Background Canadian fire managers rely on the value of the Duff Moisture Code (DMC) for estimating lightning ignition and sustained smouldering in ground fuels. A simple rule used widely operationally suggests that lightning does not ignite fires and smouldering is not sustainable until the DMC >20. Aims We examine the strength of evidence supporting this simple rule. Methods We used daily lightning, fire and weather data from 2000 to 2019 to estimate the probability of lightning fire ignition across a number of regions in Canada. We also examined datasets of forest floor consumption from experimental burns carried out in pine forests in Canada. Key results Neither the 20 years of lightning fire ignition data nor the observed forest floor consumption data reveal consistent signals of an ignition threshold at or around DMC = 20. Conclusions and Implications Increasing DMC is associated with increasing probability of ignition from lightning and the extent of forest floor consumption, but there is little to no evidence to support the existence of a meaningful threshold across Canada when DMC is ~20. Users of this simple rule, be it for lightning ignition or fire perimeter extinction, should be aware that the data do not support a meaningful threshold around this value.

Background Suppression effectiveness is often evaluated by measuring the extent to which it slows fire spread and reduces fireline intensity. Although studies have used infrared (IR) imaging methods to explore suppression effectiveness, most do not measure or assess the influence of water application on energy release. Aims This preliminary analysis uses IR imagery to quantify the impact of suppression on fire behaviour and the reduction in energy released from a flaming fire. Methods We conducted a series of small-scale experimental burns representative of pine and grass surface litter in the Canadian boreal forest and suppressed these fires while actively monitoring fire behaviour with overhead IR imagery. We used detailed measurements of fire radiative power to estimate fire radiative energy density, forward rate of spread and fireline intensity. Key results We observed changes in fire behaviour due to suppression, quantified the duration of those reductions and detected a suppression signal through an analysis of radiative energy during the flaming combustion phase. Conclusions IR methodology is able to capture the changes in energy released from a fire due to known aspects of water application. Implications Our findings can inform methodologies for field studies on suppression effectiveness, where ground sampling techniques are impractical but airborne IR methods can be employed.

Background Fire management agencies use the proportion of fires classified as initial attack (IA) success as a suppression performance metric, making IA success a common indicator of suppression effectiveness in research. The criteria and definition for IA success vary based on operational objectives, making comparisons across studies difficult. Aims To examine the sensitivity of different time and size-based IA success definitions on model predictive accuracy and compare different modelling approaches. Methods Using 30 years of historical fire report data from Ontario, Canada (n = 26,171), we developed logistic regression models, bagged classification trees and random forest models to predict IA success for eight different definitions. Model predictive accuracy, sensitivity and specificity were assessed on an independent validation dataset. Key results The eight definitions classified between 79 and 98% of fires as IA successes. There was no clear pattern between model strength across prediction metrics and IA success definition. Logistic regression generally outperformed machine learning methods in classifying IA escapes. Conclusions and implications The definition of IA success does not greatly impact model performance across the modelling techniques used. Models of IA success and suppression-system performance metrics should be set with specific research or operational objectives in mind.

Holdover fires are usually associated with lightning-ignited wildfires (LIWs), which can experience a smoldering phase or go undetected for several hours, days or even weeks before being reported. Since the existence and duration of the smoldering combustion in LIWs is usually unknown, holdover time is conventionally defined as the time between the lightning event that ignited the fire and the time the fire is detected. Therefore, all LIWs have an associated holdover time, which may range from a few minutes to several days. However, we lack a comprehensive understanding of holdover times. Here, we introduce a global database on holdover times of LIWs. We have collected holdover time data from 29 different studies across the world through a literature review and datasets assembled by authors of the original studies. The database is composed of three data files (censored data, non-censored data, ancillary data) and three metadata files (description of database variables, list of references, reproducible examples). Censored data are the core of the database and consist of different frequency distributions reporting the number or relative frequency of LIWs per interval of holdover time. In addition, ancillary data provide further information to understand the methods and contexts in which the data were generated in the original studies. The first version of the database contains 42 frequency distributions of holdover time built with data on more than 152 375 LIWs from 13 countries in five continents covering a time span from 1921 to 2020. This database is the first freely available, harmonized and ready-to-use global source of holdover time data, which may be used in different ways to investigate LIWs and model the holdover phenomenon. The complete database can be downloaded at https://doi.org/10.5281/zenodo.7352172 (Moris et al., 2022).

Wildland fire is an important natural disturbance in many vegetated areas of the world. However, fire management actions are critical not only to prevent and suppress unwanted fires, but also mitigate and recover from the negative impacts of fire on people and communities. Advancements in wildland fire science can help inform these necessary actions in wildland fire management. How science is created and integrated into these fire management decision-making processes, whether through collaborations with external researchers and/or with scientists within a wildland fire management agency itself, requires a conscious understanding of how the science is useful and goes beyond the simple existence of knowledge. This chapter outlines the goal of integrating fire science and management using a conceptual knowledge exchange (KE) framework, informed from existing work on KE. We provide a review of the KE literature relevant to wildland fire management and develop a KE framework for the fire management context. In this context, we address the potential barriers and facilitators throughout this process followed by a discussion of an active learning approach aimed at developing effective data translation skills amongst students in a data analytics consulting course.

Background Among the most successful examples of Knowledge Exchange (KE) between researchers and practitioners in Canadian wildland fire management is the development and integration of the Canadian Forest Fire Danger Rating System (CFFDRS) into operational use. Aims Our aim was to identify key factors for this success. Methods Through a case study, we investigated historical KE of two CFFDRS components in Ontario, Canada. We held semi-structured interviews with principal Canadian Forest Service researchers and Ontario fire management practitioners active in development and implementation of CFFDRS from the late 1960s to 2010s. Key results The importance of both formal and informal facilitators to support KE was emphasised. Conclusion Participants were most likely to associate successful implementation with informal facilitators such as personal relationships, shared field-based experiences, and opportunities for dialogue between researchers and practitioners. Critical to success were the credibility and soft skills of the knowledge brokers, early engagement, and consideration of training needs for end users in the design of products. Implications This identification of factors that facilitated or hindered the development and implementation of CFFDRS can enhance the impact of research that will help wildland fire management deal with its present and future challenges.

This paper is concerned with wildfire hotspot detection.An autonomous unmanned aerial system (UAS) for wildfire hotspot detection missions is presented and implemented on a fixed wing low altitude short endurance (LASE) UAV.The custom built system includes the features such as hotspot detection, real-time localisation and alert of the ground control station.The on-board computer processes fire information collected by the UAV and integrates with flight data to provide a comprehensive and reliable fire detection algorithm.The proof-of-concept system has been successfully tested through flight experiments.

We celebrate the 50th anniversary of the Canadian Journal of Forest Research by reflecting on the considerable progress accomplished in select areas of Canadian wildland fire science over the past half century. Specifically, we discuss key developments and contributions in the creation of the Canadian Forest Fire Danger Rating System; the relationships between wildland fire and weather, climate, and climate change; fire ecology; operational decision support; and wildland fire management. We also discuss the evolution of wildland fire management in Banff National Park as a case study. We conclude by discussing some possible directions in future Canadian wildland fire research including the further evaluation of fire severity measurements and effects; the efficacy of fuel management treatments; climate change effects and mitigation; further refinement of models pertaining to fire risk analysis, fire behaviour, and fire weather; and the integration of forest management and ecological restoration with wildland fire risk reduction. Throughout the paper, we reference many contributions published in the Canadian journal of Forest Research, which has been at the forefront of international wildland fire science.

Wildland fire management decision-makers need to quickly understand large amounts of quantitative information under stressful conditions. Categorization and visualization “schemes” have long been used to help, but how they are done affects the speed and accuracy of interpretation. Using traditional fire management schemes can unduly restrict the design of new products. Our design process for Ontario’s fine-scale, spatially explicit, daily fire occurrence prediction (FOP) models led us to develop guidance for designing new schemes. We show selected historical fire management schemes and describe our method. It includes specifying goals and requirements, exploring design options and making trade-offs. The design options include gradient continuity, hue selection, range completeness and scale linearity. We apply our method to a case study on designing the scheme for Ontario’s FOP models. We arrived at a smooth, nonlinear scale that accommodates data spanning many orders of magnitude. The colouring draws attention according to levels of concern, reveals meaningful spatial patterns and accommodates some colour vision deficiencies. Our method seems simple now but reconciles complex considerations and is useful for mapping many other datasets. Our method improved the clarity and ease of interpretation of several information products used by fire management decision-makers.

This study describes the development of a prototype bi-spectral microbolometer sensor system designed explicitly for radiometric measurement and characterization of wildfire mid- and long-wave infrared radiances. The system is tested experimentally over moderate-scale experimental burns coincident with FLIR reference imagery. Statistical comparison of the fire radiative power (FRP; W) retrievals suggest that this novel system is highly reliable for use in collecting radiometric measurements of biomass burning. As such, this study provides clear experimental evidence that mid-wave infrared microbolometers are capable of collecting FRP measurements. Furthermore, given the low resource nature of this detector type, it presents a suitable option for monitoring wildfire behaviour from low resource platforms such as unmanned aerial vehicles (UAVs) or nanosats.

Despite increasing concern about wildland fire risk in Canada, there is little synthesis of knowledge that could contribute to the development of a comprehensive risk framework for a wide range of values, which is an essential need for the country. With dramatic variability in costs and losses from this natural hazard, there must be more support for complex decision-making under the uncertainty of how to assess and manage risk to coexist with wildland fire. A long history of Canadian wildland fire research offers solid foundational knowledge related to risk, but the key knowledge gaps must be addressed to fully consider risk in a comprehensive manner. We provide a review of the current context in which risk is variably defined, and recommend use of the general paradigm where risk is the product of both the likelihood and the potential impacts of wildland fire. Wethen synthesize research related to wildland fire risk from the Canadian scientific literature. With this review, weaim to provide a better understanding of research challenges, limitations, and opportunities for future work on fire risk within the country.

Parks Canada, in collaboration with Nova Scotia Lands and Forests and Natural Resources Canada, documented shrub fire behaviour in multiple plots burned over two periods: a spring period in June 2014 and a summer period in July 2017. The study area, located within Cape Breton Highlands National Park, comprised fifteen burn units (20 m by 20 m in size). Each unit was ignited by line ignition and burned under a wide range of conditions. Pre-burn fuel characteristics were measured across the site and used to estimate pre-fire fuel load and post-fire fuel consumption. This fuel complex was similar to many flammable shrub types around the world, results show that this shrub fuel type had high elevated fuel loads (3.17 ± 0.84 kg/m2) composed of exposed live and dead stunted black spruce as well as ericaceous shrubs, mainly Kalmia angustifolia (evergreen) and Rhodora canadensis (deciduous). Data show that the dead moisture content in this fuel complex is systematically lower than expected from the traditional relationship between FFMC and moisture content in the Canadian Fire Weather Index System but was statistically correlated with Equilibrium Moisture Content. A significant inverse relationship between bulk density and fire rate of spread was observed as well as a clear seasonal effect between the spring burns and the summer burns, which is likely attributable to the increase in bulk density in the summer. Unlike most shrub research, wind and dead moisture content did not have a statistically significant association with fire spread rates. However, we believe this to be due to noise in wind data and small dataset. Rate of spread as high as 14 m/min and flame lengths over 4 m were recorded under Initial Spread Index values of 6.4 and relative humidity of 54%. A comparison with a number of well-known shrubland spread rate prediction models was made. An aid to operational fire prediction behaviour is proposed, using a fuel type from the Canadian Fire Prediction System (O-1b) and a modified estimate of fuel moisture of the elevated fuel in the fuel complex.

Catastrophic wildfires are increasingly common across the globe. However, fire plays also a necessary and useful tool for food security, preservation of cultural landscapes and associated ecosystems. Global fire activity is shaped by diverse social, economic, and natural drivers, which determine the likelihood of a landscape to burn. The effects of climate change associated to other planetary changes are transforming fire activity in ways that it will likely be dramatic, with potential consequences to nature and society in case of adaptation failure. Based on the limited available statistics, there is a growing trend in the costs of wildfires. The key to wildfire disaster risk reduction in a changing world now lies in learning to live with fire. Our analysis revealed the following key issues for landscape management and governance: (i) Climate change in combination with other environmental changes linked to population growth and unsustainable land-use practices, is contributing to extreme wildfire events that exceed existing fire management capacities; (ii) Fire is an inherent feature of the Earth system and many ecosystems, are dependent on it for their long-term survival; nevertheless, ongoing changes in global fire activity in terms of location, intensity, severity, and frequency will likely have immense costs to biodiversity, ecosystem services, human well-being and livelihoods, and national economies; (iii) Engagement with local communities, land-owners, businesses and stakeholders is crucial to restore and maintain landscapes that are biodiverse and functional, respectful of local cultures and identities, economically productive, and above all, fire-resilient; (iv) People have historically achieved sustainable co-existence with flammable ecosystems and have often used fire as a land-management tool, thereby shaping many modern and long-standing landscapes around the world. Traditional fire knowledge is thus key to adapting to local changes in fire activity; (v) Building adaptive capacity to confront fires must be based on knowledge of the natural and cultural roles of fire, how they have shaped our modern landscapes, and their importance in the long-term functioning of socio-ecological systems; (vi) Catastrophic fires are part of our future. Current scientific estimates are likely conservative, meaning that changes in fire activity might likely be worse than anticipated.

Na medida em que todas as obras da UC Digitalis se encontram protegidas pelo Código do Direito de Autor e Direitos Conexos e demais legislação aplicável, toda a cópia, parcial ou total, deste documento, nos casos em que é legalmente admitida, deverá conter ou fazer-se acompanhar por este aviso. Modelling the performance of forest and wildland fire aerial detection systems Autor(es): Martell, David L.; McFayden, Colin; Santiago, Robin; Woolford, Douglas G.; Wotton, B. Mike Publicado por: Imprensa da Universidade de Coimbra URL persistente: URI:http://hdl.handle.net/10316.2/44705 DOI: DOI:https://doi.org/10.14195/978-989-26-16-506_187

The original publication [1] has an error in the citation of figure 1. Below you will find the correct version.

Introduction The Canadian Forest Fire Danger Rating System (CFFDRS) is a globally known wildland fire risk assessment system, and two major components, the fire weather index system and the fire behavior prediction system, have been extensively used both nationally and internationally to aid operational wildland fire decision making. Methods In this paper, we present an overview of an R package cffdrs, which is developed to calculate components of the CFFDRS, and highlight some of its functionality. In particular, we demonstrate how these functions could be used for large data analysis. Results and Discussion With this cffdrs package, we provide a portal for not only a collection of R functions dealing with all available components in CFFDRS but also a platform for various additional developments that are useful for the understanding of fire occurrence and behavior. This is the first time that all relevant CFFDRS methods are incorporated into the same platform, which can be accessed by both the management and research communities.