Data from: Scaling up flammability from individual leaves to fuel beds
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https://datadryad.org/dataset/doi:10.5061/dryad.3kk70
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资源简介:
Wildfires play an important role in vegetation composition and structure,
nutrient fluxes, human health and wealth, and are interlinked with climate
change. Plants have an influence on wildfire behaviour and predicting this
feedback is a high research priority. For upscaling from leaf traits to
wildfire behaviour we need to know if the same leaf traits are important
for the flammability of (i) individual leaves, and (ii) multiple leaves
packed in fuel beds. Based on a conceptual framework, we hypothesised that
fuel packing properties, through airflow limitation, would overrule the
effects of individual leaf morphology and chemistry. To test this
hypothesis we compared the results of two experiments, respectively
addressing individual leaf flammability and monospecific fuel bed
flammability of 25 perennial species from eastern Australia. Across
species, fuel bed packing ratio and bulk density scaled negatively with
fire spread and positively with maximum temperature and burning time.
Species with “curlier” leaves, higher specific leaf area, lower tannin
concentrations and lower tissue density promoted faster fire spread
through fuel beds. We found that species with shorter individual leaf
ignition times had a faster fire spread, shorter burning times and lower
temperatures in fuel beds. Leaf traits that affect the flammability of
individual leaves (e.g. specific leaf area), continue to do so even when
packed in fuel beds. While previous studies have focused on either
flammability of individual plant particles or fire behaviour in fuel beds,
this is the first time that an overarching combination of the two
approaches was made for a wide range of species. Our findings provide a
better understanding of fuel bed flammability based on interspecific
variation in morphological and some chemical leaf traits. This can be a
first step in linking leaf traits to fire behaviour in the field.
提供机构:
Dryad
创建时间:
2017-04-02



