New Projections of Global Forest Carbon and Ecosystems at Risk for Increased Greenhouse Gas Emissions From Disturbance and Forest Degradation
Abstract
Widely cited forest carbon values from look-up tables and statistical correlations with aboveground biomass have proven to be inadequate to discern details of national carbon stocks in forest pools. Similarly, global estimates based on biome-average (tropical, temperate, boreal, etc.) carbon measurements are generally insufficient to support REDD incentives (Reductions in Emission from Deforestation in Developing countries). The NASA-CASA (Carnegie-Ames-Stanford Approach) ecosystem model published by Potter et al. (1999 and 2003) offers several unique advantages for carbon accounting that cannot be provided by conventional inventory techniques. First, CASA uses continuous satellite observations to map land cover status and changes in vegetation on a monthly time interval over the past 25 years. NASA satellites observe areas that are too remote or rugged for conventional inventory-based techniques to measure. Second, CASA estimates both aboveground and belowground pools of carbon in all ecosystems (forests, shrublands, croplands, and rangelands). Carbon storage estimates for forests globally are currently being estimated for the Cisco Planetary Skin open collaborative platform (www.planetaryskin.org ) in a new series of CASA model runs using the latest input data from the NASA MODIS satellites, from 2000 to the present. We have also developed an approach for detection of large-scale ecosystem disturbance (LSED) events based on sustained declines in the same satellite greenness data used for CASA modeling. This approach is global in scope, covers more than a decade of observations, and encompasses all potential categories of major ecosystem disturbance - physical, biogenic, and anthropogenic, using advanced methods of data mining and analysis. In addition to quantifying forest areas at various levels of risk for loss of carbon storage capacity, our data mining approaches for LSED events can be adapted to detect and map biophysically unsuitable areas for deforestation worldwide and to develop carbon risk scoring algorithms that can enable large scale finance for conservation and reforestation efforts globally.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2009
- Bibcode:
- 2009AGUFM.B24B..08K
- Keywords:
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- 0315 ATMOSPHERIC COMPOSITION AND STRUCTURE / Biosphere/atmosphere interactions;
- 0428 BIOGEOSCIENCES / Carbon cycling