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A novel approach to fuel biomass sampling for 3D fuel characterization
Surface fuels are the critical link between structure and function in frequently burned pine ecosystems, which are found globally (Williamson and Black, 1981; Rebertus et al., 1989; Glitzenstein et al., 1995) [[1], [2], [3]]. We bring fuels to the forefront of fire ecology through the concept of the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6313825/ https://www.ncbi.nlm.nih.gov/pubmed/30622922 http://dx.doi.org/10.1016/j.mex.2018.11.006 |
Sumario: | Surface fuels are the critical link between structure and function in frequently burned pine ecosystems, which are found globally (Williamson and Black, 1981; Rebertus et al., 1989; Glitzenstein et al., 1995) [[1], [2], [3]]. We bring fuels to the forefront of fire ecology through the concept of the Ecology of Fuels (Hiers et al. 2009) [4]. This concept describes a cyclic process between fuels, fire behavior, and fire effects, which ultimately affect future fuel distribution (Mitchell et al. 2009) [5]. Low-intensity surface fires are driven by the variability in fine-scale (sub-m level) fuels (Loudermilk et al. 2012) [6]. Traditional fuel measurement approaches do not capture this variability because they are over-generalized, and do not consider the fine-scale architecture of interwoven fuel types. Here, we introduce a new approach, the “3D fuels sampling protocol” that measures fuel biomass at the scale and dimensions useful for characterizing heterogeneous fuels found in low-intensity surface fire regimes. • Traditional fuel measurements are oversimplified, prone to sampling bias, and unrealistic for relating to fire behavior (Van Wagner, 1968; Hardy et al., 2008) [7,8]. • We developed a novel field sampling approach to measuring 3D fuels using an adjustable rectangular prism sampling frame. This voxel sampling protocol records fuel biomass, occupied volume, and fuel types at multiple scales. • This method is scalable and versatile across ecosystems, and reduces sampling bias by eliminating the need for ocular estimations. |
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