:: Volume 9, Issue 18 (10-2021) ::
PEC 2021, 9(18): 363-388 Back to browse issues page
Habitat modeling and determination of environmental factors affecting on distribution of Persian oak (Quercus brantii Lindl.) in forest habitats of Lorestan Province
Sorour Mahmoudvand , Hamed Khodayari * , Farajollah Tarnian
, khodayari.h@lu.ac.ir
Abstract:   (2749 Views)
Species distribution models (SDMs) are the most important ecological models used to model species distribution, identify new habitats, and protect endangered species. In this study, habitat potential modeling and determine the most important factors affecting on distribution of Persian oak (Quercus brantii Lindl.) was investigated using MaxEnt model in Lorestan province. To map the potential distribution of Persian oak, 22 environmental layers were prepared in ArcGIS 10.4.1 and converted to ASCII format. Then 5064 species presence points were extracted using 1.5 × 1.5 km grid from the map of geographical distribution of the Persian oak species (1:250000) and converted to CSV format. After preparing the layers, MaxEnt 3.3.3 software was used to model distribution of the species. The results showed that 7 variables were more important among of the 22 environmental variables affecting on distribution of Persian oak. Annual mean temperature, Precipitation of wettest quarter and Min temperature of coldest month had the highest impact on distribution of the species with 38, 24.2 and 13.3 %, respectively. The area under the curve (AUC) of the model was 0.669 and the threshold value of 0.33 was used to convert the probability map to the presence and absence maps. The potential vegetation map of Persian oak shows that approximately 62.5% of the area of Lorestan province has the potential for growing Persian oak. The main new habitat is located in Khorramabad, Aligudarz, Kuhdasht and Poldokhtar, which recommended for restoration and rehabilitation.
Keywords: Persian oak, Bioclimatic variables, Ecological models, MaxEnt.
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Type of Study: Applicable | Subject: Special
Received: 2020/04/3 | Accepted: 2021/01/30 | Published: 2021/09/28
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