Abstract
Field measurements demonstrate a carbon sink in the Amazon and Congo basins, but the cause of this sink is uncertain. One possibility is that forest landscapes are experiencing transient recovery from previous disturbance. Attributing the carbon sink to transient recovery or other processes is challenging because we do not understand the sensitivity of conventional remote sensing methods to changes in aboveground carbon density (ACD) caused by disturbance events. Here we use ultra-high-density drone lidar to quantify the impact of a blowdown disturbance on ACD in a lowland rain forest in Costa Rica. We show that the blowdown decreased ACD by at least 17.6%, increased the number of canopy gaps, and altered the gap size-frequency distribution. Analyses of a canopy-height transition matrix indicate departure from steady-state conditions. This event will initiate a transient sink requiring an estimated 24–49 years to recover pre-disturbance ACD. Our results suggest that blowdowns of this magnitude and extent can remain undetected by conventional satellite optical imagery but are likely to alter ACD decades after they occur.
Original language | English |
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Article number | 11279 |
Journal | Scientific Reports |
Volume | 11 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2021 |
Externally published | Yes |
Funding
Lidar collection in 2019 was supported by an award to JRK through the NSF Grants for Rapid Response Research (RAPID) program and by an award to SS and JRK from the National Aeronautics and Space Administration. The CARBONO Project was supported by grants from the NSF, most recently DEB-0841872, DEB-1357097. KCC was supported by an NSF Graduate Research Fellowship, the Brown Presidential Fellowship, the Institute at Brown for Environment and Society at Brown University, and the Department of Energy’s NGEE-Tropics Initiative.
Funders | Funder number |
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National Science Foundation | |
U.S. Department of Energy | |
National Aeronautics and Space Administration | DEB-0841872, DEB-1357097 |
Center for Selective C-H Functionalization, National Science Foundation | |
Center for Hierarchical Manufacturing, National Science Foundation |