Slowness and acceleration: a new method to quantify the activity budget of chelonians

Lagarde, Frédéric; Guillon, Michaël; Dubroca, Laurent; Bonnet, Xavier; Kaddour, K. Ben; Slimani, Tahar; Mouden, El Hassan El

doi:10.1016/j.anbehav.2007.01.010

Cited by 42 publications

(58 citation statements)

References 46 publications

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“…Accelerometry is increasingly being used to classify behaviour states based on patterns of animal movement, and is a promising tool for identifying feeding events remotely (Lagarde et al, 2008;Grünewälder et al, 2012;Nathan et al, 2012). Extensive highresolution data describing continuous profiles of animal movement can now be collected reliably and cost-effectively, and the computational tools to mine this information are being accessed by ecologists (e.g.…”

Section: Introductionmentioning

confidence: 99%

Supervised accelerometry analysis can identify prey capture by penguins at sea

Carroll

Slip

Jonsen

et al. 2014

Journal of Experimental Biology

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Determining where, when and how much animals eat is fundamental to understanding their ecology. We developed a technique to identify a prey capture signature for little penguins from accelerometry, in order to quantify food intake remotely. We categorised behaviour of captive penguins from HD video and matched this to time-series data from back-mounted accelerometers. We then trained a support vector machine (SVM) to classify the penguins' behaviour at 0.3 s intervals as either 'prey handling' or 'swimming'. We applied this model to accelerometer data collected from foraging wild penguins to identify prey capture events. We compared prey capture and non-prey capture dives to test the model predictions against foraging theory. The SVM had an accuracy of 84.95±0.26% (mean ± s.e.) and a false positive rate of 9.82±0.24% when tested on unseen captive data. For wild data, we defined three independent, consecutive prey handling observations as representing true prey capture, with a false positive rate of 0.09%. Dives with prey captures had longer duration and bottom times, were deeper, had faster ascent rates, and had more 'wiggles' and 'dashes' (proxies for prey encounter used in other studies). The mean (±s.e.) number of prey captures per foraging trip was 446.6±66.28. By recording the behaviour of captive animals on HD video and using a supervised machine learning approach, we show that accelerometry signatures can classify the behaviour of wild animals at unprecedentedly fine scales.

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Section: Introductionmentioning

confidence: 99%

Supervised accelerometry analysis can identify prey capture by penguins at sea

Carroll

Slip

Jonsen

et al. 2014

Journal of Experimental Biology

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“…Remote monitoring of behavior with accelerometers is an increasingly common method for measuring behavior in wild animals while mitigating these problems (Brown et al, 2013;Davis et al, 1999;Kays et al, 2015;Lagarde et al, 2008;Nakamura et al, 2015;Shamoun-Baranes et al, 2012;Weimerskirch et al, 2005;Wilmers et al, 2015). Thus far, accelerometers have mainly been deployed on larger species because of the weight limitations imposed by smaller-bodied animals ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Using accelerometers to remotely and automatically characterize behavior in small animals

Hammond

Springthorpe

Walsh

et al. 2016

Journal of Experimental Biology

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Activity budgets in wild animals are challenging to measure via direct observation because data collection is time consuming and observer effects are potentially confounding. Although tri-axial accelerometers are increasingly employed for this purpose, their application in smallbodied animals has been limited by weight restrictions. Additionally, accelerometers engender novel complications, as a system is needed to reliably map acceleration to behaviors. In this study, we describe newly developed, tiny acceleration-logging devices (1.5-2.5 g) and use them to characterize behavior in two chipmunk species. We collected paired accelerometer readings and behavioral observations from captive individuals. We then employed techniques from machine learning to develop an automatic system for coding accelerometer readings into behavioral categories. Finally, we deployed and recovered accelerometers from free-living, wild chipmunks. This is the first time to our knowledge that accelerometers have been used to generate behavioral data for small-bodied (<100 g), free-living mammals.

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“…Our study did not show signifi cant diff erences in distances traveled by sex and age. Other studies such as (Lagarde, 2008) and (Díaz-Paniagua, 1995) show no diff erence in moving between males and females.…”

Section: Discussionmentioning

confidence: 80%

“…2002;Ben Kaddour et al, 2005;Rouag et al, 2007). However, Testudo graeca habitat and activity patterns have been few studied in northern Africa (Lagarde et al, 2008;Lagarde et al, 2012). So, the aim of this work is to study the modes of exploitation of the habitat by the species in a dune maquis in the National Park of El Kala.…”

Section: Introductionmentioning

confidence: 99%

Home Range of the Spur-Thighed Tortoise, Testudo graeca (Testudines, Testudinidae), in the National Park of El Kala, Algeria

Rouag¹,

Ziane²,

Benyacoub³

2017

Vestnik Zoologii

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Home Range of the Spur-Th ighed Tortoise, Testudo graeca (Testudines, Testudinidae), in the National Park of El Kala, Algeria. Rouag, R., Ziane, N., Benyacoub, S. -Spur-thighed tortoise is a vulnerable species, the local declines of populations require an imperative need for conservation. Research on habitat use is essential for understanding population ecology. To investigate the home range and movement patterns we studied a population which occupies an enclosed area of 30 ha in northeastern Algeria. Studies of movement showed that home ranges were substantially smaller than in Spain. Th is diff erence was due to the high trophic availability with signifi cant richness in plants which make part of the diet of the tortoise. Th e home range varied from 0.287 ha in males to 0.354 ha for females; there was no sexual diff erence. Th e males are the most active with a distance of 3.79 m/d. Females and juveniles are respectively about 2.25 m/d and 2.11 m/d. Th e distance moved each day do not vary signifi cantly by sex and ages. Results from this study are important for establishing conservation strategies for this vulnerable species.

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Slowness and acceleration: a new method to quantify the activity budget of chelonians

Cited by 42 publications

References 46 publications

Supervised accelerometry analysis can identify prey capture by penguins at sea

Supervised accelerometry analysis can identify prey capture by penguins at sea

Using accelerometers to remotely and automatically characterize behavior in small animals

Home Range of the Spur-Thighed Tortoise, Testudo graeca (Testudines, Testudinidae), in the National Park of El Kala, Algeria

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