Johanne Pelletier and her colleagues from McGill University have, for the first time, looked at the uncertainty and detectability of emissions reductions for REDD+ for an entire country – Panama. They chose Panama because it is one of the first countries to be selected for funding by the Forest Carbon Partnership Facility of the World Bank and the UN-REDD initiative and it is currently starting its readiness phase for REDD+.

The researchers found errors of up to 50% when compared with a reference emissions level, with the primary source of error being the mature forest carbon stock estimates. "The problem is that the data available in Panama was not collected for REDD, but for other purposes, making it unsuitable for REDD estimates," Pelletier told environmentalresearchweb. "Without better data it will be hard for a country like Panama to fully benefit from REDD."

Pelletier and the team found that other factors which contribute to uncertainty in land-cover change emissions include historical map quality, land-cover classification accuracy, the time interval between two land-cover assessments, and unavailability of data regarding fallow carbon stocks.

"Producing an accurate satellite map of Panama is challenging because of cloud cover," said Pelletier. "We found that the maps that were made available to us, which were ostensibly from 1992 and 2000, were in fact mosaics made up of images from a range of different years." One solution to this problem would be to use radar images instead, which, although more expensive, would be possible for Panama because it is a relatively small country.

The conclusion from Pelletier's research is that under current capabilities, Panama would most likely produce estimates that are too uncertain to allow a clear detection of emission reductions. "We found that much of the deforestation reduction would produce emission reductions that are not distinguishable from errors," said Pelletier. "So, even if deforestation reduction is effective, it could be argued that these perceived emission reductions are simply due to errors in estimates."

Pelletier hopes the series of recommendations in her paper will help countries to improve the accuracy and precision of their emission estimates from deforestation in a cost-effective way and that tackling these main sources of error could greatly improve the overall accuracy in the future.

The researchers published their research in Environmental Research Letters (ERL).