AUTHOR=Ferreira Igor J. M. , Campanharo Wesley A. , Barbosa Maria L. F. , Silva Sonaira S. da , Selaya Galia , Aragão Luiz E. O. C. , Anderson Liana O. 

TITLE=Assessment of fire hazard in Southwestern Amazon

JOURNAL=Frontiers in Forests and Global Change

VOLUME=Volume 6 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/forests-and-global-change/articles/10.3389/ffgc.2023.1107417

DOI=10.3389/ffgc.2023.1107417

ISSN=2624-893X

ABSTRACT=Fires are among the main causes of forest degradation in Amazonia causing multiple socioeconomic and environmental damages. Although human-ignited sources account for most of the fire events in Amazonia, extended droughts may magnify its occurrence and propagation. The southwestern Amazonia, a transnational region shared by Brazil, Peru, and Bolivia known as MAP region, have been articulating co-ordinated actions to prevent disasters, including fire, in order to reduce their negative impacts. Therefore, to understand fire patterns in the MAP region, we investigated its main drivers and the changes in the suitability of fire occurrence for the years 2005, 2010, 2016 and 2020. We used a maximum entropy (MaxEnt) model approach based on active fire data, from satellites, climatic data and land use and land cover mapping to spatially quantify the suitability of fire occurrence and its drivers. We used the year 2015 to calibrate the models. For climatic data and active fire count, we only considered grid cells with active fire count over the third quartile. All our models had a satisfactory performance, with values of the Area Under the Curve (AUC) above 0.75 and p-value <0.05. Additionally, all models showed sensitivity rates higher than 0.8 and false positive rates below 0.25. We estimated that on average 38.5% of the study region had suitable conditions for fire occurrence during the study period. Most of the fire prone areas belong to Acre, representing about 74% of the entire MAP region. The percentage of deforested areas, productive lands, forest edges and high temperatures were the main drivers of fire occurrence in southwestern Amazonia, indicating the high vulnerability of fragmented landscapes under extreme climatic conditions to fire occurrence. We showed that the modelling approach based on MaxEnt is a useful tool for evaluating the implications of climatic and anthropogenic variables on fire distribution. Furthermore, because the model can be easily employed to predict suitable and non-suitable locations for fire occurrence, it can help anticipate planning to prevent potential impacts associated with large-scale wildfires in the future at regional levels.