of sound types differed between groups, reflecting essential traits of each soundscape, and tracing the gradient of urbanization. However, some associations were universal: Natural Sounds were primarily associated with positive emotions, whereas Mechanical and Industrial Sounds were linked to negative emotions. Within non-urban environments, natural sounds were associated with a much wider range of emotions. Our analyses suggest that Natural Sounds could be considered as valuable natural resources that promotes human wellbeing. Special attention is required within these endangered forest locations, which should be classified as a “threatened soundscapes,” as well as “threatened ecosystems,” as we begin to understand the role of soundscape for the wellbeing of the local communities. The methodology presented in this article offers a fast, cheap tool for identifying reactions towards landscape modification and identifying sounds of social relevance. The potential contribution of soundscape perception within the current conservation approaches is discussed.

Background. Wellbeing issues are increasingly incorporated within conservation biology and 5 environmental sciences, both in academic research and in applied policies such as the global 6 sustainable development plans. The role of landscape on human wellbeing has been widely 7 reported, but a comprehensive understanding of the role of soundscape has yet to be explicated. 8Research on the influences of sound on wellbeing has been conducted across a range of disciplines, 9 but integration of findings is impeded by linguistic and cultural differences across disciplinary 10 boundaries. This study presents the largest systematic literature review (2499 publications) of 11 research to date, addressing the association between soundscape and human/ecological wellbeing. 12Method. It is divided in two components: 1. rapid visualisation of publication metrics using the

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 approaches. In line with the emerging field of Soundscape Ecology (Pijanowski et al., 2011), the acoustic approach is based on the rationale that the ecological processes occurring within a landscape are tightly linked to and reflected in the high-level structure of the patterns of sounds emanating from those landscapes – the soundscape. Rather than attempting to recognise species-specific calls, either manually or automatically, analysis of the high-level structure of the soundscape tackles the problem of diversity assessment at the community (rather than species) level (Pijanowski et al., 2011; Farina, 2014). Preliminary work has attempted to make a case for community-level acoustic indices (e.g. Pieretti et al., 2011; Farina, 2014; Sueur et al., 2008); existing indices provide simple statistical summaries of the frequency or time domain signal. We suggest that under this approach, the opportunity to analyse spectro-temporal structural information is diminished, limiting power both as monitoring and investigative tools. In this paper we consider sparse-coding and source separation algorithms (SIPLCA-2D) as a means to access and summarise ecologically-meaningful sound objects. In doing so we highlight a possible new approach for understanding and assessing ecologically relevant interactions within the conceptual framework of Soundscape Ecology.