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Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions

Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been develo...

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Detalles Bibliográficos
Autores principales: De Angelis, Antonella, Ricotta, Carlo, Conedera, Marco, Pezzatti, Gianni Boris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332634/
https://www.ncbi.nlm.nih.gov/pubmed/25679957
http://dx.doi.org/10.1371/journal.pone.0116875
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author De Angelis, Antonella
Ricotta, Carlo
Conedera, Marco
Pezzatti, Gianni Boris
author_facet De Angelis, Antonella
Ricotta, Carlo
Conedera, Marco
Pezzatti, Gianni Boris
author_sort De Angelis, Antonella
collection PubMed
description Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition.
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spelling pubmed-43326342015-02-24 Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions De Angelis, Antonella Ricotta, Carlo Conedera, Marco Pezzatti, Gianni Boris PLoS One Research Article Fire regimes are strongly related to weather conditions that directly and indirectly influence fire ignition and propagation. Identifying the most important meteorological fire drivers is thus fundamental for daily fire risk forecasting. In this context, several fire weather indices have been developed focussing mainly on fire-related local weather conditions and fuel characteristics. The specificity of the conditions for which fire danger indices are developed makes its direct transfer and applicability problematic in different areas or with other fuel types. In this paper we used the low-to-intermediate fire-prone region of Canton Ticino as a case study to develop a new daily fire danger index by implementing a niche modelling approach (Maxent). In order to identify the most suitable weather conditions for fires, different combinations of input variables were tested (meteorological variables, existing fire danger indices or a combination of both). Our findings demonstrate that such combinations of input variables increase the predictive power of the resulting index and surprisingly even using meteorological variables only allows similar or better performances than using the complex Canadian Fire Weather Index (FWI). Furthermore, the niche modelling approach based on Maxent resulted in slightly improved model performance and in a reduced number of selected variables with respect to the classical logistic approach. Factors influencing final model robustness were the number of fire events considered and the specificity of the meteorological conditions leading to fire ignition. Public Library of Science 2015-02-13 /pmc/articles/PMC4332634/ /pubmed/25679957 http://dx.doi.org/10.1371/journal.pone.0116875 Text en © 2015 De Angelis et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
De Angelis, Antonella
Ricotta, Carlo
Conedera, Marco
Pezzatti, Gianni Boris
Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title_full Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title_fullStr Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title_full_unstemmed Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title_short Modelling the Meteorological Forest Fire Niche in Heterogeneous Pyrologic Conditions
title_sort modelling the meteorological forest fire niche in heterogeneous pyrologic conditions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4332634/
https://www.ncbi.nlm.nih.gov/pubmed/25679957
http://dx.doi.org/10.1371/journal.pone.0116875
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