Determinants of fire intensity in a mesic West Africa savanna: a statistical analysis of fire characteristics
Document Type: Thesis
Author(s): Rebecca L. Jacobs
Publication Year: 2018

Cataloging Information

  • Africa
  • fire intensity
  • fire severity
  • Mali
  • multiple regression analysis
  • savannas
  • season of burn
  • International
Record Maintained By:
Record Last Modified: January 24, 2019
FRAMES Record Number: 57147


A fundamental premise of savanna fire ecology is that late dry season fires burn more intensely than early dry season fires. Late dry season fires are considered a major determinant of savanna woody vegetation as they are thought to be more damaging to trees, thus shaping the grass/tree dynamic of savannas. Most savanna fire experiments have adopted the early/late fire convention in their experimental design, based on the pioneering work of Aubréville. Recent research suggests that numerous factors determine fire intensity, and that the widely accepted dichotomous view of fire intensity as driven by early/late seasonal timing greatly oversimplifies a complex phenomenon. In particular, wind direction may be a significant factor in determining fire intensity. To determine the factors that influence fire intensity, experimental fires were conducted in the mesic savanna of Mali. Data were collected for fire season, biomass consumed, grass type, scorch height, speed of fire front, fire type, and ambient air conditions for each burn. Multiple regression analyses were used to determine the key factors affecting the fire intensity and severity. Results suggest there are fundamental differences in fire behavior and intensity depending on wind direction relative to the fire. Intensity is not explained by any tested variables in head fires. Intensity of back fires is determined primarily by seasonal timing and, to a lesser extent, grass characteristics.

Online Link(s):
Jacobs, Rebecca L. 2018. Determinants of fire intensity in a mesic West Africa savanna: a statistical analysis of fire characteristics. MS Thesis. Long Beach, CA: California State University-Long Beach. 73 p.