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.
CITATION STYLE
Liu, L., Gong, F., Chen, X., Su, Y., Fan, L., Wu, S., … Zhou, C. (2022). Bidirectional drought-related canopy dynamics across pantropical forests: a satellite-based statistical analysis. Remote Sensing in Ecology and Conservation, 8(1), 72–91. https://doi.org/10.1002/rse2.229
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