
Determination of optimum number of ecological groups in vegetation classification (Case study: Kheiroudkenar Forests) | ||
تحقیقات جنگل و صنوبر ایران | ||
Article 11, Volume 16, Issue 3 - Serial Number 33, December 2008, Pages 466-455 PDF (231.49 K) | ||
Document Type: Research article | ||
Authors | ||
Javad Eshaghi Rad* 1; Ghavamoddin Zahedi Amiri2; Asadollah Mataji3 | ||
1Assistant Prof., University of Urmia | ||
2Associate Prof., University of Tehran | ||
3Assistant Prof., Azad University, Science and Research Branch | ||
Abstract | ||
This study was carried out in Carpino-Fagetum orientalis, Rusco-Fagetum orientalis, Fagetum orientalis and Alno-Fagetum orientalis forest communities of Namkhaneh, Gorazbon and Chelir districts of Kheiroudkenar forests. The aim of the research was determination of the optimum number of ecological groups in the study area using indicator species analysis. Selective stratification sampling method was used to locate samples. One plot was laid out on each aspect and on each community. Totally, 120 samples were selected in the Fagus orientalis communities in the study area. The plot size was 400m2 considering to minimal area method. At each sample, floristic list in separate strata (trees, shrubs and herbs) were recorded using Braun-Blanquet scales. Cluster analysis was used for classification of samples. In this method, Sorenson distance measure was applied to calculate the distance matrix and flexible beta method as a cluster linkage measure. Indicator species analysis accompanied with Monte Carlo test was used to choose the optimum number of the clusters. Results showed that if four clusters were selected in the vegetation classification of Fagus orientalis communities in the study area based on cluster analysis, the number of indicator species, which had significant indicator values, would be maximum. Therefore, four groups could be introduced as the optimum number of ecological groups of Fagus orientalis communities in the study area. | ||
Keywords | ||
beech; ecological groups; cluster analysis; indicator species analysis | ||
References | ||
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