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...
Published in: | Remote Sensing |
---|---|
Main Authors: | , |
Format: | Text |
Language: | English |
Published: |
Multidisciplinary Digital Publishing Institute
2023
|
Subjects: | |
Online Access: | https://doi.org/10.3390/rs15133401 |
id |
ftmdpi:oai:mdpi.com:/2072-4292/15/13/3401/ |
---|---|
record_format |
openpolar |
spelling |
ftmdpi:oai:mdpi.com:/2072-4292/15/13/3401/ 2023-08-20T04:10:06+02:00 Global Patterns and Dynamics of Burned Area and Burn Severity Víctor Fernández-García Esteban Alonso-González agris 2023-07-04 application/pdf https://doi.org/10.3390/rs15133401 EN eng Multidisciplinary Digital Publishing Institute Forest Remote Sensing https://dx.doi.org/10.3390/rs15133401 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 15; Issue 13; Pages: 3401 fire severity burn severity spatial patterns trends biomes continents climate warming Text 2023 ftmdpi https://doi.org/10.3390/rs15133401 2023-08-01T10:44:39Z 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. Text taiga Tundra MDPI Open Access Publishing Remote Sensing 15 13 3401 |
institution |
Open Polar |
collection |
MDPI Open Access Publishing |
op_collection_id |
ftmdpi |
language |
English |
topic |
fire severity burn severity spatial patterns trends biomes continents climate warming |
spellingShingle |
fire severity burn severity spatial patterns trends biomes continents climate warming 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 climate warming |
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 |
Text |
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 |
Multidisciplinary Digital Publishing Institute |
publishDate |
2023 |
url |
https://doi.org/10.3390/rs15133401 |
op_coverage |
agris |
genre |
taiga Tundra |
genre_facet |
taiga Tundra |
op_source |
Remote Sensing; Volume 15; Issue 13; Pages: 3401 |
op_relation |
Forest Remote Sensing https://dx.doi.org/10.3390/rs15133401 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs15133401 |
container_title |
Remote Sensing |
container_volume |
15 |
container_issue |
13 |
container_start_page |
3401 |
_version_ |
1774724050971525120 |