Recognizing Ecological Species Groups and their Relationships with Environmental Factors at Chamanbid-Jozak Protected Area, North Khorasan Province, Iran
الموضوعات :Mohabat Nadaf 1 , hamid Ejtehadi 2 , Mansour Mesdaghi 3 , Mohamad Farzam 4
1 - Ph.D Student, Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran
2 - Professor, Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Mashhad, Iran,
3 - Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran
4 - Associate Professor, Department of Range and Watershed Management, Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran
الکلمات المفتاحية: CCA, Euclidean distance, Ward's method of clustering, Indicator species,
ملخص المقالة :
Classification of Ecological Species Groups (ESG) in plant community analysis is one method to describe vegetation and relating them to environmental factors. This study was conducted to recognize ESG and their relationships with some environmental factors in Chamanbid-Jozak protected area from 2014 to 2016. This area is located in the eastern part of North Khorasan province, Iran. The study area contains steppe vegetation with some woodlands and shrubs of Paliurus spina–christi, Cerasus pseudoprostrata, and Cerasus microcarpa. To recognize ESG, a systematic-random sampling, by using 1 m2 Sampling Unit (SU), was carried out to provide a matrix of 74 sampling units and 42 species. Canopy cover percentage of different species was recorded in each SU. Physiographical, physical, and chemical factors, including altitude, slope, soil texture, gravel percentages, Organic Carbon (OC), Nitrogen (N), Potassium (K), lime, soil acidity (pH), Phosphorus (P), and Electrical Conductivity (EC) were measured. Euclidean distance and Ward's method of clustering were used to classify the plant species. Six ESG were detected in clustering and indicator species analyses. The relationships among these ESG and environmental factors were analyzed using Canonical Correspondence Analysis (CCA). The first ESG consisting four indicator species was influenced by organic carbon and K of almost f.0 fertile soils. ESG2 and ESG3 consisting four and one, indicator species, respectively. These ESG were only slightly affected by phosphorus and less by environmental factors evaluated in this study. ESG4, including eight indicator species was mostly affected by environmental factors such as altitude, slope, pH, and N. Both ESG5 and ESG6 were affected by gravel percentages. ESG classification of vegetation for sound and proper resource management in future via using long-term projects is recommended.
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