Abstract
Recently developed solar-induced chlorophyll fluorescence-related vegetation indices (e.g., near infrared reflectance of vegetation (NIRv) and kernel normalized difference vegetation index (kNDVI)) have been reported to be appropriate proxies for vegetation photosynthesis. These vegetation indices can be used to estimate gross primary productivity (GPP) without considering meteorological constraints. However, it is not clear whether such a statement holds true under various environmental conditions. In this study, we explored whether these vegetation indices require meteorological constraints to better characterize GPP under extreme drought conditions using three extreme drought cases in Europe in 2003, 2010, and 2018. According to the long-term series of observations, vegetation indices (NIRv and kNDVI) alone explained 60% and 57%, respectively, of the weekly GPP variation across the 66 flux sites. The explained variation increased to 69% and 64%, respectively, for the models that take into account radiative effects (NIRv and kNDVI multiplied by radiation). However, without considering meteorological constraints, these vegetation index-based estimations severely underestimated negative GPP anomalies under drought stress, especially in models that incorporate radiative effects. After incorporating vapor pressure deficit (VPD)-based meteorological constraints, the GPP estimations exhibited more pronounced negative anomalies during drought periods while maintaining model accuracy (at 70% and 65%, respectively). In addition, the GPP models based on site observations were applied at the regional scale (Europe). Our results indicated that the models without meteorological constraints again underestimated the impact of drought on GPP. This study emphasizes the importance of meteorological constraints in the estimation of GPP, especially under extreme drought conditions.
Original language | English |
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Article number | e2023JG007499 |
Pages (from-to) | 1-15 |
Number of pages | 15 |
Journal | Journal of Geophysical Research: Biogeosciences |
Volume | 129 |
Issue number | 1 |
Early online date | 23 Jan 2024 |
DOIs | |
Publication status | Published - Jan 2024 |
Bibliographical note
Funding Information:We acknowledge the flux data provided by Integrated Carbon Observation System (ICOS). This study was supported by the Natural Science Foundation of Qinghai Province (Nos. 2023‐QLGKLYCZX‐10, 2023‐QLGKLYCZX‐4), the National Natural Science Foundation of China (Nos. 42161144003, 42130506, and 31570464) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Nos. KYCX22_1128, KYCX23_1322).
Publisher Copyright:
© 2024. American Geophysical Union. All Rights Reserved.
Funding
We acknowledge the flux data provided by Integrated Carbon Observation System (ICOS). This study was supported by the Natural Science Foundation of Qinghai Province (Nos. 2023‐QLGKLYCZX‐10, 2023‐QLGKLYCZX‐4), the National Natural Science Foundation of China (Nos. 42161144003, 42130506, and 31570464) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Nos. KYCX22_1128, KYCX23_1322).
Funders | Funder number |
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Postgraduate Research & Practice Innovation Program of Jiangsu Province | KYCX23_1322, KYCX22_1128 |
National Natural Science Foundation of China | 31570464, 42161144003, 42130506 |
National Natural Science Foundation of China | |
Natural Science Foundation of Qinghai Province | 2023‐QLGKLYCZX‐10, 2023‐QLGKLYCZX‐4 |
Natural Science Foundation of Qinghai Province |
Keywords
- drought
- gross primary productivity
- meteorological constraints
- vegetation index