Quantile Regression Analysis of the Modifying Industrial Operations Protocol’s Impact on Forestry Fire Incremental Growth

Abstract

Abstract Governmental legislation, regulations, and policies are used to prevent and mitigate the negative impact of human-caused wildland fires. In Ontario, Canada, the Modifying Industrial Operations Protocol (MIOP) aims to manage and limit the risk associated with fires ignited because of industrial forestry operations while maintaining flexibility in terms of daily restrictions. The MIOP was enacted in Ontario in 2008, when it replaced the Woods Modifications Guidelines, which had been in effect since 1989. We use quantile regression to quantify how the distribution of incremental growth has changed when contrasting three prevention time periods (MIOP, Woods Guidelines, Pre-Woods) while controlling for several possible confounding variables that drive fire growth. We analyze data of industrial forestry-caused wildland fires ignited on Crown forest land in Ontario from 1976 to 2019. This type of retrospective analysis is important for monitoring the performance of Ontario’s prevention and mitigation efforts and providing insight for the future, especially in a changing environment. Our findings provide evidence of MIOP succeeding at its goal of mitigating the negative impact of ignited industrial forestry fires when compared against previous regulations.