1. Introduction
In early May 2025, severe wildfires broke out in various parts of Manitoba, Canada, and spread rapidly. As of the time of writing, three of the most intense fires have collectively burned approximately 1,400 square kilometers of land and forest (
Figure 1). This wildfire caused the deaths of two people and led to the evacuation of approximately 1,000 residents from Lac du Bonnet and surrounding areas [
1]. These fires emerged under conditions of ongoing drought and unseasonably warm weather, contributing to rapid fire spread and extensive damage to the landscape. The disaster occurred amid an exceptional heat wave in Manitoba, with temperatures in Winnipeg reaching 37°C (99°F) — the highest recorded in 125 years [
1]. A national map, based on data from the Canadian Drought Monitor, showing drought intensity across Canada as of the end of April 2025, with parts of Manitoba marked as abnormally dry (D0) and under moderate drought (D1) conditions (
Figure 1a). This event emphasizes the need for improved wildfire preparedness and more comprehensive monitoring of drought trends across Canada, particularly in vulnerable provinces like Manitoba.
Severe wildfires erupted in various locations across Manitoba, in May 2025, showing rapid progression over a short period (
Figure 1b). A Landsat 8 image acquired on 4 May 2025 shows the burned area one day after ignition, with initial fire scars and smoke clearly visible (
Figure 1c, left). By 10 May, Sentinel-2 imagery reveals that the fire had expanded dramatically to cover 381.5 km2, indicating rapid spread over less than a week (
Figure 1c, right). Further east, a fire that started on 12 May had already grown to 952.7 km2 by 14 May, with a clear smoke plume along its southern boundary indicating ongoing fire activity and wind-driven transport (
Figure 1d). Another fire that began on 10 May in southeastern Manitoba reached 64.8 km² by 14 May, exhibiting a compact burn pattern within a forest-agriculture interface (
Figure 1e).
Advancements in remote sensing technologies have greatly enhanced our ability to monitor and detect wildfires [
2,
3]. Optical satellite imageries such as Landsat and Sentinel-2 allows for precise delineation of wildfire boundaries and the extent of their spread [
4]. Furthermore, remote sensing provides valuable insights into the underlying causes, dynamics, and characteristics that drive wildfire intensification, enabling more effective fire management and mitigation strategies. Understanding how these environmental factors interact with wildfire dynamics is essential, especially in the context of changing climate and land surface conditions that are reshaping fire regimes in boreal ecosystems. Recent shifts in climatic parameters and land surface conditions have significantly altered fire regimes in boreal ecosystems [
5]. This study analyzes April anomalies in snow cover, precipitation, temperature, leaf area index (LAI), normalized difference vegetation index (NDVI) and soil moisture across the province of Manitoba to assess their combined role in influencing wildfire risk.
2. Results and Discussion
The spatial anomalies of April 2025 across Manitoba point to a combination of environmental stressors conducive to wildfire ignition and spread (
Figure 2). Negative anomalies in LAI (-0.0241), precipitation (-7.6 mm), and temperature (-0.368°C) reflect suppressed vegetation activity, dry atmospheric conditions, and cooler-than-average air temperatures, respectively. Despite the latter, a slightly positive soil moisture anomaly (+0.031) indicates marginal subsurface retention, though likely insufficient to offset surface dryness. These variables suggest that vegetation stress, fueled by moisture deficits, created a flammable landscape particularly vulnerable to ignition sources.
The province exhibited a mean LAI anomaly of -0.024, indicating a general reduction in vegetative greenness and canopy density (
Figure 2a). This decline in LAI reflects early signs of vegetation stress or dieback, potentially driven by water scarcity and temperature conditions during the pre-fire season. The precipitation anomaly averaged -7.6 mm, suggesting a province-wide deficit in rainfall relative to the climatological norm. The central and southern regions were particularly affected, as evident in the anomaly map, which shows extensive zones in brown and yellow, signaling significantly drier-than-normal conditions (
Figure 2b). Such early-season dryness leads to rapid fuel desiccation, particularly in fine fuels like grasses and small shrubs, which are critical to initial fire ignition and spread. Although not extreme across the province, air temperature anomalies display positive deviations, particularly in southern Manitoba (
Figure 2c). These warmer-than-average patches are crucial, as they likely accelerated snowmelt and evaporative losses in April, reducing residual soil moisture ahead of the critical fire-prone period in May. In contrast, soil moisture anomaly averaged slightly positive (+0.031), which initially suggests sufficient subsurface moisture. However, the spatial distribution tells a different story. Significant parts of northern Manitoba exhibit negative soil moisture anomalies, represented by yellow to red tones on the map (
Figure 2d). This suggests that, despite the presence of slightly above-average soil moisture in burned areas during April, other compounding factors—such as vegetation density and precipitation deficits—played a more dominant role in creating favorable conditions for fire ignition and spread.
3. Conclusions
The May 2025 wildfires in Manitoba resulted from multiple interacting environmental stressors, including reduced April precipitation, early snowmelt, vegetation stress, and declining greenness, all contributing to a highly flammable landscape. While each anomaly alone appeared moderate, their combined impact significantly increased wildfire susceptibility, particularly in forest-agriculture transition zones. This study highlights the critical need for incorporating satellite-derived environmental indicators into operational fire risk assessments to anticipate better and manage spring wildfire outbreaks in boreal ecosystems.
Author Contributions
Conceptualization, A.A. and H.B.; methodology, A.A.; software, A.A.; validation, A.A.; formal analysis, A.A.; investigation, A.A.; resources, A.A.; data curation, A.A.; writing—original draft preparation, A.A.; writing—review and editing, A.A., H.B. and S.J.G; visualization, A.A.; supervision, H.B. and S.J.G; project administration, H.B. and S.J.G; funding acquisition, H.B. and S.J.G. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Data Availability Statement
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Acknowledgments
We gratefully acknowledge NASA for providing MODIS and Landsat satellite data, and the European Space Agency (ESA) for access to Sentinel-2 imagery, which were essential for wildfire monitoring and vegetation assessment. Drought data used in this study were obtained from the Canadian Drought Monitor, made available by Agriculture and Agri-Food Canada. We also acknowledge the Copernicus Climate Change Service (C3S) and the European Centre for Medium-Range Weather Forecasts (ECMWF) for providing ERA5-Land climate reanalysis data.
Conflicts of Interest
The authors declare no conflicts of interest.
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