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.
Highlights
Land cover change is known to make up a significant proportion of global greenhouse gas emissions
A broad agreement within the United Nations Framework Convention on Climate Change (UNFCCC) was reached to implement a scheme titled ‘Reducing Emissions from Deforestation and Forest Degradation’ (REDD) as a means to encourage the reduction of these emissions, later expanding the schemes’ scope to include the sustainable management of forests and the conservation and enhancement of forest carbon stocks, termed REDD+ [7]
Overview The method follows seven stages (Figure 2), summarised here and described in detail below: (1) Obtain a land cover map for the region to identify land cover categories; (2) Systematically search for regionally appropriate carbon estimates, including identical land cover types from nearby regions, for all five Intergovernmental Panel on Climate Change (IPCC) carbon pools for each land cover category; (3) Match studies to land cover categories; (4) If data for carbon pools are missing or sparse, systematically search for ratios by which they can be calculated from other carbon pools with adequate data coverage; (5) Weight by sampling effort; (6) Weight by distance from the focal region; (7) Produce median and 95% confidence intervals (CI) using re-sampling techniques
Summary
Land cover change is known to make up a significant proportion of global greenhouse gas emissions. A broad agreement within the United Nations Framework Convention on Climate Change (UNFCCC) was reached to implement a scheme titled ‘Reducing Emissions from Deforestation and Forest Degradation’ (REDD) as a means to encourage the reduction of these emissions, later expanding the schemes’ scope to include the sustainable management of forests and the conservation and enhancement of forest carbon stocks, termed REDD+ [7]. Many developing countries lack the data to perform some of the recommended carbon accounting methods [7] and as such often resort to so-called ‘Tier 1’ analyses using global default carbon storage values for given land cover types [11,12]. Carbon stock is known to vary spatially on IPCC term Tier 1 Tier 2 Tier 3 Aboveground live carbon Coarse woody debris carbon
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