Welcome to Chinese Journal of Applied Ecology! Today is Share:

Chinese Journal of Applied Ecology ›› 2012, Vol. 23 ›› Issue (07): 1733-1742.

• Articles • Previous Articles     Next Articles

Responses of Pinus tabulaeformis forest ecosystem in North China to climate change and elevated CO2: A simulation based on BIOME-BGC model and tree-ring data.

PENG Jun-jie1,2, HE Xing-yuan1, CHEN Zhen-ju1, CUI Ming-xing1,2, ZHANG Xian-liang1,2,ZHOU Chang-hong3   

  1. (1State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China;2Graduate University of Chinese Academy of Sciences, Beijing 100049, China;3Stateowned Forest Bureau of MulanWeichang, Chengde 068450, Hebei, China)
  • Online:2012-07-18 Published:2012-07-18

Abstract: Based on BIOME-BGC model and tree-ring data, a modeling study was conducted to estimate the dynamic changes of the net primary productivity (NPP) of Pinus tabulaeformis forest ecosystem in North China in 1952-2008, and explore the responses of the radial growth and NPP to regional climate warming as well as the dynamics of the NPP in the future climate change scenarios. The simulation results indicated the annual NPP of the P. tabulaeformis ecosystem in 1952-2008 fluctuated from 244.12 to 645.31 g C·m-2·a-1, with a mean value of 418.6 g C·m-2·a-1. The mean air temperature in May-June and the precipitation from previous August to current July were the main factors limiting the radial growth of P. tabulaeformis and the NPP of P. tabulaeformis ecosystem. In the study period, both the radial growth and the NPP presented a decreasing trend due to the regional warming and drying climate condition. In the future climate scenarios, the NPP would have positive responses to the increase of air temperature, precipitation, and their combination. The elevated CO2 would benefit the increase of the NPP,and the increment would be about 16.1% due to the CO2 fertilization. At both ecosystem and regional scales, the treering data would be an ideal proxy to predict the ecosystem dynamic change, and could be used to validate and calibrate the process-based ecosystem models including BIOME-BGC.