摘要：In preparation for the deployment of a new mechanism that could address as much as one fifth of
global greenhouse gas emissions by reducing emissions from deforestation and forest degradation (REDD +), important work on methodological issues is still needed to secure the capacity
to produce measurable, reportable, and verifiable emissions reductions from
REDD + in developing countries. To contribute to this effort, we have diagnosed the main sources of
uncertainty in the quantification of emission from deforestation for Panama, one of the first
countries to be supported by the Forest Carbon Partnership Facility of the World Bank
and by UN-REDD. Performing sensitivity analyses using a land-cover change emissions
model, we identified forest carbon stocks and the quality of land-cover maps as the key
parameters influencing model uncertainty. The time interval between two land-cover
assessments, carbon density in fallow and secondary forest, and the accuracy of
land-cover classifications also affect our ability to produce accurate estimates.
Further, we used the model to compare emission reductions from five different
deforestation reduction scenarios drawn from governmental input. Only the scenario
simulating a reduction in deforestation by half succeeds in crossing outside the
confidence bounds surrounding the baseline emission obtained from the uncertainty
analysis. These results suggest that with current data, real emission reductions in
developing countries could be obscured by their associated uncertainties. Ways of
addressing the key sources of error are proposed, for developing countries involved in
REDD + ,
for improving the accuracy of their estimates in the future. These new considerations confirm the
importance of current efforts to establish forest monitoring systems and enhance capabilities for
REDD + in developing countries.
