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Bidirectional drought‐related canopy dynamics across pantropical forests: a satellite‐based statistical analysis

Authors :
Liyang Liu
Yongxian Su
Shengbiao Wu
Lei Fan
Philippe Ciais
Wenping Yuan
Xiuzhi Chen
Jing Zhang
Chenghu Zhou
Fanxi Gong
Xueqin Yang
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE)
Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)
Institut Pierre-Simon-Laplace (IPSL (FR_636))
École normale supérieure - Paris (ENS-PSL)
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)
School of biological sciences (Hong Kong, Chine)
The University of Hong Kong (HKU)
2020A151501091, 2020GDASYL‐20200102002
National Natural Science Foundation of China, NSFC: 31971458, 41971275
National Key Research and Development Program of China, NKRDPC: 2016YFA0602701
This research was funded by the National Key Research and Development Program of China, grant number 2016YFA0602701
the National Natural Science Foundation of China, grant numbers 31971458 and 41971275
Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), grant number 311021009
the Guangdong Basic and Applied Basic Research Foundation, grant number 2020A151501091
GDAS Special Project of Science and Technology Development, grant number 2020GDASYL‐20200102002.
National Natural Science Foundation of China, grant numbers 31971458 and 41971275
Source :
Remote Sensing in Ecology and Conservation, Vol 8, Iss 1, Pp 72-91 (2022), Remote Sensing in Ecology and Conservation, Remote Sensing in Ecology and Conservation, 2022, 8 (1), pp.72-91. ⟨10.1002/rse2.229⟩
Publication Year :
2021
Publisher :
Wiley, 2021.

Abstract

International audience; Droughts cause extreme anomalies in tropical forest growth, but the direction and magnitude of tropical forests in response to droughts are still widely debated. Here, we used four satellite-based canopy growth proxies (CGPs), including three optical and one passive microwave, and in situ fluxes observations from eddy covariance (EC) measurements for a retrospective investigation of the impacts of historical droughts on tropical forest growth from a statistical point of view. Results indicate two opposite directions in drought-related canopy dynamics across pantropical forests. The canopy of tropical forests with higher CGPs is more vulnerable to drought stress and recovers faster in the post-drought recovery period. In contrast, the canopy of tropical forests with lower CGPs increases during the drought period and declines in the subsequent recovery period, which is beyond general expectation. In situ measurements from eddy-covariance flux towers showed that forests with higher gross primary production and latent heat flux decreased photosynthesis and evapotranspiration during the drought period but increased photosynthesis and evapotranspiration faster during the post-drought recovery period, supporting the findings from satellite observations. Our statistical analysis against climatic factors predicts that higher-CGPs tress with probably taller and bigger canopies are more responsive to shortage of water availability caused by drought; while lower-CGPs tress with shorter and smaller canopies are more responsive to sunlight availability and tend to increase their canopy leaves and enhance photosynthesis in sunnier days during the drought period. Our results highlight the differences in tropical forests in responding to drought stress, which are worth incorporated in Earth system models for time-series evaluations.

Details

ISSN :
20563485
Volume :
8
Database :
OpenAIRE
Journal :
Remote Sensing in Ecology and Conservation
Accession number :
edsair.doi.dedup.....deccf722c29cf8de91f3649821ac843a