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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. We used statistical modelling and machine learning to model the probability of initial attack (IA) success for eight different time and size-based definitions. We found no substantial differences in model predictive accuracy across the different definitions. Models of IA success should be defined using specific research or operational objectives. [ABSTRACT FROM AUTHOR]

Background. Canadian fire management agencies track drought conditions using the Drought Code (DC) in the Canadian Forest Fire Danger Rating System. The DC represents deep organic layer moisture. Aims. To determine if electronic soil moisture probes and land surface model estimates of soil moisture content can be used to supplement and/or improve our understanding of drought in fire danger rating. Methods. We carried out field studies in the provinces of Alberta and Ontario. We installed in situ soil moisture probes at two different depths in seven forest plots, from the surface through the organic layers, and in some cases into the mineral soil. Results. Our results indicated that the simple DC model predicted the moisture content of the deeper organic layers (10-18 cm depths) well, even compared with the more sophisticated land surface model. Conclusions. Electronic moisture probes can be used to supplement the DC. Land surface model estimates of moisture content consistently underpredicted organic layer moisture content. Implications. Calibration and validation of the land surface model to organic soils in addition to mineral soils is necessary for future use in fire danger prediction. [ABSTRACT FROM AUTHOR]

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. We describe the barriers and facilitators for knowledge exchange for wildland fire management elicited from a case study of the Canadian Forest Fire Danger Rating System development and implementation in Ontario. These findings can help guide the development and implementation of future innovations for wildland fire management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Wildfires play an important role in forest management, while an accurate assessment of current wildfire status is imperative for fire management. In this paper, a Kalman filter-based methodology is proposed to estimate the wildfire progress with online measurements that are collected by a system of unmanned aerial vehicles. The method is developed to estimate the wildfire propagation behavior as well as fire front contour. It is enabled by developing a scalar field wildfire model and utilizing the Kalman filter to estimate the parameters of the model. In addition, an uncertainty function is developed to describe the performance of the estimation results. The effectiveness of the algorithm is demonstrated in an independent fire simulation environment. [ABSTRACT FROM AUTHOR]

Reference 1 Hanes C., Wotton M., Woolford D.G., Martell D.L., Flannigan M. Preceding Fall Drought Conditions and Overwinter Precipitation Effects on Spring Wildland Fire Activity in Canada. Preceding Fall Drought Conditions and Overwinter Precipitation Effects on Spring Wildland Fire Activity in Canada. The authors wish to make the following corrections to this paper [[1]]: Error in Figure The authors found an error in Figure 3. [Extracted from the article]

Abstract: We used Cumulative Severity Rating (CSR), a weather-based fire danger metric, to examine the potential influence of climate change on global fire season severity. The potential influence of climate change on fire season length was also addressed. We used three General Circulation Models (GCMs) and three emission scenarios to calculate the CSR and fire season length for mid-century (2041–2050) and late century (2091–2100) relative to the 1971–2000 baseline. Our results suggest significant increases in the CSR for all models and scenarios. Increases were greatest (more than three times greater than the baseline CSR) for the Northern Hemisphere at the end of the century. Fire season length changes were also most pronounced at the end of the century and for northern high latitudes where fire season lengths will increase by more than 20days per year. The implications from this study are that fire seasons will be more severe in future and that conventional fire management approaches may no longer be effective. [Copyright &y& Elsevier]

Forest fires are a significant and natural element of the circumboreal forest. Fire activity is strongly linked to weather, and increased fire activity due to climate change is anticipated or arguably has already occurred. Recent studies suggest a doubling of area burned along with a 50% increase in fire occurrence in parts of the circumboreal by the end of this century. Fire management agencies' ability to cope with these increases in fire activity is limited, as these organizations operate with a narrow margin between success and failure; a disproportionate number of fires may escape initial attack under a warmer climate, resulting in an increase in area burned that will be much greater than the corresponding increase in fire weather severity. There may be only a decade or two before increased fire activity means fire management agencies cannot maintain their current levels of effectiveness. [ABSTRACT FROM AUTHOR]

Reports on the general circulation model simulations that suggest that the Earth's climate will be 1?3.5 C warmer by AD 2100. Temperature that will influence disturbances such as forest fires, which are important to circumpolar boreal forest dynamics and, hence, the global carbon cycle; Suggestion that climate warming will cause increased fire activity and area burned; Use of the Canadian Forest Fire Weather Index to simulate future forest fire danger, showing the expected increase in most of Canada but with significant regional variability including a decrease in much of eastern Canada; Results that are in general agreement with paleoecological data and general circulation model results from the 6000 calendar years BP interval, which was a time of a warmer climate that may be an analogue for a future climate.

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. [ABSTRACT FROM AUTHOR]