4.7 Article

Soil carbon sequestration potential as affected by soil physical and climatic factors under different land uses in a semiarid region

期刊

CATENA
卷 171, 期 -, 页码 62-71

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.catena.2018.07.005

关键词

Soil organic carbon; Carbon stock; Stepwise multiple regression; Clay to carbon concept; Aggregate stability

资金

  1. Isfahan University of Technology

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Carbon (C) sequestration in soil is recognized as a possible solution for climate change mitigation. Different land uses may alter carbon sequestration in soil. In the semiarid regions of central Iran, during the last decades, land use changes from native cover to farmlands have altered the C sink role of soil to a source of CO2 emission to the atmosphere. This study was conducted to evaluate and compare changes and the potential of soil organic carbon (SOC) sequestration from 1988 to 2014, under different land uses, in western central Iran (Lordegan). The land uses included pasture, forest, rain-fed, and irrigated farmlands. Soil (450 samples) from 50 points across the study basin (390 km(2)) was collected in three depth increments (0-5, 5-15 and 15-30 cm) during three sampling times (June and November 2014, and June 2015). Mean SOC concentrations in the pasture, forest, rain-fed and irrigated farmlands were 10.3, 20.2, 9.2 and 10.1 g kg(-1), respectively. The SOC concentration in the forest soil was significantly greater than the other land uses, and any reduction in forestland area would lead to the SOC stock decline. About 1390 Gg organic carbon was found to be stored in the top 0-30 cm depth of the study area. Comparing land use maps between 1988 and 2014 indicated an alteration in the relative contribution of each land use across the study area leading to SOC stock reduction by 100 Gg carbon during this period. The results showed that all studied soils comprised non-complexed clay, suggesting a considerable potential capacity for sequestering carbon. The results also indicated that the SOC controlling factors varied considerably among different land uses and soil depths. Mean weight diameter of aggregates (MWD), bulk density, clay and sand content, and altitude were identified as the important controlling variables by the stepwise multiple linear regression analysis.

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