Volume 13, Issue 4 (12-2019)                   مرتع 2019, 13(4): 560-570 | Back to browse issues page

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Bagheri H, Ghorbani A, Zare Chahouki M, Jafari A, Sefidi K. Modelling spatial distribution of Limonium iranicum and Aeluropus littoralis species by logistic regression method: a case study of Meighan playa rangelands. مرتع 2019; 13 (4) :560-570
URL: http://rangelandsrm.ir/article-1-818-en.html
Department of natural resource, Faculty of Agricultre and natural resource, University of Mohaghegh Ardabibli, Ardabil
Abstract:   (4083 Views)
This study was conducted to model the distribution of two species: Limonium iranicum (Bornm.) Lincz. and Aeluropus littoralis (Gouan) Parl. Logistic regression was the method and surrounding rangelands of Meighan playa the study area. Samples were taken through random- systematic method with 2 to 4 square meters plots. For each plots, density and canopy cover were measures and recorded. Within the vegetation types, soil samples were taken from the beginning and the end of each transect at two depth levels, 0-30 (1st depth) and 30-80 cm (2nd depth). Notes were also taken from habitat factors such as topography and soil data. Maps of environmental variables were prepared using geographic information system (GIS) and geostatistical methods. Spatial distribution maps of the species were drawn using logistic regression by SPSS. GIS. Kappa coefficient was used to verify the accuracy of the map V.S. the real world. According to the results, for the second depth lime and silt are important factors on the growth of L. iranicum, while sand was mostly important in the first depth. The most important variables in the A. littoralis habitat preference were lime of the first depth and elevation. Moreover, the map of the model was well plotted for A. littoralis habitat (kappa = 0.65) and much better for the L. iranicum habitat (kappa = 0.83). In conclusion, this model has the ability to predict the distribution of species in the halophyte habitats.
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Type of Study: Research | Subject: Special
Received: 2020/01/17 | Accepted: 2020/01/17 | Published: 2020/01/17

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