Plant responses to environmental conditions control the moisture content of living fine fuels

Anne Griebel, Matthias M. Boer, Chris Blackman, Brendan Choat, David S. Ellsworth, Paul Madden, Belinda Medlyn, V´ıctor Resco de Dios, Agnieszka Wujeska-Klause, Marta Yebra, Nicolas Younes Cardenas, Rachael H. Nolan

This is a plain language summary of a Functional Ecology research article which can be found here.

The moisture content of living tissues is an important predictor of the occurrence of wildfires as it affects the flammability of vegetation. Fine fuels contribute most to fire ignition and rate of spread, and the moisture content of living fine fuels (LFMC) is determined by the plant’s access to and loss of water. Since plants respond dynamically to changes in environmental conditions, it remains challenging to predict LFMC, particularly when plants are water stressed by severe water limitations during drought.

A dry sclerophyll eucalypt forest during a prescribed fuel reduction burn (credit: Marta Yebra)

We closely monitored LFMC, environmental conditions and a range of plant water-use and leaf traits at the Eucalyptus Free-Air CO2 enrichment (EucFACE) facility in Sydney, Australia. A drought provided an opportunity to assess the interaction of water stress and atmospheric CO2 concentrations on LFMC and associated plant water-use and leaf traits. We then derived a biophysical model to predict LFMC dynamics, which outperformed established approaches to predict LFMC based on satellite models or on established relationships with plant traits alone. Specific leaf area (the ratio of leaf area to leaf mass) was the most important variable to predict instantaneous LFMC, followed by vapour pressure deficit (a measure of atmospheric demand for water). CO2 concentrations had no significant effect on LFMC or the examined plant traits during the three-year period that included the height of the drought and the immediate recovery from the drought.

Our study demonstrates that the co-variation of plant traits and environmental conditions can introduce significant uncertainty to predictions of LFMC during drought. Yet, we present a way forward for improving temporal and spatial models of LFMC, which opens the door for ecological forecasts of LFMC when combining biophysical and satellite-based models of LFMC with seasonal forecasts of meteorological and hydrological variables.


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