Best practices for reporting individual identification using camera trap photographs

Choo, Yan Ru; Kudavidanage, Enoka P.; Amarasinghe, Thakshila Ravindra; Nimalrathna, Thilina S.; Chua, Marcus A. H.; Webb, Edward L.

doi:10.1016/j.gecco.2020.e01294

Cited by 23 publications

(35 citation statements)

References 49 publications

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“…It was a photo or an event that was independent. The criteria for independence of animal photographs were: (i) continuous shots of the same or different individual animals; (ii) continuous photos of the same animal of the same species which were taken 30 minutes apart, and (iii) discontinuous photos of the same animal of the same species (Choo et al 2020).…”

Section: Discussionmentioning

confidence: 99%

Spatial and temporal overlaps of top predators: Dhole, tiger and leopard, and their potential preys in Huai Kha Khaeng Wildlife Sanctuary, Thailand

et al. 2021

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Abstract. Charaspet K, Sukmasuang R, Khoewsree N, Pla-Ard M, Paansri P, Keawdee B, Chanachai Y, Bhumpakphan N. 2021. Spatial and temporal overlaps of top predators: Dhole, tiger and leopard, and their potential prey in Huai Kha Khaeng Wildlife Sanctuary, Thailand. Biodiversitas 22: 580-592. The study of the spatial-temporal overlap of top predators and their prey is important to understand competition among predators and predator-prey relationships so that the viable populations of predators and other animals can be sustained. This research aimed to study the abundance of three top predators: Dhole (Cuon alpinus), tiger (Panthera tigris) and leopard (Panthera pardus), and their potential wild prey in Huai Kha Khaeng Wildlife Sanctuary, Thailand, and to investigate the spatial-temporal overlap between those three predators, and their potential wild prey. We tested two significant hypotheses: (i) tiger and leopard had the highest spatial-temporal overlap and the spatial overlap of dhole and leopard was higher in comparison to dhole and tiger due to a higher prey overlap; (ii) the three species of large carnivore avoided spatial-temporal overlap even if they were in the same area. The study was conducted using camera traps. In addition, the spatial-temporal overlap of large carnivores and their potential prey was studied to understand the important species of prey of these large carnivores. The results showed that the spatial overlap of tiger and leopard was the highest. Dhole had significant spatial overlap with leopard, which was higher in comparison to dhole and tiger. A significant temporal overlap of dhole and leopard was not found. Also, a significant temporal overlap of tiger and leopard was not found. The results were based on hypotheses that conformed to the niche overlap index of the potential prey and the temporal overlap coefficient. There were ten important species of potential prey of large carnivores: Sambar deer (Rusa unicolor), red muntjac (Muntiacus muntjak), gaur (Bos gaurus), banteng (Bos javanicus), wild boar (Sus scrofa), Malayan porcupine (Hystrix brachyura), large Indian civet (Viverra zibetha), Asiatic black bear (Ursus thibetanus), pig-tailed macaque (Macaca nemestrina) and red jungle fowl (Gallus gallus). The important recommendation is the protection of the sanctuary from wildfires which spread from the outside in, especially in dry evergreen forest. Food resources of herbivores in the area must be managed, as well as the prevention of epidemics from livestock to wild animals.

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Section: Discussionmentioning

confidence: 99%

Spatial and temporal overlaps of top predators: Dhole, tiger and leopard, and their potential preys in Huai Kha Khaeng Wildlife Sanctuary, Thailand

et al. 2021

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“…At least three well-trained observers in each site were involved in the intensive identification process of identifying lynx individuals by using an online multipurpose photographic database and cross-check verification. Identification of individuals and data processing followed minimum camera-trapping standards reported by Choo et al 47 .…”

Section: Methodsmentioning

confidence: 99%

“…At least three well-trained observers in each site were www.nature.com/scientificreports/ involved in the intensive identification process of identifying lynx individuals by using an online multipurpose photographic database and cross-check verification. Identification of individuals and data processing followed minimum camera-trapping standards reported by Choo et al 47 . Sex and age category of individuals was determined from clearly visible genital parts and captures of leading females with kittens in the pictures, as well as from videos gained through previous deterministic and opportunistic camera-trapping 32,[44][45][46] or through genetic analyses 29 .…”

Section: Identification Of Individuals and Determination Of Social Statusmentioning

confidence: 99%

Multi-seasonal systematic camera-trapping reveals fluctuating densities and high turnover rates of Carpathian lynx on the western edge of its native range

Duľa

Bojda

Chabanne

et al. 2021

Sci Rep

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Camera-trapping and capture-recapture models are the most widely used tools for estimating densities of wild felids that have unique coat patterns, such as Eurasian lynx. However, studies dealing with this species are predominantly on a short-term basis and our knowledge of temporal trends and population persistence is still scarce. By using systematic camera-trapping and spatial capture-recapture models, we estimated lynx densities and evaluated density fluctuations, apparent survival, transition rate and individual's turnover during five consecutive seasons at three different sites situated in the Czech–Slovak–Polish borderland at the periphery of the Western Carpathians. Our density estimates vary between 0.26 and 1.85 lynx/100 km2 suitable habitat and represent the lowest and the highest lynx densities reported from the Carpathians. We recorded 1.5–4.1-fold changes in asynchronous fluctuated densities among all study sites and seasons. Furthermore, we detected high individual’s turnover (on average 46.3 ± 8.06% in all independent lynx and 37.6 ± 4.22% in adults) as well as low persistence of adults (only 3 out of 29 individuals detected in all seasons). The overall apparent survival rate was 0.63 ± 0.055 and overall transition rate between sites was 0.03 ± 0.019. Transition rate of males was significantly higher than in females, suggesting male-biased dispersal and female philopatry. Fluctuating densities and high turnover rates, in combination with documented lynx mortality, indicate that the population in our region faces several human-induced mortalities, such as poaching or lynx-vehicle collisions. These factors might restrict population growth and limit the dispersion of lynx to other subsequent areas, thus undermining the favourable conservation status of the Carpathian population. Moreover, our study demonstrates that long-term camera-trapping surveys are needed for evaluation of population trends and for reliable estimates of demographic parameters of wild territorial felids, and can be further used for establishing successful management and conservation measures.

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“…These studies frequently adopt a top-down perspective in which the predominant focus is on groups (e.g., populations), with individuals simply viewed as units within the group and minimal interpretation of individual variability. As such, many of the modeling techniques employed for applied investigations, such as mark–recapture ( Royle et al 2013 ; Choo et al 2020 ), are adept at incorporating quantified uncertainty in identification. However, reliable identification of individuals in applied studies is essential to accurate enumeration and differentiation when creating generalized models based on individual observations ( Marin-Cudraz et al 2019 ).…”

Section: Applications Of Animal Identification In Field and Laboratory Settingsmentioning

confidence: 99%

“…Furthermore, in some scenarios, the acceptable level of analytical error can be reduced without compromising the investigation of specific project goals, in which case biologists may find that current computer vision techniques are sufficiently robust to address applied biological questions in a manner that is low cost, logistically efficient, and can make use of pre-existing and archival images and video footage. In particular, the mark–recapture model, commonly employed in biological and ecological studies, lends itself well to a photo-identification adjustment ( Royle et al 2013 ; Choo et al 2020 ). In a reworked format, the first photo would be a “capture,” the photo-identification would be the “mark,” and subsequent images would be the “recapture.” Other types of data or partial data, for example, time stamp or GPS location, may be incorporated to boost the success rate of photo-identification in mark–recapture models ( Augustine et al 2019 , 2020 ).…”

Section: Applications Of Animal Identification In Field and Laboratory Settingsmentioning

confidence: 99%

Perspectives on Individual Animal Identification from Biology and Computer Vision

Vidal

Wolf

Rosenberg

et al. 2021

Integrative and Comparative Biology

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Identifying individual animals is crucial for many biological investigations. In response to some of the limitations of current identification methods, new automated computer vision approaches have emerged with strong performance. Here, we review current advances of computer vision identification techniques to provide both computer scientists and biologists with an overview of the available tools and discuss their applications. We conclude by offering recommendations for starting an animal identification project, illustrate current limitations and propose how they might be addressed in the future.

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Best practices for reporting individual identification using camera trap photographs

Cited by 23 publications

References 49 publications

Spatial and temporal overlaps of top predators: Dhole, tiger and leopard, and their potential preys in Huai Kha Khaeng Wildlife Sanctuary, Thailand

Spatial and temporal overlaps of top predators: Dhole, tiger and leopard, and their potential preys in Huai Kha Khaeng Wildlife Sanctuary, Thailand

Multi-seasonal systematic camera-trapping reveals fluctuating densities and high turnover rates of Carpathian lynx on the western edge of its native range

Perspectives on Individual Animal Identification from Biology and Computer Vision

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