Abstract

Climate change is driving changes in wildfire and vegetation relationships across fine- to broad- scales, compelling a growing scientific need to forecast and manage for shifting ecosystem dynamics. Given the intertwined relationships between fire and vegetation at meso-scales, simulating present and future fire regimes requires an understanding of both fire and succession as processes over space and through time. Landscape-fire-succession (LFS) models are spatially and temporally explicit models that simulate the dynamic interactions between fire and vegetation, often in response to climate. Building on the foundation of prior modelling efforts, recent LFS models have taken advantage of rapid 21st-century computational advances to reflect a maturing scientific environment for simulating fire-vegetation dynamics. In this study, we assess the current state of LFS modelling by identifying available and maintained LFS models and characterizing their approach to simulate fire growth, fuel and vegetation succession, and feedbacks between these processes. We then ask: (i) Do LFS models allow us to use past, current, and future ignitions, weather and climate, and live vegetation and dead fuel variables to robustly simulate fire spread and intensification across space and through time? (ii) Do LFS models enable us to realistically represent the hierarchical nature of fuels and fire behaviour, their variability, and the cross-scale connections between levels in the hierarchy? (iii) Do LFS models produce reasonable predictions of fire behaviour, changes in fire regimes, vegetation responses to fire, and system-level feedbacks for research and management applications? In doing so, we identify five common challenges that constrain applications of LFS modelling to address pressing research and management questions and provide recommendations to enhance the next generation of LFS models.