Adapting a dynamic vegetation model for regional biomass, plant biogeography, and fire modeling in the Greater Yellowstone Ecosystem: Evaluating LPJ-GUESS-LMfireCF

North American forests are threatened by changes in climate and disturbance dynamics. Current efforts to model future vegetation and fire dynamics are challenged by the lack of mechanistic representation of ecological processes, the spatial resolution to capture landscape-level heterogeneity, and the ability to model regional spatial extents. To address these gaps, a dynamic vegetation model was adapted for regional applications to the western forests of the U.S. Here we present LPJ-GUESS-LMfireCF, a dynamic vegetation model that includes the ecological processes of a dynamic global vegetation model with cohort-based forest demography (LPJ-GUESS) and a mechanistic fire module (LMfire), with a newly developed routine to simulate stand-replacing crown fires (CF). The LMfireCF fire module calculates surface fire and canopy characteristics to determine if critical conditions are met for crown fire initiation and spread, and if met, calculates crown fire effects. Adapting the model to regional applications required parameterization of dominant regional plant functional types (PFTs) and additional model adjustments related to the representation of fire. Simulations driven by historical climate data from 1980 to 2016 were made to compare the two different fire modules: the original GlobFIRM and newly created LMfireCF, and two different plant functional type (PFT) parameterizations: the original global vs. newly created regional PFTs. Model performance was evaluated by comparing simulation outputs to field and satellite based estimates for landscape biomass distribution, dominant plant cover, fire activity, and forest regeneration. LPJ-GUESS-LMfireCF accurately represented vegetational zones with elevation and climate gradients in Yellowstone National Park (YNP). Total carbon in aboveground live vegetation within YNP simulated by LPJGUESS-LMfireCF with the regional PFTs overestimated satellite-based estimates by 12% (44.8 TgC vs 39.9 TgC respectively). In comparison, an LPJ-GUESS simulation using the older GlobFIRM fire module and global PFTs resulted in total carbon in aboveground live vegetation of 225 Tg C for YNP, five times the satellite-based estimates. LPJ-GUESS-LMfireCF simulated burned area and fire severity approximated satellite-based observations. Importantly, LPJ-GUESS-LMfireCF simulated the large stand-replacing fires of 1988 in Yellowstone as emergent results without model initialization of vegetation cover or fire history. LPJ-GUESS-LMfireCF simulated that 25% of the area of YNP burned in 1988, compared to 36% based on field and satellite-based estimates. However, modeled postfire regrowth was more rapid than field-based estimations, with simulated mean biomass 24 years postfire (40.1 +/- 1.65 Mg ha(-1)) 58% greater than field estimations (25.4 +/- 2.5 Mg ha(-1)), yet simulated mean biomass for mature forests (>100 years old without a major disturbance) was 24% less than field estimations (58.4 +/- 0.8 compared to 76.6 +/- 3.5 Mg ha(-1)). In summary, LPJ-GUESS-LMfireCF effectively simulates regional crown fire dynamics and vegetation to more accurately model regional biomass, plant biogeography, and fire activity.

Automated summary

North American forests are facing threats from climate change and disturbance dynamics, making it challenging to model future vegetation and fire dynamics. The LPJ-GUESS-LMfireCF model was successfully adapted for regional applications in western U.S. forests, accurately representing vegetation zones in Yellowstone National Park and providing a more accurate simulation of regional biomass, plant biogeography, and fire activity.