{"title":"快照日本2023:日本第一个全球标准化协议下的相机陷阱数据集。","authors":"Keita Fukasawa, Takahiro Morosawa, Yoshihiro Nakashima, Shun Takagi, Takumasa Yokoyama, Masaki Ando, Hayato Iijima, Masayuki U Saito, Nao Kumada, Kahoko Tochigi, Akira Yoshioka, Satsuki Funatsu, Shinsuke Koike, Hiroyuki Uno, Takaaki Enomoto, William McShea, Roland Kays","doi":"10.3897/BDJ.13.e141168","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There is an urgent need to develop global observation networks to quantify biodiversity trends for evaluating achievements of targets of Kunming-Montreal Global Biodiversity Framework. Camera traps are a commonly used tool, with the potential to enhance global observation networks for monitoring wildlife population trends and has the capacity to constitute global observation networks by applying a unified sampling protocol. The Snapshot protocol is simple and easy for camera trapping which is applied in North America and Europe. However, there is no regional camera-trap network with the Snapshot protocol in Asia.</p><p><strong>New information: </strong>We present the first dataset from a collaborative camera-trap survey using the Snapshot protocol in Japan conducted in 2023. We collected data at 90 locations across nine arrays for a total of 6162 trap-nights of survey effort. The total number of sequences with mammals and birds was 7967, including 20 mammal species and 23 avian species. Apart from humans, wild boar, sika deer and rodents were the most commonly observed taxa on the camera traps, covering 57.9% of all the animal individuals. We provide the dataset with a standard format of Wildlife Insights, but also with Camtrap DP 1.0 format. Our dataset can be used for a part of the global dataset for comparing relative abundances of wildlife and for a baseline of wildlife population trends in Japan. It can also used for training machine-learning models for automatic species identifications.</p>","PeriodicalId":55994,"journal":{"name":"Biodiversity Data Journal","volume":"13 ","pages":"e141168"},"PeriodicalIF":1.0000,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926606/pdf/","citationCount":"0","resultStr":"{\"title\":\"Snapshot Japan 2023: the first camera trap dataset under a globally standardised protocol in Japan.\",\"authors\":\"Keita Fukasawa, Takahiro Morosawa, Yoshihiro Nakashima, Shun Takagi, Takumasa Yokoyama, Masaki Ando, Hayato Iijima, Masayuki U Saito, Nao Kumada, Kahoko Tochigi, Akira Yoshioka, Satsuki Funatsu, Shinsuke Koike, Hiroyuki Uno, Takaaki Enomoto, William McShea, Roland Kays\",\"doi\":\"10.3897/BDJ.13.e141168\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>There is an urgent need to develop global observation networks to quantify biodiversity trends for evaluating achievements of targets of Kunming-Montreal Global Biodiversity Framework. Camera traps are a commonly used tool, with the potential to enhance global observation networks for monitoring wildlife population trends and has the capacity to constitute global observation networks by applying a unified sampling protocol. The Snapshot protocol is simple and easy for camera trapping which is applied in North America and Europe. However, there is no regional camera-trap network with the Snapshot protocol in Asia.</p><p><strong>New information: </strong>We present the first dataset from a collaborative camera-trap survey using the Snapshot protocol in Japan conducted in 2023. We collected data at 90 locations across nine arrays for a total of 6162 trap-nights of survey effort. The total number of sequences with mammals and birds was 7967, including 20 mammal species and 23 avian species. Apart from humans, wild boar, sika deer and rodents were the most commonly observed taxa on the camera traps, covering 57.9% of all the animal individuals. We provide the dataset with a standard format of Wildlife Insights, but also with Camtrap DP 1.0 format. Our dataset can be used for a part of the global dataset for comparing relative abundances of wildlife and for a baseline of wildlife population trends in Japan. 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Snapshot Japan 2023: the first camera trap dataset under a globally standardised protocol in Japan.
Background: There is an urgent need to develop global observation networks to quantify biodiversity trends for evaluating achievements of targets of Kunming-Montreal Global Biodiversity Framework. Camera traps are a commonly used tool, with the potential to enhance global observation networks for monitoring wildlife population trends and has the capacity to constitute global observation networks by applying a unified sampling protocol. The Snapshot protocol is simple and easy for camera trapping which is applied in North America and Europe. However, there is no regional camera-trap network with the Snapshot protocol in Asia.
New information: We present the first dataset from a collaborative camera-trap survey using the Snapshot protocol in Japan conducted in 2023. We collected data at 90 locations across nine arrays for a total of 6162 trap-nights of survey effort. The total number of sequences with mammals and birds was 7967, including 20 mammal species and 23 avian species. Apart from humans, wild boar, sika deer and rodents were the most commonly observed taxa on the camera traps, covering 57.9% of all the animal individuals. We provide the dataset with a standard format of Wildlife Insights, but also with Camtrap DP 1.0 format. Our dataset can be used for a part of the global dataset for comparing relative abundances of wildlife and for a baseline of wildlife population trends in Japan. It can also used for training machine-learning models for automatic species identifications.
Biodiversity Data JournalAgricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics
CiteScore
2.20
自引率
7.70%
发文量
283
审稿时长
6 weeks
期刊介绍:
Biodiversity Data Journal (BDJ) is a community peer-reviewed, open-access, comprehensive online platform, designed to accelerate publishing, dissemination and sharing of biodiversity-related data of any kind. All structural elements of the articles – text, morphological descriptions, occurrences, data tables, etc. – will be treated and stored as DATA, in accordance with the Data Publishing Policies and Guidelines of Pensoft Publishers.
The journal will publish papers in biodiversity science containing taxonomic, floristic/faunistic, morphological, genomic, phylogenetic, ecological or environmental data on any taxon of any geological age from any part of the world with no lower or upper limit to manuscript size.