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Copyright of Forestry Chronicle is the property of Canadian Institute of Forestry and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We describe the development and implementation of an operational human-caused wildland fire occurrence prediction (FOP) system in the province of Ontario, Canada. A suite of supervised statistical learning models was developed using more than 50 years of high-resolution data over a 73.8 million ha study area, partitioned into Ontario's Northwest and Northeast Fire Management Regions. A stratified modelling approach accounts for different seasonal baselines regionally and for a set of communities in the Far North. Response-dependent sampling and modelling techniques using logistic generalized additive models are used to develop a fine-scale, spatiotemporal FOP system with models that include nonlinear relationships with key predictors. These predictors include inter- and intra-annual temporal trends, spatial trends, ecological variables, fuel moisture measures, human land-use characteristics, and a novel measure of human activity. The system produces fine-scale, spatially explicit maps of daily probabilistic human-caused FOP based on locally observed conditions along with point and interval predictions for the expected number of fires in each region. A simulation-based approach for generating the prediction intervals is described. Daily predictions were made available to fire management practitioners through a custom dashboard and integrated into daily regional planning to support detection and fire suppression preparedness needs. Key words: fire management, forest fire occurrence, person-caused, prediction interval, wildfire occurrence. Nous traitons du developpement et de la mise en oeuvre d'un systeme operationnel de prevision de l'occurrence des feux de foret (POF) d'origine humaine dans la province d'Ontario, au Canada. Une suite de modeles d'apprentissage statistique supervise a ete developpee en utilisant plus de 50 annees de donnees a haute resolution couvrant une aire d'etude de 73,8 millions d'hectares repartis dans les regions de gestion du feu du nord-ouest et du nord-est. Une approche de modelisation stratifiee tient compte a l'echelle regionale de differents niveaux de reference saisonniers et pour un ensemble de communautes de l'extreme nord. Des techniques de modelisation et d'echantillonnage dependantes de la reaction utilisant des modeles logistiques additifs generalises ont servi a elaborer un systeme de POF spatio-temporel a fine echelle avec des modeles qui incluent des relations non lineaires avec des variables predictives cles. Ces variables predictives incluent des tendances temporelles intra-annuelles, des tendances spatiales, des variables ecologiques, des mesures de teneur en humidite des combustibles, des caracteristiques de l'utilisation des terres par l'homme et une nouvelle mesure de l'activite humaine. Le systeme produit des cartes a fine echelle spatialement explicites qui illustrent la probabilite quotidienne de la POF d'origine humaine sur la base des conditions observees localement avec une prevision ponctuelle et un intervalle du nombre attendu de feux dans chaque region. Une approche fondee sur la simulation pour generer les intervalles de prevision est decrite. Les previsions quotidiennes ont ete mises a la disposition des responsables de la gestion du feu par l'entremise d'un tableau de bord personnalise et integrees dans la planification regionale quotidienne en support aux besoins de preparation pour la detection et la suppression des feux. [Traduit par la Redaction] Mots-cles: gestion du feu, occurrence des feux de foret, d'origine humaine, intervalle de prevision, occurrence des feux de vegetation., 1. Introduction 1.1. The need for and importance of fire occurrence prediction (FOP) systems Although the province of Ontario's forest fire management organization dates back as far as 1878 with [...]

Communities interspersed throughout the Canadian wildland are threatened by fires that have become bigger and more frequent in some parts of the country in recent decades. Identifying the fireshed (source area) and pathways from which wildland fire may ignite and spread from the landscape to a community is crucial for risk‐reduction strategy and planning. We used outputs from a fire simulation model, including fire polygons and rate of spread, to map firesheds, fire pathways and corridors and spread distances for 1980 communities in the forested areas of Canada. We found fireshed sizes are larger in the north, where the mean distances between ecumene and fireshed perimeters were greater than 10 km. The Rayleigh Z test indicated that simulated fires around a large proportion of communities show significant directional trends, and these trends are stronger in the Boreal Plains and Shields than in the Rocky Mountain area. The average distance from which fire, when spreading at the maximum simulated rate, could reach the community perimeter was approximately 5, 12 and 18 km in 1, 2 and 3 days, respectively. The average daily spread distances increased latitudinally, from south to north. Spread distances were the shortest in the Pacific Maritime, Atlantic Maritime and Boreal Plains Ecozones, implying lower rates of spread compared to the rest of the country. The fire corridors generated from random ignitions and from ignitions predicted from local fire history differ, indicating that factors other than fuel (e.g. fire weather, ignition pattern) play a significant role in determining the direction that fires burn into a community. [ABSTRACT FROM AUTHOR]

Wildland fire prevention and mitigation is of mutual interest to both government and the forest industry. In 1989, the Ontario Ministry of Natural Resources and Forestry introduced the Woods Modification Guidelines that provided rules on how forestry operations should be modified based on local fire danger conditions. Those guidelines were replaced by the Modifying Industrial Operations Protocol (MIOP) in 2008. One objective of MIOP is to allow forestry operations to be done safely for as long as possible as the fire danger increases. We investigate the impacts of these sets of regulations on the frequency of industrial forestry-caused (IDF) wildland fires in the province of Ontario, Canada. Data from 1976 to 2019 are analyzed. A case-crossover study finds no evidence to suggest that MIOP's greater flexibility in operating hours has increased the probability of IDF fire occurrences. This result indicates that MIOP's regulations have had the desired effect of allowing longer working hours on days with heightened fire risk without adding to the seasonal wildland fire load. [ABSTRACT FROM AUTHOR]

Evidence‐based studies in the environmental sciences frequently rely on the presence of spatially dense climatological data. However, such data are often available only at a fixed set of locations that may be regularly or irregularly arranged across a region. Spatial interpolation enables the approximation of variables of interest at locations between those sites. When conducting interpolation in collaboration with an end user or in interdisciplinary research, mutual knowledge exchange allows for greater insight on what is required of an interpolation method since each may have different pros and cons. We outline and discuss several key considerations one should make in an interpolation study, such as the purpose of the variable and the goals of the end user, including how the variable is used to inform decisions. This process is then illustrated via case study within a wildland fire weather context. For the province of Ontario, Canada, we contrast several methods for interpolating the Fire Weather Index (FWI), comparing them quantitatively via metrics and qualitatively using a proposed categorical gradients visualization scheme. Conditional simulations and a spatial ensemble are also investigated. This work is in collaboration with the Ontario Ministry of Natural Resources and Forestry. [ABSTRACT FROM AUTHOR]