AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment

Hill, Andrew P.; Prince, P. Grace Kanmani; Piña‐Covarrubias, Evelyn; Doncaster, C. Patrick; Snaddon, Jake L.; Rogers, Alex

doi:10.1111/2041-210x.12955

Cited by 327 publications

(271 citation statements)

References 29 publications

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“…Today, two approaches dominate the scene. Here, the conversion of the sound data can be achieved by experts, semi-automated algorithms or machine learning techniques such as deep learning (Hill et al 2018, Ovaskainen et al 2018, Stowell et al 2018. The second one depends on converting the sound data to more conventional matrices of either species incidence and/or abundance at different sites (Chambert et al 2018, Darras et al 2018.…”

Section: Soundscape-area and Soundscape-time Relations As Descriptorsmentioning

confidence: 99%

Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

2019

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Automated analysis of acoustic communities is a rapidly emerging approach for the characterization and monitoring of biodiversity. To evaluate its utility, we should verify that such 'bioacoustics' can accurately detect ecological signal in spatiotemporal acoustic data. Targeting the 'Biological Dynamics of Forest Fragments Project' sites in Brazil, we ask: What is the relative contribution of the spatial, temporal and habitat dimension to variation in bird acoustic communities in a previously fragmented tropical rainforest? Does the functional diversity of bird communities scale similarly to space and time as does species diversity, when both are recorded by bioacoustics means? Overall, is the imprint of landscape fragmentation 30 years ago still audible in the present-day soundscape? We sampled forty-four sites in secondary forest and 107 sites in old-growth forest, resulting in 11 000 h of audio recordings. We detected 60 bird species with satisfactory precision and recovered a linear log-log relation between sampling time and species diversity. Sites in primary forest host more species than sites in secondary forest, but the difference decreased with sampling time, as the slope was slightly higher in secondary than primary forests. Functional diversity, as exposed by vocalizing birds, accumulates faster than does species diversity. The similarity among local communities decreases with distance in both time and space, but stability in time is remarkably high: two acoustic samples from the same site one year (or more) apart prove more similar than two samples taken at the same time but from sites situated just a few hundred meters apart. These findings suggest that habitat modification can be heard as a long-lasting imprint on the soundscape of regenerating habitats and identify soundscape-area and soundscape-time relations as a promising tool for biodiversity research, applied biomonitoring and restoration ecology.

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Section: Soundscape-area and Soundscape-time Relations As Descriptorsmentioning

confidence: 99%

Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

2019

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“…Additionally, the high price of electronic sensors in wildlife research has likely been an important driver towards the recent proliferation of open‐source technologies, such as Audiomoth (Hill et al. ) and Solo (Whytock and Christie ). Camera‐trapping could also benefit from this approach, but only with a concerted push from researchers, conservationists and technologists (Berger‐Tal and Lahoz‐Monfort ).…”

Section: Discussionmentioning

confidence: 99%

Camera‐trapping version 3.0: current constraints and future priorities for development

Glover‐Kapfer

Soto-Navarro

Wearn

2019

Remote Sens Ecol Conserv

105

111

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Camera traps are a widely used tool in wildlife research and conservation, but in situ factors such as theft, poor performance in extreme environments and damage by wildlife may be hindering the effectiveness of the technology. However, we still know little about how widespread these constraints are and which are the priorities to solve in the short‐ and mid‐term. We present results from a global survey of camera‐trappers working across a diversity of institutions and habitats, and using camera traps for a range of purposes. We show that: (1) the major current constraints on effective camera‐trapping are cost, theft and sensor performance (with 66%, 50% and 42% of respondents respectively classifying those as important or extremely important barriers for camera‐trapping); (2) the most‐needed technological developments are related to sensor performance (faster triggering responses and higher sensitivity), resistance to extreme environmental conditions (extreme temperatures and high humidity) and automated filtering of blank images; and (3) there is considerable variation among camera trap manufacturers in user‐rated performance, and none of the manufacturer ratings exhibited a trend over time, despite improvements in the technology. Our results serve as valuable market research for both open‐source and commercial camera trap developers. On the basis of our survey of camera‐trappers, we foresee a transition towards camera‐trapping 3.0 in the near‐future, consisting of both more effective camera trap units, but also greater use of wireless data transmission, sensor networks, automation of processes using algorithms and better, more collaborative tools for managing and analysing camera trap data. Ultimately, this will increase the capacity of researchers and conservationists to implement coordinated wildlife monitoring at unprecedented scales.

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“…Leveraging decades of PAM survey data will require collaborative development and maintenance of web infrastructure for the collation and public archiving of massive (multi‐gigabyte to petabyte) environmental audio datasets (e.g., https://ngdc.noaa.gov/mgg/pad/). Another possible solution to data capacity issues could be to reduce the amount of audio that is stored, for example, by applying on‐board thresholds or algorithms that only trigger recording when potential sounds of interest are present (Baumgartner et al., ; Hill et al., ). Discarding audio data is scientifically undesirable, but some degree of prior filtering can prevent datasets becoming unmanageably large, and combined with wireless data transmission (Aide et al., ) could facilitate real‐time ecological monitoring and reporting.…”

Section: Passive Acoustic Sensor Technologies and Survey Approachesmentioning

confidence: 99%

“…Opportunities to acoustically survey wildlife and environments have historically been limited by technological costs and constraints, but this situation is fast improving. For example, the recently released AudioMoth low‐cost sensor has seen broad uptake for study objectives ranging from population ecology to anthropogenic activity (Hill et al., ). Such initiatives now enable deployment of multisensor networks at scale, involving both experts and volunteers (Jones et al., ; Newson, Evans, & Gillings, ).…”

Section: Introductionmentioning

confidence: 99%

Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring

et al. 2018

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High‐throughput environmental sensing technologies are increasingly central to global monitoring of the ecological impacts of human activities. In particular, the recent boom in passive acoustic sensors has provided efficient, noninvasive, and taxonomically broad means to study wildlife populations and communities, and monitor their responses to environmental change. However, until recently, technological costs and constraints have largely confined research in passive acoustic monitoring (PAM) to a handful of taxonomic groups (e.g., bats, cetaceans, birds), often in relatively small‐scale, proof‐of‐concept studies. The arrival of low‐cost, open‐source sensors is now rapidly expanding access to PAM technologies, making it vital to evaluate where these tools can contribute to broader efforts in ecology and biodiversity research. Here, we synthesise and critically assess the current emerging opportunities and challenges for PAM for ecological assessment and monitoring of both species populations and communities. We show that terrestrial and marine PAM applications are advancing rapidly, facilitated by emerging sensor hardware, the application of machine learning innovations to automated wildlife call identification, and work towards developing acoustic biodiversity indicators. However, the broader scope of PAM research remains constrained by limited availability of reference sound libraries and open‐source audio processing tools, especially for the tropics, and lack of clarity around the accuracy, transferability and limitations of many analytical methods. In order to improve possibilities for PAM globally, we emphasise the need for collaborative work to develop standardised survey and analysis protocols, publicly archived sound libraries, multiyear audio datasets, and a more robust theoretical and analytical framework for monitoring vocalising animal communities.

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AudioMoth: Evaluation of a smart open acoustic device for monitoring biodiversity and the environment

Cited by 327 publications

References 29 publications

Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

Spatio‐temporal scaling of biodiversity in acoustic tropical bird communities

Camera‐trapping version 3.0: current constraints and future priorities for development

Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring

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