| 研究課題/領域番号 |
22KF0213
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| 補助金の研究課題番号 |
22F22100 (2022)
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| 研究種目 |
特別研究員奨励費
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| 配分区分 | 基金 (2023)
補助金 (2022) |
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| 応募区分 | 外国 |
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| 審査区分 |
小区分39060:生物資源保全学関連
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| 研究機関 | 京都大学 |
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研究代表者 |
小山 里奈 京都大学, 情報学研究科, 准教授 (50378832)
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| 研究分担者 |
RYU HEUNGJIN 京都大学, 情報学研究科, 外国人特別研究員
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| 研究期間 (年度) |
2023-03-08 – 2025-03-31
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| 研究課題ステータス |
交付 (2023年度)
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| 配分額 *注記 |
2,200千円 (直接経費: 2,200千円)
2024年度: 500千円 (直接経費: 500千円)
2023年度: 1,100千円 (直接経費: 1,100千円)
2022年度: 600千円 (直接経費: 600千円)
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| キーワード | citizen science / echolocation / bioacoustics / bats / Kyoto / Tsushima / Citizen science / Network / Bat survey / Bioacoustics / Sea |
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| 研究開始時の研究の概要 |
Citizen science -public engagement in science- is a fast-growing field in science and an efficient way to facilitate public education and change public attitudes towards the target species. Due to the COVID-19 outbreak, there are increasing concerns about bats conservation. However, data on many bat species in Japan and Korea are very scarce. In this study, by we will conduct bat surveys in Japan and Korea with citizens and try to find migrating bat species between the two countries. By doing so, we will also promote the conservation of bats in Japan and Korea and public and research networks.
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| 研究実績の概要 |
In 2023, we spearheaded two distinct surveys involving 20 citizen participants in Kyoto and the Korean Strait. The first, an urban survey, entailed conducting a bioacoustic survey on foot in Kyoto, approximately an hour after sunset. The second, a sea survey, involved deploying unmanned recorders on fishing vessels and a ferry to investigate bat migration over the sea between Japan and South Korea.
These surveys yielded fruitful results, with successful recordings of 3 to 4 bat species in Kyoto, 4 to 6 species along the coastlines, and one species over the sea. Preliminary data analysis also suggested variations in emergence times among different bat species in coastal areas and skewed bat emergence locations in Kyoto. Additionally, the establishment of networks in Tsushima Island and Kyoto for these surveys was a significant achievement.
In conjunction with data collection, we secured a research grant from Wildlife Acoustics Inc., USA. They provided five Song Meter Mini Bat devices, which were utilized to collect bat echolocation calls over the sea on the fishing vessels. Despite losing two devices due to a typhoon in August, we managed to collect over 400GB of recordings. The support from JSPS, coupled with the invaluable assistance from Wildlife Acoustics Inc., significantly contributed to the success of this project.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
2: おおむね順調に進展している
理由
The project’s progress was also largely thanks to the assistance from the staffs and other members at the host university. Their support ensured that the project proceeded as planned. All necessary research permits were obtained in a timely manner, and data collection involving citizens was executed effectively. This collaborative effort was instrumental in the smooth execution of the project.
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| 今後の研究の推進方策 |
This year, we will continue the urban survey in Kyoto from July to October, aiming to investigate potential annual variations in bat emergence and diversity within Japan’s urban areas. However, due to budget constraints, the continuation of the sea survey may not be feasible this year.
In the interim, before the surveys for this year start, we plan to explore why bats are utilizing coastal areas and why certain bat species are only detected during specific months in Kyoto. This investigation will involve analyzing variations in echolocation calls, including feeding buzzes and social calls. Factors such as insect availability and thermal preference could significantly influence the emergence times and locations of different bat species. Therefore, a thorough investigation of references and publicly available datasets will be conducted. This research will provide valuable insights into the behavior and preferences of bats, contributing to our understanding of their patterns and aiding in the development of effective conservation strategies.
One of the most critical objectives for this year is the development of a tool to manage the large volume of data collected last year. Given the size of the data, the implementation of new methods, such as deep learning or algorithm-based approaches, is necessary. This endeavor will be undertaken in collaboration with both internal and external researchers.
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