Using tri-axial accelerometers to identify wild polar bear behaviors

Pagano, Anthony M.; Rode, Karyn D.; Cutting, Amy; Owen, Megan A.; Jensen, Shannon; Ware, Jasmine V.; Robbins, Charles T.; Durner, George M.; Atwood, Todd C.; Obbard, Martyn E.; Middel, Kevin R.; Thiemann, Gregory W.; Williams, Terrie M.

doi:10.3354/esr00779

Cited by 52 publications

(109 citation statements)

References 81 publications

(94 reference statements)

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“…This contrasts alternative methods of increasing sampling duration of these devices through non-con- (Pagano et al, 2017;Wang et al, 2015) which may be driving the sudden and drastic decrease in accuracy seen at low frequency recordings (Figure 4). Our calibration of 1 Hz acceleration data yielded high overall accuracy while allowing continuous recordings on red squirrels for up to 2 months per deployment.…”

Section: Discussionmentioning

confidence: 93%

“…Pagano et al, 2017). We conclude the paper with some recommendations for behavioral classifications using low-frequency acceleration, applicable to a research context in which the priority is to accurately classify major behavioral states, recorded continuously, across a sampling period of maximum length.…”

Section: Discussionmentioning

confidence: 99%

“…Although many calibrations use captive animals or surrogate species for training data (Campbell, Gao, Bidder, Hunter, & Franklin, 2013), Pagano et al (2017) showed that highest accuracy is achieved using free-ranging individuals of the same species of interest. Although many calibrations use captive animals or surrogate species for training data (Campbell, Gao, Bidder, Hunter, & Franklin, 2013), Pagano et al (2017) showed that highest accuracy is achieved using free-ranging individuals of the same species of interest.…”

Section: Discussionmentioning

confidence: 99%

“…This results in a potential maximum recording longevity in the order of minutes to days, unless sub-sampling techniques are used (Hammond, Springthorpe, Walsh, & Berg-Kirkpatrick, 2016). However, the few studies that have directly tested this possibility suggested that low recording frequencies have significantly reduced accuracy when using current classification methods (Broell et al, 2013;Pagano et al, 2017;Wang et al, 2015). An alternative method is to extend the sampling duration by reducing the sampling rate.…”

Section: Introductionmentioning

confidence: 99%

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Behavioral classification of low‐frequency acceleration and temperature data from a free‐ranging small mammal

Studd

Landry‐Cuerrier

Menzies

et al. 2018

Ecology and Evolution

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The miniaturization and affordability of new technology is driving a biologging revolution in wildlife ecology with use of animal‐borne data logging devices. Among many new biologging technologies, accelerometers are emerging as key tools for continuously recording animal behavior. Yet a critical, but under‐acknowledged consideration in biologging is the trade‐off between sampling rate and sampling duration, created by battery‐ (or memory‐) related sampling constraints. This is especially acute among small animals, causing most researchers to sample at high rates for very limited durations. Here, we show that high accuracy in behavioral classification is achievable when pairing low‐frequency acceleration recordings with temperature. We conducted 84 hr of direct behavioral observations on 67 free‐ranging red squirrels (200–300 g) that were fitted with accelerometers (2 g) recording tri‐axial acceleration and temperature at 1 Hz. We then used a random forest algorithm and a manually created decision tree, with variable sampling window lengths, to associate observed behavior with logger recorded acceleration and temperature. Finally, we assessed the accuracy of these different classifications using an additional 60 hr of behavioral observations, not used in the initial classification. The accuracy of the manually created decision tree classification using observational data varied from 70.6% to 91.6% depending on the complexity of the tree, with increasing accuracy as complexity decreased. Short duration behavior like running had lower accuracy than long‐duration behavior like feeding. The random forest algorithm offered similarly high overall accuracy, but the manual decision tree afforded the flexibility to create a hierarchical tree, and to adjust sampling window length for behavioral states with varying durations. Low frequency biologging of acceleration and temperature allows accurate behavioral classification of small animals over multi‐month sampling durations. Nevertheless, low sampling rates impose several important limitations, especially related to assessing the classification accuracy of short duration behavior.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Behavioral classification of low‐frequency acceleration and temperature data from a free‐ranging small mammal

Studd

Landry‐Cuerrier

Menzies

et al. 2018

Ecology and Evolution

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“…Of those bears using land, the average date they return to sea ice is early November (Rode et al, 2015). While bears are on ice, the majority of their time is spent out of the water, but they have been observed in the water 17% of the time (Pagano et al, 2017). Thus, if oil is in water adjacent to ice polar bears are using, there is a reasonable chance that they could be exposed to oil, potentially fouling their fur.…”

Section: Impacts To Polar Bearsmentioning

confidence: 99%

Potential impacts of offshore oil spills on polar bears in the Chukchi Sea

Wilson

Perham

French-McCay

et al. 2018

Environmental Pollution

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a b s t r a c tSea ice decline is anticipated to increase human access to the Arctic Ocean allowing for offshore oil and gas development in once inaccessible areas. Given the potential negative consequences of an oil spill on marine wildlife populations in the Arctic, it is important to understand the magnitude of impact a large spill could have on wildlife to inform response planning efforts. In this study we simulated oil spills that released 25,000 barrels of oil for 30 days in autumn originating from two sites in the Chukchi Sea (one in Russia and one in the U.S.) and tracked the distribution of oil for 76 days. We then determined the potential impact such a spill might have on polar bears (Ursus maritimus) and their habitat by overlapping spills with maps of polar bear habitat and movement trajectories. Only a small proportion (1 e10%) of high-value polar bear sea ice habitat was directly affected by oil sufficient to impact bears. However, 27e38% of polar bears in the region were potentially exposed to oil. Oil consistently had the highest probability of reaching Wrangel and Herald islands, important areas of denning and summer terrestrial habitat. Oil did not reach polar bears until approximately 3 weeks after the spills. Our study found the potential for significant impacts to polar bears under a worst case discharge scenario, but suggests that there is a window of time where effective containment efforts could minimize exposure to bears. Our study provides a framework for wildlife managers and planners to assess the level of response that would be required to treat exposed wildlife and where spill response equipment might be best stationed. While the size of spill we simulated has a low probability of occurring, it provides an upper limit for planners to consider when crafting response plans.Published by Elsevier Ltd.

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Estimating activity of Japanese macaques (Macaca fuscata) using accelerometers

Sha

Kaneko

Suda‐Hashimoto

et al. 2017

American J Primatol

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Accelerometers have been used to study both terrestrial and aquatic wildlife, mainly for mammal and bird species. In terrestrial mammals, there is a bias toward ungulates and carnivores, with fewer studies on nonhuman primates. In this study, we tested the use of accelerometers for studying the activity of Japanese macaques (Macaca fuscata). We modeled the activity of a male and a female subject by matching continuous focal observations from video recordings to sensor parameters derived from collar-mounted accelerometers. Models achieved classification performance (AUC) of greater than 90% for both subjects, with similar results when subjects were cross-validated. Accelerometer-based estimates of activity had comparable accuracies to estimates from instantaneous sampling at 1 min and 5 min intervals. We further demonstrated the use of model estimates for analyzing circadian rhythm and night time activity of M. fuscata. Our results add support to the feasibility of using accelerometers for studying activity of nonhuman primates. We discussed the limitations, benefits and potential applications of remote-sensing technology like accelerometers for advancing primalotogical studies.

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Using tri-axial accelerometers to identify wild polar bear behaviors

Cited by 52 publications

References 81 publications

Behavioral classification of low‐frequency acceleration and temperature data from a free‐ranging small mammal

Behavioral classification of low‐frequency acceleration and temperature data from a free‐ranging small mammal

Potential impacts of offshore oil spills on polar bears in the Chukchi Sea

Estimating activity of Japanese macaques (Macaca fuscata) using accelerometers

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