Home     「応用生態工学」既刊巻号リスト     V5N2 > 189-201
会誌キーワード検索 「応用生態工学」掲載論文のタイトル・著者名・キーワード・摘要・Abstractから全文検索を行います
 

line
応用生態工学 5(2), 189-201, 2003

line


原著論文 ORIGINAL PAPER

ECEロゴマーク

分類樹木を用いた生物生息場所の分類‐河川水辺の鳥類を対象とした事例研究

加藤和弘1)・ 一ノ瀬友博2)・ 高橋俊守3)

1)東京大学大学院農学生命科学研究科附属緑地植物実験所 〒262-0018 千葉市花見川区畑町1051
2) 姫路工業大学自然・環境科学研究所/淡路景観園芸学校 〒656-1726 兵庫県津名郡北淡町野島常盤954-2
3) (財)日本生態系協会 〒171-0021 東京都豊島区西池袋2-30-20

Kazuhiro KATOH1), Tomohiro ICHINOSE2) and Toshimori TAKAHASHI3): Classiffication of habitats by "Classification Tree": a case study on riparian habitats of birds. Ecol. Civil. Eng. 5(2), 189-201, 2003.

1) Experimental Station for Landscape Plants, Graduate School of Agricultural and Life Science, the University of Tokyo, 1051, Hata-cho, Hanamigawa-ku, Chiba 262-0018, Japan
2) Institute of Natural and Environmental Science, Himeji Institute of Technology, Awaji Landscape Planning and Horticulture Academy, 954-2, Nojimatokiwa, Hokudancho, Tsuna-gun, Hyogo 656-1726, Japan
3) Ecosystem Conservation Society-Japan, 2-30-20, Nishi-Ikebukuro, Toshima, Tokyo 171-0021, Japan

Abstract:Multivariate analysis of ecological data has been applied to environmental analysis and evaluation. Recently, some ecologists reported that classification and regression trees (CART) are ideally suited for the analysis of complex ecological data. We use classification tree to analyze the relationship between avian species composition and habitat conditions from 37 study plots located in a riparian area of the Tama-gawa River, Tokyo. The data were comprised of census data of birds and vegetation structural information. First, the study plots were classified by TWINSPAN based on the avian species composition.
Then, we tried to recover the grouping of the study plots by classification tree or canonical discriminant analysis using the vegetation structural information so that we could find the relationship between avian species composition and vegetation structure. Classification tree analysis performed almost as well as canonical discriminant analysis. Classification tree models explain variation of a single response variable (here, avian fauna type) by repeatedly splitting the study plots into more homogeneous groups, using combinations of explanatory variables (here, vegetation structural parameters). This structure is simple, suitable for dealing with high-order interactions, so that classification tree can give easily interpretable results. Finally, based on the comparison of classification tree and canonical discriminant analysis, we concluded that classification tree was more suitable than discriminant analysis for landscape evaluation and planning..

Key words: classification trees, discriminant analysis, landscape planning, species composition, vegetation structure

摘要

多摩川中流部の水辺における鳥相及び植生の調査結果を「分類樹木」の手法により分析し,その有効性を検討した.分類樹木は,機能的には判別分析に相当するが,本研究において得られた判別精度は,両者でほぼ同等であった.一方,分類樹木は,Yes-No型の条件判断を繰り返すことで最終的な判別に至るという,わかりやすい構造を持っており,判別分析に比べてより広範囲に応用可能であると考えられた.また,説明変数間に交互作用がある場合にも有効な手法であることが確認された.結論として,ランドスケーブ計画においては判別分析に比べて分類樹木が利用しやすく,今後広く利用され得る手法であると言える.

line 2002年3月15日受付,2003年1月14日受理
1) e-mail: aster@mail.ecc.u-tokyo.ac.jp line
line

Copyright (C) 1999- Ecology and Civil Engineering Society