Document Type : Research Paper

Authors

1 دانشجو

2 University of Mohaghegh Ardabili, Iran.

3 Assistant Professor Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

4 nullAssistant Professor Department of Natural Resources, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract

The purpose of this research is to facilitate the quantitative evaluation of various ecological factors in determining the rangeland condition by four-factors method and six-factors method using mainly structural variables of vegetation. In this study, the condition of 28 sites located in the northern part of Ardebil province was determined by 4 and 6 factors methods, separately for grassland and shrubland habitats, and some parameters of vegetation were quantitatively measured. The results of condition determination were compared in the two mentioned methods. Finally, using Pearson correlation test, the relationship between variables of vegetation and the scores of rangeland condition were compared and regression relations were extracted. The results indicated that the average score of the rangeland condition in the modified four-factors in both grasslands and shrublands (69 and 60 scores, respectively) was higher than the six-factors method (64 and 54 respectively), and paired t-test comparison showed a significant difference (P≤ 0.05) between the two methods. Also, the results showed that variables such as canopy cover of decreasing specious canopy cover, forbs canopy cover, annual forbs canopy cover and production had the most significant positive relationship (P≤ 0.05), and the variables of invaders and pebble-gravel cover had the highest negative correlation (P≤ 0.05) with rangeland condition. The results of extraction of multivariate linear regression models by step-by-step method showed strong relationship (R2=68.46-88.41) between evaluated variables with condition score. Also, validation analysis of the models indicated the ability of both methods to predict the rangeland condition score.

Keywords