Snapshot Japan 2023: the first camera trap dataset under a globally standardised protocol in Japan.

IF 1 4区 环境科学与生态学 Q3 BIODIVERSITY CONSERVATION
Biodiversity Data Journal Pub Date : 2025-03-13 eCollection Date: 2025-01-01 DOI:10.3897/BDJ.13.e141168
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
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引用次数: 0

Abstract

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.

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。
背景:为评价昆明-蒙特利尔全球生物多样性框架目标的实现情况,迫切需要建立量化生物多样性趋势的全球观测网络。相机陷阱是一种常用的工具,有可能加强监测野生动物种群趋势的全球观测网,并有能力通过应用统一的抽样协议构成全球观测网。快照协议是简单和容易的相机捕获,应用于北美和欧洲。然而,在亚洲没有使用Snapshot协议的区域性摄像机陷阱网络。新信息:我们展示了2023年在日本使用Snapshot协议进行的协作相机陷阱调查的第一个数据集。我们在9个阵列的90个地点收集了数据,总共进行了6162个陷阱夜的调查工作。与哺乳动物和鸟类的序列总数为7967条,其中哺乳动物20种,鸟类23种。除人类外,野猪、梅花鹿和啮齿动物是相机陷阱中最常见的分类群,占所有动物个体的57.9%。我们提供的数据集具有野生动物洞察的标准格式,但也有Camtrap DP 1.0格式。我们的数据集可以作为全球数据集的一部分,用于比较野生动物的相对丰度,并作为日本野生动物种群趋势的基线。它还可以用于训练机器学习模型,用于自动物种识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biodiversity Data Journal
Biodiversity Data Journal Agricultural 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.
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