Updated on 2021/11/02

写真a

 
WATANABE Shuntaro
 
Organization
Research Field in Science, Science and Engineering Area Graduate School of Science and Engineering (Science) Department of Science Biorogy Program Assistant Professor
Title
Assistant Professor
Contact information
メールアドレス

Degree

  • Doctor (Environmental Science) ( 2014.11   The University of Shiga Prefecture )

Research Interests

  • Plant Ecology

Research Areas

  • Life Science / Ecology and environment

  • Environmental Science/Agriculture Science / Environmental dynamic analysis

  • Life Science / Forest science

Research History

  • Kagoshima University   Research Field in Science, Science and Engineering Area Graduate School of Science and Engineering (Science) Department of Science Biorogy Program   Assistant Professor

    2020.4

  • Kagoshima University   Research Field in Science, Science and Engineering Area Graduate School of Science and Engineering (Science) Earth and Environmental Sciences Course   Assistant Professor

    2020.3

Professional Memberships

  • THE SOCIETY FOR THE STUDY OF SPECIES BIOLOGY

  • THE ECOLOGICAL SOCIETY OF JAPAN

 

Papers

  • Shuntaro Watanabe;Yuri Maesako .  Co-occurrence pattern of congeneric tree species provides conflicting evidence for competition relatedness hypothesis .  PeerJ   2021.11Co-occurrence pattern of congeneric tree species provides conflicting evidence for competition relatedness hypothesisReviewed

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: 10.7717/peerj.12150

  • Shuntaro Watanabe, Kazuaki Sumi, Takeshi Ise .  Identifying the vegetation type in Google Earth images using a convolutional neural network: a case study for Japanese bamboo forests .  BMC Ecology20 ( 1 )   2020.12Reviewed

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    Publishing type:Research paper (scientific journal)   Publisher:Springer Science and Business Media LLC  

    <title>Abstract</title><sec>
    <title>Background</title>
    Classifying and mapping vegetation are crucial tasks in environmental science and natural resource management. However, these tasks are difficult because conventional methods such as field surveys are highly labor-intensive. Identification of target objects from visual data using computer techniques is one of the most promising techniques to reduce the costs and labor for vegetation mapping. Although deep learning and convolutional neural networks (CNNs) have become a new solution for image recognition and classification recently, in general, detection of ambiguous objects such as vegetation is still difficult. In this study, we investigated the effectiveness of adopting the chopped picture method, a recently described protocol for CNNs, and evaluated the efficiency of CNN for plant community detection from Google Earth images.


    </sec><sec>
    <title>Results</title>
    We selected bamboo forests as the target and obtained Google Earth images from three regions in Japan. By applying CNN, the best trained model correctly detected over 90% of the targets. Our results showed that the identification accuracy of CNN is higher than that of conventional machine learning methods.


    </sec><sec>
    <title>Conclusions</title>
    Our results demonstrated that CNN and the chopped picture method are potentially powerful tools for high-accuracy automated detection and mapping of vegetation.


    </sec>

    DOI: 10.1186/s12898-020-00331-5

    Other Link: http://link.springer.com/article/10.1186/s12898-020-00331-5/fulltext.html

  • Shuntaro Watanabe, Kazuaki Sumi, Takeshi Ise .  Identifying the vegetation type in Google Earth images using a convolutional neural network: a case study for Japanese bamboo forests .  BMC Ecology   2020.11Identifying the vegetation type in Google Earth images using a convolutional neural network: a case study for Japanese bamboo forestsReviewed

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    Language:English   Publishing type:Research paper (scientific journal)  

  • 渡部俊太郎, 大西信徳, 皆川まり, 伊勢武史 .  深層学習による画像認識技術の生態学への応用 -植物種と植生の識別を中心に- .  保全生態学研究   2020.3深層学習による画像認識技術の生態学への応用 -植物種と植生の識別を中心に- Reviewed

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

  • Shuntaro Watanabe, Masanori Onishi, Mari Minagawa, Takeshi Ise .  深層学習による画像認識技術の生態学への応用-植物種と植生の識別を中心に- .  Japanese Journal of Conservation Ecology   2020.3深層学習による画像認識技術の生態学への応用-植物種と植生の識別を中心に-Reviewed

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Research paper (scientific journal)  

  • 前迫ゆり、渡部俊太郎、中野智之 .  田辺湾畠島の植生 .  地域自然史と保全41 ( 2 ) 131 - 141   2020田辺湾畠島の植生Reviewed

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

  • 前迫ゆり、渡部俊太郎、中野智之 .  田辺湾畠島の植生 .  地域自然史と保全   2019.12田辺湾畠島の植生 Reviewed

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

  • Takeshi Ise, Shigeki Ikeda, Shuntaro Watanabe, Kazuhito Ichii .  Regional-scale data assimilation of a terrestrial ecosystem model: leaf phenology parameters are dependent on local climatic conditions. .  Frontiers in environmental science   2018.9Regional-scale data assimilation of a terrestrial ecosystem model: leaf phenology parameters are dependent on local climatic conditions. Reviewed

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    Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.3389/fenvs.2018.00095

  • Shuntaro Watanabe, Koh‑Ichi Takakura, Yuko Kaneko, Naohiko Noma, Takayoshi Nishida .  Skewed male reproductive success and pollen transfer in a small fragmented population of the heterodichogamous tree Machilus thunbergii. .  Journal of Plant Research   2018.2Skewed male reproductive success and pollen transfer in a small fragmented population of the heterodichogamous tree Machilus thunbergii. Reviewed

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    Language:English   Publishing type:Research paper (scientific journal)  

  • Watanabe S, Sumi K, Ise T .  Using deep learning for bamboo forest detection from Google Earth images. .  bioRxiv   2018Using deep learning for bamboo forest detection from Google Earth images.

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    Language:English   Publishing type:Research paper (scientific journal)  

  • Watanabe S, Takakura K, Kaneko Y, Noma N, Nishida T .  Skewed male reproductive success and pollen transfer in a small fragmented population of the heterodichogamous tree Machilus thunbergii. .  Journal of Plant Research131   623 - 631   2018Skewed male reproductive success and pollen transfer in a small fragmented population of the heterodichogamous tree Machilus thunbergii.Reviewed

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    Language:English   Publishing type:Research paper (scientific journal)  

  • Ise T, Ikeda S, Watanabe S, Ichii K .  Regional-scale data assimilation of a terrestrial ecosystem model: leaf phenology parameters are dependent on local climatic conditions. .  Frontiers in Environmental Science6   1 - 10   2018Regional-scale data assimilation of a terrestrial ecosystem model: leaf phenology parameters are dependent on local climatic conditions.Reviewed

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    Language:English   Publishing type:Research paper (scientific journal)  

  • Shuntaro Watanabe, Yuko Kaneko, Yuri Maesako, Naohiko Noma .  Detecting the Early Genetic Effects of Habitat Degradation in Small Size Remnant Populations of Machilus thunbergii Sieb. et Zucc. (Lauraceae) .  International Journal of Forestry Research   2017.2Detecting the Early Genetic Effects of Habitat Degradation in Small Size Remnant Populations of Machilus thunbergii Sieb. et Zucc. (Lauraceae)Reviewed

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.1155/2017/9410626

  • Shuntaro Watanabe, Yuko Kaneko, Yuri Maesako, Naohiko Noma .  Detecting the Early Genetic Effects of Habitat Degradation in Small Size Remnant Populations of Machilus thunbergii Sieb. et Zucc. (Lauraceae) .  International Journal of Forestry Research2017   2017Detecting the Early Genetic Effects of Habitat Degradation in Small Size Remnant Populations of Machilus thunbergii Sieb. et Zucc. (Lauraceae)Reviewed

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Hindawi Limited  

    Habitat degradation caused by human activities has reduced the sizes of many plant populations worldwide, generally with negative genetic impacts. However, detecting such impacts in tree species is not easy because trees have long life spans. Machilus thunbergii Sieb. et Zucc. (Lauraceae) is a dominant tree species of broad-leaved evergreen forests distributed primarily along the Japanese coast. Inland habitats for this species have become degraded by human activities. To investigate the effects of habitat degradation on genetic structure, we compared the genetic diversities of mature and juvenile trees of five M. thunbergii populations around Lake Biwa in Japan. Allelic diversity was influenced by past lineage admixture events, but the effects of forest size were not clear. On the other hand, the inbreeding coefficient of the juvenile stage was higher in small populations, whereas large populations maintained panmictic breeding. Also, the extent of genetic differentiation was greater in juveniles than in mature trees. We detected the early genetic effects of habitat degradation in small, isolated M. thunbergii populations, indicating that habitat degradation increases inbreeding and genetic differentiation between populations.

    DOI: 10.1155/2017/9410626

    Scopus

  • Shuntaro Watanabe, Naohiko Noma, Takayoshi Nishida .  Flowering phenology and mating success in the heterodichogamous tree Machilus thunbergii Sieb. et Zucc (Lauraceae). .  Plant Species Biology   2016.3Flowering phenology and mating success in the heterodichogamous tree Machilus thunbergii Sieb. et Zucc (Lauraceae).Reviewed

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    Authorship:Lead author, Corresponding author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.1111/1442-1984.12078

  • Shuntaro Watanabe, Yuko Kaneko, Yuri Maesako, Naohiko Noma .  Range expansion and lineage admixture of the Japanese evergreen tree Machilus thunbergii in central Japan .  Journal of Plant Research   2014.11Range expansion and lineage admixture of the Japanese evergreen tree Machilus thunbergii in central Japan Reviewed

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)  

    DOI: https://doi.org/10.1007/s10265-014-0650-2

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Books

  • Monitoring tropical insects in the 21st century International journal

    Greg Lamarre, Tom Fayle, Simon Segard, Benita Laird-Hopkins, Akihiro Nakamura, Daniel Souto-Vilarósa, Shuntaro Watanabe, Yves Basset( Role: Joint author)

    Elsevier  2020.3 

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    Language:English Book type:Scholarly book

    DOI: https://doi.org/10.1016/bs.aecr.2020.01.004

  • Monitoring tropical insects in the 21st century

    Lamarre GP, Fayle TM, Segar ST, Laird-Hopkins B, Nakamura A, Souto-Vilarós D, Watanabe S, Basset Y( Role: Contributor)

    2020.3 

MISC

  • Applications of image recognition technology for biodiversity monitoring Invited

    Shuntaro Watanabe, Takeshi Ise

    Image Laboratory   32 ( 1 )   45 - 50   2021.1

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    Authorship:Lead author, Corresponding author   Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

Awards

  • Plant Species Biology Best Paper Award

    2017   The Society for the Study of Species Biology  

    Watanabe Shuntaro

Research Projects

  • 植物らしさとは何か:ディープラーニングによる革新的な植生自動識別手法の開発と応用

    2018.4

    文部科学省  科学研究費補助金(基盤研究(B)) 

    伊勢 武史

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    Grant type:Competitive

 

Teaching Experience

  • 森林環境学I

    Institution:滋賀県立大学

  • 基礎スキル演習1

  • フィールドプラクティス2

  • フィールドスタジオ演習2