Spatial patterns of ecosystem carbon residence time in Chinese forests  

作　　者：ZHOU Tao1,2, SHI PeiJun1,2, JIA GenSuo3, LI XiuJuan1,2 & LUO YiQi4 1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China 2 Academy of Disaster Reduction and Emergency Management, Ministry of Civil Affairs & Ministry of Education, Beijing 100875, China 3 Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Chinese Academy of Sciences, Beijing 100029, China 4 Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019, USA 

出　　处：《Science China Earth Sciences》2010年第8期1229-1240,共12页中国科学（地球科学英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos.30970514,30590384,40671173,40425008);the Open Funding from the Key Laboratory of Regional Climate-Environment Research for Temperate East Asia

摘　　要：Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3 years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (38.1 and 37.3 years, respectively), and the evergreen broadleaf forest had the lowest value (31.7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.Capacity of carbon sequestration in forest ecosystem largely depends on the trend of net primary production (NPP) and the length of ecosystem carbon residence time. Retrieving spatial patterns of ecosystem carbon residence time is important and necessary for accurately predicting regional carbon cycles in the future. In this study, a data-model fusion method that combined a process-based regional carbon model (TECO-R) with various ground-based ecosystem observations (NPP, biomass, and soil organic carbon) and auxiliary data sets (NDVI, meteorological data, and maps of vegetation and soil texture) was applied to estimate spatial patterns of ecosystem carbon residence time in Chinese forests at steady state. In the data-model fusion, the genetic algorithm was used to estimate the optimal model parameters related with the ecosystem carbon residence time by minimizing total deviation between modeled and observed values. The results indicated that data-model fusion technology could effectively retrieve model parameters and simulate carbon cycling processes for Chinese forest ecosystems. The estimated carbon residence times were highly heterogenous over China, with most of regions having values between 24 and 70 years. The deciduous needleleaf forest and the evergreen needleleaf forest had the highest averaged carbon residence times (73.8 and 71.3 years, respectively), the mixed forest and the deciduous broadleaf forest had moderate values (38.1 and 37.3 years, respectively), and the evergreen broadleaf forest had the lowest value (31.7 years). The averaged carbon residence time of forest ecosystems in China was 57.8 years.

关 键 词：CARBON RESIDENCE time CARBON cycle FOREST ECOSYSTEM data-model fusion inverse modeling GENETIC algorithm 

分 类 号：P593[天文地球—地球化学]