Analysis of Impact of Altitude on Vertical Distribution Pattern of Soil Organic Carbon in Mountainous Regions of Southeastern Tibet

【Objective】The spatial heterogeneity of alpine ecosystems in southeastern Tibet in the vertical distribution zone was analyzed, and the distribution characteristics and influencing factors of soil organic carbon(SOC)reserves at different altitudes were studied.【Methods】Taking the Sejila Mountain, a typical mountain in southeastern Tibet in the alpine and semi-humid region, as the research object, sampling was carried out at an altitude of 3 400-4 600 m with an altitude gradient of 200 m, and the altitude was investigated by combining field investigation and indoor analysis. The impact of altitude on the vertical distribution characteristics of SOC and its correlation with other physical and chemical indicators.【Result】There was a great spatial heterogeneity among the soil physical indexes in the Sejila Mountain at an altitude of 3 400~4 600 m. The soil bulk density, total porosity, capillary porosity and non-capillary porosity varied 0.72-1.08 g/cm3, 51.76%-67.06%, 47.11%-58.03% and 9.03%-11.04%. SOC was mainly distributed in the 0-60 cm soil layer, and the SOC contents of different altitude gradients(1.57%-8.24%)showed a downward trend with the increase of soil depth, and the SOC content of the alpine meadow at an altitude of 4 618 m was the highest, which was 1.76-3.07 times that of other altitudes; SOC reserve was 117.14-220.63 t/hm2, among which the SOC reserve in the soil layer at an altitude of 4 255 m was significantly higher than that at other altitudes, equivalent to 2 times that at an altitude of 3 393 m; different altitudes significantly affected the SOC reserves in the 0-60 cm soil layer, showing a single peak as a whole curve change trend.【Conclusion】There are significant differences in the vertical distribution of SOC under different vegetation types in the Sejila Mountain, and the change of altitude gradient will directly or indirectly affects the accurate estimation of SOC, and then affects the spatial distribution and prediction of SOC.