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Using a prescribed fire to test custom and standard fuel models for fire behaviour prediction in a non-native, grass-invaded tropical dry shrublandAuthor(s): Andrew D. Pierce; Sierra McDaniel; Mark Wasser; Alison Ainsworth; Creighton M. Litton; Christian P. Giardina; Susan Cordell; Ralf Ohlemuller
Source: Applied Vegetation Science. 17(4): 700-710
Publication Series: Scientific Journal (JRNL)
Station: Pacific Southwest Research Station
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DescriptionQuestions: Do fuel models developed for North American fuel types accurately represent fuel beds found in grass-invaded tropical shrublands? Do standard or custom fuel models for firebehavior models with in situ or RAWS measured fuel moistures affect the accuracy of predicted fire behavior in grass-invaded tropical shrublands? Location: Hawai’i Volcanoes National Park, Island of Hawai’i, Hawai’i, USA. Methods: Fuel loads of coarse woody debris, live herbaceous and live woody fuel loads were quantified with Brown’s transects and biomass sampling to create a custom fuel model for nonnative grass invaded shrublands in Hawai’i. In situ fuel moistures were quantified using oven dried vegetation samples, and compared to Remote Automated Weather Station (RAWS) generated fuel moistures. Fire behavior was recorded on a stationary video camera and used to quantify flame length (FL) and rate of spread (ROS). Observed fire behavior was compared to BehavePlus predicted fire behavior parameterized with both standard and customized fuel models, and in situ and RAWS-based estimates of fuel moisture. Results: The custom fuel model and measured fuel moistures performed better than most standard models, but over-predicted actual ROS and FL by 29% and 26%, respectively. The best match between observed and modeled fire behavior came from a standard fuel model for shrublands with a grassy matrix (23% under-prediction for ROS and 9% under-prediction for FL) using measured fuel moistures. Using fuel moistures and wind speeds from the nearest RAWS station (5 km from the fire) decreased prediction accuracy of the custom fuel model and increased its relative error to 71% over-prediction of ROS and 45% over-prediction of FL. Conclusions: Fire behavior in at least some tropical fuel beds can be accurately modeled by certain standard or custom fuel models, but standard fuel models should not be applied uncritically to systems outside of North America, as our comparison showed 38 widely ranging accuracy across six standard models. In addition, the current reliance on RAWS data for meteorological inputs to predict fire behavior in the tropics, especially in the U.S. affiliated tropical Pacific, must be used with caution, and field-measured fuel moistures should be preferred.
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CitationPierce, Andrew D.; McDaniel, Sierra; Wasser, Mark; Ainsworth, Alison; Litton, Creighton M.; Giardina, Christian P.; Cordell, Susan; Ohlemuller, Ralf. 2014. Using a prescribed fire to test custom and standard fuel models for fire behaviour prediction in a non-native, grass-invaded tropical dry shrubland. Applied Vegetation Science. 17(4): 700-710.
KeywordsFire behavior, BehavePlus, flame length, rate of spread, Hawai‘i Volcanoes National Park, video analysis, fuel model, invasive grasses
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