Habitat utility modeling of organic (wild) pistachios (Pistacia Vera) using Maximum Entropy Method (MaxEnt) in Sarakhs Forest Area (Gonbadli in khorasan Province)

Document Type : Research Article


1 Assistant Professor, Faculty of New Sciences and Technologies, University of Tehran

2 MSc. Student in Ecohydrology, Faculty of New Sciences and Technologies, University of Tehran


Organic (wild) Pistacia vera is a species of broadleaf forest. One of the most important natural forest habitats in the world is located at northwest and southwest of the city of Sarakhs, Khorasan Razavi Province, Iran. In addition, the unique ecological features of this habitat and the economic value of organic pistachio greatly impact the lives of people residing in this region and the country. Unfortunately, continuous overharvesting and drought-stricken development endanger natural life, regrowth and cultivation of this unique species. Understanding spatial distribution of this species plays a significant role in assessing regional protection and development; on the other hand, it can be helpful to recognize effective ecological factors on its habitat. Therefore, modeling this distribution is very important. In this paper, habitat modeling of this species is studied using maximum entropy method according to edaphic, climatic and physiographic data in the city of Sarakhs (in district of Gonbadli). The results of Jackknife test for surveying significance of variables shows that changes in soil properties such as gravel percentage, exchangeable sodium adsorption ratio, sodium content soil, gypsum, climatic factors (temperature and precipitation) and height above sea level are the most important factors affecting the distribution of habitats. The accuracy of model is assessed by kappa coefficient to be 0.72 and AUC 0.92. Moreover, the obtained  results reveal that maximum entropy method is an appropriate method for habitat modeling.


Main Subjects

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Volume 4, Issue 3
September 2017
Pages 817-824
  • Receive Date: 12 January 2017
  • Revise Date: 04 May 2017
  • Accept Date: 19 April 2017
  • First Publish Date: 23 September 2017
  • Publish Date: 23 September 2017