摘要
利用中国气象局锦州农田野外观测站的碳通量观测数据分析玉米农田生态系统生长季CO2通量变化。结果表明,2008~2011年生长季的夜间呼吸速率、白天净碳交换速率年际差异不大,8天累积净碳交换量呈U型分布,碳吸收强度在生长季中期最大。夜间呼吸作用Reco与EVIs×Ws(EVIs和Ws分别为增强型植被指数EVI、陆地表面水分指数LSWI对光合作用的影响函数)线性相关,与地表温度LST满足L-T方程。基于遥感数据的呼吸模型估算呼吸作用效果良好,在东北地区玉米农田生态系统碳收支评估中具有重要作用。四年间该生态系统生长季均表现为碳汇,呼吸作用消耗的碳占光合作用固定的碳的比例差别不大,累积碳交换量分别为-513.37、-489.86、-482.06、-398.67 g/m^(2),碳交换能力较稳定。
Based on the carbon flux data over an agroecosystem in Jinzhou field station of China Meteorological Administration,the changes of CO;flux in the growing seasons of the maize farmland ecosystem was analyzed.There was little interannual difference in night respiration rate and daytime net carbon exchange rate in the growing season from 2008 to 2011.The cumulative net carbon exchange in 8 days showed a U-shaped distribution,and the carbon absorption intensity was the largest in the middle of the growing season.The nocturnal ecosystem respiration is linear correlated with EVIs×Ws(EVIsand Wsare the functions of enhanced vegetation index and land surface water index on photosynthesis,respectively),and its response to land surface temperature follows L-T equation.The results showed that the respiration model based on remote sensing data was effective in estimating ecosystem respiration,which play an important role in carbon budget assessment of maize farmland ecosystem in Northeast China.In the four years,the growth season of the ecosystem showed carbon sink,and the proportion of carbon consumed by respiration to carbon fixed by photosynthesis was not different.The cumulative carbon exchange capacity was-513.37,-489.86,-482.06,-398.67 g/m;respectively,and the carbon exchange capacity was relatively stable.
作者
叶昊天
姜海梅
李荣平
YE Hao-tian;JIANG Hai-mei;LI Rong-ping(Henan Provincial Key Laboratory of Agrometeorological Ensuring and Applied Technique,China Meteorological Administration,Zhengzhou 450003;Henan Institute of Meteorological Sciences,Zhengzhou 450003;Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration,Nanjing 210044;School of Atmospheric Physics,Nanjing University of Information Science and Technology,Nanjing 210044;Liaoning Institute of Meteorological Sciences,Shenyang 110000,China)
出处
《玉米科学》
CAS
CSCD
北大核心
2022年第1期77-85,92,共10页
Journal of Maize Sciences
基金
国家重点研发计划(2017YFC0209801)
国家自然科学基金(41505006)
中国气象局河南省农业气象保障与应用技术重点实验室应用技术研究基金项目(KM202018)。