Combining ecophysiology and combustion traits: a pyro-ecophysiological approach to live fuel moisture prediction in common shrubs

Abstract Background Quantifying fuel moisture content accurately is critical for understanding global vegetation flammability. While models representing changes in dead fuel moisture are relatively advanced, the mechanisms driving fluctuations in live fuel moisture content (LFMC) have been difficult to capture. Living plants make up a large proportion of the fuel complex for wildfires, yet linking plant and combustion science to advance our understanding of wildfire risk has, to date, been limiting. Developing mechanistic approaches to link these two disciplines will confer greater understanding and capacity to model landscape fire risk in vegetated areas across the globe. Results Here, we present a mechanistic model that combines ecophysiology and combustion traits to determine LFMC. We evaluate model performance for seasonal fluctuations in LFMC for six shrubs common to the inter-mountain west USA. Finally, we demonstrate how these measurements can be used to parameterize a physics-based coupled fire model (QUIC-fire) and used to assess how shrube seasonal dynamics impact modeled fire behavior and subsequent fuel consumption. We collected 860 foliage samples across 2022 and 2023 to test the performance of the mechanistic model. The model decomposes LFMC into leaf mass area (LMA), relative water content (RWC), surface-area-to-volume ratio (SAV), and the volumetric saturated water holding capacity ( $$\kappa$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> ). We tested ten model variants using combinations of fixed and time-varying inputs to understand model performance using summarized inputs. The best performing model included time-varying LMA and RWC, and seasonally fixed inputs for SAV and $$\kappa$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>κ</mml:mi> </mml:math> ( $$r^2=0.89$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mi>r</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>=</mml:mo> <mml:mn>0.89</mml:mn> </mml:mrow> </mml:math> , MAE = 11.38%) across all shrub species. Physical and chemical model inputs from a single species across a season were then input to QUIC-fire, where fuel consumption changed from 2.37% early in the season (May) to 97.33% toward the end of summer in late August. Conclusions Mechanistic calculations of LFMC from the same physical and chemical variables used to parameterize the physics-based fire model represents a step forward in our capacity to link ecophysiology and combustion science. These linkages will enable us to bridge decades of plant physiology and combustion science using fire models and simulators and it will improve our ability to interpret field measurements of LFMC across plant functional types.