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

Abstract

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.

Spatiotemporal patterns of unburned areas within fire perimeters in the northwestern United States from 1984 to 2014

“…While this approach is widely used and accepted as a proxy for holistic fire effects, the empirical links between spectral indices and biometric measures of fire intensity and effects are still quite limited and lacking robust ecological connections and applications (Lentile et al 2006, Kolden et al 2015b, particularly because there is rarely pre-fire biometric or field data from which to assess relative change. Recent efforts to quantify relationships between fire energy released and physiological tree responses have demonstrated the utility of an alternative framework (Smith et al 2016b, Sparks et al 2016.…”

Reply to referee #1

“…Under controlled experiments on saplings, a toxicological "dose-response" relationship was observed, whereby increasing FRE resulted in decreasing net photosynthesis in surviving Pinus contorta and Larix occidentalis saplings and increased mortality 1 year post-fire . Furthermore, Sparks et al (2017) observed decreasing radial growth in mature Pinus ponderosa 1.5 years post-fire with increasing peak FRP. These findings suggest that there is a strong link between measures of fire intensity and subsequent vegetation productivity and mortality.…”

“…Recent studies have observed that increasing fire radiative energy (FRE: J ) and peak fire radiative power (FRP: W ) incident on trees results in reduced tree growth and increased mortality Sparks et al, , 2017. FRP is the instantaneous radiative flux, which is strongly related to common field-based fire intensity metrics (Kaufman et al, 1996;Kremens et al, 2012;Sparks et al, 2017), and its temporal integral is FRE.…”

“…Recent studies have observed that increasing fire radiative energy (FRE: J ) and peak fire radiative power (FRP: W ) incident on trees results in reduced tree growth and increased mortality Sparks et al, , 2017. FRP is the instantaneous radiative flux, which is strongly related to common field-based fire intensity metrics (Kaufman et al, 1996;Kremens et al, 2012;Sparks et al, 2017), and its temporal integral is FRE. These are two of the most com-monly used metrics to quantify fire intensity from satellite remote sensing products (Andela et al, 2015;Freeborn et al, 2016;Heward et al, 2013;Roberts et al, 2011;Smith and Wooster, 2005).…”

Integrated System for Auto-Registered Hyperspectral and 3D Structure Measurement at the Point Scale

“…The former provides rich spectrum that can reflect the biochemical information of the target and the latter provides detailed geometric information relating to the structural properties of the object. Both of the two techniques have been widely applied in vegetation physiology [3], precision agriculture [4], radiative transfer modeling [5], etc.…”