Title : ( Predicting the potential habitat of Russian-Olive (Elaeagnus angustifolia) in urban landscapes )
Authors: Azita Farashi , Zahra Karimian ,Access to full-text not allowed by authors
Abstract
Russian-olive (Elaeagnus angustifolia) is a species native to southern Europe and central and eastern Asia. This species plays an important role in urban land-scape design because of its rapid growth, resistance in harsh climates and tolerance to human-caused pressure. Understanding its potential dispersal and restricting param-eters are the first steps toward the sustainable use of this species. Here, we used Spe-cies Distribution Models to predict the potential distribution of Russian-olivein Iran climate and estimate the possible limiting factors for its spread. Our results highlighted the importance of environmental variables including climatic factors, soil, and lithol-ogy in the distribution of this species throughout the country. According to these results, suitable habitats for Russian-olive are located in the north of Iran along the Alborz and Koppeh-Dagh mountain ranges. Therefore, the suitable habitats for this species are limited to only nine percent of the country. A habitat suitability map can be used to evaluate future developments in urban areas and predict the dispersal range of Russian-olive in Iran. Our results show that Russian-olive can be used to create new green spaces in urban climates in the northern regions of Iran.
Keywords
, climate, green space, ornamental tree, SDM, urban areas@article{paperid:1085977,
author = {Farashi, Azita and Karimian, Zahra},
title = {Predicting the potential habitat of Russian-Olive (Elaeagnus angustifolia) in urban landscapes},
journal = {Italian Journal of Agrometeorology},
year = {2021},
volume = {1},
number = {1},
month = {August},
issn = {2038-5625},
pages = {3--19},
numpages = {16},
keywords = {climate; green space; ornamental tree; SDM; urban areas},
}
%0 Journal Article
%T Predicting the potential habitat of Russian-Olive (Elaeagnus angustifolia) in urban landscapes
%A Farashi, Azita
%A Karimian, Zahra
%J Italian Journal of Agrometeorology
%@ 2038-5625
%D 2021