Atmospheric Sciences Research Spotlight

Smoke Signals in the Amazon

Forest fires can occur naturally, but in the world's largest rain forest, fire can signal large-scale deforestation.

Source: Global Biogeochemical Cycles

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In the world’s largest rain forest, forest fires have increased in recent decades. The great Amazon rainforest in South America is typically resistant to fire because of damp foliage and the humid environment. However, scientists are seeing a surge in burning in the Amazon region, increasing carbon emissions into the atmosphere and affecting water cycles downstream of the Amazon River.

Researchers estimate that about 15% of the Amazon was deforested between 1976 and 2010. In that time, humans converted tropical forests and savannas to agricultural lands, sometimes using the slash-and-burn method, which makes an environment favorable to fires.

In a new study, van Marle et al. looked into the recent history of burning in the region from 1973 to 2014. Calculating the emissions from fires in the Amazon during that time and how much was connected to deforestation could help researchers better understand the impact of deforestation in the world’s largest tropical rain forest.

The researchers used human-observed data gathered by World Meteorological Organization weather stations positioned throughout the Amazon. These observations included daily records of visibility around the weather station, using landmarks to measure how clear the day was or if smoke impeded the view. The advantage of this data source is that it has a longer record than the satellite observations currently used to monitor fires around the globe.

Visibility can be negatively affected by pollution and by weather conditions, such as rain or fog,. Therefore, the scientists excluded rainy and foggy days from their data set and aggregated the observations from each weather station into a daily average, which made it easier to compare the data. From there the researchers created a monthly record across 41 years.

The visibility data were compared to satellite estimates of fire emissions, where total particulate matter was taken from the Global Fire Emissions Database and carbon monoxide was directly observed by the Measurements of Pollution in the Troposphere (MOPITT) satellite. Both particulate matter and carbon monoxide are products of forest fires. Finally, they compared the results to the net forest loss in the region, which comes from satellite data.

Fire estimates in the Amazon indicate that before 1987, fire-driven deforestation was relatively low. That changed rapidly in the 1990s when fire emissions increased overall but with substantial variability from year to year. Although the decrease in deforestation in the Brazilian Amazon is to some degree reflected in the data showing lower fire emissions more recently, drought years such as 2010 still show high fire emissions. After comparing their burning estimates to deforestation data sets, the scientists concluded that deforestation could explain 33% of the fire signals observed in the Amazon region.

The results of the study reveal that converting forest to agriculture began toward the end of the 1980s, then increased quickly through the next decade, causing more burning in the process. However, the authors are somewhat cautious in their conclusions, acknowledging that deforestation methods could have changed since the 1980s and thus that the link between deforestation and fire may have changed over time. They also acknowledge that the subjective nature of human observation data could cause variability in the data set.

The study remains a solid estimate of the number of forest fires caused by anthropogenic deforestation across several decades and will be useful to climate scientists tracking the amount of carbon being released into the atmosphere from this region. (Global Biogeochemical Cycles, doi:10.1002/2016GB005445, 2016)

—Alexandra Branscombe, Freelance Writer

© 2017. The authors. CC BY-NC-ND 3.0

Citation: Branscombe, A. (2017), Smoke signals in the Amazon, Eos, 98, doi:10.1029/2017EO065731. Published on 05 January 2017.