فهرست مطالب f. dadjou

The aim of the study was to determine the most important environmental factors (topography, climate, and soil) affecting changes in production and canopy cover of plant variations and to prepare prediction maps, based on the most important factor, in semi-steppe rangelands of Hir-Baghrou, Ardabil province, Iran. First, by detecting the vegetation types and different classes of environmental factors, the production and canopy cover were estimated in 1-m2 plots at full flower stage of dominant species. Then, to determine the most important environmental factors, affecting the production and canopy cover changes, the principal component analysis (PCA) was used. For modeling, first, the correlation between the most effective environmental factors was obtained from the PCA. Then, the highly correlated factors were eliminated and the quadratic polynomial models were obtained. Finally, the obtained models were simulated in GIS. The results of the PCA showed that the first six components with 71.65% had the greatest effect on the production and canopy cover changes. Based on the root mean squared error (RMSE), simulating maps of production (RMSE=0.76) and canopy cover (RMSE=0.48) by effective factor (annual precipitation) showed the highest accuracy. The results of this study can be used to manage the rangelands of Ardabil province to create a balance between supply and demand of production and also to balance carbon.

The purpose of this study was to model biomass with soil parameters in Hir-Neur rangelands of Ardabil Province. Initially, considering the vegetation types and different classes of environmental factors, at the maximum vegetative growth stage, using one square meter plot, biomass was estimated by clipping and weighing method. For each transect, a soil sample was taken and transferred to the soil laboratory and the various parameters were measured by conventional methods. The relationship between soil factors and the rangeland biomass was analyzed and simulated using linear multiple regression. Among the measured soil factors, the Silt, EC, Ca, Ksoluble, OC, POC, pH, Mg, TNV, clay, P, and volumetric moisture had the highest effect and percentage of biomass forecast (p<0.01). The accuracy of the simulated maps was analyzed using RMSE criteria and for grasses, forbs, shrubs, and total biomass were equal to 0.81, 0.65, 0.34, and 0.46, respectively. The results of this study, not only point out the importance of soil factors on the biomass but also as a baseline data for managing rangelands, supply-demand, and carbon balance can be used in the current section.