Forest degradation causes environmental damage and carbon emissions, but its extent and magnitude are not well understood. New methods for monitoring forest degradation and deforestation show that more disturbance has occurred in the Amazon in recent decades than previously realized, indicating an unaccounted for source of carbon emissions and damage to Amazon ecosystems.
Forest degradation and natural disturbance change a landscape, but the visible damage apparent in satellite images may be temporary and difficult to differentiate from undisturbed forests. Time series analysis of Landsat data used in a spectral mixture analysis improves monitoring of forest degradation and natural disturbance. In addition, the use of statistical inference accounts for classification bias and provides an estimate of uncertainty.
Application of the methodology developed in this dissertation to the Amazon Ecoregion found that forest degradation and natural disturbance were more prevalent than deforestation from 1995 to 2017. Of consequence, the total area of forest in the Amazon that has been recently disturbed is greater than previously known. Overall, deforestation affected 327,900 km2 (±15,500) of previously undisturbed forest in the Amazon while degradation and natural disturbance affected 434,500 km2 (±22,100). Forest degradation and natural disturbance occur more frequently during drought years, which have increased in frequency and severity in recent years. Deforestation has largely decreased since 2004, while forest degradation and natural disturbance have remained consistent.
Previously disturbed forests are lower in biomass than undisturbed forests, yet regeneration after disturbance gradually sequesters carbon. A carbon flux model shows that gross aboveground carbon loss from forest degradation and natural disturbance and deforestation from 1996 to 2017 in the Amazon were 2.2-2.8 Pg C and 3.3-4.3 Pg C, respectively. Since 2008, however, carbon loss from degradation and natural disturbance has been approximately the same as from deforestation.
The methodologies developed in this dissertation are useful for monitoring deforestation and degradation throughout the world’s forest ecosystems. By leveraging dense data time series, statistical inference, and carbon modeling it is possible to quantify areas of deforestation and forest degradation in addition to the resulting carbon emissions. The results of this dissertation stress the importance of degradation and natural disturbance in the global carbon cycle and information valuable for climate science and conservation initiatives.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/39522 |
| Date | 10 February 2020 |
| Creators | Bullock, Eric L. |
| Contributors | Woodcock, Curtis |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution-NonCommercial-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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