Long temporal trend and seasonal variation analysis of forest fires in Brazilian biomes: A stochastic approach




Palabras clave:

Bayesian modeling, Brazilian biomes, long-term trends, Poisson model, stochastic variation, wildfires


This study uses a Bayesian Structural Poisson model to address the increasing frequency of wildfires in Brazilian biomes. Long-term trends, seasonal behavior, and the impact of certain meteorological variables on the occurrence of forest fires were identified in the following biomes: Amazon, Caatinga, Cerrado, Atlantic Forest, Pampa, and Pantanal. Nonlinear temporal trends were observed in all biomes, with varying annual increments between 1999-2020: 5.5 % in Pampa, 4.9 % in Pantanal, 3.0 % in Caatinga, 2.3 % in Amazon, 2.2 % in Atlantic Forest, and 2.2 % in Cerrado. Seasonal patterns were present in all biomes, with similarities among the Amazon, Caatinga, Cerrado, and Atlantic Forest, while the Pampa and Pantanal displayed a bimodal pattern. Environmental factors such as evapotranspiration, precipitation, and temperature had significant effects on fire occurrence in different biomes. The findings of this study contribute valuable insights into fire patterns and their relationships with environmental factors in Brazilian biomes, helping to inform fire management and prevention strategies.


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Cómo citar

Villar, Bartolo de Jesús, Paulino Pérez Rodríguez, y Amaury de Souza. 2024. «Long Temporal Trend and Seasonal Variation Analysis of Forest Fires in Brazilian Biomes: A Stochastic Approach». Revista Mexicana De Ciencias Forestales 15 (84). México, ME:29-53. https://doi.org/10.29298/rmcf.v15i84.1402.



Artículo Científico