Predicting the Distribution of Leucanthemum Vulgare Lam. Using Logistic Regression in Fandoghlou Rangelands of Ardabil Province, Iran

Abstract

Species Distribution Modelling (SDM) is an important tool for conservation planning and resource management. Invasive species represent a good opportunity to evaluate SDMs predictive accuracy with independent data as their invasive range can expand quickly. Thus, the aim of this study was to investigate the relationships between presence of <em>Leucanthemum vulgare </em>Lam. and environmental variables in Fandoghlou rangeland, Ardabil, Iran using logistic regression model. Sampling was conducted in six sites as presence/absence of <em>L. vulgare</em> by a systematic random method in 2016. Physiographic, climatic, surface coverage and density of <em>L. vulgare</em> were measured in sampling sites. In the beginning, middle and end of each transect, soil samples were taken from the depth of rootstock of range plants including <em>L. vulgare</em>. Soil attributes were measured in the laboratory. The maps of physiographic and climate were derived from digital elevation model, and selected soil attributes were derived using Kriging interpolation method. Derived regression equation from the presence of <em>L. vulgare</em> was applied to map the effective environmental variables, and a prediction map was produced for the study area. The comparison between the predicted and actual maps was assessed using the Kappa coefficient. Results showed that the presence of <em>L. vulgare</em> had a positive relationship with temperature and volumetric soil water content factors and had a negative relationship with electrical conductivity, sodium, diffusible clay factors. Therefore, <em>L. vulgare </em>type is significantlyaffected by the presence of these factors (p<0.01). The Kappa coefficient was 0.55 for derived predicted map. The evaluation of the model indicated that logistic regression was able to predict the distribution of <em>L. vulgare </em>habitats. The results of this study gave more insight and understanding from the habitats and effective environmental factors in <em>L. vulgare </em>distribution.