• Korean Journal of Environment and Ecology
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• v.29 no.3
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• pp.344-352
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• 2015

This study aims to identify the difference in the starting time of the dawn chorus of different species of birds and related environmental conditions. For this study, the bird songs were recorded every 2 hours a day starting from 2 hours before sunrise for a whole spring season (from April to June, 2014) in Korea. The recorded sounds were analyzed to find the starting time of each species' song by sonogram pattern using a sound analyzing program (Adobe Audition CC). To analyze the relationship between the environmental conditions and the time of the birdsong of each species, we collected the data of environmental conditions: daily precipitation, Julian date, time of sunrise and moonrise, temperature data and twilight time from the Korea Meteorological Office. As a result of this study, it was found that there are several statistical correlation between the starting time of the birdsong and environmental conditions (every environmental condition except daily precipitation and time of moonrise). Also, the difference of the starting time among each species were identified. The species were divided into 3 groups (early, mid and late) by their wake-up time. Ring-necked pheasant and yellow-throated bunting were categorized as 'Early' group and all woodpeckers were categorized as'Late' group. This study is significant as it first presented a classification of wild birds in Korea by the starting time of their dawn chorus. However, further studies are required to identify why each species to do their dawn singing at different times.

• Korean Journal of Environment and Ecology
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• v.33 no.6
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• pp.636-644
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• 2019

The purpose of this study was to investigate the callings of nocturnal birds using bioacoustic recording technology to identify species and to analyze the ecological characteristics of each species. Three sites - Seoraksan National Park, National Institute of Ecology, and Mudeungsan National Park - were investigated. The investigation period was from the middle of April 2018 to early March 2019 for Seoraksan national park, from late February of 2018 to the middle of February 2019 for the National Institute of Ecology, and from the middle of February 2018 to the end of August 2018 for Mudeungsan National Park. The main research results are as follows. Firstly, nocturnal bird species identified by the survey included Caprimulgus indicus, Otus sunia, Zoothera aurea, Bubo bubo, and Strix uralensis, 5 species in total. Secondly, the breeding call period of each species was from early May to early August for C. indicus, from early April to the end of September for O. sunia, from early March to early October for Z. aurea, from late September to early February for B. bubo, and from mid-January to early March for S. uralensis. Thirdly, the mating call rhythm was between 16:00 and 10:00 on the following day for all the observed species in the three regions, and the peak time zone was from 20:00 to 06:00 on the following day. Fourthly, there was no correlation between the cumulative call frequency and the precipitation for each species. Fifthly, the mean temperature during the period when the specific calls of nocturnal birds were detected was -4.00 ℃ for S. uralensis, 2.58 ℃ for B. bubo, 13.66 ℃ for Z. aurea, 19.50 ℃ for O. sunia, and 20.77 ℃ for C. indicus. The ANOVA results showed that there was a significant difference in mean temperature for the calling by species and that the mean temperature was S. uralensis, B. bubo, Z. aurea, and O. sunia-C. indicus, in the ascending order, for 4 groups in total. The period of the specific mating calls confirmed by the study is a period in which the frequency of calls was the highest among the periods when the specific calls were detected. Since it is associated with the known mating period of each species, the period of the high frequency of calls confirmed by the bioacoustic monitoring can be regarded as the mating season. This study is meaningful in that it is the early research that has used the bioacoustic recording technology to identify species and ecological characteristics of species of nocturnal birds in Korea.

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.411-418
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• 2014

This study seeks to identify the effects of light pollution and environmental factors on Great Tits(Parus major) bird's chirping at dawn. For this research, the campus of Sanji University, Wonju, South Korea was selected as the area with light pollution and the western forest of the Chiaksan National Park was chosen as the natural area herein. The Recording period was between March 26th and May 30th, 2014. As a result of analyzing the chirping time according to light pollution, it was found that the light pollution area clearly showed earlier chirping time than the natural area (p<0.05). Great Tits(P. major) normally start their first chirping before sunrise and in most of the days under investigation of this research, those in Sanji University started to chirp earlier. This faster chirping time seems to improve the chance for the female birds to mate with immature males thus, baby birds hatch earlier than the appropriate breeding season and results in the lack of feed resources. The correlation between Great Tits'(P. major) dawn chirping and environmental factors were investigated herein including the time of sunrise, civil twilight, navigation twilight, astronomical twilight, average temperature, highest temperature, lowest temperature, time of moonrise and cloudiness. The first chirping time of wild birds in the day was found to have correlations with all of the environmental factors excluding the time of moonrise and cloudiness. Great Tits(P. major) started their first chirping before sunrise when the day started to break around civil twilight. Along with the earlier sunrise and higher air temperature, their dawn chirping time was also quickened. The time of moonrise and cloudiness did not show a correlation and further follow-up studies will be necessary in this regard.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.15-25
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• 2024

For effective analysis of animal ecosystems, technology that can automatically identify the current status of animal habitats is crucial. Specifically, animal sound classification, which identifies species based on their sounds, is gaining great attention where video-based discrimination is impractical. Traditional studies have relied on a single deep learning model to classify animal sounds. However, sounds collected in outdoor settings often include substantial background noise, complicating the task for a single model. In addition, data imbalance among species may lead to biased model training. To address these challenges, in this paper, we propose an animal sound classification scheme that combines predictions from multiple models using Focal Loss, which adjusts penalties based on class data volume. Experiments on public datasets have demonstrated that our scheme can improve recall by up to 22.6% compared to an average of single models.

• Korean Journal of Environment and Ecology
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• v.37 no.5
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• pp.327-336
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• 2023

This study aimed to propose an effective method for surveying wild birds by comparing the results of bioacoustic detection with those obtained through a field survey. The study sites were located at Dongbaek-dongsan and a 1100-altitude wetland in Jeju-do, South Korea. The bioacoustic detection was conducted over the course of 12 months in 2020. For the bioacoustic detection, a Song-meter SM4 device was installed at each study site, recording bird songs in 1-min per hour, .wav, and 44,100 Hz format. The findings of the field survey were taken from the 「Long-term trends of Bird Community at Dongbaekdongsan and 1100-Highland Wetland of Jeju Island, South Korea.」 by Banjade et al. (2019). The results of this study are as follows. First, the avifauna identified using bioacoustic detection comprised 29 families and 46 species in Dongbaek-dongsan, and 16 families and 25 species in the 1100-altitude wetland. Second, based on the song frequency, the dominant species in Dongbaek-dongsan were Hypsipetes amaurotis (Brown-eared Bulbul, 33.62%), Horornis diphone (Japanese Bush Warbler, 12.13%), and Zosterops japonicus (Warbling White-eye, 9.77%). In the 1100-altitude wetland the dominant species were Corvus macrorhynchos (Large-billed Crow, 27.34%), H. diphone (19.43%), and H. amaurotis (16.56%). Third, in the field survey conducted at Dongbaek-dongsan, the number of detected bird species was 39 in 2009, 51 in 2012, 35 in 2015, and 45 in 2018, while the bioacoustic detection identified 46 species. In the field survey conducted in the 1100-altitude wetland, the number of detected bird species was 37 in 2009, 42 in 2012, 34 in 2015, and 38 in 2018, while the bioacoustics detection identified 25 species. Overall, 43.6% of the 78 species detected in the field survey in Dongbaek-dongsan (34 species) were identified using bioacoustic detection, and 38.3% of the 47 species detected in the field survey in the 1100-altitude wetland (18 species) were identified using bioacoustic detection. Fourth, the bioacoustic detection identified 9 families and 12 species of birds in Dongbaek-dongsan, and 3 families and 7 species of birds in the 1100-altitude wetland. No results from field survey were available for these species. The identified birds were predominantly nocturnal, including Otus sunia (Oriental Scops Owl) and Ninox japonica (Northern Boobook), passage migrants, including Larvivora cyane (Siberian Blue Robin), L. sibilans (Rufous-tailed Robin), and winter visitors with a relatively small number of visiting individuals, such as Bombycilla garrulus (Bohemian Waxwing) and Loxia curvirostra (Red Crossbill). Fifth, the birds detected in the field survey but not through bioacoustic detection included 18 families and 48 species in Dongbaek-dongsan and 14 families and 27 species in the 1100-altitude wetland; the most representative families were Ardeidae, Accipitridae, and Muscicapidae. This study is significant as it provides essential data supporting the possibility of an effective survey combining bioacoustic detection with field studies, given the increasing use of bioacoustic devices in ornithological studies in South Korea.