Global Vegetation biomass carbon stocks - 1 km resolution

This global gridded dataset depicts vegetation biomass carbon stocks at the native processing resolution of 0.0089 decimal degrees (~1km by ~1km). We used the mean aggregate ArcInfo command to resample this dataset to 5 and 10 minute spatial resolution (please note that the 10 minute data includes the extent of Antarctica, while the others do not). The 1km data is expressed in 0.01 tons of biomass carbon per hectare, while the 5 and 10 minute data are expressed in tons of biomass carbon per hectare; soil carbon stocks are not included. Each map is geo-referenced to the WGS1984 coordinate system, and in geographic projection.

The vegetation biomass carbon database was created in two main steps: 1) estimate
carbon stocks, and 2) map values using a range of spatiallyexplicit climate and vegetation datasets. Creators followed the IPCC GPG Tier1 method for estimating vegetation carbon stocks using the globally consistent default values provided for aboveground biomass (IPCC 2006). They added belowground biomass (root) carbon stocks using the IPCC root to shoot ratios for each vegetation type, and then converted total living vegetation biomass to carbon stocks using the carbon fraction for each vegetation type (varies between forests, shrublands and grasslands). All estimates and conversions were specific to each continent, ecoregion and vegetation type (stratified by age of forest). Thus, we compiled a total of 124 carbon zones
or regions with unique carbon stock values based on the IPCC Tier1 methods. Please refer to Tables 1a-i (http://cdiac.ornl.gov/epubs/ndp/global_carbon/carbon_documentation.html)
to review the details associated with each of these carbon zones. A small number
of carbon zones were not included in the original IPCC default data but were in the land
cover map such as mixed and burnt forest and natural vegetation/cropland mosaic categories.

The continental regions, ecofloristic zones, and frontier forest shapefiles were combined to
determine the spatial distribution of global carbon_zones. These data were then gridded and
combined with the GLC2000 data. An ESRI ArcInfo script was used to apply the associated
carbon values to each pixel within a carbon zone. Specifically, we clipped out the carbon
zone boundaries from the GLC2000 gridded land cover data and then used a series of carbon
remap tables, created from the values listed in tables 1a1i, to assign carbon values to the gridded data. These clipped GLC2000 carbon zone grids were then
merged back together to form a single contiguous global dataset at 1 kilometer by 1 kilometer
resolution.

This spatial database is likely the best available, globally consistent
map depicting vegetation carbon stocks, circa 2000, and follows the widely accepted IPCC methods for estimating carbon stocks at the national level. However, the methods employed here are not directly linked to groundbased measures of carbon stocks and have not been validated with field data. We essentially applied a sophisticated paint-by-numbers
approach, which consequently masks variations within classes and may lead to unnatural, abrupt gradients between vegetation classes as defined by the GLC 2000 and FAO ecoregions (Gibbs et al. 2007).