1. Fallen plant material such as leaves, needles and branches form litter beds which strongly influence fire ignition and spread. Traits of the dominant species influence litter flammability directly by determining how individual leaves burn and indirectly through the structure of the litter bed. However, we are yet to determine the relative importance of these different drivers across a range of plant species from different biomes. 2. We undertook a meta-analysis, combining leaf trait, litter structure and flammability data for 106 species from North America, South America, Europe, Asia and Australia. The dataset encompassed broad-leaved and coniferous species from seven different experimental studies. Relationships between leaf traits, litter structure and key flammability metrics-sustainability, combustibility and consumability-were analysed using bivariate and piecewise structural equation modelling (SEM). 3. Traits which characterise the three-dimensional nature of the leaf and how much space a leaf occupies showed much stronger associations to litter structure and flammability than other morphological traits. Leaf curl, surface area to volume ratio (SAV) and SLA predominately influence litter flammability indirectly via litter structure with SLA being the only leaf trait which had a negative direct effect on flame duration. Packing ratio and bulk density were influenced by different combinations of leaf traits and, in turn, they aligned with different flammability metrics. Bulk density predicted flame spread rate and flame duration whereas packing ratio predicted consumption. 4. Synthesis. We identified key leaf and litter traits which influence different components of litter bed flammability. Importantly, we show that the effects of these leaf and litter traits are consistent across a wide range of taxa and biomes. Our study represents a significant step towards developing trait-based models for predicting surface wildfire behaviour. Such models will more flexibly accommodate future shifts in the composition of plant species triggered by altered fire regimes and climate change.

High frequency wildfires can shift the structure and composition of obligate seeder forests and initiate replacement with alternative vegetation states. In some forests, the alternative stable state is drier and more easily burned by subsequent fires, driving a positive feedback that promotes further wildfire and perpetuates alternative stable states. Mountain Ash (Eucalyptus regnans (F.Muell.)) forests are highly valued for their biodiversity, water, timber and carbon. Fires are a natural part of the lifecycle of these forests, but too frequent fires can eliminate Mountain Ash and trigger a transition to lower stature, non-eucalypt forests which are dominated by understorey species. This study sought to better understand the fuel moisture dynamics of alternative stable states resulting from high frequency wildfires. A vegetation mosaic in the Central Highlands, Victoria created a unique opportunity to measure fuel moisture in adjacent forest stands that differed in overstorey species composition and time since fire. Specifically, we measured fuel moisture and microclimate at two eucalypt sites (9 and 79 years old) and three non-eucalypt sites (two 9 year old and one 79 year old). Fuel availability, defined here as the number of days surface fuels were below 16% and dry enough to ignite and sustain fire, was calculated to estimate flammability. Fuel availability differed between sites, particularly as a function of time since fire, with recently burnt sites available to burn more often (4–17 versus 0–3 days). There were differences in fuel availability between non-eucalypt sites of the same age, suggesting that high frequency fire does not always lead to the same vegetation condition or outcome for fuel availability. This indicates there is potential for both positive and negative flammability feedbacks following state transition depending on the composition of the non-eucalypt state. This is the first study to provide empirical insight into the fuel moisture dynamics of alternative stable states in Mountain Ash forests.

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Climate warming is expected to increase fire frequency in many productive obligate seeder forests, where repeated high-intensity fire can initiate stand conversion to alternative states with contrasting structure. These vegetation–fire interactions may modify the direct effects of climate warming on the microclimatic conditions that control dead fuel moisture content (FMC), which regulates fire activity in these high-productivity systems. However, despite the well-established role of forest canopies in buffering microclimate, the interaction of FMC, alternative forest states and their role in vegetation–fire feedbacks remain poorly understood. We tested the hypothesis that FMC dynamics across alternative states would vary to an extent meaningful for fire and that FMC differences would be attributable to forest structural variability, with important implications for fire-vegetation feedbacks. FMC was monitored at seven alternative state forested sites that were similar in all aspects except forest type and structure, and two proximate open-weather stations across the Central Highlands in Victoria, Australia. We developed two generalised additive mixed models (GAMMs) using daily independent and autoregressive (i.e., lagged) input data to test the importance of site properties, including lidar-derived forest structure, in predicting FMC from open weather. There were distinct differences in fuel availability (days when FMC < 16%, dry enough to sustain fire) leading to positive and negative fire–vegetation feedbacks across alternative forest states. Both the independent (r2 = 0.551) and autoregressive (r2 = 0.936) models ably predicted FMC from open weather. However, substantial improvement between models when lagged inputs were included demonstrates nonindependence of the automated fuel sticks at the daily level and that understanding the effects of temporal buffering in wet forests is critical to estimating FMC. We observed significant random effects (an analogue for forest structure effects) in both models (p < 0.001), which correlated with forest density metrics such as light penetration index (LPI). This study demonstrates the importance of forest structure in estimating FMC and that across alternative forest states, differences in fuel availability drive vegetation–fire feedbacks with important implications for forest flammability.

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