First steps towards a dynamical model for forest fire behaviour in Argentinian landscapes

Denham, Mónica Malén; Laneri, Karina; Zimmerman, Viviana; Waidelich, Sigfrido

doi:10.24215/16666038.20.e09

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…Finally, predictions from re spread models may help during the suppression process. This study points out directions to improve the performance of re spread models recently developed in the region (Morales et al 2015;Laneri et al 2020), by including variables such as elevation, NDVI and vegetation type.…”

Section: Spatial Patterns: Re Activity As a Function Of Biophysical A...mentioning

confidence: 99%

Disentangling the effects of vegetation and physical drivers on fire

Barberá,

Cingolani,

Tiribelli

et al. 2024

Preprint

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Background Understanding the drivers of fire is frequently challenging because some of them interact and influence each other. In particular, vegetation type is a strong control of fire activity, but at the same time it responds to physical and human factors that also affect fire, so their effects are often confounded. We developed a 30 m resolution record of fire for north-western Patagonia spanning 24 years (July 1998-June 2022), and present an updated description of fire patterns and drivers. We analysed interannual variation in fire activity in relation to interannual climatic variation, and assessed how topography, precipitation, and human factors determine spatial patterns of fire either directly or by affecting the distribution of vegetation types along physical and human-influence gradients.Results We mapped 234 fires ≥ 10 ha that occurred between 1999 and 2022, which burned 5.77% of the burnable area. Both the annual burned area and the number of fires increased in warm and dry years. Spatially, burn probability decreased with elevation and increased with slope steepness, irrespective of vegetation type. Precipitation decreased burn probability, but this effect was evident only across vegetation types, not within them. Controlling for physical drivers, wet forests showed the lowest burn probability, and shrublands, the highest.Conclusions Interannual climatic variation strongly controls fire activity in north-western Patagonia, which is higher in warmer and drier years. The climatic effect is also evident across space, with fire occurring mostly in areas of low elevation (high temperature) and low to intermediate precipitation. Spatially, the effect of topography on fire activity results from how it affects fuel conditions, and not from its effect on the distribution of vegetation types. Conversely, the effect of precipitation resulted mostly from the occurrence of vegetation types with contrasting fuel properties along the precipitation gradient: vegetation types with higher fine fuel amount and continuity and intrinsically lower fuel moisture occurred at low and intermediate precipitation. By quantifying the variation in burn probability among vegetation types while controlling for physical factors, we identified which vegetation types are intrinsically more or less flammable. This may contribute to generate fuel management guidelines.

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Section: Spatial Patterns: Re Activity As a Function Of Biophysical A...mentioning

confidence: 99%

Disentangling the effects of vegetation and physical drivers on fire

Barberá,

Cingolani,

Tiribelli

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…We included two mathematical models for fire propagation that the user can select within the SIP menu: the statistical model explained in previous works (Morales, Mermoz, Gowda and Kitzberger (2015); Denham and Laneri (2018)) and the Reaction-Diffusion-Convection (RDC) model, presented in (Laneri, Waidelich, Zimmerman and Denham (2020)). If the model is changed, the fire restarts from the initial ignition point and the simulation starts using the selected model.…”

Section: Mathematical Models For Fire Progress Simulationmentioning

confidence: 99%