Factors determining hurricane disturbance and forest recovery in ELM-FATES
[Shi et al., 2024] The linear regression coefficient of biomass recovery (R recovery ) for experiments with varied hurricane mortality rates. (a) and (b) show the R recovery based on a relatively equal and realistic pre-hurricane biomass partition between plant types.
The Science
Hurricanes are affecting the tropical forests. This study uses the Functionally Assembled Terrestrial Ecosystem Simulator of the Energy Exascale Earth System Model Land Model (ELM-FATES). The model simulations in the Luquillo Experimental Forest (LEF) of Puerto Rico and the random forest feature importance imply that hurricane mortality and background mortality are the two major factors regulating post-hurricane forest recovery. Increased hurricane mortality leads to the transformation of the LEF into an ecosystem dominated by light-demanding plant functional types. ELM-FATES provides a reasonable representation of the seasonality of carbon and water fluxes at the LEF, when compared to various data products.
The Impact
This research improves understanding of the Functionally Assembled Terrestrial Ecosystem Simulator of the Energy Exascale Earth System Model (E3SM) Land Model (ELM-FATES) behavior associated with hurricane disturbance and post-hurricane forest recovery. This accomplishment involved conducting model simulations that incorporated hurricane disturbances of varying intensity at the Luquillo Experimental Forest of Northeast Puerto Rico. Additionally, random forest feature importance estimates were used in the process. This research provides guidance for ELM-FATES parameterization and dynamic vegetation model development in representing hurricane induced forest damage with various intensities.
Summary
To enhance the understanding of forest recovery after hurricanes, we implemented hurricane induced forest damage into the Functionally Assembled Terrestrial Ecosystem Simulator, coupled with the Energy Exascale Earth System Model Land Model (ELM-FATES). We performed ensemble ELM-FATES simulations with varied forest damage intensities in the Luquillo Experimental Forest, Puerto Rico, and used the output to identify factors controlling the post-hurricane forest recovery, which was further evaluated with random forest feature importance (RFFI) that quantifies the sensitivity of the key model parameters to the post-hurricane forest recovery. The results imply that hurricane mortality and background mortality are the major factors regulating post-hurricane forest recovery. Changes to the intensity of simulated hurricanes could alter forest composition and structure during recovery, which modifies forest ecological processes and potentially shift the wet forests in Puerto Rico to states with increased vulnerability to tropical cyclones. This research enhances our understanding of the ELM-FATES model behavior associated with hurricane disturbance and broadens the application of RFFI in quantifying the parameter sensitivity of a dynamic global vegetation model (DGVM). This research addresses the essential role of representing hurricane induced forest damage in DGVMs, an advanced tool for the future studies of tropical forest dynamics.
Contact
Mingjie Shi
Pacific Northwest National Laboratory
mingjie.shi@pnnl.gov
Funding
This research was conducted at Pacific Northwest National Laboratory, operated for the U.S. Department of Energy by Battelle Memorial Institute under contract DE-AC05-76RL01830. This study was supported by the Department of Energy’s (DOE) Office of Biological and Environmental Research as part of the Terrestrial Ecosystem Science program through the Next-Generation Ecosystem Experiments (NGEE)-Tropics project.
Publications
Shi, M., Keller, M., Bomfim, B., Li, L.,et al. “Functionally assembled terrestrial ecosystem simulator (FATES) for hurricane disturbance and recovery.” Journal of Advances in Modeling Earth Systems, 16, e2023MS003679 (2024). [https://doi.org/10.1029/2023MS003679].