Global Patterns and Dynamics of Burned Area and Burn Severity

It is a widespread assumption that burned area and severity are increasing worldwide due to climate change. This issue has motivated former analysis based on satellite imagery, revealing a decreasing trend in global burned areas. However, few studies have addressed burn severity trends, rarely relat...

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Published in:Remote Sensing
Main Authors: Víctor Fernández-García, Esteban Alonso-González
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2023
Subjects:
Q
Online Access:https://doi.org/10.3390/rs15133401
https://doaj.org/article/7a66a19beb9244589a2fa8088ef0924b
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spelling ftdoajarticles:oai:doaj.org/article:7a66a19beb9244589a2fa8088ef0924b 2023-07-30T04:07:13+02:00 Global Patterns and Dynamics of Burned Area and Burn Severity Víctor Fernández-García Esteban Alonso-González 2023-07-01T00:00:00Z https://doi.org/10.3390/rs15133401 https://doaj.org/article/7a66a19beb9244589a2fa8088ef0924b EN eng MDPI AG https://www.mdpi.com/2072-4292/15/13/3401 https://doaj.org/toc/2072-4292 doi:10.3390/rs15133401 2072-4292 https://doaj.org/article/7a66a19beb9244589a2fa8088ef0924b Remote Sensing, Vol 15, Iss 3401, p 3401 (2023) fire severity burn severity spatial patterns trends biomes continents Science Q article 2023 ftdoajarticles https://doi.org/10.3390/rs15133401 2023-07-16T00:34:46Z It is a widespread assumption that burned area and severity are increasing worldwide due to climate change. This issue has motivated former analysis based on satellite imagery, revealing a decreasing trend in global burned areas. However, few studies have addressed burn severity trends, rarely relating them to climate variables, and none of them at the global scale. Within this context, we characterized the spatiotemporal patterns of burned area and severity by biomes and continents and we analyzed their relationships with climate over 17 years. African flooded and non-flooded grasslands and savannas were the most fire-prone biomes on Earth, whereas taiga and tundra exhibited the highest burn severity. Our temporal analysis updated the evidence of a decreasing trend in the global burned area (−1.50% year −1 p < 0.01) and revealed increases in the fraction of burned area affected by high severity (0.95% year −1 p < 0.05). Likewise, the regions with significant increases in mean burn severity, and burned areas at high severity outnumbered those with significant decreases. Among them, increases in severely burned areas in the temperate broadleaf and mixed forests of South America and tropical moist broadleaf forests of Australia were particularly intense. Although the spatial patterns of burned area and severity are clearly driven by climate, we did not find climate warming to increase burned area and burn severity over time, suggesting other factors as the primary drivers of current shifts in fire regimes at the planetary scale. Article in Journal/Newspaper taiga Tundra Directory of Open Access Journals: DOAJ Articles Remote Sensing 15 13 3401
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic fire severity
burn severity
spatial patterns
trends
biomes
continents
Science
Q
spellingShingle fire severity
burn severity
spatial patterns
trends
biomes
continents
Science
Q
Víctor Fernández-García
Esteban Alonso-González
Global Patterns and Dynamics of Burned Area and Burn Severity
topic_facet fire severity
burn severity
spatial patterns
trends
biomes
continents
Science
Q
description It is a widespread assumption that burned area and severity are increasing worldwide due to climate change. This issue has motivated former analysis based on satellite imagery, revealing a decreasing trend in global burned areas. However, few studies have addressed burn severity trends, rarely relating them to climate variables, and none of them at the global scale. Within this context, we characterized the spatiotemporal patterns of burned area and severity by biomes and continents and we analyzed their relationships with climate over 17 years. African flooded and non-flooded grasslands and savannas were the most fire-prone biomes on Earth, whereas taiga and tundra exhibited the highest burn severity. Our temporal analysis updated the evidence of a decreasing trend in the global burned area (−1.50% year −1 p < 0.01) and revealed increases in the fraction of burned area affected by high severity (0.95% year −1 p < 0.05). Likewise, the regions with significant increases in mean burn severity, and burned areas at high severity outnumbered those with significant decreases. Among them, increases in severely burned areas in the temperate broadleaf and mixed forests of South America and tropical moist broadleaf forests of Australia were particularly intense. Although the spatial patterns of burned area and severity are clearly driven by climate, we did not find climate warming to increase burned area and burn severity over time, suggesting other factors as the primary drivers of current shifts in fire regimes at the planetary scale.
format Article in Journal/Newspaper
author Víctor Fernández-García
Esteban Alonso-González
author_facet Víctor Fernández-García
Esteban Alonso-González
author_sort Víctor Fernández-García
title Global Patterns and Dynamics of Burned Area and Burn Severity
title_short Global Patterns and Dynamics of Burned Area and Burn Severity
title_full Global Patterns and Dynamics of Burned Area and Burn Severity
title_fullStr Global Patterns and Dynamics of Burned Area and Burn Severity
title_full_unstemmed Global Patterns and Dynamics of Burned Area and Burn Severity
title_sort global patterns and dynamics of burned area and burn severity
publisher MDPI AG
publishDate 2023
url https://doi.org/10.3390/rs15133401
https://doaj.org/article/7a66a19beb9244589a2fa8088ef0924b
genre taiga
Tundra
genre_facet taiga
Tundra
op_source Remote Sensing, Vol 15, Iss 3401, p 3401 (2023)
op_relation https://www.mdpi.com/2072-4292/15/13/3401
https://doaj.org/toc/2072-4292
doi:10.3390/rs15133401
2072-4292
https://doaj.org/article/7a66a19beb9244589a2fa8088ef0924b
op_doi https://doi.org/10.3390/rs15133401
container_title Remote Sensing
container_volume 15
container_issue 13
container_start_page 3401
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