|本期目录/Table of Contents|

[1]郭舒艳,任小丽,盖艾鸿,等.基于FLUXNET的CLM模型生态系统呼吸模拟验证[J].应用与环境生物学报,2019,25(04):862-876.[doi:10.19675/j.cnki.1006-687x.2018.11008]
 GUO Shuyan,REN Xiaoli**,et al.Benchmarking the ecosystem respiration simulated by CLM based on FLUXNET[J].Chinese Journal of Applied & Environmental Biology,2019,25(04):862-876.[doi:10.19675/j.cnki.1006-687x.2018.11008]
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基于FLUXNET的CLM模型生态系统呼吸模拟验证
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《应用与环境生物学报》[ISSN:1006-687X/CN:51-1482/Q]

卷:
25卷
期数:
2019年04期
页码:
862-876
栏目:
生态系统养分循环与保护恢复专栏
出版日期:
2019-08-25

文章信息/Info

Title:
Benchmarking the ecosystem respiration simulated by CLM based on FLUXNET
作者:
郭舒艳;?任小丽;?盖艾鸿;?张黎;?李攀;?葛蓉;?李睿;?何洪林
1甘肃农业大学资源与环境学院 兰州 730070 2中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室 北京 100101 3中国科学院大学资源与环境学院 北京 100190 4中国科学院地球化学研究所,环境地球化学国家重点实验室 贵阳 550002 5中国科学院大学 北京 100190 6南京信息工程大学应用气象学院 南京 210044
Author(s):
GUO Shuyan1;? 2;? REN Xiaoli2**;? GAI Aihong1**;? ZHANG Li2;? 3;? LI Pan4;? 5;? GE Rong2;? 5;? LI Rui2;? 6 & HE Honglin2;? 3
1 College of Resources and Environmental Sciences, Gansu Agricultural University, Lanzhou 730070, China 2 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China 3 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China 4 State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550002, China 5 University of Chinese Academy of Sciences, Beijing 100190, China 6 College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China
关键词:
生态系统呼吸;?通用陆面模型(CLM);?全球通量网(FLUXNET);?模拟效果
Keywords:
ecosystem respiration;? Community Land Model (CLM);? FLUXNET;? simulated performance
分类号:
Q148
DOI:
10.19675/j.cnki.1006-687x.2018.11008
摘要:
准确估算陆地生态系统呼吸(Ecosystem respiration,RE)对全球陆地生态系统碳收支研究具有重要意义. 模型模拟是估算陆地RE变化的一种常用手段. 然而目前陆地生态系统过程模型的RE模拟尚未得到充分验证. 基于耦合模式比较计划第五阶段(Coupled Model Intercomparison Project Phase 5,CMIP5)的通用陆面模型(Community land model,CLM)RE模拟结果和全球通量网(FLUXNET)66个站点的涡度相关通量观测数据(277条站点年数据)评估CLM模型对RE的模拟效果. 结果表明:(1)在空间尺度上,CLM低估了高纬度站点RE,高估了低纬度站点RE,但高纬度低估量更大导致空间格局整体低估(相对误差为-3.56%).(2)在时间尺度上,CLM模型基本捕捉了RE的年际和季节变化,相关系数分别为0.60(P < 0.001)和0.63(P < 0.001);CLM低估年尺度和月尺度的RE(以C计),绝对误差分别是-182.21 g m-2 a-1、-120.16 g m-2 mon-1,相对误差分别是-17.84%、-10.60%.(3)CLM模型对不同植被功能型的RE模拟效果不同,由优及差依次为混交林、常绿针叶林、草地、农田、落叶阔叶林、常绿阔叶林. 本研究在时空尺度上量化了CLM模型的生态系统呼吸模拟误差,并分析了土壤呼吸Q10和MRbase参数以及土壤碳库模拟等因素的影响,可为CLM模型的生态系统呼吸模块参数优化提供依据,进而提升其模拟精度. (图4 表3 参80 附图2 附表2)
Abstract:
Accurate estimation of terrestrial ecosystem respiration (RE) is of great significance to the study of the global terrestrial ecosystem’s carbon budget. Model simulation is a common method to simulate terrestrial RE changes. However, the RE simulation of the current terrestrial ecosystem’s process models has not been fully verified yet. In this study, we evaluated the RE simulated by the Community Land Model (CLM) using eddy covariance flux observations of 66 stations from FLUXNET (277 site-years). The results showed that: (1) CLM underestimated RE at high latitude sites while overestimated it at low latitude stations. The magnitude of the former was larger than that of the latter, thus leading to the overall underestimation of RE (the relative error was -3.56%). (2) At the temporal scale, CLM roughly captured the interannual and seasonal variation of RE. The correlation coefficients were 0.60 (P < 0.001) and 0.63 (P < 0.001), respectively. CLM underestimated the annual and monthly RE, with the absolute error of 182.21 g C m-2 a-1 and 120.16 g C m-2 mon-1, respectively. The relative errors were 17.84% and 10.60%, respectively. (3) The simulation results of the different plant functional types from the best to worst were ranked as mixed forest, evergreen coniferous forest, grassland, farmland, deciduous broadleaved forest, and evergreen broadleaved forest. This study quantified the error of CLM-RE simulation at the spatial-temporal scale and analyzed its influence factors, such as soil respiration Q10 , MRbase parameters, and soil carbon reservoir simulation. The results can help in optimizing CLM-RE and improving the accuracy of RE simulations.

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更新日期/Last Update: 2019-08-25