A Study of the Relationships between Vegetation Types and Environmental Factors at Jhuokou River Basin
| Autor: | Ren-Yi Wang, 王仁義 |
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| Rok vydání: | 2006 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 94 Patterns of plant species composition and their relationships to environmental factors were investigated in Jhuokou River basin. 102, 20 × 20 m plots with woody stems ≧1.0 cm diameter at breast height (DBH) data and 12 environmental variables were analysed by Two Way Indicator Species Analysis (TWINSPAN), Detrended Correspondence Analysis (DCA) and Canonical Correspondence Analysis (CCA) to classify the vegetation types and determine the significant environmental variables that affect the distribution of vegetation. Classification and regression tree (CART) were then used to perform vegetation classification tree based on these significant variables. The vegetation classification result showed that 102 sampling plots can be classified into 9 vegetation types : 1. Daphniphyllum hlaucescens subsp. oldhamii - Cyclobalanopsis morii vegetation type ; 2. Neolitsea acuminatissima - Cyclobalanopsis morii vegetation type ; 3. Adinandra formosana - Lithocarpus lepidocarpus - Machilus thunbergii vegetation type ; 4. Elaeocarpus japonicus - Castanopsis cuspidate - Machilus thunbergii vegetation type ; 5. Ardisia quinquegona - Tricalysia dubia - Beilschmiedia erythrophloia vegetation type ; 6. Schefflera octophylla - Helicia formosana - Beilschmiedia erythrophloia vegetation type ; 7. Castanopsis formosana - Mallotus paniculatus - Schefflera octophylla vegetation type ; 8. Cyclobalanopsis glauca - Glochidion rubrum - Sapindus mukorossii vegetation type ; 9. Champereia manillana - Kleinhovia hospita - Murraya vegetation type. DCA and CCA distinguished 8 significant environmental variables from 12 measured variables. Altitude and warmth index were the most important variables in 8 significant environmental variables, but were highly correlated. When used vegetation classification tree to predict the position of the reference vegetation alliance, average accuracy was 56.9 %. The results indicated that the current data was still insufficient to predict the vegetation type at alliances level with environmental variables. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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