Understanding and modelling wildfire regimes: an ecological perspective

Abstract

Recent extreme wildfire seasons in several regions have been associated with exceptionally hot, dry conditions, made more probable by climate change. Much research has focused on extreme fire weather and its drivers, but natural wildfire regimes—and their interactions with human activities—are far from being comprehensively understood. There is a lack of clarity about the ‘causes’ of wildfire, and about how ecosystems could be managed for the co-existence of wildfire and people. We present evidence supporting an ecosystem-centred framework for improved understanding and modelling of wildfire. Wildfire has a long geological history and is a pervasive natural process in contemporary plant communities. In some biomes, wildfire would be more frequent without human settlement; in others they would be unchanged or less frequent. A world without fire would have greater forest cover, especially in present-day savannas. Many species would be missing, because fire regimes have co-evolved with plant traits that resist, adapt to or promote wildfire. Certain plant traits are favoured by different fire frequencies, and may be missing in ecosystems that are normally fire-free. For example, post-fire resprouting is more common among woody plants in high-frequency fire regimes than where fire is infrequent. The impact of habitat fragmentation on wildfire crucially depends on whether the ecosystem is fire-adapted. In normally fire-free ecosystems, fragmentation facilitates wildfire starts and is detrimental to biodiversity. In fire-adapted ecosystems, fragmentation inhibits fires from spreading and fire suppression is detrimental to biodiversity. This interpretation explains observed, counterintuitive patterns of spatial correlation between wildfire and potential ignition sources. Lightning correlates positively with burnt area only in open ecosystems with frequent fire. Human population correlates positively with burnt area only in densely forested regions. Models for vegetation-fire interactions must be informed by insights from fire ecology to make credible future projections in a changing climate.

Global and Regional Trends and Drivers of Fire Under Climate Change

“…On evolutionary timescales, climate and fire have shaped the biogeographical distribution of ecoregions, and the vegetation of different ecoregions bears various traits and employs survival strategies that influence the flammability of the landscape (Archibald et al., 2013; Bond & Keeley, 2005; Bowman et al., 2009; Harrison et al., 2021; He et al., 2019; Pausas & Ribeiro, 2013; Pausas et al., 2017; Rogers et al., 2015). Meanwhile, variability in weather on interannual and sub‐decadal timescales influences vegetation productivity and moisture levels on shorter timescales, thus determining the availability and dryness of fuels during any particular fire season (Alvarado et al., 2020; Forkel et al., 2017; Kelley et al., 2019; Y. Chen et al., 2017).…”

“…Climate and its variability have fundamentally influenced the global biogeography of forests, savannahs, shrublands, and grasslands and the species traits of vegetation, and fire has also interacted with climate to influence vegetation in many parts of the world (Bond & Keeley, 2005; Bowman et al., 2009; Harrison et al., 2021; Pausas & Keeley, 2009; Pausas et al., 2017; Whitlock et al., 2010). Annual BA peaks globally at around 10%–30% tree cover, where fires typically return every 10–30 years, and falls with tree cover (Archibald et al., 2009; Andela et al., 2017); at 60%–80% tree cover, fires typically return on the timescale of hundreds of years.…”

Impact of the extinct megaherbivore Steller’s sea cow (Hydrodamalis gigas) on kelp forest resilience

“…For example, wildfires in western North America that have been growing in frequency, intensity and multi-seasonality, are being increasingly addressed with management techniques that intervene directly in forest composition and dynamics, such as tree thinning and prescribed burns [57]. Those techniques in turn are informed by ecological models [58], field experimentation [59], as well as deep Indigenous histories of active landscape management [60, 61]. Similar interventions are largely absent from marine systems, with efforts focused instead on species conservation and restoration via managed harvesting and marine protected areas.…”

Assessing the predictive efficacy of six machine learning algorithms for the susceptibility of Indian forests to fire

“…Fires in tropical and temperate deciduous forests are detrimental, as these forest landscapes are not adapted to regular or intense burning, this therefore adversely impacting their ecological and commercial value (Juárez-Orozco et al 2017;Harrison et al 2021). Large-scale and intense fires have not been part of natural disturbances of tropical rainforests.…”

“…Large-scale and intense fires have not been part of natural disturbances of tropical rainforests. However, their intensity and severity in recent decades (Herawati and Santoso 2011), mainly owing to warm and dry conditions associated with changing climate have significantly increased (Harrison et al 2021). According to the FAO (2020), forest fires are one of the leading drivers of forest degradation each year.…”