<UnorderedList Mark="Bullet"> <ItemContent> Forest soils have the highest soil organic carbon and microbial biomass carbon, while grasslands have the lowest. </ItemContent> <ItemContent> Shrubland shows significantly higher readily oxidizable carbon and grasslands have a higher proportion of non-labile organic carbon. </ItemContent> <ItemContent> Forests show significant advantages in carbon pool activity, carbon activity index, and the carbon pool management index. </ItemContent> <ItemContent> Soil water content, total nitrogen, and available phosphorus are key drivers of carbon components. </ItemContent> <ItemContent> Vegetation type strongly influences soil carbon dynamics, with forests promoting carbon accumulation and activity, while grasslands show greater stability. </ItemContent> </UnorderedList>This study evaluated the spatial distribution and drivers of soil organic carbon (SOC), microbial biomass carbon (MBC), readily oxidizable carbon (ROC), non-labile organic carbon (NLOC), and the carbon pool management index (CPMI) in the 0–40 cm soil layer across forest, shrubland, and grassland on the southern slope of the Qilian Mountains. Results showed that forest soils had the highest SOC and MBC, while grassland soils had the lowest. ROC was significantly higher in shrubland, and grasslands had a higher proportion of NLOC. Forest soils also exhibited higher carbon pool activity (A), carbon activity index (AI), and CPMI, whereas grasslands had significantly lower values. Correlation analysis revealed significant positive relationships between SOC, NLOC, and MBC with soil water content (SWC), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), and enzyme activities (alkaline phosphatase, PHO; β-glucosidase, BG). ROC and CPMI were mainly influenced by electrical conductivity (EC), SWC, TN, AN, and total phosphorus (TP). Redundancy analysis (RDA) explained 96.02% and 89.8% of the variation in carbon components and CPMI, respectively. Monte Carlo tests identified TN, AP, and SWC as key drivers of carbon components, and SWC, EC, AN, and AP as major factors shaping CPMI. The study suggests that vegetation type strongly regulates soil carbon dynamics in high-altitude regions, with forests promoting greater carbon accumulation and activity, while grasslands exhibit higher stability.

Analysis of the impact factors of soil carbon pool and management index in typical ecosystems of the northeastern Tibetan Plateau

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发表日期：

2026年5月18日

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Xunxun Qiu,
Guangchao Cao,
Meiliang zhao,
Shuang Ji

摘要

Forest soils have the highest soil organic carbon and microbial biomass carbon, while grasslands have the lowest.

Shrubland shows significantly higher readily oxidizable carbon and grasslands have a higher proportion of non-labile organic carbon.

Forests show significant advantages in carbon pool activity, carbon activity index, and the carbon pool management index.

Soil water content, total nitrogen, and available phosphorus are key drivers of carbon components.

Vegetation type strongly influences soil carbon dynamics, with forests promoting carbon accumulation and activity, while grasslands show greater stability.

This study evaluated the spatial distribution and drivers of soil organic carbon (SOC), microbial biomass carbon (MBC), readily oxidizable carbon (ROC), non-labile organic carbon (NLOC), and the carbon pool management index (CPMI) in the 0–40 cm soil layer across forest, shrubland, and grassland on the southern slope of the Qilian Mountains. Results showed that forest soils had the highest SOC and MBC, while grassland soils had the lowest. ROC was significantly higher in shrubland, and grasslands had a higher proportion of NLOC. Forest soils also exhibited higher carbon pool activity (A), carbon activity index (AI), and CPMI, whereas grasslands had significantly lower values. Correlation analysis revealed significant positive relationships between SOC, NLOC, and MBC with soil water content (SWC), total nitrogen (TN), available nitrogen (AN), available phosphorus (AP), and enzyme activities (alkaline phosphatase, PHO; β-glucosidase, BG). ROC and CPMI were mainly influenced by electrical conductivity (EC), SWC, TN, AN, and total phosphorus (TP). Redundancy analysis (RDA) explained 96.02% and 89.8% of the variation in carbon components and CPMI, respectively. Monte Carlo tests identified TN, AP, and SWC as key drivers of carbon components, and SWC, EC, AN, and AP as major factors shaping CPMI. The study suggests that vegetation type strongly regulates soil carbon dynamics in high-altitude regions, with forests promoting greater carbon accumulation and activity, while grasslands exhibit higher stability.