Study of Forest Disturbance and Recovery in Puerto Rico with Field Measurements and E3SM Land Model-FATES

Authors

Mingjie Shi1* ([email protected]), Michael Keller2,3, Barbara Bomfim4, Jessica Needham4, Charles Koven4, Lara Kueppers4,5, Ruby Leung1, Jeffrey Chambers4

Institutions

1Pacific Northwest National Laboratory, Richland, WA; 2U.S. Forest Service, Rio Piedras, Puerto Rico; 3NASA Jet Propulsion Laboratory, Pasadena, CA; 4Lawrence Berkeley National Laboratory, Berkeley, CA; 5University of CaliforniaBerkeley, CA

URLs

Abstract

Tropical cyclones are important natural disturbances in coastal tropical and sub-tropical forests. In the past three decades, Puerto Rico experienced five hurricanes that met or exceeded category 3 (i.e., wind speed greater than 178 km/h); these major storms caused severe forest structural damage and elevated tree mortality. To improve the prediction of post-hurricane forest function and structure changes, researchers used in situ forest measurements at the Bisley Watershed study site in the Luquillo Experimental Forest of Northeast Puerto Rico and FATES coupled with the E3SM Land Model (ELM-FATES). Numerical experiments were performed to replicate hurricane damage on forest structure including defoliation, structural-damage-induced biomass reduction, and hurricane mortality rates for the simulation period 1950 to 2017. The study compared litterfall fluxes obtained by field census and model simulation and tree biomass in terms of plant functional types (PFTs) and diameter at breast height (DBH) size classes. By constraining model parameterization with key plant trait observations (e.g., maximum rate of carboxylation or Vcmax, wood density, and specific leaf area), ELM-FATES can reasonably represent PFT-level, pre- and post-hurricane leaf and aboveground biomass reduction and recovery. The model–data comparison reveals that these ELM-FATES simulations tend to overestimate the number of exceedingly large DBH trees (≥95 cm). This bias may be associated with deficiencies in the model for representing size-related mortality or with the representation of carbon allocation relative to tree size in ELM-FATES. The parameterization that constrains mortality rates for certain DBH groups reduces the number of trees with large DBH values (≥95 cm). This research addresses the importance of implementing hurricane disturbance representations in dynamic global vegetation models integrated into Earth system models.