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Abstract
The observed forest carbon sink, i.e. positive net ecosystem productivity (NEP), in East Asia reported by the eddy covariance flux tower network is an integrated result of forests themselves (e.g. age) and abiotic factors such as climate. However the relative contribution of climate alone to that sink is highly uncertain and has been in debate. In this study we de-trended a primary effect of forest age on carbon sinks by a statistical regression model between NEP and forest ages. Then, modeled residual NEP was regressed against climate factors again so that its relative contribution could be evaluated appropriately in the region. The analysis for data from the 2000s showed that forest age appeared to be the primary impact factor on the carbon sink of the region (R 2 = 0.347), and the mean annual temperature (MAT) was the second (R 2 = 0.23), while the mean annual precipitation effect might not be as apparent as MAT. Particularly for forests in China, climate might contribute to about 31.7% of the total NEP of 0.540 Pg C yr−1. Given that forests in China are relatively young under current climate conditions, we predicted that they would be capable of atmospheric carbon sequestration in the near future.
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Details
1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, People’s Republic of China; Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing 100875, People’s Republic of China
2 State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, People’s Republic of China
3 State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, People’s Republic of China; Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs and Ministry of Education, Beijing 100875, People’s Republic of China; Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019, USA