PNNL

Abstract

Tropical cyclones are an important cause of disturbance in coastal tropical and subtropical forests. Major storms cause severe forest structural damage and elevated tree mortality. However, understanding of post-hurricane forest recovery and the essential factors regulating recovery is still limited. We use numerical modeling to study the processes and the key factors regulating forest recovery after a hurricane disturbance. We used a vegetation demography model, the Functionally Assembled Terrestrial Ecosystem Simulator, which has been coupled with the Energy Exascale Earth System Model (E3SM) Land Model (ELM-FATES). We performed numerical experiments for the Luquillo Experimental Forest (LEF), Puerto Rico. In this research, we implemented hurricane induced forest damage, including defoliation, biomass reduction, and mortality in ELM-FATES, and performed parameter sensitivity tests with forest damage at varied intensities. We performed ensemble model simulations and analyzed the simulations to identify factors controlling the post-hurricane forest recovery. The ELM-FATES results indicated a tendency for the tropical forests at LEF to shift towards the light demanding plant functional type (PFT), when the forests experienced severe hurricane disturbance with hurricane mortality > 60% for both the light demanding and shade tolerant types. However, with observed lower mortality rates for shade tolerant compared to light demanding PFTs, the recovery of the light demanding PFT was effectively suppressed. Hurricane mortality and background mortality were the two major factors regulating post-hurricane forest recovery in simulations. This result implies that changes to the frequency and intensity of simulated hurricanes could alter forest composition and structure during recovery, which could alter forest ecological processes and potentially shift the wet forests in Puerto Rico to a state with increased vulnerability to tropical cyclonic storms. This research improves understanding of the ELM-FATES model behavior associated with hurricane disturbance and provides guidance for dynamic vegetation model development in representing hurricane induced forest damage with varied intensities.