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A cellular necrosis process model for estimating conifer crown scorch

Author

Listed:
  • Fuller, Kate J.
  • Kobziar, Leda N.
  • Linn, Rodman R.
  • Hood, Sharon M.

Abstract

Fire-caused tree mortality has major impacts on forest ecosystems. One primary cause of post-fire tree mortality in non-resprouting species is crown scorch, the percentage of foliage in a crown that is killed by heat. Despite its importance, the heat required to kill foliage is not well-understood. We used the “lag” model to describe time- and temperature-dependent leaf cell necrosis as a method of predicting leaf scorch. The lag model includes two rate parameters that describe 1) the process of cells accumulating non-lethal damage, and 2) damage becoming lethal to the cell. To parameterize models, we used a water bath to apply heat to newly expanded and one-year-old spring and autumn needles of Pinus ponderosa (ponderosa pine) and Pseudotsuga menziesii (Douglas-fir) at five temperatures (45, 50, 55, 60, and 65 °C), for 2 s to 2 h and 50 min. Electrolyte leakage measurements were used as indicators of percent cell survival. We fit the lag model to resulting survival curves and developed models of leaf scorch that can be applied across a range of temperatures and under fluctuating temperatures. Newly expanded foliage in spring was the most heat sensitive for both species examined. P. menziesii foliage sampled in spring was significantly more heat sensitive than foliage sampled in autumn, regardless of needle age. These findings indicate the importance of species, season, and age of foliage for crown scorch estimation. The models and methodologies developed in this study are directly applicable to fire effects models to improve precision of crown scorch estimates.

Suggested Citation

  • Fuller, Kate J. & Kobziar, Leda N. & Linn, Rodman R. & Hood, Sharon M., 2025. "A cellular necrosis process model for estimating conifer crown scorch," Ecological Modelling, Elsevier, vol. 507(C).
  • Handle: RePEc:eee:ecomod:v:507:y:2025:i:c:s0304380025001772
    DOI: 10.1016/j.ecolmodel.2025.111192
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