Carbon Storage in an Extensive Karst-distributed Region of Southwestern China based on Multiple Methods

Abstract:

Accurate estimation of carbon storage is crucial to better understand the processes of global and regional carbon cycles and to more precisely project ecological and economic scenarios for the future. Southwestern China has broadly and continuously distribution of karst landscapes with harsh and fragile habitats which might lead to rocky desertification, an ecological disaster which has significantly hindered vegetation succession and economic development in karst regions of southwestern China. In this study we evaluated the carbon storage in eight political divisions of southwestern China based on four methods: forest inventory, carbon density based on field investigations, CASA model driven by remote sensing data, and BIOME4/LPJ global vegetation models driven by climate data. The results show that: (1) The total vegetation carbon storage (including agricultural ecosystem) is 6763.97 Tg C based on the carbon density, and the soil organic carbon (SOC) storage (above 20cm depth) is 12475.72 Tg C. Sichuan Province (including Chongqing) possess the highest carbon storage in both vegetation and soil (1736.47 Tg C and 4056.56 Tg C, respectively) among the eight political divisions because of the higher carbon density and larger distribution area. The vegetation carbon storage in Hunan Province is the smallest (565.30 Tg C), and the smallest SOC storage (1127.40 Tg C) is in Guangdong Province; (2) Based on forest inventory data, the total aboveground carbon storage in the woody vegetation is 2103.29 Tg C. The carbon storage in Yunnan Province (819.01 Tg C) is significantly higher than other areas while tropical rainforests and seasonal forests in Yunnan contribute the maximum of the woody vegetation carbon storage (account for 62.40% of the total). (3) The net primary production (NPP) simulated by the CASA model is 68.57 Tg C/yr, while the forest NPP in the non-karst region (account for 72.50% of the total) is higher than that in the karst region. (4) BIOME4 and LPJ models predicted higher carbon storages than the CASA model with various spatial patterns. More investigations should be further performed to clarify processes of carbon cycle in ecosystems on karst terrain and to accelerate the development of a regional dynamic vegetation model which was appropriate for karst ecosystems.