Listening to Lions: Animal-Borne Acoustic Sensors Improve Bio-logger Calibration and Behaviour Classification Performance

Wijers, Matthew; Trethowan, Paul; Markham, Andrew; Preez, Byron du; Chamaillé‐Jammes, Simon; Loveridge, Andrew J.; Macdonald, David W.

doi:10.3389/fevo.2018.00171

Cited by 25 publications

(47 citation statements)

References 34 publications

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“…(e.g., Bee and Gerhardt, 2001;Reby and McComb, 2003;Fischer et al, 2004). However, successful applications of acoustics to record behavior all highlight the considerable wealth of information contained in this media form including bodily functions (e.g., heart rate; Couchoux et al, 2015), behavior (e.g., chewing, grooming, wingbeats;Ilany et al, 2013;Stowell et al, 2017;Wijers et al, 2018), and environmental noise (e.g., anthropogenic noise, wind, vocalization of other species; Lynch et al, 2015;Stowell et al, 2017).…”

Section: Biologging Behaviormentioning

confidence: 99%

“…Acoustic data has been incorporated into many fields within ecology providing new means of quantifying biodiversity (e.g., Depraetere et al, 2012;Gasc et al, 2013), soundscapes (Pijanowski et al, 2011), and animal communication (e.g., Reby and McComb, 2003;Fischer et al, 2004;Thiebault et al, 2016). More recently, a few studies have even revealed the potential of acoustic devices to record non-vocal behavior (e.g., flying, feeding, walking; Ilany et al, 2013;Lynch et al, 2013;Stowell et al, 2017;Wijers et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Use of Acceleration and Acoustics to Classify Behavior, Generate Time Budgets, and Evaluate Responses to Moonlight in Free-Ranging Snowshoe Hares

et al. 2019

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Technological miniaturization is driving a biologging revolution that is producing detailed and sophisticated techniques of assessing individual behavioral responses to environmental conditions. Among the many advancements this revolution has brought is an ability to record behavioral responses of nocturnal, free-ranging species. Here, we combine captive validations of acceleration signatures with acoustic recordings from free-ranging individuals to classify behavior at two resolutions. Combining these classifications with ∼2 month-long recordings, we describe winter time budgets, and responses of free-ranging snowshoe hares to changing moonlight. We successfully classified snowshoe hare behavior into four categories (not moving, foraging, hopping, and sprinting) using low frequency accelerometry, with an overall model accuracy of 88%, and acoustic recordings to three categories (silence, hopping, and chewing) with an accuracy of 94%. Broad-scale accelerometer-classified categories were composed of multiple fine-scale behavioral states with the composition varying between individuals and across the day. Time budgets revealed that hares spent ∼50% of their time foraging and ∼50% not moving, with most foraging and feeding occurring at night. We found that hares adjusted timing of activity in response to moon phase, with a 6% reduction in foraging and 30% reduction in traveling during the night when the moon was full. Hares compensated for this lost foraging time by extending foraging into the morning hours of the following day. Using two biologging technologies to identify behavior, we demonstrate the possibility of combining multiple devices when documenting behavior of cryptic species.

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Section: Biologging Behaviormentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Use of Acceleration and Acoustics to Classify Behavior, Generate Time Budgets, and Evaluate Responses to Moonlight in Free-Ranging Snowshoe Hares

et al. 2019

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“…Here, captive bats are recorded feeding on different types of fruit while the amount they eat is monitored using video. Assessing food intake using sound is of course not restricted to bats and can be performed on any other organism for which chewing or food processing is audible, as has already been demonstrated in several animals, including humans (Bi et al, 2016), lions (Wijers et al, 2018) and mule deer (Lynch et al, 2013;Nelson et al, 2005). Recording sound on-board free-flying bats allows us to connect foraging behaviour to environmental conditions.…”

Section: Using Sound To Study Foragingmentioning

confidence: 99%

“…In walking animals, one can distinguish between different locomotion modes (e.g. resting, trotting, running), thereby giving insight into activity patterns and circadian rhythms (Insley et al, 2008;Itai and Yasukawa, 2007;Iyengar et al, 2007;Wijers et al, 2018). In Fig.…”

Section: Using Sound To Extract Additional Informationmentioning

confidence: 99%

Using on-board sound recordings to infer behaviour of free-moving wild animals

Greif

Yovel

2019

Journal of Experimental Biology

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Technological advances in the last 20 years have enabled researchers to develop increasingly sophisticated miniature devices (tags) that record an animal's behaviour not from an observational, external viewpoint, but directly on the animals themselves. So far, behavioural research with these tags has mostly been conducted using movement or acceleration data. But on-board audio recordings have become more and more common following pioneering work in marine mammal research. The first questions that come to mind when recording sound on-board animals concern their vocal behaviour. When are they calling? How do they adjust their behaviour? What acoustic parameters do they change and how? However, other topics like foraging behaviour, social interactions or environmental acoustics can now be addressed as well and offer detailed insight into the animals' daily life. In this Review, we discuss the possibilities, advantages and limitations of on-board acoustic recordings. We focus primarily on bats as their active-sensing, echolocating lifestyle allows many approaches to a multi-faceted acoustic assessment of their behaviour. The general ideas and concepts, however, are applicable to many animals and hopefully will demonstrate the versatility of on-board acoustic recordings and stimulate new research.

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“…To avoid expense or to gain features, there has been a rise in recent years of researchers building their own devices (Clark et al, ; Fischer et al, ). This has generally come with the caveat that researchers have worked with engineers or computer scientists to develop devices that are highly specific and difficult to replicate (Wijers et al, ).…”

Section: Introductionmentioning

confidence: 99%

Open‐source, low‐cost modular GPS collars for monitoring and tracking wildlife

Foley

Sillero‐Zubiri

2020

Methods Ecol Evol

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Monitoring the movements and behaviour of wildlife using radio telemetry or GPS devices has been critical to the fields of ecology and conservation over several decades. For many field projects however, commercially available devices can be expensive and may not always be ideally suited for collecting desired data. We present a low‐cost solution of customizable tracking devices based on the open‐source Arduino system. These devices can be custom designed for specific studies and easily programmed to collect desired data. Custom‐built collars with GPS and accelerometer units were trialled on 30 free‐ranging domestic dogs in rural Ethiopia. These collars collected high‐resolution data at a frequency of 10 fixes per hour and accelerometer data at 10 Hz over a 10‐day period, at a cost of approximately £100 ($130 USD) per collar. These devices can be placed on any species that can handle a weight of 15.4 g plus battery and housing. The current configuration weighs approximately 240 g which would be suitable for any animal above 8 kg living in terrestrial environments.

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Listening to Lions: Animal-Borne Acoustic Sensors Improve Bio-logger Calibration and Behaviour Classification Performance

Cited by 25 publications

References 34 publications

Use of Acceleration and Acoustics to Classify Behavior, Generate Time Budgets, and Evaluate Responses to Moonlight in Free-Ranging Snowshoe Hares

Use of Acceleration and Acoustics to Classify Behavior, Generate Time Budgets, and Evaluate Responses to Moonlight in Free-Ranging Snowshoe Hares

Using on-board sound recordings to infer behaviour of free-moving wild animals

Open‐source, low‐cost modular GPS collars for monitoring and tracking wildlife

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