Applied Ecology and Environmental Sciences
ISSN (Print): 2328-3912 ISSN (Online): 2328-3920 Website: http://www.sciepub.com/journal/aees Editor-in-chief: Alejandro González Medina
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Applied Ecology and Environmental Sciences. 2019, 7(5), 190-205
DOI: 10.12691/aees-7-5-5
Open AccessArticle

Bioclimatic Classification of South East of Iran Using Multivariate Statistical Methods

Khatibi Rasool1, , Soltani Saeed2 and Khodagholi Morteza3

1Department of Soil and Water, Zabol University, Zabol, Iran

2Department of Natural Resources, Isfahan University of Technology, Isfahan, 84156-83111, Iran

3Soil Conservation and Watershed Management Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran

Pub. Date: November 10, 2019

Cite this paper:
Khatibi Rasool, Soltani Saeed and Khodagholi Morteza. Bioclimatic Classification of South East of Iran Using Multivariate Statistical Methods. Applied Ecology and Environmental Sciences. 2019; 7(5):190-205. doi: 10.12691/aees-7-5-5

Abstract

Traditional zoning by necessity and based on one or a few climate variables, tended to separate climatic zones while the climate contains several variables and is a cumulative process. Effective management and proper exploitation of each ecosystem requires a comprehensive understanding of its components. Climate can exert direct and indirect effects on all components of ecosystems. While most systems of bioclimatic classification depend on limited variables such as precipitation, temperature, and their combinations, describing the climate of a region requires the evaluation of more factors. The present study was an attempt toward the bioclimatic classification of South east of Iran (including Sistan and baluchestan Province). Using multivariate statistical methods, 72 climatic variables, which affected the distribution of dominant plant species in the study area, were selected. After performing principal component analysis to identify the main factors, cluster analysis was conducted to determine the bioclimatic classes and their characteristics. Overall, six climatic factors (i.e. temperature and warm season rainfall, Warm season winds, Spring dust, Spring and autumn wind, Relative humidity and Cool season rainfall) were found to explain 98% of the total variance in primary variables. Cluster analysis Ward’s method divided the study area into 7 bioclimatic zones. The comparison of the obtained results with the results of four common methods of climate classification (Koppen’s, Gaussen’s, Emberger’s, and de Martonne’s methods) suggested the higher ability of multivariate statistical methods to discriminate between bioclimatic zones. The dominant species in each zone were finally described.

Keywords:
factor analysis bioclimatic classification sistan and baluchestan province multivariate statistical methods Koppen’s method Gaussen’s method Emberger’s method de Martonne’s method

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