Modeling the carbon dynamics of ecosystem in a typical permafrost area

Yusheng Wang; Deyong Yu; Jingwen Li; Ting Huang

doi:10.1016/j.scitotenv.2024.173204

Modeling the carbon dynamics of ecosystem in a typical permafrost area

Sci Total Environ. 2024 Jul 15:934:173204. doi: 10.1016/j.scitotenv.2024.173204. Epub 2024 May 14.

Authors

Yusheng Wang¹, Deyong Yu², Jingwen Li³, Ting Huang⁴

Affiliations

¹ State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
² State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China; Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation, Ministry of Education, Qinghai Normal University, Xining 810016, China. Electronic address: ydy@bnu.edu.cn.
³ Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
⁴ Beijing School, Beijing 101117, China.

PMID: 38750735
DOI: 10.1016/j.scitotenv.2024.173204

Abstract

Climate change poses mounting threats to fragile alpine ecosystem worldwide. Quantifying changes in carbon stocks in response to the shifting climate was important for developing climate change mitigation and adaptation strategies. This study utilized a process-based land model (Community Land Model 5.0) to analyze spatiotemporal variations in vegetation carbon stock (VCS) and soil organic carbon stock (SOCS) across a typical permafrost area - Qinghai Province, China, from 2000 to 2018. Multiple potential factors influencing carbon stocks dynamics were analyzed, including climate, vegetation, soil hydrothermal status, and soil properties. The results indicated that provincial vegetation carbon storage was 0.22 PgC (0.32 kg/m²) and soil organic carbon pool was 9.12 PgC (13.03 kg/m²). VCS showed a mild increase while SOCS exhibited fluctuating uptrends during this period. Higher carbon stocks were observed in forest (21.74 kg/m²) and alpine meadow (18.08 kg/m²) compared to alpine steppes (9.63 kg/m²). Over 90 % of the carbon was stored in the 0-30 cm topsoil layer. The contribution rates of soil carbon in the 30-60 cm and 60-100 cm soil layers were significantly small, despite increasing stocks across all depths. Solar radiation, temperature, and NDVI emerged as primary influential factors for overall carbon stocks, exhibiting noticeable spatial variability. For SOCS at different depths, the normalized differential vegetation index (NDVI) was the foremost predictor of landscape-level carbon distributions, which explained 52.8 % of SOCS variability in shallow layers (0-30 cm) but dropped to just 12.97 % at the depth of 30-60 cm. However, the dominance of NDVI diminished along the soil depth gradients, superseded by radiation and precipitation. Additionally, with an increase in soil depth, the influence of inherent soil properties also increased. This simulation provided crucial insights for landscape-scale carbon responses to climate change, and offered valuable reference for other climate change-sensitive areas in terms of ecosystem carbon management.

Keywords: Carbon stocks; Community Land Model; Driving factors; Permafrost.