Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world

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dc.contributor.authorWillcock, Simon
dc.contributor.authorPhillips, Oliver L.
dc.contributor.authorPlatts, Philip J
dc.contributor.authorBalmford, Andrew
dc.contributor.authorBurgess, Neil D.
dc.contributor.authorLovett, Jon C.
dc.contributor.authorAhrends, Antje
dc.contributor.authorMbilinyi, Boniface
dc.contributor.authorLewis, Simon L.
dc.date.accessioned2022-05-19T14:37:48Z
dc.date.available2022-05-19T14:37:48Z
dc.date.issued2012-09-14
dc.description.abstractMonitoring 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.en_US
dc.identifier.urihttps://www.suaire.sua.ac.tz/handle/123456789/4195
dc.language.isoenen_US
dc.publisherPLOS ONEen_US
dc.subjectError-Bounded Landscapeen_US
dc.subjectRegionalen_US
dc.subjectCarbon Storageen_US
dc.subjectData-Deficient Areasen_US
dc.titleTowards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the worlden_US
dc.typeArticleen_US
dc.urlwww.plosone.orgen_US

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