TY - EJOUR
AU - Ghorbani, Ardavan
AU - Moameri, Mehdi
AU - Moameri, Mehdi
AU - Esfanjani, Javad
PY - 2024
DA - January
TI - Predicting the Distribution of Leucanthemum Vulgare Lam. Using Logistic Regression in Fandoghlou Rangelands of Ardabil Province, Iran
T2 - Journal of Rangeland Science
VL - 10
L1 - https://oiccpress.com/journal-of-rangeland-science/article/predicting-the-distribution-of-leucanthemum-vulgare-lam-using-logistic-regression-in-fandoghlou-rangelands-of-ardabil-province-iran/
N2 - 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.
IS - 1
PB - OICC Press
KW - Environmental factors, Invasive species, Namin County, Arid ecosystem, Species distribution modelling 
EN -