Terrestrial ecosystems have continued to provide the critical service of slowing the atmospheric CO2 growth rate. Terrestrial net primary productivity (NPP) is thought to be a major contributing factor to this trend. Yet our ability to estimate NPP at the regional scale remains limited due to large uncertainties in the response of NPP to multiple interacting climate factors and uncertainties in the driver data sets needed to estimate NPP. In this study, we introduced an improved NPP algorithm that used local driver data sets and parameters in China. We found that bias decreased by 30% for gross primary production (GPP) and 17% for NPP compared with the widely used global GPP and NPP products, respectively. From 2000 to 2012, a pixel-level analysis of our improved NPP for the region of China showed an overall decreasing NPP trend of 4.65TgCa(-1). Reductions in NPP were largest for the southern forests of China (-5.38TgCa(-1)), whereas minor increases in NPP were found for North China (0.65TgCa(-1)). Surprisingly, reductions in NPP were largely due to decreases in solar radiation (82%), rather than the more commonly expected effects of drought (18%). This was because for southern China, the interannual variability of NPP was more sensitive to solar radiation (R-2 in 0.29-0.59) relative to precipitation (R-2<0.13). These findings update our previous knowledge of carbon uptake responses to climate change in terrestrial ecosystems of China and highlight the importance of shortwave radiation in driving vegetation productivity for the region, especially for tropical forests.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/623106 |
| Date | 01 1900 |
| Creators | Wang, J., Dong, J., Yi, Y., Lu, G., Oyler, J., Smith, W. K., Zhao, M., Liu, J., Running, S. |
| Contributors | Univ Arizona, Sch Nat Resources & Environm, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research; Chinese Academy of Sciences; Beijing China, Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research; Chinese Academy of Sciences; Beijing China, Numerical Terradynamic Simulation Group, College of Forestry and Conservation; University of Montana; Missoula Montana USA, Department of Grassland Science, Agriculture and Animal Husbandry College; Qinghai University; Xining China, Numerical Terradynamic Simulation Group, College of Forestry and Conservation; University of Montana; Missoula Montana USA, School of Natural Resources and the Environment; University of Arizona; Tucson Arizona USA, Numerical Terradynamic Simulation Group, College of Forestry and Conservation; University of Montana; Missoula Montana USA, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research; Chinese Academy of Sciences; Beijing China, Numerical Terradynamic Simulation Group, College of Forestry and Conservation; University of Montana; Missoula Montana USA |
| Publisher | AMER GEOPHYSICAL UNION |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article |
| Rights | ©2017. American Geophysical Union. All Rights Reserved. |
| Relation | http://doi.wiley.com/10.1002/2016JG003417 |
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