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Snapshot Japan 2023: the first camera trap dataset under a globally standardised protocol in Japan
Keita Fukasawa1, Takahiro Morosawa2, Yoshihiro Nakashima3
1Biodiversity Division, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan Biodiversity Division, National Institute for Environmental Studies Tsukuba, Ibaraki Japan.
Biodiversity Data Journal
|March 24, 2025
Summary
This study introduces Japan's first camera-trap dataset using the Snapshot protocol, vital for global biodiversity monitoring. The data aids in tracking wildlife populations and supports machine learning for species identification.
Area of Science:
- Ecology
- Conservation Biology
- Wildlife Management
Background:
- Global biodiversity monitoring is crucial for evaluating conservation targets.
- Camera traps offer a scalable solution for wildlife population monitoring.
- The Snapshot protocol, widely used in North America and Europe, lacks a regional network in Asia.
Purpose of the Study:
- To establish the first camera-trap dataset in Japan utilizing the Snapshot protocol.
- To provide baseline data for wildlife population trends in Japan.
- To contribute to global biodiversity observation networks.
Main Methods:
- A collaborative camera-trap survey was conducted across 90 locations in Japan in 2023.
- Data collection involved 6162 trap-nights of survey effort.
- The Snapshot protocol was employed for standardized data collection.
Main Results:
- The survey captured 7967 sequences of mammals and birds, representing 20 mammal and 23 avian species.
- Wild boar, sika deer, and rodents were the most frequently observed species, comprising 57.9% of individuals.
- The dataset is available in Wildlife Insights and Camtrap DP 1.0 formats.
Conclusions:
- This dataset represents a significant contribution to biodiversity monitoring in Japan and globally.
- It serves as a baseline for assessing wildlife population dynamics and informing conservation strategies.
- The data can be utilized for training machine learning models for automated species identification.

