Literature DB >> 21774310

[Variation trends of natural vegetation net primary productivity in China under climate change scenario].

Dong-sheng Zhao1, Shao-hong Wu, Yun-he Yin.   

Abstract

Based on the widely used Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ) for climate change study, and according to the features of natural environment in China, the operation mechanism of the model was adjusted, and the parameters were modified. With the modified LPJ model and taking 1961-1990 as baseline period, the responses of natural vegetation net primary productivity (NPP) in China to climate change in 1991-2080 were simulated under the Special Report on Emissions Scenarios (SRES) B2 scenario. In 1961-1990, the total NPP of natural vegetation in China was about 3.06 Pg C a(-1); in 1961-2080, the total NPP showed a fluctuant decreasing trend, with an accelerated decreasing rate. Under the condition of slight precipitation change, the increase of mean air temperature would have definite adverse impact on the NPP. Spatially, the NPP decreased from southeast coast to northwest inland, and this pattern would have less variation under climate change. In eastern China with higher NPP, especially in Northeast China, east of North China, and Loess Plateau, the NPP would mainly have a decreasing trend; while in western China with lower NPP, especially in the Tibetan Plateau and Tarim Basin, the NPP would be increased. With the intensive climate change, such a variation trend of NPP would be more obvious.

Mesh:

Year:  2011        PMID: 21774310

Source DB:  PubMed          Journal:  Ying Yong Sheng Tai Xue Bao        ISSN: 1001-9332


  2 in total

1.  Simulated responses of permafrost distribution to climate change on the Qinghai-Tibet Plateau.

Authors:  Qing Lu; Dongsheng Zhao; Shaohong Wu
Journal:  Sci Rep       Date:  2017-06-19       Impact factor: 4.379

2.  Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China.

Authors:  Dongsheng Zhao; Shaohong Wu; Yunhe Yin
Journal:  PLoS One       Date:  2013-04-11       Impact factor: 3.240

  2 in total

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