Tatsuro Nakaji 研究室

AI 要約（直近 5 年の研究成果）

※ AI（Claude）が、公開されている論文要旨から研究の問い・手法・主要な発見を事実情報として抽出・再構成して自動生成しています。誤りを含む可能性があるため、正確性は研究室公式情報でご確認ください。

研究成果（23 件）

• [2026] Variation in fine root production across four different forest types in Japan
  DOI: https://doi.org/10.1016/j.foreco.2026.124030
• [2026] A novel method based on high‐resolution imaging spectroscopy to predict fine‐root traits and the economics space of fresh tree roots
  DOI: https://doi.org/10.1111/nph.71366
• [2026] Development of GCOM-C/SGLI ground-area-based chlorophyll content estimation: a computationally efficient algorithm free from LAI and vegetation classification
  DOI: https://doi.org/10.5194/egusphere-egu26-16127
• [2026] Characterizing typhoon-disturbed biomass dynamics using multitemporal LiDAR, high-resolution imagery, and deep learning in cool-temperate forest, northern Japan
  DOI: https://doi.org/10.1016/j.foreco.2026.123692
• [2026] Spatio-temporal variation and determinants of fish community structure in a mountain floodplain stream.
  DOI: https://doi.org/10.3825/ece.24-00013
• [2025] Responses of growth and root dynamics to soil compaction stress in Japanese larch ( <i>Larix kaempferi</i> ) seedlings
  DOI: https://doi.org/10.1080/13416979.2025.2595366
• [2025] Adding color to spring: exuberant body color variation in brown frog tadpoles
  DOI: https://doi.org/10.1093/cz/zoaf072
• [2025] The JapanFlux2024 dataset for eddy covariance observations covering Japan and East Asia from 1990 to 2023
  DOI: https://doi.org/10.5194/essd-17-3807-2025
• [2025] UAVによって拡がる生態学
• [2025] High‐resolution digital canopy height models, terrain models, ortho‐mosaic photos, and canopy tree crown shapes derived from <scp>UAV</scp> ‐borne <scp>LiDAR</scp> at 22 tree census plots across Japanese natural forests
  DOI: https://doi.org/10.1111/1440-1703.12555

科研費（0 件）

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所属学会・役職（0 件）

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