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 tonnes 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 spatially explicit
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).