Impact assessment of the big earthquake on meiofaunal assemblage using a rapid and automated analysis method

2018 Fiscal Year Final Research Report

• Project/Area Number: 16K21698
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Biodiversity/Systematics; Environmental dynamic analysis
• Research Institution: Japan Agency for Marine-Earth Science and Technology
• Principal Investigator: KITAHASHI Tomo 国立研究開発法人海洋研究開発機構, 海洋生物多様性研究分野, 特任技術副主任 (60713807)
• Project Period (FY): 2016-04-01 – 2019-03-31
• Keywords: メイオファウナ / 巨大地震 / 環境影響評価 / FlowCAM / 深層学習

Outline of Final Research Achievements

In this study, I developed a new method for investigating meiofauna using a imaging flow cytometer (FlowCAM) to investigate rapidly and automatically meiofauna, which has been needed time-consuming works to be investigated. Meiofaunal specimens were extracted from sediment using the centrifugal separation method with colloidal silica solution and then pipetted into the FlowCAM system and imaged. The results based on this new method were comparable to that based on the traditional microscopic methods, which indicating that this new method is useful to investigate meiofaunal assemblage. In addition, I established the image database of meiofauna captured using this new method and tried to automatically classify the images by deep learning methods.

Free Research Field

深海生態学

Academic Significance and Societal Importance of the Research Achievements

メイオファウナは浅海・深海にかかわらず、人為的・自然撹乱が生物に与えた影響をモニタリングする対象として有用である。本研究で確立したFlowCAMを用いたメイオファウナの解析手法により、メイオファウナ群集の解析が格段にスピードアップするため、生物群集の変化をより迅速に検出でき、環境改変による環境影響評価を素早く行うことができる。また、深層学習による自動分類システムが完成すれば、半自動で精度の高い影響評価を行うことができると期待される。