Animal‐borne video systems provide insight into the reproductive behavior of the Asian black bear

Naganuma, Tomoko; Tanaka, Mii; Tezuka, Shiori; Steyaert, Sam M. J. G.; Tochigi, Kahoko; Inagaki, Akino; Myojo, Hiroaki; Yamazaki, Koji; Koike, Shinsuke

doi:10.1002/ece3.7722

Cited by 11 publications

(13 citation statements)

References 33 publications

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“…In total, we equipped four Asian black bears with camera collars (two 4-year-old males, a 12-year-old female, and a 4-year-old female) for an average of 41.3 days ( Naganuma et al 2021 ; Table 1 ). The total number of clips per bear was somewhat less than the theoretical maximum number of clips for the observation period—average success rate = 99.4%; range = 99.2% (Female A) to 99.7% (Female B) because the cameras occasionally failed to work properly, resulting in nothing being recorded on some clips.…”

Section: Resultsmentioning

confidence: 99%

“…1 ). Additionally, the results of the video analysis showed that all collared individuals spent an average of more than 40% of their days with other individuals without collars because the study occurred during their mating season ( Naganuma et al 2021 ). Therefore, even if the scats were collected in clusters, it could not be determined that they were from the individuals being tracked.…”

Section: Methodsmentioning

confidence: 99%

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Comparing information derived on food habits of a terrestrial carnivore between animal-borne video systems and fecal analyses methods

Tezuka

Tanaka

Naganuma

et al. 2022

Journal of Mammalogy

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In recent years, animal-borne video cameras have been used to identify the food habits of many species. However, the usefulness and difficulties of identifying food habits from animal-borne video cameras have not been sufficiently discussed in terrestrial mammals, especially large omnivores. The aim of this study is to compare the video analysis of foraging behavior by Asian black bears (Ursus thibetanus) acquired by camera collars with estimates from fecal analysis. We attached GPS collars equipped with video cameras to four adult Asian black bears in the Okutama mountains in central Japan from May to July 2018 and analyzed video clips for foraging behavior. Simultaneously, we collected bear feces in the same area to determine food habits. We found that using video analyses was advantageous to recognize foods, such as leaves or mammals, that were physically crushed or destroyed while bears chewed and digested foods, which are difficult to identify to species using fecal analyses. On the other hand, we found that camera collars are less likely to record food items that are infrequently or quickly ingested. Additionally, food items with a low frequency of occurrence and short foraging time per feeding were less likely to be detected when we increased the time between recorded clips. As one of the first applications of the video analysis method for bears, our study shows that video analysis can be an important method for revealing individual differences in diet. Although video analysis may have limitations for understanding the general foraging behavior of Asian black bears at the present stage, the accuracy of food habit data from camera collars can be improved by using it in combination with established techniques such as microscale behavior analyses.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Comparing information derived on food habits of a terrestrial carnivore between animal-borne video systems and fecal analyses methods

Tezuka

Tanaka

Naganuma

et al. 2022

Journal of Mammalogy

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“…This indicates that bears in hyperphagia periods have more complex modes of activity than mating periods. In mating periods when mating partners are accompanied, time of resting is increased and that of foraging is reduced (Naganuma et al, 2021), while daily activity is increased in hyperphagia periods (Kozakai et al, 2013). This behavioral change can be associated with the detected between‐period change in movement patterns.…”

Section: Discussionmentioning

confidence: 99%

Composite Brownian walks best explain the movement patterns of Asian black bears, irrespective of sex, seasonality, and food availability

Ando

Yoshikawa

Kozakai

et al. 2022

Ecological Research

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Large solitary carnivores need to correspond to spatial and temporal variations in food resources, and therefore are expected to change their movement strategies seasonally and annually. Movement strategy of an animal is also mediated by internal factors such as sex. We investigate movement strategy of Asian black bears (Ursus thibetanus) in two biological periods (mating and hyperphagia periods), by fitting random walk models including Brownian walks (BWs), Lévy walks (LWs), and composite Brownian walks (CBWs). We explored the best random walk models approximating the movement paths of 59 trajectories performed by 29 Asian black bears, obtained in years with different food availability. The results strongly supported the occurrence of CBW patterns over scale‐free LW patterns for their movements. We found some differences in composition of the best CBW models between mating and hyperphagia periods, though no distinctive differences were found among the best models regarding sex and food availability. Our findings demonstrated that the CBW is the best model to describe the movement of the Asian black bears among the random walk models tested, and indicate the importance of understanding multiple modes of their activity or movement.

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“…For example, accelerometers are commonly used to record stereotyped behavioral states such as resting, feeding, and locomotion, but generally cannot capture more complete behavioral repertoires (Brown et al, 2013). On-board cameras can record the social interactions, foraging decisions, and physical surroundings of instrumented individuals, but are restricted in their fields of view and prone to occlusion (Ehlers et al, 2021; Naganuma et al, 2021). Interpreting data from secondary sensors can also be challenging.…”

Section: Introductionmentioning

confidence: 99%

“…This is time-consuming and often conducted using captive animals or relatively brief observations of wild animals, which is likely to exclude rare or context-dependent behaviors (Brown et al, 2013; Wang et al, 2015). Data from animal-borne cameras typically must be manually reviewed by experts, and variable image quality can prevent extraction of relevant data (Moll et al, 2007; Naganuma et al, 2021). Alternatively, social behavior can be studied by instrumenting most or all animals of interest (e.g.…”

Section: Introductionmentioning

confidence: 99%

Quantifying the movement, behavior, and environmental context of group-living animals using drones and computer vision

Koger

Deshpande

Kerby

et al. 2022

Preprint

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1. Methods for collecting animal behavior data in natural environments, such as direct observation and bio-logging, are typically limited in spatiotemporal resolution, the number of animals that can be observed, and information about animals' social and physical environments. 2. Video imagery can capture rich information about animals and their environments, but image-based approaches are often impractical due to the challenges of processing large and complex multi-image datasets and transforming resulting data, such as animals' locations, into geographic coordinates. 3. We demonstrate a new system for studying behavior in the wild that uses drone-recorded videos and computer vision approaches to automatically track the location and body posture of free-roaming animals in georeferenced coordinates with high spatiotemporal resolution embedded in contemporaneous 3D landscape models of the surrounding area. 4. We provide two worked examples in which we apply this approach to videos of gelada monkeys and multiple species of group-living African ungulates. We demonstrate how to track multiple animals simultaneously, classify individuals by species and age-sex class, estimate individuals' body postures (poses), and extract environmental features, including topography of the landscape and game trails. 5. By quantifying animal movement and posture, while simultaneously reconstructing a detailed 3D model of the landscape, our approach opens the door to studying the sensory ecology and decision-making of animals within their natural physical and social environments.

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Animal‐borne video systems provide insight into the reproductive behavior of the Asian black bear

Cited by 11 publications

References 33 publications

Comparing information derived on food habits of a terrestrial carnivore between animal-borne video systems and fecal analyses methods

Comparing information derived on food habits of a terrestrial carnivore between animal-borne video systems and fecal analyses methods

Composite Brownian walks best explain the movement patterns of Asian black bears, irrespective of sex, seasonality, and food availability

Quantifying the movement, behavior, and environmental context of group-living animals using drones and computer vision

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