Remote Sensing (Jul 2016)

Spectral Indices Accurately Quantify Changes in Seedling Physiology Following Fire: Towards Mechanistic Assessments of Post-Fire Carbon Cycling

  • Aaron M. Sparks,
  • Crystal A. Kolden,
  • Alan F. Talhelm,
  • Alistair M.S. Smith,
  • Kent G. Apostol,
  • Daniel M. Johnson,
  • Luigi Boschetti

DOI
https://doi.org/10.3390/rs8070572
Journal volume & issue
Vol. 8, no. 7
p. 572

Abstract

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Fire activity, in terms of intensity, frequency, and total area burned, is expected to increase with a changing climate. A challenge for landscape-level assessment of fire effects, often termed burn severity, is that current remote sensing assessments provide very little information regarding tree/vegetation physiological performance and recovery, limiting our understanding of fire effects on ecosystem services such as carbon storage/cycling. In this paper, we evaluated whether spectral indices common in vegetation stress and burn severity assessments could accurately quantify post-fire physiological performance (indicated by net photosynthesis and crown scorch) of two seedling species, Larix occidentalis and Pinus contorta. Seedlings were subjected to increasing fire radiative energy density (FRED) doses through a series of controlled laboratory surface fires. Mortality, physiology, and spectral reflectance were assessed for a month following the fires, and then again at one year post-fire. The differenced Normalized Difference Vegetation Index (dNDVI) spectral index outperformed other spectral indices used for vegetation stress and burn severity characterization in regard to leaf net photosynthesis quantification, indicating that landscape-level quantification of tree physiology may be possible. Additionally, the survival of the majority of seedlings in the low and moderate FRED doses indicates that fire-induced mortality is more complex than the currently accepted binary scenario, where trees survive with no impacts below a certain temperature and duration threshold, and mortality occurs above the threshold.

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