Investigation of performance of Genetic Algorithm (GARP), MaxEnt and Logistic Regression in Analysis of Distribution of Astragalus, Sp.

Subject Areas : Journal of Plant Ecophysiology

عباس احمدی ¹ , َAmir Ghahremanian ² , Hamid Toranjzar ³ , جواد وروانی ⁴ , نوراله عبدی ⁵

1 - گروه منابع طبیعی و محیط زیست ،دانشکده فنی ،مهندسی و کشاورزی ، دانشگاه آزاد اسلامی ،واحد اراک ، اراک ، ایران
2 - Department of Natural Resources and Environment, Islamic Azad University, Arak Branch, Arak, Iran
3 - Arak azad university
4 - عضو هیئت علمی دانشگاه آزاد اسلامی واحد اراک
5 - دکترای تخصصی علوم مرتع، هیات علمی دانشگاه آزاد اسلامی، واحد اراک

Received: 2023-05-12 Accepted : 2023-11-23 Published : 2024-10-15

Keywords:

Abstract :

In order to determine the potential habitat of plant species, it is essential to know the ecological needs of the species as well as climatic and edaphic characteristics to apply management in accordance with the ecological conditions of the studied area. In this research, in order to develop model for the distribution of Astragalus Sp., using different statistical methods in part of the pastures of the Savar-Abad Basin, at first by producing using topographic, slop, aspect maps, types of vegetation in study area were determined. In the specified types, a number of sampling sites with dimensions of 2 to 10 square meters were selected. Information related to the presence and absence of Astragalus sp as dependent variable and other environmental information as independent variables was measured. In each homogenous unit, three transects of 750 meters, two transects along the most gradients (height, direction and slope), And another transect established perpendicular to those two transects. Along each transect, 15 plots were placed at a distance of 50 meters, thus 47 plots were established in each homogeneous unit. (Total 2 units, 94 plots). The size of sampling plots was determined according to the type and distribution of plant species using the Minimum Surface Method. In each plot, the type and number of plant species and their coverage percentage were recorded. For soil sampling, At the beginning and end of each transect, the soil profile was dug and soil sampling was done according to existing standards, and soil variables including gravel, clay, sand, silt, lime, organic matter, acidity and electrical conductivity were measured in the laboratory. Also, in each sampling unit, latitude, longitude, slope, direction and height from the sea level were also determined. In this study, the dependent variables are the data of the presence and absence of vegetation types, and the independent variables include soil and topography characteristics. The best distribution model was determined using statistical analysis. The results showed that the MaxEnt model has a better performance than the logistic regression and genetic algorithm models. However, the findings of the research show that altitude, acidity and salinity have a greater effect on the distribution of different species in the study area.