Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado

Detalhes bibliográficos
Autor(a) principal: dos Santos, Ana Carla
Data de Publicação: 2019
Outros Autores: da Rocha Montenegro, Samuel, Belloni Schmidt, Isabel
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Biodiversidade Brasileira
Texto Completo: https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1233
Resumo: Fire is one of the main factors determining the structure of mesic savannas like the Brazilian Cerrado. Its plant species have evolved with fire for millions of years, but intense human use in the past century has been threatening biodiversity. Until recently, the governmental strategy to cope with it has been fire exclusion, which leads to grassy fuel loading and intensification of late-dry season wildfires. A fire management program was established since 2014 in some Protected Areas (PA) to try to solve the problem, including a series of practices such as late-wet and early-dry season prescribed burns. However, the behavior of these fires had not been characterized prior to this study, so our aim was to do so to inform PA staff decision making. We set up seven 50 x 100 m plots for each of the burning treatments: biennial early-dry season management fires (MF) and late-dry season fires (LF). Fires were lit in 2015 and 2017 in the same plots. For each burn, we calculated fire intensity, heat released, burn efficiency and flame height (only for 2017 fires). We fit linear models for each of these variables, considering fire season, pre-fire biomass, air humidity, wind speed and percentage of dicots in the fine fuel (only for 2017 fires) as explanatory variables (p ≤ 0.05). We compared AICc values to select the fittest models for each parameter. Considering all fires, fire intensity and heat released were best explained by pre-fire biomass and fire season, whilst wind speed and fire season best explained burn efficiency. As for 2017 fires, fire intensity and flame height were best explained by fire season alone, while heat released and burn efficiency were best predicted by fire season, pre-fire biomass and dicot percentage. LF were more intense, consumed more fuel and released more heat than MF. This indicates that season, time since last fire and local conditions that facilitate fuel loading might all be crucial in determining fire behavior. Therefore, frequent (< 4 yrs.) prescribed burns in the early-dry season should be used to prevent the occurrence of intense wildfires in areas with quick fuel build-up.
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spelling Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern CerradoFire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern CerradoFire is one of the main factors determining the structure of mesic savannas like the Brazilian Cerrado. Its plant species have evolved with fire for millions of years, but intense human use in the past century has been threatening biodiversity. Until recently, the governmental strategy to cope with it has been fire exclusion, which leads to grassy fuel loading and intensification of late-dry season wildfires. A fire management program was established since 2014 in some Protected Areas (PA) to try to solve the problem, including a series of practices such as late-wet and early-dry season prescribed burns. However, the behavior of these fires had not been characterized prior to this study, so our aim was to do so to inform PA staff decision making. We set up seven 50 x 100 m plots for each of the burning treatments: biennial early-dry season management fires (MF) and late-dry season fires (LF). Fires were lit in 2015 and 2017 in the same plots. For each burn, we calculated fire intensity, heat released, burn efficiency and flame height (only for 2017 fires). We fit linear models for each of these variables, considering fire season, pre-fire biomass, air humidity, wind speed and percentage of dicots in the fine fuel (only for 2017 fires) as explanatory variables (p ≤ 0.05). We compared AICc values to select the fittest models for each parameter. Considering all fires, fire intensity and heat released were best explained by pre-fire biomass and fire season, whilst wind speed and fire season best explained burn efficiency. As for 2017 fires, fire intensity and flame height were best explained by fire season alone, while heat released and burn efficiency were best predicted by fire season, pre-fire biomass and dicot percentage. LF were more intense, consumed more fuel and released more heat than MF. This indicates that season, time since last fire and local conditions that facilitate fuel loading might all be crucial in determining fire behavior. Therefore, frequent (< 4 yrs.) prescribed burns in the early-dry season should be used to prevent the occurrence of intense wildfires in areas with quick fuel build-up.Fire is one of the main factors determining the structure of mesic savannas like the Brazilian Cerrado. Its plant species have evolved with fire for millions of years, but intense human use in the past century has been threatening biodiversity. Until recently, the governmental strategy to cope with it has been fire exclusion, which leads to grassy fuel loading and intensification of late-dry season wildfires. A fire management program was established since 2014 in some Protected Areas (PA) to try to solve the problem, including a series of practices such as late-wet and early-dry season prescribed burns. However, the behavior of these fires had not been characterized prior to this study, so our aim was to do so to inform PA staff decision making. We set up seven 50 x 100 m plots for each of the burning treatments: biennial early-dry season management fires (MF) and late-dry season fires (LF). Fires were lit in 2015 and 2017 in the same plots. For each burn, we calculated fire intensity, heat released, burn efficiency and flame height (only for 2017 fires). We fit linear models for each of these variables, considering fire season, pre-fire biomass, air humidity, wind speed and percentage of dicots in the fine fuel (only for 2017 fires) as explanatory variables (p ≤ 0.05). We compared AICc values to select the fittest models for each parameter. Considering all fires, fire intensity and heat released were best explained by pre-fire biomass and fire season, whilst wind speed and fire season best explained burn efficiency. As for 2017 fires, fire intensity and flame height were best explained by fire season alone, while heat released and burn efficiency were best predicted by fire season, pre-fire biomass and dicot percentage. LF were more intense, consumed more fuel and released more heat than MF. This indicates that season, time since last fire and local conditions that facilitate fuel loading might all be crucial in determining fire behavior. Therefore, frequent (< 4 yrs.) prescribed burns in the early-dry season should be used to prevent the occurrence of intense wildfires in areas with quick fuel build-up.Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)2019-11-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistaeletronica.icmbio.gov.br/BioBR/article/view/123310.37002/biodiversidadebrasileira.v9i1.1233Biodiversidade Brasileira ; v. 9 n. 1 (2019): Wildfire Conference: Resumos; 91Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 91Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 912236-288610.37002/biodiversidadebrasileira.v9i1reponame:Biodiversidade Brasileirainstname:Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)instacron:ICMBIOenghttps://revistaeletronica.icmbio.gov.br/BioBR/article/view/1233/737Copyright (c) 2019 Os autores mantêm os direitos autorais de seus artigos sem restrições, concedendo ao editor direitos de publicação não exclusivos.https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessdos Santos, Ana Carlada Rocha Montenegro, SamuelBelloni Schmidt, Isabel2023-05-09T12:56:02Zoai:revistaeletronica.icmbio.gov.br:article/1233Revistahttps://revistaeletronica.icmbio.gov.br/BioBRPUBhttps://revistaeletronica.icmbio.gov.br/BioBR/oaifernanda.oliveto@icmbio.gov.br || katia.ribeiro@icmbio.gov.br2236-28862236-2886opendoar:2023-05-09T12:56:02Biodiversidade Brasileira - Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)false
dc.title.none.fl_str_mv Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
title Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
spellingShingle Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
dos Santos, Ana Carla
title_short Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
title_full Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
title_fullStr Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
title_full_unstemmed Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
title_sort Fire Season and fuel Load Predict Fire Behavior in Open Savannas in Northern Cerrado
author dos Santos, Ana Carla
author_facet dos Santos, Ana Carla
da Rocha Montenegro, Samuel
Belloni Schmidt, Isabel
author_role author
author2 da Rocha Montenegro, Samuel
Belloni Schmidt, Isabel
author2_role author
author
dc.contributor.author.fl_str_mv dos Santos, Ana Carla
da Rocha Montenegro, Samuel
Belloni Schmidt, Isabel
description Fire is one of the main factors determining the structure of mesic savannas like the Brazilian Cerrado. Its plant species have evolved with fire for millions of years, but intense human use in the past century has been threatening biodiversity. Until recently, the governmental strategy to cope with it has been fire exclusion, which leads to grassy fuel loading and intensification of late-dry season wildfires. A fire management program was established since 2014 in some Protected Areas (PA) to try to solve the problem, including a series of practices such as late-wet and early-dry season prescribed burns. However, the behavior of these fires had not been characterized prior to this study, so our aim was to do so to inform PA staff decision making. We set up seven 50 x 100 m plots for each of the burning treatments: biennial early-dry season management fires (MF) and late-dry season fires (LF). Fires were lit in 2015 and 2017 in the same plots. For each burn, we calculated fire intensity, heat released, burn efficiency and flame height (only for 2017 fires). We fit linear models for each of these variables, considering fire season, pre-fire biomass, air humidity, wind speed and percentage of dicots in the fine fuel (only for 2017 fires) as explanatory variables (p ≤ 0.05). We compared AICc values to select the fittest models for each parameter. Considering all fires, fire intensity and heat released were best explained by pre-fire biomass and fire season, whilst wind speed and fire season best explained burn efficiency. As for 2017 fires, fire intensity and flame height were best explained by fire season alone, while heat released and burn efficiency were best predicted by fire season, pre-fire biomass and dicot percentage. LF were more intense, consumed more fuel and released more heat than MF. This indicates that season, time since last fire and local conditions that facilitate fuel loading might all be crucial in determining fire behavior. Therefore, frequent (< 4 yrs.) prescribed burns in the early-dry season should be used to prevent the occurrence of intense wildfires in areas with quick fuel build-up.
publishDate 2019
dc.date.none.fl_str_mv 2019-11-15
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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dc.identifier.uri.fl_str_mv https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1233
10.37002/biodiversidadebrasileira.v9i1.1233
url https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1233
identifier_str_mv 10.37002/biodiversidadebrasileira.v9i1.1233
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistaeletronica.icmbio.gov.br/BioBR/article/view/1233/737
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)
publisher.none.fl_str_mv Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio)
dc.source.none.fl_str_mv Biodiversidade Brasileira ; v. 9 n. 1 (2019): Wildfire Conference: Resumos; 91
Biodiversidade Brasileira ; Vol. 9 No. 1 (2019): Wildfire Conference: Resumos; 91
Biodiversidade Brasileira ; Vol. 9 Núm. 1 (2019): Wildfire Conference: Resumos; 91
2236-2886
10.37002/biodiversidadebrasileira.v9i1
reponame:Biodiversidade Brasileira
instname:Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
instacron:ICMBIO
instname_str Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
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institution ICMBIO
reponame_str Biodiversidade Brasileira
collection Biodiversidade Brasileira
repository.name.fl_str_mv Biodiversidade Brasileira - Instituto Chico Mendes de Conservação da Biodiversidade (ICMBIO)
repository.mail.fl_str_mv fernanda.oliveto@icmbio.gov.br || katia.ribeiro@icmbio.gov.br
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