Abstract
Alongside gradual changes in climate, extreme events such as droughts and heatwaves have increased in frequency globally. Together, chronic change and extreme events have been linked to forest die‐off, as well as larger, more severe wildfires. Increased disturbance frequency inevitably increases the likelihood of compounding effects, highlighting the importance of understanding forest responses and recovery. This study investigated physiological characteristics of the dominant canopy tree species, Eucalyptus marginata , on sites affected by a drought/heatwave event (2011) and five years later by a wildfire (2016) in southwestern Australia. Using a factorial design of drought vulnerability (sites with high and low vulnerability to drought), and sites that had experienced moderate and high fire severity, physiological measurements including pre‐dawn leaf water potential, stomatal conductance, chlorophyll fluorescence, leaf temperature, specific leaf area, and live foliar moisture content were quantified to reveal impacts and potential compound effects on tree function. Measurements were taken during a summer heatwave and typical wet‐winter conditions to span periods of high and low stress. High drought vulnerability/ high severity wildfire sites had significantly lower pre‐dawn leaf water potentials, and stomatal conductance. Although E. marginata is known to be drought and fire tolerant, this forest stand had visible tree death and canopy contractions (via leaf drop) between summer and winter measurements, suggesting low plant available water in summer approached E. marginata 's threshold for survival in high severity fire sites. Trees on high drought vulnerability sites experienced significantly more stress, but fire severity effects primarily manifested within these sites, measured via decreased specific leaf area and chlorophyll fluorescence. These results reveal interactive, contingent nature of multiple disturbances and their implications for future forest recovery. Monitoring forest health and function is central to developing predictive capacity of forest dynamics and tree responses as extreme events increase in frequency, severity, and scale.
