Soil Moisture Dominates the Forest Productivity Decline During the 2022 China Compound Drought‐Heatwave Event

Dayang Zhao, Zhaoying Zhang, Yongguang Zhang

Geophysical Research Letters · 07 September 2023

In one sentence. Machine learning attributes the 2022 China compound drought-heatwave forest productivity decline mainly to soil moisture rather than VPD, identifying a tipping point.

Abstract

Abstract Compound drought‐heatwave (CDHW) events threaten ecosystem productivity and are often characterized by low soil moisture (SM) and high vapor pressure deficit (VPD). However, the relative roles of SM and VPD in constraining forest productivity during CDHWs remain controversial. In the summer of 2022, China experienced a record‐breaking CDHW event (DH2022). Here, we applied satellite remote‐sensing data and meteorological data, and machine‐learning techniques to quantify the individual contributions of SM and VPD to forest productivity variations and investigate their interactions during the development of DH2022. The results reveal that SM, rather than VPD, dominates the forest productivity decline during DH2022. We identified a possible critical tipping point of SM below which forest productivity would quickly decline with the decreasing SM. Furthermore, we illuminated the evolution of SM, VPD, evapotranspiration, forest productivity, and their interactions throughout DH2022. Our findings broaden the understanding of forest response to extreme CDHWs at the ecosystem scale.

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