Detection of photosynthetic responses of cool-temperate forests following extreme climate events using Bayesian inversion

The increase in extreme climate events associated with ongoing global warming may create severe damage to terrestrial ecosystems, changing plant structure and the eco-physiological functions that regulate ecosystem carbon exchange. However, most damage is usually due to moderate, rather than catastrophic, disturbances. The nature of plant functional responses to such disturbances, and the resulting effects on the terrestrial carbon cycle, remain poorly understood. To unravel the scientific question, tower-based eddy covariance data in the cool-temperate forests were used to constrain plant eco-physiological parameters in a persimoneous ecosystem model that may have affected carbon dynamics following extreme climate events using the statistic Bayesian inversion approach. In the present study, we raised two types of extreme events relevant for cool-temperate regions, i.e. a typhoon with mechanistic foliage destraction and a heat wave with severe drought. With appropriate evaluation of parameter and predictive uncertainties, the inversion analysis shows annual trajectory of activated photosynthetic responses following climate extremes compared the pre-disturbance state in each forest. We address that forests with moderate disturbance show substantial and rapid photosynthetic recovery, enhanced productivity, and, thus, ecosystem carbon exchange, although the effect of extreme climatic events varies depending on the stand successional phase and the type, intensity, timing and legacy of the disturbance.