首页> 外文期刊>Global and planetary change >Geographical statistical assessments of carbon fluxes in terrestrial ecosystems of China: Results from upscaling network observations
【24h】

Geographical statistical assessments of carbon fluxes in terrestrial ecosystems of China: Results from upscaling network observations

机译:中国陆地生态系统碳通量的地理统计评估:网络观测结果升级的结果

获取原文
获取原文并翻译 | 示例
       

摘要

Accurate quantifying the magnitudes and distributions of carbon budgets is helpful for strategies in mitigating global climate change. Based on spatial patterns of carbon fluxes (gross ecosystem productivity (GEP), ecosystem respiration (ER) and net ecosystem productivity (NEP)) and their drivers, we constructed geographical statistical assessment schemes and quantified the magnitudes of carbon fluxes in China. The optimal assessment scheme was then validated with observed eddy covariance data to analyze the spatial distributions of carbon fluxes. Using climate-based geographical statistical assessment schemes, our estimates of GEP, ER and NEP in China during 2000s were 7.51 ± 0.51,5.82 ±0.16 and 1.91 ± 0.15 PgCyr~(-1), corresponding to 4.29%-6.80%, 5.65%-6.06% and 9.10%-12.73% of global annual carbon fluxes, respectively. The spatial distributions of GEP, ER and NEP, generated from the optimal scheme, were similar, following a southeast-northwest decreasing gradient. The maximum values for GEP, ER and NEP were 1790,1300 and 490 gC m~(-2) yr~(-1) respectively, which occurred in Central subtropics and Southern subtropics. Climate-based geographical statistical assessment schemes provided an independent dataset for the regional carbon budget assessment, which can be deemed as the potential carbon fluxes. Meanwhile, most areas in China were potential carbon sink especially Eastern China and the largest potential carbon sink appeared in Central subtropics and Southern subtropics.
机译:准确量化碳预算的数量和分布有助于制定缓解全球气候变化的战略。基于碳通量的空间格局(总生态系统生产力(GEP),生态系统呼吸(ER)和净生态系统生产力(NEP))及其驱动力,我们构建了地理统计评估方案并量化了中国碳通量的大小。然后,利用观测到的涡度协方差数据验证最优评估方案,以分析碳通量的空间分布。使用基于气候的地理统计评估方案,我们对2000年代中国GEP,ER和NEP的估计为7.51±0.51、5.82±0.16和1.91±0.15 PgCyr〜(-1),分别为4.29%-6.80%,5.65%分别占全球年度碳通量的-6.06%和9.10%-12.73%。由最优方案产生的GEP,ER和NEP的空间分布相似,遵循东南-西北递减的梯度。 GEP,ER和NEP的最大值分别为1790,1300和490 gC m〜(-2)yr〜(-1),分别发生在中亚热带和南亚热带。基于气候的地理统计评估方案为区域碳预算评估提供了独立的数据集,可以将其视为潜在的碳通量。同时,中国大部分地区是潜在的碳汇,特别是华东地区,最大的潜在碳汇出现在中亚热带和南亚热带。

著录项

  • 来源
    《Global and planetary change》 |2014年第7期|52-61|共10页
  • 作者单位

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Chaoyang District, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China;

    Key Lab of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun 666303, China;

    Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;

    South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;

    State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;

    Faculty of Life Science and Technology, Central South University of Forestry and Technology, Changsha 410004, China;

    University of Chinese Academy of Sciences, Beijing 100049, China;

    Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China;

    University of Chinese Academy of Sciences, Beijing 100049, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China;

    Institute of Agricultural Resources and Regional Planning,Chinese Academy of Agricultural Sciences, Beijing 100081, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Shijiazhuang 050021, China;

    Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha 410125, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

    Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling,Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    eddy covariance; gross ecosystem productivity; net ecosystem productivity; ecosystem respiration; carbon budget assessment; potential carbon sink;

    机译:涡动协方差生态系统总生产力;生态系统净生产力;生态系统呼吸;碳预算评估;潜在的碳汇;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号