Feasibility assessment of active and passive acoustic monitoring of sika deer populations

Enari, Hiroto; Enari, Haruka S.; Okuda, Kei; Yoshita, Miho; Kuno, Toshiki; Okuda, Kana

doi:10.1016/j.ecolind.2017.04.004

Cited by 25 publications

(18 citation statements)

References 38 publications

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“…Additionally, the physical nature of each habitat alters species detectability, with increased detection reported for non‐forested areas (Enari et al. ) and flat riparian habitats (Ribeiro et al. ).…”

Section: Spatial Samplingmentioning

confidence: 99%

A roadmap for survey designs in terrestrial acoustic monitoring

Sugai

Desjonquères

Silva

et al. 2019

Remote Sens Ecol Conserv

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Passive acoustic monitoring (PAM) is increasingly popular in ecological research and conservation programs, with high-volume and long-term data collection provided by automatized acoustic sensors offering unprecedented opportunities for faunal and ecosystem surveys. Practitioners and newcomers interested in PAM can easily find technical specifications for acoustic sensors and microphones, but guidelines on how to plan survey designs are largely scattered over the literature. Here, we (i) review spatial and temporal sampling designs used in passive acoustic monitoring, (ii) provide a synthesis of the crucial aspects of PAM survey design and (iii) propose a workflow to optimize recording autonomy and recording schedules. From 1992 to 2018, most of the 460 studies applying PAM in terrestrial environments have used a single recorder per site, covered broad spatial scales and rotated recorders between sites to optimize sampling effort. Continuous recording of specific diel periods was the main recording procedure used. When recording schedules were applied, a larger number of recordings per hour was generally associated with a smaller recording length. For PAM survey design, we proposed to (i) estimate memory/battery autonomy and associated costs, (ii) assess signal detectability to optimize recording schedules in order to recover maximum biological information and (iii) evaluate cost-benefit scenarios between sampling effort and budget to address potential biases from a given PAM survey design. Establishing standards for PAM data collection will improve the quality of inferences over the broad scope of PAM research and promote essential standardization for cross-scale research to understand long-term biodiversity trends in a changing world.

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Section: Spatial Samplingmentioning

confidence: 99%

A roadmap for survey designs in terrestrial acoustic monitoring

Sugai

Desjonquères

Silva

et al. 2019

Remote Sens Ecol Conserv

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“…PAM approaches have important conservation implications, particularly if they can be used to improve understanding of how great argus respond to anthropogenic disturbance. There has been increasing interest in applying PAM approaches to estimate occurrence and density of vocal animals in terrestrial environments [ 83 – 86 ]. A crucial next step in PAM of great argus pheasants will be in the development of effective methods of estimating occurrence and density across large spatial scales.…”

Section: Discussionmentioning

confidence: 99%

Not by the light of the moon: Investigating circadian rhythms and environmental predictors of calling in Bornean great argus

et al. 2021

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Great argus pheasants are known for their elaborate visual mating displays, but relatively little is known about their general ecology. The use of passive acoustic monitoring—which relies on long-term autonomous recorders—can provide insight into the behavior of visually cryptic, yet vocal species such as the great argus. Here we report the results of an analysis of vocal behavior of the Bornean great argus (Argusianus argus grayi) in Sabah, Malaysia, using data collected with 11 autonomous recording units. Great argus regularly emitted two call types, the long call and the short call, and we found that although both call types were emitted throughout the day, the short calls were more likely to occur during the morning hours (06:00–12:00LT). Great argus were less likely to call if there was rain, irrespective of the time of day. A substantial portion of calls at our site (~20%) were emitted between the hours of 18:00–06:00LT. We found that for nighttime calls, calling activity increased during new moon periods and decreased during periods of rain. We attribute the negative influence of rain on calling to increased energetic costs of thermoregulation during wet periods, and propose that the influence of the lunar cycle may be related to increased predation risk during periods with high levels of moonlight. Little is known about the behavioral ecology of great argus on Borneo, so it is difficult to know if the results we report are typical, or if we would see differences in calling activity patterns depending on breeding season or changes in food availability. We advocate for future studies of great argus pheasant populations using paired camera and acoustic recorders, which can provide further insight into the behavior of this cryptic species.

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“…Davis et al., 2020; Fournet et al., 2018; Martin et al., 2013), and there has been a substantial increase in use in terrestrial systems in recent years (Sugai et al., 2019). Terrestrial applications of PAM include the assessment of occurrence (Vu & Tran, 2019) and movement patterns (Kalan et al., 2016), estimating population density (Dawson & Efford, 2009; Enari et al., 2017) and monitoring behaviour and activity patterns (e.g. Clink et al., 2020b; Wrege et al., 2017).…”

Section: Introductionmentioning

confidence: 99%

Unsupervised acoustic classification of individual gibbon females and the implications for passive acoustic monitoring

Clink

Klinck

2020

Methods Ecol Evol

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Passive acoustic monitoring (PAM) has the potential to greatly improve our ability to monitor cryptic yet vocal animals. Advances in automated signal detection have increased the scope of PAM, but distinguishing between individuals—which is necessary for density estimation—remains a major challenge. When individual identity is known, supervised classification techniques can be used to distinguish between individuals. Supervised methods require labelled training data, whereas unsupervised techniques do not. If the acoustic signals of individuals are sufficiently different, the number of clusters might represent the number of individuals sampled. The majority of applications of unsupervised techniques in animal vocalizations have focused on quantifying species‐specific call repertoires. However, with increased interest in PAM applications, unsupervised methods that can distinguish between individuals are needed. Here we use an existing dataset of Bornean gibbon female calls with known identity from five sites on Malaysian Borneo to test the ability of three different unsupervised clustering algorithms (affinity propagation, K‐medoids and Gaussian mixture model‐based clustering) to distinguish between individuals. Calls from different gibbon females are readily distinguishable using supervised techniques. For internal validation of unsupervised cluster solutions, we calculated silhouette coefficients. For external validation, we compared clustering results with female identity labels using a standard metric: normalized mutual information. We also calculated classification accuracy by assigning unsupervised cluster solutions to females based on which cluster had the highest number of calls from a particular female. We found that affinity propagation clustering consistently outperformed the other algorithms for all metrics used. In particular, classification accuracy of affinity propagation clustering was more consistent as the number of females increased, and when we randomly sampled females across sites. We conclude that unsupervised techniques may be useful for providing additional information regarding individual identity for PAM applications. We stress that although we use gibbons as a case study, these methods will be applicable for any individually distinct vocal animal.

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Feasibility assessment of active and passive acoustic monitoring of sika deer populations

Cited by 25 publications

References 38 publications

A roadmap for survey designs in terrestrial acoustic monitoring

A roadmap for survey designs in terrestrial acoustic monitoring

Not by the light of the moon: Investigating circadian rhythms and environmental predictors of calling in Bornean great argus

Unsupervised acoustic classification of individual gibbon females and the implications for passive acoustic monitoring

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