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Article

Large-Scale Spatiotemporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America)

by
Wendi Zhao
1,2,†,
Qingchen Zhu
3,†,
Qiuling Chen
3,
Xiaohan Meng
3,
Kexu Song
3,
Diego I. Rodriguez-Hernandez
4,
Manuel Esteban Lucas-Borja
5,6,
Demetrio Antonio Zema
7,
Tong Zhang
8 and
Xiali Guo
1,2,*
1
Guangxi Key Laboratory of Forest Ecology and Conservation, Key Laboratory of National Forestry and Grassland Administration on Cultivation of Fast-Growing Timber in Central South China, College of Forestry, Guangxi University, Nanning 530004, China
2
Guangxi Youyiguan Forest Ecosystem Observation and Research Station, Pingxiang 532600, China
3
Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi 276000, China
4
School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK
5
Escuela Técnica Superior de Ingeniería Agronómica y de Montes y Biotecnología, Departamento de Ciencia y Tecnología Agroforestal y Genética, Universidad de Castilla-La Mancha, 02071 Albacete, Spain
6
Instituto Botánico, Universidad de Castilla-La Mancha, 02071 Albacete, Spain
7
AGRARIA Department, Mediterranea University of Reggio Calabria, Località Feo di Vito, 89122 Reggio Calabria, Italy
8
Guangxi Lijiangyuan Forest Ecosystem Research Station/Xing’an Guilin Lijiangyuan Forest Ecosystem Observation and Research Station of Guangxi, Guangxi Forestry Research Institute, Nanning 530002, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Forests 2025, 16(8), 1282; https://doi.org/10.3390/f16081282
Submission received: 12 June 2025 / Revised: 29 July 2025 / Accepted: 4 August 2025 / Published: 6 August 2025
(This article belongs to the Special Issue Forest Disturbance and Management)
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Abstract

Due to climate effects and human influences, wildfire regimes in boreal forests are changing, leading to profound ecological consequences, including shortened fire return intervals and elevated tree mortality. However, a critical knowledge gap exists concerning the spatiotemporal dynamics of fire-induced tree mortality specifically within the vast North American boreal forest, as previous studies have predominantly focused on Mediterranean and tropical forests. Therefore, in this study, we used satellite observation data obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua and Terra MCD64A1 and related database data to study the spatial and temporal variability in burned area and forest mortality due to wildfires in North America (Alaska and Canada) over an 18-year period (2003 to 2020). By calculating the satellite reflectance data before and after the fire, fire-driven forest mortality is defined as the ratio of the area of forest loss in a given period relative to the total forest area in that period, i.e., the area of forest loss divided by the total forest area. Our findings have shown average values of burned area and forest mortality close to 8000 km2/yr and 40%, respectively. Burning and tree loss are mainly concentrated between May and September, with a corresponding temporal trend in the occurrence of forest fires and high mortality. In addition, large-scale forest fires were primarily concentrated in Central Canada, which, however, did not show the highest forest mortality (in contrast to the results recorded in Northern Canada). Critically, based on generalized linear models (GLMs), the results showed that fire size and duration, but not the burned area, had significant effects on post-fire forest mortality. Overall, this study shed light on the most sensitive forest areas and time periods to the detrimental effects of forest wildfire in boreal forests of North America, highlighting distinct spatial and temporal vulnerabilities within the boreal forest and demonstrating that fire regimes (size and duration) are primary drivers of ecological impact. These insights are crucial for refining models of boreal forest carbon dynamics, assessing ecosystem resilience under changing fire regimes, and informing targeted forest management and conservation strategies to mitigate wildfire impacts in this globally significant biome.

1. Introduction

Forest ecosystems cover approximately 30% of the Earth’s land surface and store more than 80% of the terrestrial carbon, playing an important role in promoting global ecological processes [1,2,3]. However, tree mortality and forest dieback have increased over the last decades [4,5]. Forest wildfires are among the most critical drivers of these severe impacts [6,7,8]. As a result, high-severity wildfire events reshape the global distribution of forests and alter the carbon stock dynamics on a global scale [9,10,11].
The increased incidence of forest fires, particularly those of extreme severity [12], poses serious threats to forest ecosystem structure and function. These events reduce forest biodiversity and productivity as well as lead to large carbon emissions and severe hydrological impacts in the burned forests [3,13,14]. Generally, the time for forest recovery after a severe wildfire is long. As a consequence, their capacity to play the common ecosystem functions (e.g., carbon storage) is lost for a long time [15,16]. Furthermore, global-change-driven extreme drought events amplify wildfire severity and impacts [17,18,19,20]. Recurring and highly impacting wildfires may be precursors to changing global fire regimes [21]. Annually, the total burned area affected by forest fires worldwide is approximately 67 × 106 ha [22]. For example, in Australia, between 2019 and 2020, the area burned by fire was more than double compared to the historical record since 1930. In this environment, carbon emissions due to fire were the highest since 2003 [23,24]. Similarly, in South America, fire emissions increase about 1.5 to 2.8 times during seasons of severe drought compared to other years [25]. The boreal forests of North America, dominated by coniferous forests, are one of the most important of Earth’s biomes, accounting for about 30% of the total area of forests in the world. Therefore, this large extent of boreal forests plays a significant role in regulating the global carbon cycle [26,27]. Additionally, in these Northern Hemisphere ecosystems, wildfires have severely affected the structure and functioning of forest ecosystems [20,28,29]. A recent study has shown that carbon emissions from boreal fires reached the highest value since 2000, specifically due to the increasing occurrence and severity of wildfires. Forest fires in boreal biomes release about 10 to 20 times more carbon per unit burned area compared to other forest ecosystems [20]. Despite this significance, most of these studies focus on describing fire area, occurrence frequency, or overall carbon cycle impacts, but there has been a lack of in-depth exploration of the spatiotemporal patterns of fire-driven forest mortality and the interactions between specific fire attributes, and boreal wildfire impacts remain understudied relative to tropical systems, with limited research on fire-driven mortality [27,30]. Therefore, investigating spatiotemporal dynamics and the occurrence of wildfires in boreal forests is essential for understanding forest resilience and carbon-climate feedbacks. The latter gives forest managers feedback for predicting an ecosystem’s resilience to climate change and insights for developing more effective management strategies. In other words, there is a need to identify, also by a low-resolution study, which fire-affected areas are able to more rapidly recover after fire disturbance [15]. This knowledge may also advance our capacity to accurately simulate and predict the impacts of forest fires on ecosystem dynamics [31,32].
To fill this gap, this study addresses these issues by integrating wildfire event databases and applying spatial statistical and data analysis methods, assessing the spatiotemporal patterns of wildfire-induced mortality of boreal forests, together with its potential fire drivers (such as fire size, duration, and burned area) in Canada and Alaska. The specific objectives of this study are as follows: (i) to evaluate the forest areas that have burned in the region over the period of 2003–2020; (ii) to quantify tree mortality in the same period and area; and (iii) to identify the potential factors determining forest mortality among key wildfire attributes, including size, duration, and burned area. Based on the research objectives, we propose the following testable hypotheses: (1) Forest fires primarily occur during relatively warm climatic periods and are spatially concentrated in Central Canada. (2) Fire-driven forest mortality rates remain at high levels across the entire study area, with high mortality rates also concentrated during warm periods. (3) Larger fire sizes and longer fire durations lead to higher tree mortality rates, while burn areas have a smaller impact on tree mortality rates.

2. Materials and Methods

2.1. Overview of the Study Area

The climate and vegetation within the study area exhibit pronounced cold-temperate characteristics, displaying significant regional heterogeneity driven by environmental factors. The region is characterized by prolonged, severe winters with extreme temperatures plunging below −50 °C. Summers are short and cool; the average temperatures in the southern sectors range between 10 and 20 °C, accompanied by substantial diurnal temperature fluctuations. Precipitation is relatively low, with annual averages in inland areas approximating 200–400 mm. Notably, over 80% of this precipitation occurs as snowfall.
Influenced by climatic and edaphic conditions, vegetation distribution follows distinct zonal patterns. The southern region is dominated by cold-adapted coniferous species, notably Picea asperata, Abies fabri, and Larix gmelinii [33,34]. These trees typically exhibit short statures and shallow root systems, adaptations facilitating survival in permafrost environments. However, this structural morphology also heightens their susceptibility to natural disturbances, such as lightning strikes [21], which constitute a primary ignition source for forest fires. In contrast, the northern polar region is primarily covered by tundra vegetation, where tree growth is precluded. Collectively, the vegetation forms a unique northern forest ecosystem demonstrating high sensitivity to global climate change [27,35].

2.2. Data Collection

2.2.1. Burned Area and Fire Regime

Data on burned area extent from 2003 to 2020 were obtained from the Terra MCD64A1 with 500 m resolution and Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua. It has a significant advantage in providing long-term, continuous, and full-season data, which is essential for capturing all fire events during the study period. Additionally, this coarse resolution was deliberately chosen to avoid excessive computational effort for this large-scale study.
Individual fire events for the same period (2003 to 2020) were extracted from the Global Fire Atlas (GFA) database. This database was built at a daily and 500 m spatial resolution using geographical data from MODIS Collection 6 MCD64A1 [12,36]. The quality of information in this database regarding fire regime (size, duration, and spread rate) was verified in previous studies [12].

2.2.2. Data of Forest Loss

Data on forest loss at the annual scale (2003 to 2022) in the Global Forest Change (GFC) was extracted from Landsat satellite data at 30 m resolution (version 1.7) [5]. In addition, the Landsat-derived 30 m resolution tree cover data in the GFC dataset in 2000 was used to calculate the forest area (AreaForest).
In order to facilitate the calculation of forest mortality and loss area caused by fire, we reprojected these 30 m resolution annual forest loss data onto a 500 m sinusoidal grid and expressed it as a percentage of forest loss area per 500 m pixel (AreaForestLoss).

2.2.3. Land Cover and Forest Types

Forest areas and types for each year were identified using the land cover map prepared by the European Space Agency (ESA) (300 m resolution, period of 2002 to 2019) within the Climate Change Initiative (CCI) (period of 2002–2019). In more detail, land cover types labeled as “tree cover” were considered as forests. The forest types were classified as follows: evergreen coniferous forest (ENF), deciduous coniferous forest (DNF), evergreen broadleaf forest (corrected to EBF for discrimination from ENF), mixed forest (i.e., a mixture of broadleaf and coniferous forest types), and deciduous broadleaf forest (DBF). The forest type was identified from the map updated to the year preceding the fire event (Table 1).

2.3. Data Analysis

2.3.1. Identification and Calculation of the Burned Area

The pixels related to the burned area were matched to those related to the fire over time if both of the following conditions occurred: (i) the center of the forest area pixel was located inside the burned area; and (ii) the date of the forest area was between the start and end dates of the fire.

2.3.2. Calculation of Forest Mortality Due to Wildfire

In this study, we use a spatial overlay-based approach to quantify forest losses caused by global fires [37]. We overlaid MODIS BA and Landsat-derived 500 m resolution forest loss data on forest areas based on tree coverage in 2000 for each year from 2003 to 2020. If MODIS BA data are consistent with Landsat-derived forest loss data in the year of fire and two years after fire (i.e., t + 0, t + 1, t + 2), the pixel is marked as experiencing fire-induced forest loss. This method is used to consider the delay effect of tree death after fire [37]. After identifying fire-induced forest loss pixels, we superimpose MODIS forest burned pixels, forest loss area, and forest area data with a resolution of 500 m, covering each month from 2003 to 2020. Therefore, we defined forest mortality as the ratio of the area of forest loss in a given period relative to the total forest area in that period, i.e., the area of forest loss divided by the total forest area [8]. To address the delayed effects of fires on tree mortality, the values of forest mortality (”Mt”) for a given year “t” were calculated for pairs of two consecutive years (i.e., “t” to “t + 2”) after the fire year (“t”) [37].
M = A L o s s t + 0 + A L o s s t + 1 + A L o s s t + 2 A F o r e s t 2000
where A F o r e s t 2000 is the total area (in 2000) and A L o s s t + 0 , A L o s s t + 1 , and A L o s s t + 2 are the areas of forest loss at the years “t”, “t + 1”, and “t + 2”.

2.3.3. Spatiotemporal Patterns of Forest Mortality and Burned Area

The data of burned area forest mortality due to wildfire was compared in the temporal (annual and monthly scales, between 2003 and 2020) and spatial (0.5° × 0.5° grid cell) domains to explore the spatial and temporal patterns. The spatial domain was classified into the following regions of Alaska and Canada: (I) Alaska; (II) Northern Canada; (III) Western Canada; (IV) Central Canada; (V) Ontario, Canada; and (VI) Eastern Canada (Figure 1).

2.3.4. Statistical Processing

To identify the drivers of forest mortality, Pearson’s analysis was applied to identify correlations (expressed as the correlation coefficient “r”) between forest mortality, fire characteristics, and burned area. Furthermore, we used a generalized linear model (GLM) with a Gaussian distribution and an identity link—basically a standard linear model (LM), with forest mortality as the dependent variable and fire size, fire duration, and burned area as the independent variables—to assess the impact of fire size, fire duration, and burned area (including their interactions) on forest mortality during the study period (2003–2020). To determine the optimal combination of predictor variables (including interaction terms), we conducted a systematic model selection based on the information criteria. The candidate models included a baseline model containing only main effects (fire size, fire duration, and burned area), models containing pairwise interaction terms (e.g., fire size × fire duration, fire size × burned area, and fire duration × burned area), and a full model incorporating all main effects and three-way interaction terms (fire size × fire duration × burned area). We compared these candidate models using the Akaike Information Criterion (AIC), which balances model fit and parsimony. The model with the lowest AIC value was selected as the final model. Additionally, to ensure the robustness and reliability of the selected GLM, we assessed the residual normality using the Shapiro–Wilk test and residual Q-Q plots, confirming that the residuals approximately follow a normal distribution. We also evaluated the homoscedasticity using the Breusch–Pagan test and residual plots, verifying that the residual variance remains constant across the range of predicted values, thereby ensuring a linear relationship between the predictor variables and the dependent variable. We also conducted goodness-of-fit assessments, evaluating the significance of each predictor variable using standard errors, t-values, and p-values. The generalized linear models (GLMs) used the “glm” function in the “stats” package of the R 4.4.2 software [38].

3. Results

3.1. Spatiotemporal Patterns of Fire-Induced Burned Area

The average burned area of North American boreal forests was 19,501 km2/yr during 2003–2020. This area always exceeded 8000 km2/yr, except in 2000 (1160 km2/yr), with a peak of 37,870 km2/yr in 2013 (Figure 2A). The evolutionary trend of the burned area over time shows a high seasonality, since the highest extent (about 98% of the total burned area) is concentrated in May to September (Figure 2B).
The spatial distribution of forest fires in the region is uneven, occurring in Central, Northern, and Eastern Canada (regions II, III, and IV) and Alaska, all being dominated by a forest cover (Figure 3). Central Canada alone accounted for 39% of the burned area in the study area, while Ontario showed the lowest percentage (4.5%) (Table 2).
The analysis of the inter-annual variations of the burned area in the geographical regions shows large forest fires in Central Canada every year during the study period. Peaks of this value are evident also in Northern (5013 km2 in 2013) and in Eastern Canada (3071 km2 in 2014) (Figure 4A). The seasonal trends of burned areas were largely similar in the study area since wildfires were concentrated from May to September in all regions, with the highest peak in July (Central Canada) (Figure 4B).

3.2. Spatiotemporal Patterns of Forest Mortality

Average forest mortality due to wildfires was 53.1% during 2003–2020. The highest values were recorded in 2016 (64.9%), 2017 (62.1%), and 2019 (63.8%), all exceeding 40%, except in 2020 (28.2%) (Figure 5A). The intra-annual mortality patterns mirrored burned area seasonality, with the highest values from May to September (mean: 50.7%). During other months, the mortality averaged <13%, reaching a minimum of 3.5% in January (Figure 5B).
In the study, forest mortality exceeded 50% in most regions (Figure 6), except in Western Canada (30.7%) (Table 2). The average forest mortality in each region was above 51%, and the highest peak was recorded in Northern Canada (91%, 2020). The annual and seasonal variations were not noticeably different over the study area, and a relatively low inter-annual variability was recorded in Western Canada (Figure 7A). Forest mortality was predominantly concentrated from May to September and exceeded 60% in all geographical regions. It is worth noting that, in some regions (Western and Central Canada), forest mortality was noticeable also in some other months (January to April) (Figure 7B).

3.3. Correlations Among Forest Mortality, Fire Characteristics, and Burned Area

The generalized linear model revealed that fire size, fire duration, and their interaction significantly influenced forest mortality (p < 0.001), whereas burned area played a minor role in driving this variable (p = 0.316; Table 3). There was a high and positive correlation between fire size and duration (r = 0.81) as well as between these characteristics and burned area (r > 0.49). The coefficients of correlations between the fire regime on one side and forest mortality on the other side were much lower but significant (r > 0.18). No significant correlation was observed between burned area and forest mortality (r = 0.07; Figure 8).

4. Discussion

Studies have found that the factors triggering the occurrence of fires are different in time and space and must be ascribed to both natural and anthropogenic factors as well as to climate variability [39]. This study explores the spatiotemporal patterns of burned areas and forest mortality across 18 years of recurrent forest wildfires in North America.
In addition, previous studies have shown that most forest fires in East Asia occur in spring and winter, and most forest fires are caused by human ignition, but fire-driven forest mortality is the largest between late spring and midsummer [8]. Our study reveals consistently high burned area (>8000 km2/yr) and fire-induced forest mortality (>40%) across the 2003–2020 period in North America, with minimal inter-annual exceptions. Approximately 98% of wildfires occurred during drier months, coinciding with peak tree mortality. The lower occurrence of fire in the cooler seasons may be explained by the increase in albedo (winter and spring), which promotes surface cooling and suppresses fire activity [33,40]. In contrast, higher temperatures and drier air in the summer noticeably increase the fire hazard, which is also enhanced by the accumulation of dead fuel [34,41]. These forests are more vulnerable to high-intensity fires and result in higher forest mortality. High forest mortality during the monitoring period is due to the predominance of crown fires, typical of the environments in North America [41,42]. These high-intensity fires consume fuel loads per unit area orders of magnitude greater than surface fires [43]. It is well known that the accumulation of fuel loads tends to increase the fire occurrence [44], and, as a consequence, trees are easily killed by these wildfires [33,45]. Therefore, the increases in temperature and dryness combined with high-intensity crown fires are the main causes of tree mortality from May to September.
This study further reveals a regional disparity: while severe fires were concentrated in Central Canada (approx. 40% of the total burned area), fire-driven mortality peaked elsewhere. Nevertheless, substantial forest loss occurred across all regions, except Western Canada, where both burned area and mortality were notably the lowest. The generally high forest mortality may be related to the simpler forest structural complexity compared to tropical rainforests, potentially elevating fire susceptibility [46]. Compared with other biomes, boreal forests in North America have lower species diversity [45], and the forests are dominated by coniferous species [47], including Picea mariana, Pinus banksiana, and Picea glauca [33,34]. Due to their lower water content and higher thickness and flammability of leaves, coniferous species are easier to burn than broad-leaved species [48]. Previous studies have found that forest fires show a significant preference among forest types, and fires have been shown to strongly select coniferous forests rather than stands with a large number of deciduous components [49]. Thus, coniferous forests are more likely to experience fires compared to mixed forests with a high proportion of deciduous species [49]. For example, the probability of fire occurrence in pure coniferous forests is about 24 times higher than in pure broad-leaved forests in the boreal environment [50]. In Canada, pure coniferous stands represent more than 60% of the forest area, and more than half of forest fires are dominated by high-intensity crown fires [41,42], which usually lead to the rapid death of these conifer species.
Our findings demonstrate that fire size and duration are primary drivers of post-fire tree mortality in North American boreal forests. Fire combustion unleashes a substantial amount of energy [41,43,51], which consequently prolongs the fire duration. This energy could also increase the probability of death of heat-damaged trees, and long-term high temperatures could also kill trees directly [8,52]. Additionally, the increased frequency of long-term droughts has led to more frequent fires. Coupled with heatwaves, they have increased the probability of fire occurrence across all forest biomes [53]. Wildfires in forests with high intensity and severity may last for months [54,55], leading to extremely high tree mortality. Under the current climate change scenario, the rising frequency of heatwaves and extreme drought events is increasing the likelihood of larger, longer-duration, and higher-intensity fires in the boreal forests of North America, ultimately driving higher rates of forest mortality.
These findings help management departments to adopt proactive and adaptive forest management strategies, formulate more effective emergency plans and fire-fighting measures, and, thus, improve the response speed and efficiency of emergency response. In addition, by assessing the impact of fires on forest ecosystems, the effects of different management measures can be further evaluated to provide a basis for taking effective actions to reduce the damage of fires to forest resources, biodiversity, and the ecological environment, thereby supporting forest ecological restoration. However, the MODIS data with a resolution of 500 m used in this study may have some errors in accuracy, and there are some limitations. There are still some deficiencies in distinguishing the death directly caused by fire and the death after fire driven by secondary pressure factors. Scientific and reasonable acquisition of data with higher accuracy plays a vital role in improving the depth of research. In addition, the impact of other environmental factors on forest death caused by fire should also be fully considered. In future research, we will use more sophisticated research methods so that we can better study the issues related to forest wildfires and will be more active in exploring the role of different environmental parameters so as to more accurately assess the impact of forest fires on forest ecosystems.

5. Conclusions

Employing diverse satellite observation data, we conducted a study on the spatial and temporal distribution of forest burned areas and fire-induced forest mortality in the northern regions of North America, specifically in Alaska and Canada, and evaluated the strength of the relationship between post-fire forest mortality and different fire regime factors and forest burned area. We found that both the fire-driven forest mortality and burned area in the region remained at a high level over an 18-year period (from 2003 to 2020), over 8000 km2/yr and 40%, respectively. Forest fires mainly occurred from May to September, and, spatially, forest fires in this region mainly occurred in Central (represented more than 40% of the burned area), Northern, and Eastern Canada and Alaska, and the mortality rate of the burned forests across the different regions remained relatively high. Furthermore, the fire size and duration were the main drivers of the high forest mortality. Our study indicates which areas and time periods are the most sensitive to the detrimental effects of forest wildfires in the boreal forests of North America, reflects the spatiotemporal dynamic patterns of forest death following fire impact across the boreal forests of North America, and provides a scientific basis for the implementation of better forest management strategies, the prediction of forest ecosystem resilience to fire regimes, and the identification of the areas more vulnerable to fire-driven mortality in boreal North America. In future research, we should continue to optimize data methods, analyze mechanisms in depth, and expand multi-scale correlation and application practices.

Author Contributions

Conceptualization, M.E.L.-B., T.Z. and X.G.; Methodology, D.A.Z. and X.G.; Software, W.Z., Q.Z. and Q.C.; Validation, W.Z.; Data curation, Q.Z., Q.C., X.M. and K.S.; Writing — original draft, W.Z., D.I.R.-H. and D.A.Z.; Supervision, X.G.; Funding acquisition, X.G. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (32201543, 32201283), Guikesci AD25069098, the Guangxi Forestry Science and Technology Demonstration Project (Research and Technology Breakthrough Category, 2024GXLK24), and the Research Start-up Funding for the First Cohort of Young Talent Inclusive Support Policy.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Figure 1. Classification of the territory of the study area (Alaska and Canada in regions) (I, Alaska; II, Northern Canada; III, Western Canada; IV, Central Canada; V, Ontario, Canada; and VI, Eastern Canada).
Figure 1. Classification of the territory of the study area (Alaska and Canada in regions) (I, Alaska; II, Northern Canada; III, Western Canada; IV, Central Canada; V, Ontario, Canada; and VI, Eastern Canada).
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Figure 2. Inter-annual ((A), km2) and intra-annual ((B), km2/yr) variations of burned forest area (2003–2020) in the study area (Alaska and Canada).
Figure 2. Inter-annual ((A), km2) and intra-annual ((B), km2/yr) variations of burned forest area (2003–2020) in the study area (Alaska and Canada).
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Figure 3. Spatial distribution of burned forest areas (2003–2020) in the study area (Alaska and Canada).
Figure 3. Spatial distribution of burned forest areas (2003–2020) in the study area (Alaska and Canada).
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Figure 4. Annual ((A), km2) and monthly ((B), km2/yr) pattern of burned area in the period of 2003–2020.
Figure 4. Annual ((A), km2) and monthly ((B), km2/yr) pattern of burned area in the period of 2003–2020.
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Figure 5. Annual (A) and monthly (B) pattern of forest mortality due to wildfire (2003–2020) in the study area (Alaska and Canada).
Figure 5. Annual (A) and monthly (B) pattern of forest mortality due to wildfire (2003–2020) in the study area (Alaska and Canada).
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Figure 6. Spatial pattern of the forest mortality due to wildfire (2003–2020) in the study area (Alaska and Canada).
Figure 6. Spatial pattern of the forest mortality due to wildfire (2003–2020) in the study area (Alaska and Canada).
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Figure 7. Annual (A) and monthly (B) pattern of forest mortality due to wildfire in the period of 2003–2020.
Figure 7. Annual (A) and monthly (B) pattern of forest mortality due to wildfire in the period of 2003–2020.
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Figure 8. Pearson’s correlation coefficients among fire characteristics, burned area, and forest mortality (period of 2003–2020) in the study area (Alaska and Canada).
Figure 8. Pearson’s correlation coefficients among fire characteristics, burned area, and forest mortality (period of 2003–2020) in the study area (Alaska and Canada).
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Table 1. Classification of the forest types analyzed in this study based on the land cover data from ESA-CCI data.
Table 1. Classification of the forest types analyzed in this study based on the land cover data from ESA-CCI data.
ESA-CCI DataThis Study
(IGBP Classification)
CodeDescription
50Tree cover, broadleaved, evergreen, closed to openEvergreen broadleaf forest
60Tree cover, broadleaved, deciduous, closed to openDeciduous broadleaf forest
61Tree cover, broadleaved, deciduous, closed
62Tree cover, broadleaved, deciduous, open
70Tree cover, coniferous, evergreen, closed to openEvergreen coniferous forest
71Tree cover, coniferous, evergreen, closed
72Tree cover, coniferous, evergreen, open
80Tree cover, coniferous, deciduous, closed to openDeciduous coniferous forest
81Tree cover, coniferous, deciduous, closed
82Tree cover, coniferous, deciduous, open
90Tree cover, mixed leaf typeMixed forest
Note: ESA-CCI: European Space Agency—Climate Change Initiative.
Table 2. Burned forest area and mortality (annual average over the period of 2003–2020) in the study area (Alaska and Canada).
Table 2. Burned forest area and mortality (annual average over the period of 2003–2020) in the study area (Alaska and Canada).
RegionsBurned Area
(km2/yr)		Ratio on Total Area (%)Forest Mortality (%)
Alaska276514.255.7
Northern Canada391120.162.1
Western Canada208710.730.7
Central Canada758338.954.4
Ontario (Canada)8714.4651.1
Eastern Canada228111.757.4
Table 3. Parameters of the generalized linear model (GLM) setup to test the effects of fire characteristics and burned area on forest mortality (period of 2003–2020) in the study area (Alaska and Canada).
Table 3. Parameters of the generalized linear model (GLM) setup to test the effects of fire characteristics and burned area on forest mortality (period of 2003–2020) in the study area (Alaska and Canada).
FactorEstimateStd. Dev.t-Valuep-Value
Fire size15.3021.17513.025<0.001 ***
Fire duration0.4910.1233.993<0.001 ***
Burned area−0.0550.055−1.0030.316
Fire size × duration−0.3950.092−4.314<0.001 ***
Fire size × burned area0.0120.0170.7350.462
Fire duration × burned area0.0020.0011.3980.162
Fire size × duration × burned area−0.001<0.001−1.1980.231
Note: significant effects (*** p < 0.001) are evidenced in bold.
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MDPI and ACS Style

Zhao, W.; Zhu, Q.; Chen, Q.; Meng, X.; Song, K.; Rodriguez-Hernandez, D.I.; Lucas-Borja, M.E.; Zema, D.A.; Zhang, T.; Guo, X. Large-Scale Spatiotemporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America). Forests 2025, 16, 1282. https://doi.org/10.3390/f16081282

AMA Style

Zhao W, Zhu Q, Chen Q, Meng X, Song K, Rodriguez-Hernandez DI, Lucas-Borja ME, Zema DA, Zhang T, Guo X. Large-Scale Spatiotemporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America). Forests. 2025; 16(8):1282. https://doi.org/10.3390/f16081282

Chicago/Turabian Style

Zhao, Wendi, Qingchen Zhu, Qiuling Chen, Xiaohan Meng, Kexu Song, Diego I. Rodriguez-Hernandez, Manuel Esteban Lucas-Borja, Demetrio Antonio Zema, Tong Zhang, and Xiali Guo. 2025. "Large-Scale Spatiotemporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America)" Forests 16, no. 8: 1282. https://doi.org/10.3390/f16081282

APA Style

Zhao, W., Zhu, Q., Chen, Q., Meng, X., Song, K., Rodriguez-Hernandez, D. I., Lucas-Borja, M. E., Zema, D. A., Zhang, T., & Guo, X. (2025). Large-Scale Spatiotemporal Patterns of Burned Areas and Fire-Driven Mortality in Boreal Forests (North America). Forests, 16(8), 1282. https://doi.org/10.3390/f16081282

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