Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world
Loading...
Date
2012-09-14
Journal Title
Journal ISSN
Volume Title
Publisher
PLOS ONE
Abstract
Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may
be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global
levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as ‘lowland
tropical forest’ are often used, termed ‘Tier 1 type’ analyses by the Intergovernmental Panel on Climate Change (IPCC). Such
estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading
to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate
land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon
storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter,
coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing
inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method
meets the IPCC ‘Tier 2’ reporting standard. We use this method to estimate carbon storage over an area of33.9 million
hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92–6.74) Pg
C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global
studies show a mean carbon storage value of ,50% of that reported using our regional values, with four of the five studies
reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of
Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows
how such values can be produced for a relatively low investment.
Description
Keywords
Error-Bounded Landscape, Regional, Carbon Storage, Data-Deficient Areas