Forest Structure Drives Fuel Moisture Response across Alternative Forest States

• Published in: Fire (Basel, Switzerland) Switzerland), 2021-09, Vol.4 (3), p.48
• Main Authors: Brown, Tegan P., Inbar, Assaf, Duff, Thomas J., Burton, Jamie, Noske, Philip J., Lane, Patrick N. J., Sheridan, Gary J.
• Format: Article
• Language: English
• Subjects: alternative state; Automation; Autoregressive models; Availability; Buffers; Climate change; Climate effects; Climate models; Conversion; Ecosystems; Equilibrium; Estimation; Eucalyptus regnans; feedbacks; fire; Flammability; Forest fires; Forests; Fuels; Global warming; Lidar; Light penetration; Microclimate; Moisture content; obligate seeder; Rain; Vegetation; Water content; Weather; Weather stations
• ISSN: 2571-6255; 2571-6255
• DOI: 10.3390/fire4030048

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.