Modelling Human-Fire Interactions: Combining Alternative Perspectives and Approaches

Abstract

Although it has long been recognised that human activities affect fire regimes, the interactions between humans and fire are complex, imperfectly understood, constantly evolving, and lacking any kind of integrative global framework. Many different approaches are used to study human-fire interactions, but in general they have arisen in different disciplinary contexts to address highly specific questions. Models of human-fire interactions range from conceptual local models to numerical global models. However, given that each type of model is highly selective about which aspects of human-fire interactions to include, the insights gained from these models are often limited and contradictory, which can make them a poor basis for developing fire-related policy and management practices. Here, we first review different approaches to modelling human-fire interactions and then discuss ways in which these different approaches could be synthesised to provide a more holistic approach to understanding human-fire interactions. We argue that the theory underpinning many types of models was developed using only limited amounts of data and that, in an increasingly data-rich world, it is important to re-examine model assumptions in a more systematic way. All of the models are designed to have practical outcomes but are necessarily simplifications of reality and as a result of differences in focus, scale and complexity, frequently yield radically different assessments of what might happen. We argue that it should be possible to combine the strengths and benefits of different types of model through enchaining the different models, for example from global down to local scales or vice versa. There are also opportunities for explicit coupling of different kinds of model, for example including agent-based representation of human actions in a global fire model. Finally, we stress the need for co-production of models to ensure that the resulting products serve the widest possible community.

Global and Regional Trends and Drivers of Fire Under Climate Change

“…Arguably, the role of humans is the greatest source of complexity in our understanding and model representation of modern fire patterns (Ford et al., 2021). Human relationships with fire are as long as human history itself, and they are also regionally complex due to the diverse regional histories of controlling and using fire (Bowman et al., 2011).…”

“…Much of the unexplained variability in fire‐climate relationships and predictive models stems from the patterns and (un)predictability of human relationships with fire, and how they have diverged over time (Ford et al., 2021). Hence, it is increasingly appreciated that more must be done to represent human‐fire relationships with quantitative variables that have potential to aid diagnostic models of fire activity and to be implemented within predictive models of future fire activity (Bowman et al., 2009; Ford et al., 2021; Forkel et al., 2017; Glikson, 2013; Kelley et al., 2019; Lasslop & Kloster, 2017; Pechony & Shindell, 2009).…”

“…Substantial variability in the relationships between fire and population, agriculture and GDP per capita is seen at fine scales, especially with respect to the balance of ignitions and suppression in regions of low population density (Andela et al., 2017; Archibald et al., 2010; Balch et al., 2017; Knorr et al., 2014; Parisien et al., 2016; Syphard et al., 2009; Vannière et al., 2016). Existing DGVM algorithms typically express human ignition and suppression of fires as a function of population density (Ford et al., 2021; Hantson et al., 2016; Pechony & Shindell, 2009; Teckentrup et al., 2019): ignitions are broadly modeled to increase at low population densities up to a threshold, and reduce thereafter, while suppression is broadly modeled to increase with population density. However, these high‐level indicators of human activity generally fail to capture the spectrum of socioeconomic and cultural factors that influence the relationship between humans, fire, and the landscape (Coughlan, 2015; Coughlan & Petty, 2012).…”

Fragmentation-Driven Divergent Trends in Burned Area in Amazonia and Cerrado

“…Our results show that the Amazonia and the Cerrado biomes exhibit divergent patterns in the relationship between BA fraction, landscape fragmentation, and agricultural fraction which is exacerbated during drought years. Although most of global fire-vegetation models include some consideration of the role of human activity in fire regimes (Rabin et al, 2017), this is one of the components that is treated most simplistically in the current generation of models (Ford et al, 2021) with most including global relationships, e.g., a single relationship between fire and population density applicable to all biomes. This study provides empirical evidence of the biome-specific relationships which will inform the fire-modeling community.…”

Human Fire Use and Management: A Global Database of Anthropogenic Fire Impacts for Modelling

“…More fundamentally, quantitative measures are not usually the way in which Indigenous and traditional communities understand their fire use and management [82]. Rather, researchers have found participatory methods such as fire calendars, fuzzy cognitive maps and rich pictures to be effective in enabling open dialogue with traditional fire practitioners [83]. There is also a clear danger of researcher extractivism, where knowledge is acquired from Indigenous people and integrated into existing power dynamics, with limited benefit to those communities themselves [84].…”