Widespread Amazon forest tree mortality from a single cross-basin squall line event
Abstract
Climate change is expected to increase the intensity of extreme precipitation events in Amazonia that in turn might produce more forest blowdowns associated with convective storms. Yet quantitative tree mortality associated with convective storms has never been reported across Amazonia, representing an important additional source of carbon to the atmosphere. Here we demonstrate that a single squall line (aligned cluster of convective storm cells) propagating across Amazonia in January, 2005, caused widespread forest tree mortality and may have contributed to the elevated mortality observed that year. Forest plot data demonstrated that the same year represented the second highest mortality rate over a 15-year annual monitoring interval. Over the Manaus region, disturbed forest patches generated by the squall followed a power-law distribution (scaling exponent α = 1.48) and produced a mortality of 0.3-0.5 million trees, equivalent to 30% of the observed annual deforestation reported in 2005 over the same area. Basin-wide, potential tree mortality from this one event was estimated at 542 ± 121 million trees, equivalent to 23% of the mean annual biomass accumulation estimated for these forests. Our results highlight the vulnerability of Amazon trees to wind-driven mortality associated with convective storms. Storm intensity is expected to increase with a warming climate, which would result in additional tree mortality and carbon release to the atmosphere, with the potential to further warm the climate system.
- Publication:
-
Geophysical Research Letters
- Pub Date:
- August 2010
- DOI:
- 10.1029/2010GL043733
- Bibcode:
- 2010GeoRL..3716701N
- Keywords:
-
- Atmospheric Composition and Structure: Biosphere/atmosphere interactions (0426;
- 1610);
- Biogeosciences: Carbon cycling (4806);
- Atmospheric Processes: Convective processes;
- Atmospheric Processes: Land/atmosphere interactions (1218;
- 1631;
- 1843);
- Biogeosciences: Remote sensing