Peng Shunlei, Wen Ding, He Nianpeng, Yu Guirui, Ma Anna, Wang Qiufeng
Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China; Key laboratory of Ecological Restoration in the Hilly Area Pingdingshan University Pingdingshan He'nan Province 467000 China.
Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China.
Ecol Evol. 2016 Apr 3;6(10):3129-45. doi: 10.1002/ece3.2114. eCollection 2016 May.
Carbon (C) storage for all the components, especially dead mass and soil organic carbon, was rarely reported and remained uncertainty in China's forest ecosystems. This study used field-measured data published between 2004 and 2014 to estimate C storage by three forest type classifications and three spatial interpolations and assessed the uncertainty in C storage resulting from different integrative methods in China's forest ecosystems. The results showed that C storage in China's forest ecosystems ranged from 30.99 to 34.96 Pg C by the six integrative methods. We detected 5.0% variation (coefficient of variation, CV, %) among the six methods, which was influenced mainly by soil C estimates. Soil C density and storage in the 0-100 cm soil layer were estimated to be 136.11-153.16 Mg C·ha(-1) and 20.63-23.21 Pg C, respectively. Dead mass C density and storage were estimated to be 3.66-5.41 Mg C·ha(-1) and 0.68-0.82 Pg C, respectively. Mean C storage in China's forest ecosystems estimated by the six integrative methods was 8.557 Pg C (25.8%) for aboveground biomass, 1.950 Pg C (5.9%) for belowground biomass, 0.697 Pg C (2.1%) for dead mass, and 21.958 Pg C (66.2%) for soil organic C in the 0-100 cm soil layer. The R:S ratio was 0.23, and C storage in the soil was 2.1 times greater than in the vegetation. Carbon storage estimates with respect to forest type classification (38 forest subtypes) were closer to the average value than those calculated using the spatial interpolation methods. Variance among different methods and data sources may partially explain the high uncertainty of C storage detected by different studies. This study demonstrates the importance of using multimethodological approaches to estimate C storage accurately in the large-scale forest ecosystems.
在中国森林生态系统中，所有组分尤其是枯落物和土壤有机碳的碳（C）储量鲜有报道，仍存在不确定性。本研究利用2004年至2014年间发表的实地测量数据，通过三种森林类型分类和三种空间插值方法估算碳储量，并评估了中国森林生态系统中不同整合方法导致的碳储量不确定性。结果表明，通过六种整合方法，中国森林生态系统中的碳储量在30.99至34.96Pg C之间。我们检测到六种方法之间存在5.0%的变化（变异系数，CV，%），这主要受土壤碳估算的影响。0-100cm土层的土壤碳密度和储量分别估计为136.11-153.16Mg C·ha(-1)和20.63-23.21Pg C。枯落物碳密度和储量分别估计为3.66-5.41Mg C·ha(-1)和0.68-0.82Pg C。六种整合方法估计的中国森林生态系统平均碳储量中，地上生物量为8.557Pg C（25.8%），地下生物量为1.950Pg C（5.9%），枯落物为0.697Pg C（2.1%），0-100cm土层的土壤有机碳为21.958Pg C（66.2%）。R:S比为0.23，土壤中的碳储量是植被中碳储量的2.1倍。相对于森林类型分类（38个森林亚型）的碳储量估计值比使用空间插值方法计算的值更接近平均值。不同方法和数据源之间的差异可能部分解释了不同研究检测到的碳储量的高不确定性。本研究证明了使用多方法途径准确估算大规模森林生态系统中碳储量的重要性。
