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

Document Type : Research and Full Length Article


1 Associate Professor, University of Mohaghegh Ardabili, Ardabil, Iran

2 Ph.D. Student of Rangeland Sciences, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

3 Assistant Professor, University of Mohaghegh Ardabili, Ardabil, Iran

4 Ph.D. Candidate of Range Management, Department of Range & Watershed Management, University of Mohaghegh Ardabili, Ardabil, Iran


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 Leucanthemum vulgare Lam. and environmental variables in Fandoghlou rangeland, Ardabil, Iran using logistic regression model. Sampling was conducted in six sites as presence/absence of L. vulgare by a systematic random method in 2016. Physiographic, climatic, surface coverage and density of L. vulgare 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 L. vulgare. 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 L. vulgare 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 L. vulgare 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, L. vulgare 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 L. vulgare habitats. The results of this study gave more insight and understanding from the habitats and effective environmental factors in L. vulgare distribution.


Main Subjects

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Volume 10, Issue 1
January 2020
Pages 98-111
  • Receive Date: 21 April 2019
  • Revise Date: 06 August 2019
  • Accept Date: 06 August 2019
  • First Publish Date: 01 January 2020