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基于通量和光谱观测的中亚热带人工针叶林光能利用效率的反演

陈蝶聪1,2,王绍强1**,黄昆1,2,周蕾1,于泉洲1,2,王辉民1,3,孙雷刚4   

  1. 1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; 2中国科学院大学, 北京 100049;
    3中国科学院千烟洲红壤丘陵综合开发试验站, 江西泰和 343700; 4河北省科学院地理科学研究所, 石家庄 050000)
  • 出版日期:2015-11-18 发布日期:2015-11-18

Estimation of light-use efficiency of China’s midsubtropical planted coniferous forest based on flux measurements and spectral observations.

CHEN Die-cong1,2, WANG Shao-qiang1, HUANG Kun1,2, ZHOU Lei1, YU Quan-zhou1,2, WANG Hui-min1,3, SUN Lei-gang4   

  1. (1Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; 2University of Chinese Academy of Sciences, Beijing 100049, China; 3Qianyanzhou Integrated Ecological Station of Red Soil Hilly Land, Chinese Academy of Sciences, Taihe 343700, Jiangxi, China; 4Institute of Geographical Sciences, Hebei Academy of Sciences, Shijiazhuang 050000, China)
  • Online:2015-11-18 Published:2015-11-18

摘要: 利用光谱反射率测量的光化学植被指数(PRI)估算植被光合作用的光能利用效率(LUE),能够更好地为生态系统总初级生产力的估算及尺度扩展提供重要的技术支撑.本研究以中国通量网(ChinaFLUX)千烟洲通量观测站为研究区域,2013年9月和12月在通量塔上测量了中亚热带人工针叶林的植被反射光谱,并获取了通量塔上同步观测的气象数据和涡度相关通量数据,对两者进行回归分析.结果表明: PRI-LUE相关关系(R2=0.20,P<0.001)优于NDVILUE.在整个观测期内,土壤水分含量(SWC)与PRI组合的二元回归模型能够提高LUE的估算精度(日间观测R2=0.29,P<0.001;正午观测R2=0.30,P<0.01),而在秋季,饱和水汽压差(VPD)与PRI组合的二元回归模型能较好地估算正午LUE(R2=0.448, P<0.001),表明环境因子SWC和VPD是影响PRI-LUE关系的重要因素,不同季节的二元回归模型所选择的最佳环境变量有所不同.

Abstract: The photochemical reflectance index (PRI) calculated from spectral reflectance has universally become a proxy for the lightuse efficiency (LUE), which significantly improves the LUEbased estimation of ecosystem gross primary productivity on a large scale through upscaling. In this study, we observed the vegetation spectral reflectance of a planted subtropical coniferous forest from the top of a flux tower at Qianyanzhou Station, one of the ChinaFLUX sites, in September and December 2013, and simultaneously measured CO2 flux and meteorological variables for correlation and regression analysis. Results showed that PRI had a better correlation with LUE (R2=0.20, P<0.001) than that of normalized difference vegetation index (NDVI), i.e., PRI was preferred in LUE retrieval. During the whole observation period, PRI and soil water content (SWC)based bivariate regression model correlated well with LUE (R2=0.29, P<0.001 and R2=0.30, P<0.01 for daytime and midday observation, respectively), but in autumn the bivariate regression model of PRI and vapor pressure deficit (VPD) had a higher correlation with LUE (R2=0.448, P<0.001) for midday observation, which showed that environmental factors, i.e., SWC and VPD, had a potential in improving the LUE retrieval from PRI, but the choice of appropriate environmental factors depended on season.