Spatiotemporal variation in fire occurrence in the state of Amazonas, Brazil, between 2003 and 2016

Abstract

Wildland fires can be responsible for negative impacts on the environment, causing damage to the fauna and flora and increasing the release of greenhouse gases. In the state of Amazonas, wildland fires represent a risk for biodiversity conservation, since more than 95% of the state is covered by Amazon rainforest, one of the largest and most biodiverse tropical forests of the world. This study aimed to analyze the spatiotemporal variation of fire occurrence from 2003 to 2016 in the state of Amazonas, based on data from the AQUA satellite processed by the Brazilian National Institute for Space Research, using the “Collection 5” detection algorithm. The correlation between fire incidence versus anthropogenic and climatic variables was also tested. A significant uptrend was observed in the number of hot spots recorded over the years. About 83% of the wildland fires occurred during the months of August, September and October. The variables that correlated significantly with the number of hot spots for each municipality were deforested area, pasture area, agricultural area, municipality area and mean annual rainfall. The municipality with the highest number of hot spots detected was Lábrea, while Careiro da Várzea presented the highest incidence per km2. The southern and eastern regions of the state were the areas most affected by fire during the analyzed period. The results from this study emphasize the need for implementation of public policies aimed to reduce deforestation and wildland fires in the state, thus ensuring the conservation of the Amazon rainforest and its biodiversity.

Satellite Detection of Wildland Fires in South America

“…The variation in the number and density of hot spots detected throughout the South America countries is due to the differences on cultural aspects of the population and on environmental factors that influence fire propagation such as weather conditions, vegetation and topography (SOARES;BATISTA, 2007;WHITE;WHITE, 2016). In a similar study done in the state of Amazonas, Brazil, for example, White (2018) concluded that the municipalities with the highest number of hot spots detected were the ones that presented the largest deforested, pasture and agricultural areas; and were the ones with the lowest mean annual rainfall. According to the same author, the cultural practice of using fire for clearing forests, pastures and agricultural areas during the driest months of the year and, most of the time, without using fire safety measurements, is responsible for a large number of high intensity wildfires that are easily detected by satellite sensors.…”

“…In such ecosystems, the incidence of solar radiation in the understory is reduced by the canopy cover and the air humidity is high due to the evapotranspiration of the trees. Consequently, the moisture content of the fuel load is usually high, making it difficult for a fire to ignite and propagate (WHITE;SILVA, 2018).…”

“…Also, they leave the soil more susceptible to erosion while releasing large amounts of greenhouse gases (SOARES;BATISTA, 2007). Although there are some ecosystems fire dependent, such as Savannas and the Brazilian Cerrado, where species have adapted to living in fire-prone environments, the exclusion or increase in fire frequency can also have negative environmental impacts (WHITE;WHITE, 2016). Moreover, the smoke often causes problems for human health, especially respiratory complications and represents, in some locations, a public health issue.…”

“…Additionally, fire detection may also be restricted when fires started and ended during the interval between the satellite passage; by the presence of dense clouds above the burning area; surface fire under closed canopy vegetation; and fire on mountainsides opposite to the satellite observation path (PEREIRA et al 2012;INPE 2018). Therefore, the number of wildland fires recorded corresponds with only a part of the total number (BATISTA, 2004;WHITE;WHITE, 2016;WHITE, 2018).…”

Spatiotemporal Variation of Fire Occurrence in the State of Bahia, Brazil, Between 2003 and 2019

“…These variables were chosen due to availability of historical data and because they have been shown to influence the wildland fire occurrence (e.g. Ajin et al, 2016;Suryabhagavan et al, 2016;White, 2018b).…”