Author = Behzad Behtari

Identification of Carbon Sequestration Patterns under the Influence of Climatic, Soil, and Topographic Factors in the Rangelands of Northern Sabalan

Volume 78, Issue 4, Winter 2026, Pages 491-512

https://doi.org/10.22059/jrwm.2025.395345.1831

vahideh moradzadeh, Ardavan Ghorbani, Leila Nemati Sham-Asbi, Mehdi Moameri, Zeinab Hazbavi, Ali Teymourzadeh, Behzad Behtari

Abstract Rangelands, as natural ecosystems, play a significant role in maintaining carbon balance of the environment. This study aimed to Identification of Carbon Sequestration Patterns under the Influence of Climatic, Soil, and Topographic Factors in the Rangelands of Northern Sabalan, located in Meshginshahr County. Soil sampling was conducted in two types of vegetation cover- grassland and shrubland- across four main geographical directions and at two soil depths (0–15 and 15–30 cm). Data were collected for 24 different soil properties. To perform statistical analyses, the normality of the data was first assessed, followed by a one-way analysis of variance (ANOVA) and Duncan’s multiple range test to compare the mean values of different properties between grasslands and shrublands. Principal Component Analysis (PCA) was also used to evaluate data structure. The results revealed that clay content, silt, organic carbon, particulate organic carbon, total nitrogen, and soil carbon sequestration were significantly higher in grasslands than in shrublands (p<0.01). In contrast, sand content, pH, and electrical conductivity were significantly higher in shrublands than in grasslands (p<0.01). The northern slope exhibited higher levels of clay, silt, organic carbon, and carbon sequestration compared to the southern slope. Additionally, increasing soil depth led to decreases in organic carbon, total nitrogen, and carbon sequestration. PCA showed that the first two components explained 36.30% of the total variance. Sand content, precipitation, and organic carbon having the highest correlation with the first component, while slope percentage and litter showing the strongest correlation with the second component. These findings indicate that soil physical and chemical properties- particularly those affected by climatic gradients and topography- significantly influence carbon sequestration.

Measurement and Modeling of the heterotrophic soil respiration response to temperature in grazing and grazing exclosure rangeland

Volume 71, Issue 3, Autumn 2018, Pages 613-627

https://doi.org/10.22059/jrwm.2018.240364.1160

behzad behtari, Zeinab Jafarian, Hossenali Alikhani

Abstract Soil heterotrophic respiration, which is the result of soil organic matter decomposition, is affected by environmental factors, especially temperature. A variety of models have been proposed to understanding the respiration response of the soil to temperature and respiration sensitivity to temperature (Q10). The aim of this study was to evaluate the respiration response of soil to temperature variations using incubation technique and to examine variety of models in two different management systems. For this purpose, Intact soil samples were collected from a grazing and grazing exclosure in Fandoghlo Ardebil, incubated for 4 weeks at 10, 20 and 30 ° C temperature. Soil respiration was measured by alkaline adsorption method. Nonlinear regression method and The Levenberg-Marquardt algorithm were used to determine the parameters of models. Both ecosystem showed an exponential increase in Soil heterotrophic respiration with temperature. The rate of respiration in soil of grazing, at all three temperature levels, was higher than grazing exclosure. Most models describing the relationship between soil respiration and temperature showed a good fit to the experimental data, especially in the grazing exclosure. Q10 in the grazing (1.21) was higher than the grazing exclosure (0.97). In general, based on the coefficients of the models and the Q10 analysis, the Arrhenius model can be better than the others of model for expressing the relationship between soil respiration with temperature, as well as good numerical estimation for Q10 of soil.