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. Live fuel moisture content (LFMC) plays a critical role inwildfire dynamics, but little is known about responses of LFMC tomultivariate climate change, e.g., warming temperature, CO2fertilization, and altered precipitation patterns, leading to a limitedprediction ability of future wildfire risks. Here, we use a hydrodynamicdemographic vegetation model to estimate LFMC dynamics of chaparral shrubs,a dominant vegetation type in fire-prone southern California. Weparameterize the model based on observed shrub allometry and hydraulictraits and evaluate the model's accuracy through comparisons betweenobserved and simulated LFMC of three plant functional types (PFTs) undercurrent climate conditions. Moreover, we estimate the number of days peryear of LFMC below 79 % (which is a critical threshold for wildfire dangerrating of southern California chaparral shrubs) from 1960 to 2099 for eachPFT and compare the number of days below the threshold for medium and highgreenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climatechange could lead to more days per year (5.2 %–14.8 % increase) with LFMCbelow 79 % between the historical (1960–1999) and future (2080–2099)periods, implying an increase in wildfire danger for chaparral shrubs insouthern California. Under the high greenhouse gas emission scenario duringthe dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1 %–18.6 % reduction in LFMC. Lower precipitation in the spring leads to a 6.3 %–8.1 % reduction in LFMC. Thecombined impacts of warming and precipitation change on fire season lengthare equal to the additive impacts of warming and precipitation changeindividually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5 %–4.8 % increase in LFMC. Our results suggestthat multivariate climate change could cause a significant net reduction inLFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

Assessing climate change impacts on live fuel moisture and wildfire risk using a hydrodynamic vegetation model