Lightning patterns in the Pantanal: Untangling natural and anthropogenic-induced wildfires

Abstract

The identification of fire causes and characteristics is of fundamental importance to better understand fire regimes and drivers. Particularly for Brazil, there is a gap in the quantification of lightning-caused fires. Accordingly, this work is a novel probabilistic assessment of the spatial-temporal patterns of lightning-ignited wildfires in the Pantanal wetland. Here, remote sensing information such as VIIRS active fires, MODIS burned area (BA) and STARNET lightning observations from 2012 to 2017, were combined to estimate the location, number of scars and amount of BA associated with atmospheric discharges on a seasonal basis. The highest lightning activity occurs during summer (December–February), and the lowest during winter (June–August). Conversely, the highest fire activity occurred during spring (September–November) and the lowest during autumn (March–May). Our analysis revealed low evidence of an association between fires and lightning, suggesting that human-related activities are the main source of ignitions. Weak evidence of natural-caused fire occurrence is conveyed by the low spatial-temporal match of lightning and fire throughout the studied period. Natural-caused fires accounted for only 5% of the annual total scars and 83.8% of the BA was human-caused. Most of the fires with extension larger than 1000 ha were not related to lighting. Lightning-fires seem an important element of the summer fire regime given that around half of the total BA during this season may be originated by lightning. By contrast, in the rest of the year the lightning-fires represent a minor percentage of the fire activity in the region. The density of lightning-ignited fires varies considerably, being higher in the north part of the Pantanal. This work provides a basis for a better understanding of lightning-related fire outbreaks in tropical ecosystems, particularly wetlands, which is fundamental to improve region-based strategies for land management actions, ecological studies and modeling climatic and anthropogenic drivers of wildfires.