A global forest growing stock, biomass and carbon map based on FAO statistics

Kindermann, G. ORCID: https://orcid.org/0000-0003-4297-1318, McCallum, I. ORCID: https://orcid.org/0000-0002-5812-9988, Fritz, S. ORCID: https://orcid.org/0000-0003-0420-8549, & Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769 (2008). A global forest growing stock, biomass and carbon map based on FAO statistics. Silva Fennica 42 (3) 387-396. 10.14214/sf.244.

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Abstract

Currently, information on forest biomass is available from a mixture of sources, including in-situ measurements, national forest inventories, administrative-level statistics, model outputs and regional satellite products. These data tend to be regional or national, based on different methodologies and not easily accessible. One of the few maps available is the Global Forest Resources Assessment (FRA) produced by the Food and Agriculture Organization of the United Nations (FAO 2005) which contains aggregated country-level information about the growing stock, biomass and carbon stock in forests for 229 countries and territories. This paper presents a technique to downscale the aggregated results of the FRA2005 from the country level to a half degree global spatial dataset containing forest growing stock; above/belowground biomass, dead wood and total forest biomass; and above-ground, below-ground, dead wood, litter and soil carbon. In all cases, the number of countries providing data is incomplete. For those countries with missing data, values were estimated using regression equations based on a downscaling model. The downscaling method is derived using a relationship between net primary productivity (NPP) and biomass and the relationship between human impact and biomass assuming a decrease in biomass with an increased level of human activity. The results, presented here, represent one of the first attempts to produce a consistent global spatial database at half degree resolution containing forest growing stock, biomass and carbon stock values. All results from the methodology described in this paper are available online at <www.iiasa.ac.at/Research/FOR/>.

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