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A multi-model assessment of climate change impacts on the distribution and productivity of ecosystems in China

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Abstract

Potential twenty-first century changes in vegetation distribution and net primary production in China were assessed using three different vegetation models, including new process-oriented but observationally based models for net primary production and vegetation distribution. Climate change projections were derived from a set of seven global climate model outputs, pattern scaled to yield a 2 °C global warming by mid-century. The effects of the climate changes were assessed for the last three decades of the century, by which time global warming has reached 4 °C, with atmospheric carbon dioxide concentration ([CO2]) prescribed at 750 ppm. This scenario results in a limited northward expansion of tropical forests along China’s southern coast, and a larger northward shift of subtropical forest into the current temperate forest and crop areas. Alpine vegetation on the Tibetan Plateau is largely replaced by boreal and subalpine forest or shrubland. The largest uncertainties (differences between climate and/or vegetation models) occur in northeastern China. However, all models agree on shrinkage of boreal forests in the northeast and the effects of [CO2] in promoting woody vegetation at the expense of grasslands. The current cropping systems in North China extend further northward and westward. The productivity of forests in South China increases in all models, although the magnitude of the [CO2] effect remains uncertain.

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Acknowledgments

I thank the China Scholarship Council (CSC) and Macquarie University for supporting me to study at Macquarie; my supervisor Colin Prentice for his ideas and extensive use of a red pen; my associate supervisor Ian Wright for discussions and support; Nigel Arnell and the GSI project for the processed climate model outputs and Angela Gallego-Sala for providing global data sets.

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Wang, H. A multi-model assessment of climate change impacts on the distribution and productivity of ecosystems in China. Reg Environ Change 14, 133–144 (2014). https://doi.org/10.1007/s10113-013-0469-8

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