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Comparing of numerical classification of survey the vegetation ecological of east rangeland of Semnan | ||
| پژوهش های آبخیزداری | ||
| Article 10, Volume 27, Issue 2 - Serial Number 103, July 2014, Pages 93-106 PDF (868.25 K) | ||
| Document Type: Research | ||
| DOI: 10.22092/wmej.2014.106251 | ||
| Authors | ||
| Leila Khalasi Ahvazi1; Mohammad Ali Zare Chahouki* 2 | ||
| 1pHD student, Faculty of Natural Resources, University of Gorgan | ||
| 2Professor, Faculty of Natural Resources, University of Tehran | ||
| Abstract | ||
| Quantitative analysis of ecological relationships between vegetation and the environment has become an essential means in the field of research of modern vegetation ecology. The main of this study using the numerical method for Individuation plots for the formation of phyto sociology units and comparing these methods in east rangeland of Semnan. Sampling of vegetation was performed in 270 plots using randomized systematic method. Sampling was done within each unit of sampling parallel transects and 1 vertical transect with 750m length, each containing 15 quadrates (according to vegetation variations) with a distance of 50 m from each other, were established. Quadrate size was determined for each vegetation type using the minimal area method. Vegetation data including density and cover percentage were estimated quantitatively within each quadrat. In this study separation of plots based on Euclidian distance and using TWINSPAN analysis, Cluster analysis and Indicator species analysis in order to classify vegetation. Indicator species analysis accompanied with Monte Carlo test was used to choose the optimum number of the clusters. Results showed that if six clusters were selected in the vegetation classification of vegetation communities in the study area based on cluster analysis, the number of indicator species, which had significant indicator values, would be maximum. Therefore, six groups could be introduced as the optimum number of ecological groups of east rangeland of Semnan. TWINSPAN analysis was used for classification, is better than other by higher eighen value (0.65 until 0.85) and DCA analysis was better than CCA Axis 1 and axis 2 were highly associated (0.63,0.193). | ||
| Keywords | ||
| CCA; DCA; Euclidian distance; Randomized systematic; TWINSPAN | ||
| References | ||
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