Document Type : Review and Full Length Article
PhD student, Institute of Atmospheric Physics, University of Chinese Academy of Sciences
Associate Professor, State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences
Associate Professor, Department of Watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
Professor, State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, China
Land-use and land-use change can directly affect soil organic carbon. Improper land management can lead to carbon loss from the soil which can greatly intensify global warming. Despite the abundance of evidence on soil organic carbon in Iran, no paper has so far compiled the data for this region. Therefore, data were collected from 120 papers and 393 data points regarding land use and soil organic carbon changes. Stepwise regression analysis was used to analyze the relationship between SOC with annual precipitation, average annual temperature, latitude and average depth of sampling. Pearson correlation coefficients were calculated between SOC and other factors.
Based on the results, primary forests and reforested areas had significantly higher SOC stocks at the depth of 20cm by respectively containing 70.03 (±4.45) Mg C ha-1 and 84.38 (±9.01) Mg C ha-1 while there was no significant differences among other land use categories. The findings of this study showed that no changes in SOC stocks among land-use change categories and average annual rate of SOC changes. However, among farmlands, found evidence for a significant SOC reduction in cases with a historic forest land-use (-15.2%) compared with those with historic grassland use. Results indicated that farmlands and primary forests have the highest level of SOC input from litter and fine roots, respectively. By evaluating the impact of different factors on SOC using a stepwise regression analysis, demonstrated that 31% of the variations in soil carbon storage at different land-use types can be explained by precipitation, temperature, latitude, and sampling depth. Using the obtained equation, SOC variation in Iran is simulated and mapped, showing that except for a narrow strip in northern Iran, the rest of the country suffers from low SOC levels. Totally, protecting forests against land conversion is recommended as the top priority for land managers in Iran.