Abstract

Warmer and drier conditions in temperate regions are increasing the length of the wildfire season. Given the greater fire frequency and extent of burned areas under climate warming, greater focus has been placed on predicting post-fire tree mortality as a crucial component of sustainable forest management. This study evaluates the potential of logistic regression models to predict post-fire tree mortality in Korean red pine (Pinus densiflora) stands, and we propose novel means of evaluating bark injury. In the Samcheok region of Korea, we measured topography (elevation, slope, and aspect), tree characteristics (tree/crown height and diameter at breast height (DBH)), and bark injuries (bark scorch height/proportion/index) at three sites subjected to a surface fire. We determined tree status (dead or live) over three years after the initial fire. The bark scorch index (BSI) produced the best univariate model, and by combining this index with the DBH produced the highest predictive capacity in multiple logistic regression models. A three-variable model (BSI, DBH, and slope) enhanced this predictive capacity to 87%. Our logistic regression analysis accurately predicted tree mortality three years post fire. Our three-variable model provides a useful and convenient decision-making tool for land managers to optimize salvage harvesting of post-fire stands.

Keywords

bark scorch index (BSI); forest ecosystems; natural disturbances; sustainable management; tree mortality; logistic regression; Pinus densiflora; wildfire

Published in

Sustainability
2021, Volume: 13, number: 2, article number: 569
Publisher: MDPI

SLU Authors

• Montoro Girona, Miguel

  • Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences
    
  • University of Quebec Montreal (UQAM)
  • Université du Québec en Abitibi-Témiscamingue (UQAT)

Sustainable Development Goals

Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss


UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.3390/su13020569

Permanent link to this page (URI)

https://res.slu.se/id/publ/110663