• Journal of Forest and Environmental Science
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• v.33 no.3
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• pp.239-242
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• 2017

Although camera traps have been widely used to understand the abundance of wildlife in recent decades, the effort has been restricted to small sub-set of wildlife which can mark-and-recapture. The Random Encounter Model shows an alternative approach to estimate the absolute abundance from camera trap detection rate for any animals without the need for individual recognition. Our study aims to examine the feasibility and validity of the Random Encounter Model for the density estimation of endangered leopard cats (Prionailurus bengalensis) in Maekdo riparian park, Busan, South Korea. According to the model, the estimated leopard cat density was $1.76km^{-2}$ (CI 95%, 0.74-3.49), which indicated 2.46 leopard cats in $1.4km^2$ of our study area. This estimate was not statistically different from the previous leopard cat population count ($2.33{\pm}0.58$) in the same area. As follows, our research demonstrated the application and usefulness of the Random Encounter Model in density estimation of unmarked wildlife which helps to manage and protect the target species with a better understanding of their status.

• Journal of Forest and Environmental Science
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• v.34 no.1
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• pp.71-76
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• 2018

The long-tailed goral (Naemorhedus caudatus) has slowly recolonized habitats in South Korea. Because it is necessary to know the status of groups in recolonized areas, we determined detection frequencies and group sizes using camera trapping, a non-invasive monitoring method. In Uljin, a far southern goral habitat in South Korea, we used a Moultrie 5.0 camera and mineral block as bait during the breeding season in BaekAm Mountain (148 days, 18 May to 11 October) and Geumjong Mountain (63 days, 18 May to 18 July) in 2010. Totally, 155 images were captured in BaekAm Mountain, whereas four images were captured in Geumjong Mountain. The species was most frequently detected at sunrise (05:00-08:00) and sunset (18:00-20:00). Through population structure evaluation, we identified at least 11 individuals, including one solitary mature male, four females, four kids, and two solitary subadults in BaekAm Mountain. However, in Geumjong Mountain, we identified only two individuals (female with kid). Monitoring efficiency in the recolonized area differed depending on population density and habitat conditions. Because we could evaluate the population structure, and behavioral patterns in the study sites, monitoring using camera traps could be applied for the recolonized habitats in South Korea.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.211-218
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• 2023

Background: Traditional wildlife monitoring has often relied on invasive techniques posing risks to species and demanding substantial resources. To address this, camera traps emerged as non-invasive alternatives, albeit primarily tailored for larger mammals, posing limitations for small mammal research. Thus, the Mostela, an innovative tool designed to overcome these challenges, was introduced to monitor small mammals in South Korea. Results: The Mostela was deployed at two study sites in South Korea, yielding compelling evidence of its efficiency in capturing small mammal species. By analyzing the collected data, we calculated the relative abundance of each species and elucidated their activity patterns. Conclusions: In summary, the Mostela system demonstrates substantial potential for advancing small mammal monitoring, offering valuable insights into diversity, community dynamics, activity patterns, and habitat preferences. Its application extends to the detection of endangered and rare species, further contributing to wildlife conservation efforts in South Korea. Consequently, the Mostela system stands as a valuable addition to the toolkit of conservationists and researchers, fostering ethical and non-invasive research practices while advancing our understanding of small mammal populations and ecosystems.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.1
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• pp.69-80
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• 2021

The new town in Korea, developed as a large-scale housing plan, has created urban ecological corridors to provide habitat and movement routes to wildlife and to promote natural ecological flow. This study aimed to investigate the use of wildlife in 10 ecological corridors in Gwanggyo New Town through camera trap technology and confirm effectiveness by identifying environmental factors affecting the use of wildlife's urban ecological corridors. Our researchers installed 20 unmanned sensor cameras at each the entrance and exit of the ecological corridors, and monitored urban wildlife for 10 weeks. According to the monioring results, the main species in Gwanggyo New Town were identified not only raccons, cats, water deer, korean hare and avain but also magpies, dove, eurasian tree sparrow, ring-necked pheasant, and eurasian jay. The number of uses ecological corridors of urban residents was 801(13.49%), as high as that of urban wildlife (1,140, 19.20%), which was judged to have disturbed the use of ecological corridors by wildlife. However, most dominant species of urban wildlife are nocturnal so that, it was judged that they share home range with urban residents at a time interval. In addition, according to the correlation analysis results between the mammal using rate of the urban ecological corridors and environmental factors(ecological corridor-specific length, ecological corridor-specific width, cover degree, shielding degree, connected green area, separation of movement routes, and presence of streetlights), environmental factors were not statistically significant. However, the more the area of green space connected to ecological corridors, the more increasing the mammal using rate of ecological corridor(r=0.71, p<0.05). Therefore, the area of green space connected to the ecological corridors that is associated with rate of wildlife using corridors should be considered as a priority when developing an urban ecological corridors. In the future, this study will extend the observation period of the ecological corridors and continuously accumulate data by adding the number of observation cameras. Furthermore, it is expected that the results of this study can be used as basic data for the standards for urban ecological corridors installation.

• Journal of Ecology and Environment
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• v.45 no.2
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• pp.88-96
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• 2021

Background: Sika deer, Cervus nippon, were originally introduced to South Korea from Japan and Taiwan for commercial farming purposes. Unfortunately, they were released into the wild during religious events and have since begun to impact the native ecosystem and species endemic to South Korea. The study of activity patterns can improve our understanding of the environmental impact of non-native species and their association with sympatric species. Using camera traps, we studied the diel and seasonal activity patterns of non-native sika deer and quantified the temporal overlap with sympatric mammalian species in the Muljangori-oreum wetlands of Hallasan National Park, South Korea. Results: A total of 970 trap events were recorded for five mammalian species from nine locations during the camera-trap survey. Siberian roe deer (Capreolus pygargus tianschanicus) had the highest number of recorded events (72.0%), followed by sika deer (Cervus nippon) (16.2%), wild boar (Sus scrofa) (5.0%), Asian badger (Meles leucurus) (4.5%), and the Jeju weasel (Mustela sibirica quelpartis) (2.0%). Sika deer had bimodal activity patterns throughout the year, with peaks throughout the spring-autumn twilight, and day and night time throughout the winter. Relating the daily activity of sika deer with other mammalian species, roe deer expressed the highest degree of overlap (Δ₄ = 0.80) while the Asian badger demonstrated the lowest overlap (Δ₄ = 0.37). Conclusions: Our data show that sika deer are a crepuscular species with seasonal variations in daily activity patterns. Additionally, we identified the temporal differences in activity peaks between different mammals in the Muljangori-oreum wetlands and found higher degree of overlap between sika deer and roe deer during twilight hours.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.4
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• pp.17-34
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• 2023

Camera trapping has been used as a non-invasive survey method that minimizes anthropogenic disturbance to ecosystems. Nevertheless, it is labor-intensive and time-consuming, requiring researchers to quantify species and populations. In this study, we aimed to improve the preprocessing of camera trapping data by utilizing an object detection algorithm. Wildlife monitoring using unmanned sensor cameras was conducted in a forested urban forest and a green space on a university campus in Cheonan City, Chungcheongnam-do, Korea. The collected camera trapping data were classified by a researcher to identify the occurrence of species. The data was then used to test the performance of the YOLO-X object detection algorithm for wildlife detection. The camera trapping resulted in 10,500 images of the urban forest and 51,974 images of green spaces on campus. Out of the total 62,474 images, 52,993 images (84.82%) were found to be false positives, while 9,481 images (15.18%) were found to contain wildlife. As a result of wildlife monitoring, 19 species of birds, 5 species of mammals, and 1 species of reptile were observed within the study area. In addition, there were statistically significant differences in the frequency of occurrence of the following species according to the type of urban greenery: Parus varius(t = -3.035, p < 0.01), Parus major(t = 2.112, p < 0.05), Passer montanus(t = 2.112, p < 0.05), Paradoxornis webbianus(t = 2.112, p < 0.05), Turdus hortulorum(t = -4.026, p < 0.001), and Sitta europaea(t = -2.189, p < 0.05). The detection performance of the YOLO-X model for wildlife occurrence was analyzed, and it successfully classified 94.2% of the camera trapping data. In particular, the number of true positive predictions was 7,809 images and the number of false negative predictions was 51,044 images. In this study, the object detection algorithm YOLO-X model was used to detect the presence of wildlife in the camera trapping data. In this study, the YOLO-X model was used with a filter activated to detect 10 specific animal taxa out of the 80 classes trained on the COCO dataset, without any additional training. In future studies, it is necessary to create and apply training data for key occurrence species to make the model suitable for wildlife monitoring.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.2
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• pp.55-65
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• 2024

This study aimed to figure out diel activity patterns of water deer and wild boar, whose habitat is disturbed by human activity in a suburban area. Photographic data of water deer and wild boar collected by 18 camera traps from January 2021 to November 2022 was categorized into four diel periods (dawn, day, dusk, and night), and converted into frequencies per 100 CTD (Camera Trap-Days) for seasonal and spatial diel activity pattern analysis. Water deer exhibited intense nocturnality in fall, and wild boar did in fall and winter. During the fall, water deer's night-time capture rate was the highest (61.9%), and day-time photographic rate was the lowest (13.9%) among other seasons. During the fall and winter, wild boar's night-time photographic rate was relatively high (77.6%, 78.0%, respectively), and day-time photographic rate was relatively low (0.7%, 1.8%) in comparison with other seasons. In spatial diel activity analysis, both water deer and wild boar showed a tendency to avoid humans, especially near trails during day-time hours. The day-time photographic rate of water deer in trail-near group was 12.1% and trail-far group was 24.6%. The day-time photographic rate of wild boar was 3.4%, 5.7%, respectively. Because the diel activity patterns of wildlife reflect human disturbance, this study provides useful ecological information for developing appropriate management plans for the coexistence of water deer and wild boar in suburban areas.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.4
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• pp.1-14
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• 2024

Otters, designated as Class I endangered wildlife due to population declines resulting from urban development and stream burial, have seen increased appearances in freshwater environments since the nationwide ban on stream filling in 2020 and the implementation of urban stream restoration projects. There is a pressing need for scientific and strategic conservation measures for otters, an umbrella and vulnerable species in aquatic ecosystems. Therefore, this study predicts potential otter habitats using the species distribution model MaxEnt, focusing on Hwangguji Stream in Suwon, and proposes conservation strategies. Otter signs were surveyed over three years from 2019 to 2021 with citizen scientists, serving as presence data for the model. The model's outcomes were enhanced by analyzing 'river nature map' as a boundary. MaxEnt compared the performance of 60 combinations of feature classes and regularization multipliers to prevent model complexity and overfitting. Additionally, unmanned sensor cameras observed otter density for model validation, confirming correlations with the species distribution model results. The 'LQ-5.0' parameter combination showed the highest explanatory power with an AUC of 0.853. The model indicated that the 'adjacent land use' variable accounted for 31.5% of the explanation, with a preference for areas around cultivated lands. Otters were found to prefer shelter rates of 10-30% in riparian forests within 2 km of bridges. Higher otter densities observed by unmanned sensors correlated with increasing model values. Based on these results, the study suggests three conservation strategies: establishing stable buffer zones to enhance ecological connectivity, improving water quality against non-point source pollution, and raising public awareness. The study provides a scientific basis for potential otter habitat management, effective conservation through governance linking local governments, sustainable biodiversity goals, and civil organizations.

• Korean Journal of Environment and Ecology
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• v.37 no.6
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• pp.429-438
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• 2023

The forest in the lower Tumen River serves as an important ecosystem spanning the territories of North Korea, Russia, and China, and it provides habitat and movement corridors for diverse mammals, including the endangered Amur tiger (Panthera tigris) and Amur leopard (Panthera pardus). This study focuses on the Mijiang area, situated as a potential ecological corridor connecting North Korea and China in the lower Tumen River, playing a crucial role in conserving and restoring the biodiversity of the Korean Peninsula. This study aimed to identify mammal species and estimate their relative abundance, occupancy, and distribution based on the 48 camera traps installed in the Mijiang area from May 2019 to May 2021. The results confirmed the presence of 18 mammal species in the Mijiang area, including large carnivores like tigers and leopards. Among the dominant mammals, four species of ungulates showed high occupancy and detection rates, particularly the Roe deer (Capreolus pygargus) and Wild boar (Sus scrofa). The roe deer was distributed across all areas with a predicted high occupancy rate of 0.97, influenced by altitude, urban residential areas, and patch density. Wild boars showed a predicted occupancy rate of 0.73 and were distributed throughout the entire area, with factors such as wetland ratio, grazing intensity, and spatial heterogeneity in aspects of the landscape influencing their occupancy and detection rates. Sika deer (Cervus nippon) exhibited a predicted occupancy rate of 0.48, confined to specific areas, influenced by slope, habitat fragmentation diversity affecting detection rates, and the ratio of open forests impacting occupancy. Water deer (Hydropotes inermis) displayed a very low occupancy rate of 0.06 along the Tumen River Basin, with higher occupancy in lower altitude areas and increased detection in locations with high spatial heterogeneity in aspects. This study confirmed that the Mijiang area serves as a habitat supporting diverse mammals in the lower Tumen River while also playing a crucial role in facilitating animal movement and habitat connectivity. Additionally, the occupancy prediction model developed in this study is expected to contribute to predicting mammal distribution within the disrupted Tumen River basin due to human interference and identifying and protecting potential ecological corridors in this transboundary region.