Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1)

Abstract

The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a treatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18 % respectively compared to LPX.

Fire and tree death: understanding and improving modeling of fire-induced tree mortality

“…Bark thickness or tree diameter at breast height, which is strongly correlated with bark thickness, is used in many models as a surrogate for resistance to basal heating (Ryan and Reinhardt 1988, Hood et al 2008, Kelley et al 2014 because bark thickness has the largest influence on heat transfer to the underlying cambium due to bark's poor conductivity (Bova and Dickinson 2005). DGVMs and some landscape models that predict fire-caused mortality values by large grid cells and cohorts use a simplified approach with constant parameters for scorch height and bark thickness based on broad plant functional type or species grouping (Thonicke et al 2010).…”

Xylem embolism refilling and resilience against drought‐induced mortality in woody plants: processes and trade‐offs

“…Full recovery may be defined as when 'pre-disturbance' levels in defined parameters are reached. From a structural viewpoint, complete recovery of biomass or leaf area index (LAI) after disturbance might represent convenient reference points (Kelley et al 2014). Alternatively, hydraulic recovery may be defined as the point when plants reach pre-disturbance levels of transpiration, stomatal conductance (Brodribb et al 2010), or hydraulic conductivity (Ogasa et al 2013).…”

Reconstructions of biomass burning from sediment-charcoal records to improve data–model comparisons

“…Fire modeling efforts have advanced rapidly in the last decade (Arora and Boer, 2005;Kloster et al, 2010;Kelley et al, 2014;Lasslop et al, 2014;Yue et al, 2014;Le Page et al, 2015), providing a better understanding of the varied impacts that fires have on humans, the biosphere, and the atmosphere , as well as the mechanisms through which climate changes and human activities affect fire regimes. Simulations of fire activity using physically based empirical relationships between flammability and its controlling variables, such as temperature and soil moisture, have helped identify the global drivers of modern burning (Arora and Boer, 2005;Kloster et al, 2010;Pechony and Shindell, 2010;Thonicke et al, 2010;Li et al, 2013;Pfeiffer et al, 2013).…”