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CO2 Concentration, A Critical Factor Influencing the Relationship between Solar-induced Chlorophyll Fluorescence and Gross Primary Productivity
被引:23
作者:
Qiu, Ruonan
[1
]
Han, Ge
[1
]
Ma, Xin
[2
]
Sha, Zongyao
[2
]
Shi, Tianqi
[2
]
Xu, Hao
[2
]
Zhang, Miao
[3
]
机构:
[1] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China
[2] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
[3] Nanyang Normal Univ, Sch Environm Sci & Tourism, Nanyang 473061, Peoples R China
基金:
中国国家自然科学基金;
关键词:
solar-induced chlorophyll fluorescence (SIF);
CO2;
gross primary productivity (GPP);
SCOPE (soil-canopy observation of photosynthesis and energy);
photosynthesis;
OCO-2;
CARBON-CYCLE;
PHOTOSYNTHESIS;
RETRIEVAL;
CANOPY;
MODEL;
LEAF;
LIMITATION;
RESPONSES;
FLUXES;
ENERGY;
D O I:
10.3390/rs12091377
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
The uncertainty of carbon fluxes of the terrestrial ecosystem is the highest among all flux components, calling for more accurate and efficient means to monitor land sinks. Gross primary productivity (GPP) is a key index to estimate the terrestrial ecosystem carbon flux, which describes the total amount of organic carbon fixed by green plants through photosynthesis. In recent years, the solar-induced chlorophyll fluorescence (SIF), which is a probe for vegetation photosynthesis and can quickly reflect the state of vegetation growth, emerges as a novel and promising proxy to estimate GPP. The launch of Orbiting Carbon Observatory 2 (OCO-2) further makes it possible to estimate GPP at a finer spatial resolution compared with Greenhouse Gases Observing Satellite (GOSAT), Global Ozone Monitoring Experiment-2 (GOME-2) and SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY). However, whether the relationship between GPP and SIF is linear or non-linear has always been controversial. In this research, we proposed a new model to estimate GPP using SIF and the atmospheric CO2 concentration from OCO-2 as critical driven factors simultaneously (SIF-CO2-GPP model). Evidences from all sites show that the introduction of the atmospheric CO2 concentration improves accuracies of estimated GPP. Compared with the SIF-CO2-GPP linear model, we found the SIF-GPP model overestimated GPP in summer and autumn but underestimated it in spring and winter. A series of simulation experiments based on SCOPE (Soil-Canopy Observation of Photosynthesis and Energy) was carried out to figure out the possible mechanism of improved estimates of GPP due to the introduction of atmospheric CO2 concentrations. These experiments also demonstrate that there could be a non-linear relationship between SIF and GPP at half an hour timescale. Moreover, such relationships vary with CO2 concentration. As OCO-2 is capable of providing SIF and XCO2 products with identical spatial and temporal scales, the SIF-CO2-GPP linear model would be implemented conveniently to monitor GPP using remotely sensed data. With the help of OCO-3 and its successors, the proposed SIF-CO2-GPP linear model would play a significant role in monitoring GPP accurately in large geographical extents.
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页数:19
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