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Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates

CONTEXT: Wildfires play a crucial role in maintaining ecological and societal functions of North American boreal forests. Because of their contagious way of spreading, using statistical methods dealing with spatial autocorrelation has become a major challenge in fire studies analyzing how environmen...

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Detalles Bibliográficos
Autores principales: Portier, Jeanne, Gauthier, Sylvie, Robitaille, André, Bergeron, Yves
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954029/
https://www.ncbi.nlm.nih.gov/pubmed/31983808
http://dx.doi.org/10.1007/s10980-017-0578-8
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author Portier, Jeanne
Gauthier, Sylvie
Robitaille, André
Bergeron, Yves
author_facet Portier, Jeanne
Gauthier, Sylvie
Robitaille, André
Bergeron, Yves
author_sort Portier, Jeanne
collection PubMed
description CONTEXT: Wildfires play a crucial role in maintaining ecological and societal functions of North American boreal forests. Because of their contagious way of spreading, using statistical methods dealing with spatial autocorrelation has become a major challenge in fire studies analyzing how environmental factors affect their spatial variability. OBJECTIVES: We aimed to demonstrate the performance of a spatially explicit method accounting for spatial autocorrelation in burn rates modelling, and to use this method to determine the relative contribution of climate, physical environment and vegetation to the spatial variability of burn rates between 1972 and 2015. METHODS: Using a 482,000 km(2) territory located in the coniferous boreal forest of eastern Canada, we built and compared burn rates models with and without accounting for spatial autocorrelation. The relative contribution of climate, physical environment and vegetation to the burn rates variability was identified with variance partitioning. RESULTS: Accounting for spatial autocorrelation improved the models’ performance by a factor of 1.5. Our method allowed the unadulterated extraction of the contribution of climate, physical environment and vegetation to the spatial variability of burn rates. This contribution was similar for the three groups of factors. The spatial autocorrelation extent was linked to the fire size distribution. CONCLUSIONS: Accounting for spatial autocorrelation can highly improve models and avoids biased results and misinterpretation. Considering climate, physical environment and vegetation altogether is essential, especially when attempting to predict future area burned. In addition to the direct effect of climate, changes in vegetation could have important impacts on future burn rates. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10980-017-0578-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-69540292020-01-23 Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates Portier, Jeanne Gauthier, Sylvie Robitaille, André Bergeron, Yves Landsc Ecol Research Article CONTEXT: Wildfires play a crucial role in maintaining ecological and societal functions of North American boreal forests. Because of their contagious way of spreading, using statistical methods dealing with spatial autocorrelation has become a major challenge in fire studies analyzing how environmental factors affect their spatial variability. OBJECTIVES: We aimed to demonstrate the performance of a spatially explicit method accounting for spatial autocorrelation in burn rates modelling, and to use this method to determine the relative contribution of climate, physical environment and vegetation to the spatial variability of burn rates between 1972 and 2015. METHODS: Using a 482,000 km(2) territory located in the coniferous boreal forest of eastern Canada, we built and compared burn rates models with and without accounting for spatial autocorrelation. The relative contribution of climate, physical environment and vegetation to the burn rates variability was identified with variance partitioning. RESULTS: Accounting for spatial autocorrelation improved the models’ performance by a factor of 1.5. Our method allowed the unadulterated extraction of the contribution of climate, physical environment and vegetation to the spatial variability of burn rates. This contribution was similar for the three groups of factors. The spatial autocorrelation extent was linked to the fire size distribution. CONCLUSIONS: Accounting for spatial autocorrelation can highly improve models and avoids biased results and misinterpretation. Considering climate, physical environment and vegetation altogether is essential, especially when attempting to predict future area burned. In addition to the direct effect of climate, changes in vegetation could have important impacts on future burn rates. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10980-017-0578-8) contains supplementary material, which is available to authorized users. Springer Netherlands 2017-10-24 2018 /pmc/articles/PMC6954029/ /pubmed/31983808 http://dx.doi.org/10.1007/s10980-017-0578-8 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research Article
Portier, Jeanne
Gauthier, Sylvie
Robitaille, André
Bergeron, Yves
Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title_full Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title_fullStr Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title_full_unstemmed Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title_short Accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
title_sort accounting for spatial autocorrelation improves the estimation of climate, physical environment and vegetation’s effects on boreal forest’s burn rates
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954029/
https://www.ncbi.nlm.nih.gov/pubmed/31983808
http://dx.doi.org/10.1007/s10980-017-0578-8
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