The objective of the present research was to compare Ecological Niche Factor Analysis (ENFA) and Artificial Neural Networks (ANN) to determine the optimum threshold of plant species (Thymus kotschyanus Boiss and Hohen. and Dactylis glomerata L.) in rangelands of Ardabil province. Systematic random sampling of vegetation was performed, and an overall 111 sites were considered and divided into two groups, namely sites with plant species and sites without plant species. Five plots of one square meter were placed in each site. The size of the plots was based on the magnitude of one or double the average area of the most common plant species. Plots were positioned along a 40-m transect (from the bottom of the slope to high altitudes with a distance of 10 m between the plots). Soil sampling was done in a depth of 0–30 cm (selected based on the activity of root plant species). Maps of environmental factors were prepared in ArcGIS 10.4.1 software. The sensitivity and specificity were considered to specify the optimum threshold. The optimal threshold between plant species, determined by modeling methods, showed that the highest accuracy belonged to ENFA model in T. kotschyanus habitat (with optimum threshold = 0.62 and sensitivity = 0.58) and ANN model in D. glomerata habitat (with optimum threshold = 0.37 and sensitivity = 0.02) had the lowest accuracy.

本研究的目的是比较生态位因子分析（ENFA）和人工神经网络（ANN）来确定植物物种（百里香（Thymus kotschyanus Boiss和Hohen）和Dactylis glomerata）的最佳阈值。L.）在Ardabil省的牧场中。对植被进行了系统的随机采样，总共考虑了111个地点并将其分为两组，即有植物种类的地点和没有植物种类的地点。在每个站点中放置了五块一平方米的地块。地块的大小基于最常见植物物种平均面积的一倍或两倍。地块沿40米长的样线放置（从斜坡底部到高海拔，地块之间的距离为10 m）。在0–30 cm的深度（根据根植物的活性选择）进行土壤采样。在ArcGIS 10.4.1软件中准备了环境因素图。敏感性和特异性被认为可以确定最佳阈值。植物物种之间的最佳阈值T. kotschyanus生境（最佳阈值= 0.62，灵敏度= 0.58）和ANN模型在D. glomerata生境（最佳阈值= 0.37，灵敏度= 0.02）中精度最低。