Nonparametric multivariate analysis of variance for affecting factors on the extent of forest fire damage in Jilin Province, China

Abstract

Forest fires are influenced by several factors, including forest location, species type, age and density, date of fire occurrence, temperatures, and wind speeds, among others. This study investigates the quantitative effects of these factors on the degree of forest fire disaster using nonparametric statistical methods to provide a theoretical basis and data support for forest fire management. Data on forest fire damage from 1969 to 2013 was analyzed. The results indicate that different forest locations and types, fire occurrence dates, temperatures, and wind speeds were statistically significant. The eastern regions of the study area experienced the highest fire occurrence, accounting for 85.0% of the total number of fires as well as the largest average forested area burned. April, May, and October had more frequent fires than other months, accounting for 78.9%, while September had the most extensive forested area burned (63.08 ha) and burnt area (106.34 ha). Hardwood mixed forest and oak forest had more frequent fires, accounting for 31.9% and 26.0%, respectively. Hardwood-conifer mixed forest had the most forested area burned (50.18 ha) and burnt area (65.09 ha). Temperatures, wind speeds, and their interaction had significant impacts on forested area burned and area burnt.

Keywords

Jilin Province / Brown–Forsythe method / Scheirer–Ray–Hare method / Impact factors / Forest fire damage

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