Models for predicting fire ignition probability in graminoids from boreo–temperate moorland ecosystems
Victor M. Santana A B C and Rob H. Marrs AA School of Environmental Sciences, University of Liverpool, Liverpool L69 3GP, UK.
B Present address: Department of Plant Biology, Faculty of Biology, University of Barcelona, avinguda Diagonal, 643, 08028 Barcelona, Spain.
C Corresponding author. Email: vm.santana@ua.es
International Journal of Wildland Fire 25(6) 679-684 https://doi.org/10.1071/WF15126
Submitted: 15 July 2015 Accepted: 23 February 2016 Published: 23 May 2016
Abstract
An increase in both the frequency and severity of wildfires in boreo–temperate ecosystems is predicted. Therefore, to develop efficient fire rating systems, the relationship between the fuel moisture content (FMC) of vegetation and ignition thresholds needs to be determined. We developed fire ignition probability models for three graminoid species collected in central England, but common in boreo–temperate ecosystems (Eriophorum angustifolium, E. vaginatum and Molinia caerulea). Specifically, we assessed through laboratory experiments (1) seasonal differences between early spring and late summer in fuel traits such as height, fuel load, fuel bulk density and dead fuel load proportion, and (2) the role of these fuel traits, environmental conditions and dead FMC in determining the probability of ignition. There were seasonal differences in fuel traits among species, with an increase in dead fuel load proportion after winter. The dead FMC was the only variable determining initial sustained ignitions. However, the seasonal differences in dead fuel were not sufficient to affect the FMC threshold at which graminoids start to ignite. Graminoids begin to ignite at high levels of dead FMC, and there are differences between species (from 36.1% to 48.1%). This work assists in improving fire ignition predictions in graminoid-dominated ecosystems by providing warnings based on critical moisture thresholds.
Additional keywords: dead fuel, flammability, fuel moisture content, seasonal variation, wildfire.
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