Water use efficiency at multi-time scales and its response to episodic drought and wet periods in a typical subtropical evergreen forest of Southeast China

[Display omitted] •WUE responds differently to climatic drivers at monthly, 8-day intervals, daily, and half-hourly scales.•ET is the dominant factor influencing the WUE variability with a relative contribution of 57.5% for all seasons.•WUE has a remarkably high correspondence to air temperature at any time scale from monthly to half-hourly.•WUE during the episodic drought period is generally higher than that during the episodic wet period. Water use efficiency (WUE) quantifies the trade-off between carbon gain and water loss. A deep understanding of its relationships with the controlling factors is essential for predicting ecosystem responses to climate change. Our study utilized the eddy covariance measurements to analyze the variability of WUE and its influencing climate factors at the seasonal, monthly, 8-day, daily, and half-hourly scales and during the episodic drought and wet periods at a typical subtropical evergreen forest of Southeast China. The results show that ET is the dominant factor influencing the WUE variability with a relative contribution of 57.56 ± 2.26% for different seasons in this study area. Secondly, WUE responds differently to climatic drivers from monthly to half-hourly scales. Our results show that WUE has a remarkably high sensitivity to soil moisture at multi-time scales (from monthly to half-hourly), and the connection strength increases with increasing time scale. Thirdly, there is no significant relationship between VPD and WUE as time scale expands. In addition, WUEs during the episodic drought period have higher values than those during the episodic wet period on the monthly scales. The half-hourly WUE during the episodic drought period is close to the WUE during the episodic wet period from 8:30 to 19:00 but is higher from 6:00 to 8:00. These results indicate that soil moisture plays an important role on influencing WUE variation at multi-time scales and under extreme climatic conditions.