Forest Understory Fire in the Brazilian Amazon in ENSO and Non-ENSO Years: Area Burned and Committed Carbon Emissions

Abstract

Understory fires, which burn the floor of standing forests, are one of the most important types of forest impoverishment in the Amazon, especially during the severe droughts of El Niño–Southern Oscillation (ENSO) episodes. However, the authors are aware of no estimates of the areal extent of these fires for the Brazilian Amazon and, hence, of their contribution to Amazon carbon fluxes to the atmosphere. In this paper, the area of forest understory fires for the Brazilian Amazon region is calculated during an El Niño (1998) and a non–El Niño (1995) year based on forest fire scars mapped with satellite images for three locations in eastern and southern Amazonia, where deforestation is concentrated. The three study sites represented a gradient of both forest types and dry season severity. The burning scar maps were used to determine how the percentage of forest that burned varied with distance from agricultural clearings. These spatial functions were then applied to similar forest/climate combinations outside of the study sites to derive an initial estimate for the Brazilian Amazon. Ninety-one percent of the forest area that burned in the study sites was within the first kilometer of a clearing for the non-ENSO year and within the first four kilometers for the ENSO year. The area of forest burned by understory forest fire during the severe drought (ENSO) year (3.9 × 106 ha) was 13 times greater than the area burned during the average rainfall year (0.2 × 106 ha), and twice the area of annual deforestation. Dense forest was, proportionally, the forest type most affected by understory fires during the El Niño year, while understory fires were concentrated in transitional forests during the year of average rainfall. The estimate here of aboveground tree biomass killed by fire ranged from 0.049 to 0.329 Pg during the ENSO and from 0.003 to 0.021 Pg during the non-ENSO year.

Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome

“…The greatest and least number of fires occurred in 2005 and 2009, respectively. The large number of fires in 2005 has been observed by other researchers (Alencar, Nepstad, and Diaz 2006;Morton et al 2008;Silvestrini et al 2011) and is thought to be related to the extensive drought in that year (Espinoza et al 2011;Lewis et al 2011) when drier conditions increased the probability of escaped agricultural maintenance fires Nepstad et al 2001;Alencar, Solórzano, and Nepstad 2004;Alencar, Nepstad, and Diaz 2006) and opportunistic setting of fires to clear forested land (Araujo et al 2009(Araujo et al , 2010. From 2003 to 2010, deforestation decreased by almost 75% (Assunção, Gandour, and Rocha 2013;PRODES 2013;Souza et al 2013), likely associated with the promulgation of a 2008 government deforestation policy and the transparency offered by Brazilian satellite-based forest monitoring efforts (Nepstad et al 2009;Assunção, Gandour, and Rocha 2013).…”

“…The forest fire type had similar user's and producer's accuracies of 88.4% and 87.5%, respectively, with 11.6% and 0.87% of the forest fire training data misclassified as maintenance and deforestation fire types, respectively. The greater relative confusion between the maintenance and forest fire types is somewhat expected as maintenance fires and forest fires may burn similar low fuel loads and so may exhibit similar fire behavior Alencar, Solórzano, and Nepstad 2004;Alencar, Nepstad, and Diaz 2006). The deforestation fire type had the lowest producer's and user's accuracies of 75% and 88.7%, respectively.…”

“…Forest fires initially burn the forest litter, and the fires burn slowly (as little as 150 m per day) with low energy (flame heights no more than 10 cm) and are usually extinguished when the relative humidity increases in the evening, although smoldering woody debris may reignite weeks later if the conditions are conducive (Cochrane and Schulze 1998;Cochrane and Laurance 2002). In subsequent years, especially in drought years, a significant proportion of the forest biomass and not just the understory may also burn Alencar, Solórzano, and Nepstad 2004;Alencar, Nepstad, and Diaz 2006;Aragão and Shimabukuro 2010;Alencar et al 2011). In addition to emissions estimation, information on the timing, location and incidence of the different fire types are important for policy-makers and regulatory bodies to monitor and regulate the use of fire GOFC-GOLD 2010) and to provide insights into post-disturbance land management practices and vegetation dynamics that can be difficult to infer in the region (Ramankutty et al 2007;Laurance et al 2011).…”

“…Attribution of fire type to mapped burned pixels remains a research issue and has mainly been concerned with inferring the spatial extent of understory fires (Alencar, Nepstad, and Diaz 2006;Shimabukuro et al 2010;Morton et al 2013).…”

“…Previously, satellite active fire detection fire types have been inferred using different techniques including the geographic context and proximity of satellite active fire detections relative to thematic land cover classes, roads, and forest edges (Nepstad et al 2001;Schroeder et al 2005;Alencar, Nepstad, and Diaz 2006;Giglio 2007;Ten Hoeve et al 2012;Chen, Morton, et al 2013) and by consideration of the temporal persistence of satellite active fire detections Le Page et al 2010;Chen, Morton, et al 2013). These approaches have not been validated, and are expected to be less useful when new isolated forest areas are burned and because thematic land cover classes, roads, and forest edges may not be reliably mapped.…”