Predicting the amount of sequestrated carbon in rangeland soil under the effect of soil sampling depth and height using the response surface methodology (RSM)

Organic carbon is a crucial parameter for assessing soil fertility, productivity, and quality, particularly in dry and semi-dry lands. Rangelands cover approximately 50% of the Earth's land area and store over 33% of the global carbon reservoirs. Considering rangelands as significant terrestrial ecosystems and natural carbon reserves, understanding and quantifying carbon sequestration in these ecosystems is of great importance.

This research focused on rangelands in the southern domain of Damavand mountain. Four height groups were selected based on geographic conditions, regional plant cover, and slope. Each height group represented a different elevation range: group 1 (2504-2664 m), group 2 (2730-2896 m), group 3 (2923-3050 m), and group 4 (3119-3545 m). Soil sampling was conducted at two depths (0-15 cm and 15-30 cm) using 13 random points within each height group. Soil organic carbon and bulk density were measured, and carbon sequestration was calculated at the hectare level by multiplying organic carbon and depth. Regression equations and response surface models (RSM) were developed using design software to predict carbon sequestration and compare their accuracy.

Analysis of variance (ANOVA) showed that only sampling depth significantly affected soil carbon sequestration, while sampling height and the interaction between depth and height had no significant effect. Carbon sequestration was higher at a depth of 15-30 cm compared to 0-15 cm. Among the height groups, group 4 (3119-3545 m) exhibited the highest soil carbon sequestration, followed by group 1 (2504-2664 m). The highest carbon sequestration (6046.54 g/m2) was observed in height group 4 at a depth of 15-30 cm, while the lowest (2250 g/m2) was found in height group 2 at a depth of 0-15 cm. The quadratic model of the response surface methodology demonstrated higher accuracy (R2 = 0.7363) in predicting soil carbon sequestration compared to the linear model (R2 = 0.6014) and the less accurate regression model (R2 = 0.428). The response surface method successfully optimized the inputs, suggesting a height of 3500 meters and a specific depth to achieve a soil carbon sequestration amount of 8088.117 g/m2 with a satisfaction level of 0.976.

The response surface methodology (RSM) proved to be a valuable tool for predicting and optimizing soil carbon sequestration in rangelands, considering different sampling depths and heights. It can also be utilized for predicting various parameters in rangeland science, such as above and underground biomass volume and plant species coverage. RSM offers a novel approach for understanding and managing rangeland ecosystems.