Linking fire behaviour and its ecological effects to plant traits, using FRaME in R

Abstract

1. Floral fire ecology incorporates a feedback loop in which plants influence fire behaviour and fire behaviour influences the flora. Recent advances in fire behaviour modelling have quantified many plant-based drivers of fire behaviour, but the consequent ecological effects of this have not yet been adequately modelled mechanistically.2. Here, I introduce the Fire Research and Modelling Environment (FRaME) as the open-source R package frame on GitHub. FRaME calculates the influence of plants on fire behaviour using a biophysical, mechanistic model of fire behaviour, building this into complex simulations. From these, it models heat transfer from flames into surrounding surfaces, calculating its ecological effects on plants and soils. I demonstrate the application of the central analysis functions using a detailed case study, in which I validate predictions of fire behaviour and ecological effects, and derive quantitative measures for the efficacy of different management treatments to mitigate fire risk to a vulnerable ecosystem.3. FRaME modelling predicted ecological effects such as the breaking of seed dormancy, scorch and the girdling of different tree strata, consistent with observed effects and providing insights into treatment efficacy that were not captured by existing assumptions. FRaME analyses were able to identify treatments that both increased the likelihood of success in containing fires and minimised fire impacts on a fire-sensitive ecosystem.4. FRaME provides a platform to examine the full role of fire in an ecosystem, from the ways that biota drive flammability to the influence of that flammability on the ecosystem. By mechanistically incorporating the effect of biophysical drivers throughout this feedback, FRaME can provide novel insights and solutions for complex problems, quantify risk and guide effective mitigation measures. The model is extensible, providing a conceptual framework into which emerging work on flammability and fire effects can be incorporated.

Self-thinning forest understoreys reduce wildfire risk, even in a warming climate

“…Consumption of surface litter can promote regeneration following even low severity fire (e.g. figures 1(e) and (f)) by heating soil seed banks (Zylstra 2021). Therefore, cultural burning may promote less regeneration than either prescribed or wildfire.…”

Quantifying the direct fire threat to a critically endangered arboreal marsupial using biophysical, mechanistic modelling

“…FRaME is an extensible fire behaviour and fire effects model available as an R (R Core Team, 2016) package (‘frame’, Zylstra, 2021) that builds complex simulations from a biophysical fire behaviour model to calculate first‐order ecological effects. In this paper, the acronym FRaME is used to refer to the model in general, and the lower‐case name ‘frame’ refers to the R extension that implements the model.…”

“…In this paper, the acronym FRaME is used to refer to the model in general, and the lower‐case name ‘frame’ refers to the R extension that implements the model. Extensive details of FRaME have already been provided for the fire behaviour model at its core (Zylstra et al, 2016), the underlying fire behaviour sub‐models (Zylstra, 2011), and the heat transfer modelling used to calculate first‐order fire effects (Zylstra, 2021). What follows is a brief overview.…”

“…A primary modelling approach used in management (DAWE, 2022) is ‘Byram intensity’ – a value estimated from a theoretical interaction between ‘fuel load’ and the rate of fire spread (Byram, 1959). In this study, I present a development to the Fire Research and Modelling Environment (FRaME, Zylstra et al, 2016, Zylstra, 2021) to calculate first‐order or direct effects of fire on fauna. FRaME explicitly accounts for and quantifies all factors affecting animal survival during fire that were identified by Jolly et al (2022), adding to these an additional factor of refuge quality.…”

A Predictive Model of Leaf Flammability Using Leaf Traits and Radiant Heat Flux for Plants of Fire-Prone Dry Sclerophyll Forest

“…Considering recent large and destructive wildfires across the world, there is an emerging possibility that the wealth of existing global data on these two leaf traits could be used to predict plant leaf flammability. Such predictive capacity would have important ramifications for models that use the traits and flammability of leaves as informative parameters for predicting wildfire behaviour [12,[22][23][24][25].…”