Primary production in forests and grasslands of China: contrasting environmental responses of light- and water-use efficiency models
1Department of Biological Sciences, Macquarie University, Sydney, Australia
2State Key Laboratory of Vegetation and Environmental change, Institute of Botany, Chinese Academy of Science, Beijing, China
3Grantham Institute and Division of Ecology and Evolution, Imperial College, London, UK
4Alfred Wegener Institute for Polar and Marine Research, Potsdam, Germany
5State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Science, Guiyang, China
Abstract. An extensive data set on net primary production (NPP) in China's forests is analysed with two semi-empirical models based on the light use efficiency (LUE) and water use efficiency (WUE) concepts, respectively. Results are shown to be broadly consistent with other data sets (grassland above-ground NPP; globally extrapolated gross primary production, GPP) and published analyses. But although both models describe the data about equally well, they predict notably different responses to [CO2] and temperature. These are illustrated by sensitivity tests in which [CO2] is kept constant or doubled, temperatures are kept constant or increased by 3.5 K, and precipitation is changed by ±10%. Precipitation changes elicit similar responses in both models. The [CO2] response of the WUE model is much larger but is probably an overestimate for dense vegetation as it assumes no increase in runoff; while the [CO2] response of the LUE model is probably too small for sparse vegetation as it assumes no increase in vegetation cover. In the LUE model warming reduces total NPP with the strongest effect in South China, where the growing season cannot be further extended. In the WUE model warming increases total NPP, again with the strongest effect in South China, where abundant water supply precludes stomatal closure. The qualitative differences between the two formulations illustrate potential causes of the large differences (even in sign) in the global NPP response of dynamic global vegetation models to [CO2] and climate change. As it is not clear which response is more realistic, the issue needs to be resolved by observation and experiment.