Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model SSiB4/TRIFFID-Fire v1.0
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Citations
Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations
Estimating global aerodynamic parameters in 1982–2017 using remote-sensing data and a turbulent transfer model
Impact of burned areas on the northern African seasonal climate from the perspective of regional modeling
Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets.
BASNet: Burned Area Segmentation Network for Real-Time Detection of Damage Maps in Remote Sensing Images
References
Determinants of woody cover in African savannas
The global distribution of ecosystems in a world without fire
Development of a 50-Year High-Resolution Global Dataset of Meteorological Forcings for Land Surface Modeling
Interannual variability in global biomass burning emissions from 1997 to 2004
GLC2000: a new approach to global land cover mapping from Earth observation data
Related Papers (5)
Frequently Asked Questions (17)
Q2. What have the authors stated for future works in "Modeling long-term fire impact on ecosystem characteristics and surface energy using a process-based vegetation–fire model ssib4/triffid-fire v1.0" ?
It reasonably reproduces the global GPP and PFT distribution, which is important to study fire effects on the ecosystem. The SSiB4/TRIFFID-Fire is then applied to study the long-term fire effects on ecosystem characteristics and surface energy. HH conducted the simulation with suggestions from FL and YL.
Q3. What are the sources of uncertainties in the simulation of fire effects?
Other sources of uncertainties include the differences in the partitioning between latent heat and sensible heat fluxes in land surface models, the differences in the parameterization of the evaporation processes, and the changes due to atmospheric feedbacks, such as cloud cover and precipitation changes.
Q4. How much vegetation has been reduced by fire?
Over the African and South American savanna, the authors find fire has reduced the area-averaged LAI and vegetation height by 0.52 m2 m−2 (12.5 %) and 5.76 m (49.1 %), respectively.
Q5. How have fire models been used to assess the long-term impact on the terrestrial carbon cycle?
Some fire models have been used to assess long-term fire impact on the terrestrial carbon cycle by comparing a reference simulation with fire and a sensitivity simulation representing “a world without fire”.
Q6. What is the carbon density vector for the j th PFT?
In TRIFFID (Cox, 2001), the fractional change of the j th PFT ( dfjdt ) is governed by the Lotka–Volterra equation:dfj dt = λjNPPj fj Cvj[ 1− ∑ j cijfj ] − γjfj , (16)where fj is the fractional coverage of the j th PFT; λjNPPj is the carbon available for spreading;
Q7. What is the reason for the lack of a realistic fire season in some regions?
The inaccurate simulation of fire season in several fire regions could come from deficiency of the forcing data, the inaccuracy in dynamic vegetation processes, or some processes that control the fire but are not represented in the model.
Q8. What is the corresponding mortality factor for the j th PFT?
When the fire model is coupled to SSiB4/TRIFFID, the loss of PFT fraction due to fires (βj ) can be explicitly derived from the fire-induced carbon loss:βj = (ϕj +ψj ) · fjCvj , (17)where ϕj and ψj are PFT-dependent carbon loss due to combustion and post-fire mortality, respectively.
Q9. What is the average spread area of a fire?
The average spread area of a fire is assumed to be elliptical in shape, with the ignition point located at one of the foci and the fastest spread occurring along the major axis.
Q10. What is the feo factor used in the Li et al. (2012) fire?
In the Li et al. (2012) fire scheme, this factor (fθ ) is parameterized using root zone soil moisture potential factor β (0–1.0), a model-dependent variable used to calculate transpiration in CLM (Li and Lawrence, 2017).
Q11. What is the carbon density of the ith and j th PFT?
Cvj is the carbon density (g C km−2); cij is the competition coefficient between the ith and j th PFTs; and γj (s−1) is the constant disturbance representing the loss of PFT fraction due to fires, pests, windthrow, and many other processes.
Q12. What is the carbon density vector for leaf, stem, root, and litter of the j?
(13)Cj = (Cleaf,Cstem,Croot,Clitter)j is carbon density vector (g C km−2) for leaf, stem, root, and litter of the j th PFT calculated in TRIFFID.
Q13. What is the average burned area in a savanna?
The burned area in African savanna accounts for more than 60 % of the global burned area in both GFED4s and SSiB4/TRIFFID-Fire (Fig. 4b).
Q14. What are the main reasons why fire models have been used to reconstruct fire history?
Fire models have been used to reconstruct fire history before the satellite era (Yang et al., 2015; van Marle et al., 2017; Li et al., 2019).
Q15. What is the variable to describe the dependence of fuel combustibility on the preceding climate?
In SSiB4/TRIFFID-Fire, the root zone soil moisture θ is found to be the best variable to describe the dependence of fuel combustibility on the preceding climate.
Q16. What is the effect of fire on vegetation structure in the savanna?
Their results are consistent with the long-term fire experiments that reported that fire strongly affected vegetation structure, lowering the proportions of trees to fire-resistant grasses and reducing the vegetation height and aboveground biomass (Shackleton and Scholes, 2000; Higgins et al., 2007; van Wilgen et al., 2007; Furley et al., 2008; Smit et al., 2010; Devine et al., 2015), and that fire impact is more significant in wetter savanna than in drier savanna (Moreira, 2000; Sankaran et al., 2005).
Q17. What is the spatial correlation of the GFED4s and TRIFFID-Fi?
In general, the spatial distribution of carbon emissions coincides with that of the burned area: SHAF, NHAF, and SHSA are the major fire emission regions and they contribute to 65.4 % of the total emission in both GFED4s and SSiB4/TRIFFID-Fire (Fig. 8a).