Biophysical modelling of risks and feedbacks from forest fires: the role of plant traits

Climatic and demographic changes across the globe are altering the wildfire environment, with significant implications for carbon, water and nutrient cycles. This emphasises the need to more completely understand fire and its drivers, however, recent work has identified a number of fundamental controls and dynamics that play little or no role in traditional models. In some cases, these even run counter to model expectations. Changes in live plant moisture for example can limit or facilitate landscape-scale fire [1], and widespread forested areas long believed to increase in flammability due to fuel accumulation have been found to be least flammable in their long-unburnt states [2] . At a finer scale, explanations for the flammability of plant parts have been found from traits such as specific leaf area [3], dimensions [4], curliness and chemistry [5] . These findings have prompted the growing recognition that simple biomass accumulation is a poor explanation of ecosystem flammability, and that an adequate model must properly account for the various roles of plant traits [6]. Even in the simplest arrangements however, trait effects are not additive [7], and scaling from leaf to plant flammability is highly complex [8]. The Forest Flammability Model [9] provides a biophysical, mechanistic approach to modelling this complex system. The flammability of leaves is modelled in its separate components of ignitability, combustibility and sustainability, then scaled upward by calculating the ignition of new leaves from the flames produced by leaves that are already burning. By explicitly finding the effect of individual plant traits, changes in these traits such as those caused by altered atmospheric CO2 levels or phenological variation can be integrated into predictions of future fire. All sub-models of trait effects or physical processes can be updated and replaced by new research as it arises.Validation across diverse eucalypt communities and wildfire conditions found that the model explained 80% of the variability in flame heights when all plant traits were considered, but only 11% when surface fuel loads were the sole representation of forest flammability. Positive fire-flammability feedbacks in one forest community were also explained using trends in post-fire plant growth and species’ succession [10]. Due to the modelling process, flames are calculated dynamically, and the areas of burning vegetation are explicitly located within the forest profile along with the resulting flames, on a second-by-second basis. The large body of heating information that this produces is currently being constructed into a risk model for wildlife, including habitat effects such as fire severity and soil heating. Historically, fire ecology has focused on the effects of fire on flora and fauna. This body of work extends that field to quantify the full feedback, by providing a platform to integrate work on plant traits and ecosystem dynamics and thereby find the ways in which flora and fauna in turn affect the fire regimes of a forest. REFERENCES: 1. Nolan R.H., Boer M.M., Resco de Dios V., Caccamo G., Bradstock R.A. 2016. Large scale, dynamic transformations in fuel moisture drive wildfire activity across south-eastern Australia. Geophys Res Lett. 43, 4229–4238. 2. Zylstra P. 2018. Flammability dynamics in the Australian Alps. Austral Ecol. doi:10.1111/aec.12594 3. Grootemaat S., Wright I.J., van Bodegom P.M., Cornelissen J.H.C., Cornwell W.K. 2015. Burn or rot: leaf traits explain why flammability and decomposability are decoupled across species. Funct Ecol. 29, 1486-1497. 4. Cornwell W.K. , Elvira A., van Kempen L., van Logtestijn R.S. P. , Aptroot A., Cornelissen J.H.C. 2015. Flammability across the gymnosperm phylogeny: the importance of litter particle size. New Phytol. 206, 672–681. 5. Cornelissen J.H.C., Grootemaat S., Verheijen L.M., Cornwell W.K., van Bodegom P.M., van der Wal R., et al. 2017. Are litter decomposition and fire linked through plant species traits? New Phytol. 216, 653–669. 6. Archibald S., Lehmann C.E. R., Belcher C.M., Bond W.J., Bradstock R.A. , Daniau A., et al. 2018. Biological and geophysical feedbacks with fire in the Earth system. Environ Res Lett. 13, 033003. 7. de Magalhães R.M.Q., Schwilk D.W. 2012. Leaf traits and litter flammability: evidence for non-additive mixture effects in a temperate forest. J Ecol. 100, 1153–1163. 8. Pérez-Harguindeguy N., Díaz S., Garnier E., Lavorel S., Poorter H., Jaureguiberry P., et al. 2013. New handbook for standardised measurement of plant functional traits worldwide. Aust J Bot.61, 167–234. 9. Zylstra P., Bradstock R.A. , Bedward M., Penman T.D., Doherty M.D., Weber R.O., Gill, A.M., Cary, G.J. 2016. Biophysical mechanistic modelling quantifies the effects of plant traits on fire severity: species, not surface fuel loads determine flame dimensions in eucalypt forests. PLoS One.11: e0160715. 10. Zylstra P. 2013. The historical influence of fire on the flammability of subalpine Snowgum forest and woodland. Vic Nat.130, 232–239.