UNI-MB - logo
UMNIK - logo
 
E-viri
Recenzirano Odprti dostop
  • Carbon pools in China’s ter...
    Tang, Xuli; Zhao, Xia; Bai, Yongfei; Tang, Zhiyao; Wang, Wantong; Zhao, Yongcun; Wan, Hongwei; Xie, Zongqiang; Shi, Xuezheng; Wu, Bingfang; Wang, Gengxu; Yan, Junhua; Ma, Keping; Du, Sheng; Li, Shenggong; Han, Shijie; Ma, Youxin; Hu, Huifeng; He, Nianpeng; Yang, Yuanhe; Han, Wenxuan; He, Hongling; Yu, Guirui; Fang, Jingyun; Zhou, Guoyi

    Proceedings of the National Academy of Sciences - PNAS, 04/2018, Letnik: 115, Številka: 16
    Journal Article

    China’s terrestrial ecosystems have functioned as important carbon sinks. However, previous estimates of carbon budgets have included large uncertainties owing to the limitations of sample size, multiple data sources, and inconsistent methodologies. In this study, we conducted an intensive field campaign involving 14,371 field plots to investigate all sectors of carbon stocks in China’s forests, shrublands, grasslands, and croplands to better estimate the regional and national carbon pools and to explore the biogeographical patterns and potential drivers of these pools. The total carbon pool in these four ecosystems was 79.24 ± 2.42 Pg C, of which 82.9% was stored in soil (to a depth of 1 m), 16.5% in biomass, and 0.60% in litter. Forests, shrublands, grasslands, and croplands contained 30.83 ± 1.57 Pg C, 6.69 ± 0.32 Pg C, 25.40 ± 1.49 Pg C, and 16.32 ± 0.41 Pg C, respectively. When all terrestrial ecosystems are taken into account, the country’s total carbon pool is 89.27 ± 1.05 Pg C. The carbon density of the forests, shrublands, and grasslands exhibited a strong correlation with climate: it decreased with increasing temperature but increased with increasing precipitation. Our analysis also suggests a significant sequestration potential of 1.9–3.4 Pg C in forest biomass in the next 10–20 years assuming no removals, mainly because of forest growth. Our results update the estimates of carbon pools in China’s terrestrial ecosystems based on direct field measurements, and these estimates are essential to the validation and parameterization of carbon models in China and globally.