Ecology and Development Series No. 10, 2003 - ZEF
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Ecology and Development Series No. 10, 2003 - ZEF

Ecology and Development Series No. 10, 2003 - ZEF Ecology and Development Series No. 10, 2003 - ZEF

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13.07.2015 Views

Floristic analysis of the undisturbed forestdate. The two most polarized positions of the debate revolve around the ‘supper-organism’concept of Clements (1916; 1936) and the ‘individualistic’ concept of Gleason (1917;1926). Clements viewed communities as holistic and interdependent, whereas the"Gleasonians" saw plant communities as random assemblages of species with similaradaptations to the abiotic environment. There are, however, direct and indirect positiveinteractions within plant communities, and hence plant species in communities are moreinterdependent (Callaway 1997) than some current theories (Whittaker 1951; Wilson et al.1996; Ter Braak and Prentice 1998), which regarding plant communities as randomassemblages would allow. The issue of interdependence has a far-reaching implication onhow we conserve and use resources in the natural world (Callaway 1997). A community isthe product of several ecological processes, which include competition and facilitation(Callaway 1997). In this study the term "plant community" is simply used in the sense ofdescribing a group of the individuals of different plant species occupying the area understudy. In order to make a sound management decision in nature conservation, it is importantto know which species occur together, since the loss of seemingly insignificant species mayhave important effects on the other species (Ehrlich 1990; Ehrlich and Wilson 1991; Nossand Cooperrider 1994). Hence, the different groups or community types identified in thisstudy represent groups of sites that have certain internal homogeneity in their speciescomposition, and can be considered as distinct units in which specific management orconservation measures relevant for the major species comprising the assemblage can bemade.4.2 Materials and Methods4.2.1 The data setVegetation survey data from 58 study plots in the undisturbed forest were used for theanalysis. Details of the sampling design are described in chapter 3.2.1 of this dissertation.Systematic sampling design was used for data collection, in which sample plots were laidalong transects. The major sample plot is 20 m by 20 m, with subplots of 3 m x 3 m and 1m x 1 m for smaller size plants in order to sample different size classes in different sizedplots. Several vegetation and environmental data were collected from the plots (Chapter37

Floristic analysis of the undisturbed forest3.2.1). For the analysis in this chapter, only the abundance data of trees, shrubs andclimbers, and the environmental data (soils, slope altitude aspects) were used. Herbs wereexcluded since data from different plots were collected during different seasons, wet anddry. Most annual herbs die during the dry season, making data on herbs collected in wetand dry seasons not comparable. In the quantitative data analysis, rare species (i.e., withless than 5% relative frequency) were excluded to avoid noise, since cluster analysis issensitive to rare species that occur in few plots, while in Principal Component Analysis(PCA) a rare species has no significant contribution (Ter Braak 1995; Grace et al. 2000).4.2.2 Classification and indicator species analysisCluster analysis using Euclidean distances and Ward’s method of hierarchical grouping wasperformed to identify community types (McCune & Mefford 1999). Ward’s method wasused since it minimizes the total within group mean sum of squares or residual sum ofsquares (Van Tongeren 1995). In ecology, cluster analysis is used to classify sites ∗ , speciesor variables into groups based on their similarities (Van Tongeren 1995; McCune &Mefford 1999). It helps to identify structure in the data by explicitly identifying groups inthe raw data.Statistical validity of the identified groups was evaluated using the multi-responsepermutation procedure (MRPP) (Biondini et al. 1985; Mielke and Berry 2001, McCune andGrace 2002). The Euclidean distance was used as a distance measure in the MRPP test. TheMRPP is a nonparametric procedure for testing the hypothesis of ‘no difference’ betweentwo or more groups of entities (McCune & Mefford 1999). It does not require multivariatenormality or homogeneity of variances. Both cluster analysis and MRPP were performedusing PC-ORD software (McCune & Mefford 1999).A very common goal in vegetation analysis is to detect and describe the value ofdifferent species for indicating environmental conditions (McCune & Mefford 1999). Inthis study, the new alternative method of indicator species analysis proposed by Dufrêne &Legendre (1997) was used. This method provides a simple and intuitive solution foridentifying indicator species (McCune & Mefford 1999). The method combines38

Floristic analysis of the undisturbed forest3.2.1). For the analysis in this chapter, only the abundance data of trees, shrubs <strong>and</strong>climbers, <strong>and</strong> the environmental data (soils, slope altitude aspects) were used. Herbs wereexcluded since data from different plots were collected during different seasons, wet <strong>and</strong>dry. Most annual herbs die during the dry season, making data on herbs collected in wet<strong>and</strong> dry seasons not comparable. In the quantitative data analysis, rare species (i.e., withless than 5% relative frequency) were excluded to avoid noise, since cluster analysis issensitive to rare species that occur in few plots, while in Principal Component Analysis(PCA) a rare species has no significant contribution (Ter Braak 1995; Grace et al. 2000).4.2.2 Classification <strong>and</strong> indicator species analysisCluster analysis using Euclidean distances <strong>and</strong> Ward’s method of hierarchical grouping wasperformed to identify community types (McCune & Mefford 1999). Ward’s method wasused since it minimizes the total within group mean sum of squares or residual sum ofsquares (Van Tongeren 1995). In ecology, cluster analysis is used to classify sites ∗ , speciesor variables into groups based on their similarities (Van Tongeren 1995; McCune &Mefford 1999). It helps to identify structure in the data by explicitly identifying groups inthe raw data.Statistical validity of the identified groups was evaluated using the multi-responsepermutation procedure (MRPP) (Biondini et al. 1985; Mielke <strong>and</strong> Berry 2001, McCune <strong>and</strong>Grace 2002). The Euclidean distance was used as a distance measure in the MRPP test. TheMRPP is a nonparametric procedure for testing the hypothesis of ‘no difference’ betweentwo or more groups of entities (McCune & Mefford 1999). It does not require multivariatenormality or homogeneity of variances. Both cluster analysis <strong>and</strong> MRPP were performedusing PC-ORD software (McCune & Mefford 1999).A very common goal in vegetation analysis is to detect <strong>and</strong> describe the value ofdifferent species for indicating environmental conditions (McCune & Mefford 1999). Inthis study, the new alternative method of indicator species analysis proposed by Dufrêne &Legendre (1997) was used. This method provides a simple <strong>and</strong> intuitive solution foridentifying indicator species (McCune & Mefford 1999). The method combines38

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