Increasing Ecosystem Fluxes Observed from Eddy Covariance and Solar-Induced Fluorescence Data

Increasing Ecosystem Fluxes Observed from Eddy Covariance and Solar-Induced Fluorescence Data

Ecosystems modulate Earth’s climate through the exchange of carbon and water fluxes. However, long-term trends in these terrestrial fluxes remain unclear due to the lack of continuous measurements on the global scale. This study combined flux data from 197 eddy covariance sites with satellite-retrie...

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Bibliographic Details
Main Authors: Jiao Zheng, Hao Zhou, Xu Yue, Xichuan Liu, Zhuge Xia, Jun Wang, Jingfeng Xiao, Xing Li, Fangmin Zhang
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Remote Sensing
Subjects:
solar-induced fluorescence
gross primary productivity
evapotranspiration
water use efficiency
machine learning
Online Access:https://www.mdpi.com/2072-4292/17/12/2064
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Summary:Ecosystems modulate Earth’s climate through the exchange of carbon and water fluxes. However, long-term trends in these terrestrial fluxes remain unclear due to the lack of continuous measurements on the global scale. This study combined flux data from 197 eddy covariance sites with satellite-retrieved solar-induced chlorophyll fluorescence (SIF) to investigate spatiotemporal variations in gross primary productivity (GPP), evapotranspiration (ET), and their coupling via water use efficiency (WUE) from 2001 to 2020. We developed six global GPP and ET products at 0.05° spatial and 8-day temporal resolution, using two machine learning models and three SIF products, which integrate vegetation physiological parameters with data-driven approaches. These datasets provided mean estimates of 128 ± 2.3 Pg C yr<sup>−1</sup> for GPP, 522 ± 58.2 mm yr<sup>−1</sup> for ET, and 1.8 ± 0.21 g C kg<sup>−1</sup> H<sub>2</sub>O yr<sup>−1</sup> for WUE, with upward trends of 0.22 ± 0.04 Pg C yr<sup>−2</sup> in GPP, 0.64 ± 0.14 mm yr<sup>−2</sup> in ET, and 0.0019 ± 0.0005 g C kg<sup>−1</sup> H<sub>2</sub>O yr<sup>−2</sup> in WUE over the past two decades. These high-resolution datasets are valuable for exploring terrestrial carbon and water responses to climate change, as well as for benchmarking terrestrial biosphere models.
ISSN:2072-4292

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