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A leaf age‐dependent light use efficiency model for remote sensing the gross primary productivity seasonality over pantropical evergreen broadleaved forests.

Authors :
Tian, Jie
Yang, Xueqin
Yuan, Wenping
Lin, Shangrong
Han, Liusheng
Zheng, Yi
Xia, Xiaosheng
Liu, Liyang
Wang, Mei
Zheng, Wei
Fan, Lei
Yan, Kai
Chen, Xiuzhi
Source :
Global Change Biology; Aug2024, Vol. 30 Issue 8, p1-17, 17p
Publication Year :
2024

Abstract

Tropical and subtropical evergreen broadleaved forests (TEFs) contribute more than one‐third of terrestrial gross primary productivity (GPP). However, the continental‐scale leaf phenology‐photosynthesis nexus over TEFs is still poorly understood to date. This knowledge gap hinders most light use efficiency (LUE) models from accurately simulating the GPP seasonality in TEFs. Leaf age is the crucial plant trait to link the dynamics of leaf phenology with GPP seasonality. Thus, here we incorporated the seasonal leaf area index of different leaf age cohorts into a widely used LUE model (i.e., EC‐LUE) and proposed a novel leaf age‐dependent LUE model (denoted as LA‐LUE model). At the site level, the LA‐LUE model (average R2 =.59, average root‐mean‐square error [RMSE] = 1.23 gC m−2 day−1) performs better than the EC‐LUE model in simulating the GPP seasonality across the nine TEFs sites (average R2 =.18; average RMSE = 1.87 gC m−2 day−1). At the continental scale, the monthly GPP estimates from the LA‐LUE model are consistent with FLUXCOM GPP data (R2 =.80; average RMSE = 1.74 gC m−2 day−1), and satellite‐based GPP data retrieved from the global Orbiting Carbon Observatory‐2 (OCO‐2) based solar‐induced chlorophyll fluorescence (SIF) product (GOSIF) (R2 =.64; average RMSE = 1.90 gC m−2 day−1) and the reconstructed TROPOspheric Monitoring Instrument SIF dataset using machine learning algorithms (RTSIF) (R2 =.78; average RMSE = 1.88 gC m−2 day−1). Typically, the estimated monthly GPP not only successfully represents the unimodal GPP seasonality near the Tropics of Cancer and Capricorn, but also captures well the bimodal GPP seasonality near the Equator. Overall, this study for the first time integrates the leaf age information into the satellite‐based LUE model and provides a feasible implementation for mapping the continental‐scale GPP seasonality over the entire TEFs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13541013
Volume :
30
Issue :
8
Database :
Complementary Index
Journal :
Global Change Biology
Publication Type :
Academic Journal
Accession number :
179321094
Full Text :
https://doi.org/10.1111/gcb.17454