Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites

We have a new paper in Global Ecology and Biogeography that explores how satellite maps of the biomass of Amazonian forests compare to our extensive ground inventory network RAINFOR. 

Mitchard E.T.A. et al. (2014) Markedly divergent estimates of Amazon forest carbon density from ground plots and satellites. Global Ecology and Biogeography, DOI: 10.1111/geb.12168

The accurate mapping of forest carbon stocks is essential for understanding the global carbon cycle, for assessing emissions from deforestation, and for rational land-use planning. Satellite remote sensing maps are currently a key tool for this purpose, but remote sensing does not estimate vegetation biomass directly, and thus may miss significant spatial variations in forest structure. We test the stated accuracy of pantropical carbon maps using a large independent field dataset, the RAINFOR forest inventory dataset.

Two recent pantropical remote sesnsing maps of vegetation carbon (from Saatchi et al. and Baccini et al.) were compared to the RAINFOR ground-plot dataset, involving tree measurements in 413  inventory plots located in nine countries. The remote-sening maps were compared directly to field plots, and kriging of the field data was used to allow area-based comparisons.

The study finds that the two remote sensing carbon maps fail to capture the main gradient in Amazon forest biomass, from the densely wooded tall forests of the north-east, to the light-wooded, shorter forests of the south-west. The differences between plots and RS maps far exceed the uncertainties given in these studies, with whole regions over- or under-estimated by > 25%, whereas regional uncertainties for the maps were reported to be < 5%.

Pantropical biomass maps are widely used by governments and by projects aiming to reduce deforestation using carbon offsets, but we conclude that they may have significant regional biases. Carbon-mapping techniques must be revised to account for the known ecological variation in tree wood density and allometry to create maps suitable for carbon accounting. The use of single relationships between tree canopy height and above-ground biomass inevitably yields large, spatially correlated errors. This presents a significant challenge to both the forest conservation and remote sensing communities, because neither wood density nor species assemblages can be reliably mapped from space.

 The permanent archive of the field plot data can be accessed at: http://dx.doi.org/10.5521/FORESTPLOTS.NET/ 2014_1