title: Carbon storage in Chinese grassland ecosystems: Influence of different integrative methods.
abstract: The accurate estimate of grassland carbon (C) is affected by many factors at the large scale. Here, we used six methods (three spatial interpolation methods and three grassland classification methods) to estimate C storage of Chinese grasslands based on published data from 2004 to 2014, and assessed the uncertainty resulting from different integrative methods. The uncertainty (coefficient of variation, CV, %) of grassland C storage was approximately 4.8% for the six methods tested, which was mainly determined by soil C storage. C density and C storage to the soil layer depth of 100 cm were estimated to be 8.46 ± 0.41 kg C m(-2) and 30.98 ± 1.25 Pg C, respectively. Ecosystem C storage was composed of 0.23 ± 0.01 (0.7%) above-ground biomass, 1.38 ± 0.14 (4.5%) below-ground biomass, and 29.37 ± 1.2 (94.8%) Pg C in the 0-100 cm soil layer. Carbon storage calculated by the grassland classification methods (18 grassland types) was closer to the mean value than those calculated by the spatial interpolation methods. Differences in integrative methods may partially explain the high uncertainty in C storage estimates in different studies. This first evaluation demonstrates the importance of multi-methodological approaches to accurately estimate C storage in large-scale terrestrial ecosystems.
authors.affiliation: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Anna
authors.initials: A
authors.lastname: Ma
authors.affiliation: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Nianpeng
authors.initials: N
authors.lastname: He
authors.affiliation: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Guirui
authors.initials: G
authors.lastname: Yu
authors.affiliation: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Ding
authors.initials: D
authors.lastname: Wen
authors.affiliation: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
authors.forename: Shunlei
authors.initials: S
authors.lastname: Peng
mesh_terms: D002244:Carbon; D057486:Carbon Cycle; D002681:China; D017753:Ecosystem; D005843:Geography; D065948:Grassland; D062206:Spatial Analysis
chemical_list: D002244:Carbon