title: Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world.
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.
authors.affiliation: University of Leeds, Leeds, United Kingdom. gysw@leeds.ac.uk
authors.forename: Simon
authors.initials: S
authors.lastname: Willcock
authors.forename: Oliver L
authors.initials: OL
authors.lastname: Phillips
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Platts
authors.forename: Andrew
authors.initials: A
authors.lastname: Balmford
authors.forename: Neil D
authors.initials: ND
authors.lastname: Burgess
authors.forename: Jon C
authors.initials: JC
authors.lastname: Lovett
authors.forename: Antje
authors.initials: A
authors.lastname: Ahrends
authors.forename: Julian
authors.initials: J
authors.lastname: Bayliss
authors.forename: Nike
authors.initials: N
authors.lastname: Doggart
authors.forename: Kathryn
authors.initials: K
authors.lastname: Doody
authors.forename: Eibleis
authors.initials: E
authors.lastname: Fanning
authors.forename: Jonathan
authors.initials: J
authors.lastname: Green
authors.forename: Jaclyn
authors.initials: J
authors.lastname: Hall
authors.forename: Kim L
authors.initials: KL
authors.lastname: Howell
authors.forename: Rob
authors.initials: R
authors.lastname: Marchant
authors.forename: Andrew R
authors.initials: AR
authors.lastname: Marshall
authors.forename: Boniface
authors.initials: B
authors.lastname: Mbilinyi
authors.forename: Pantaleon K T
authors.initials: PK
authors.lastname: Munishi
authors.forename: Nisha
authors.initials: N
authors.lastname: Owen
authors.forename: Ruth D
authors.initials: RD
authors.lastname: Swetnam
authors.forename: Elmer J
authors.initials: EJ
authors.lastname: Topp-Jorgensen
authors.forename: Simon L
authors.initials: SL
authors.lastname: Lewis
mesh_terms: D002244:Carbon / Q000032:analysis*; D057231:Climate Change; D017753:Ecosystem; D005843:Geography; D007630:Kenya; D012987:Soil / Q000032:analysis* / Q000737:chemistry*; D013636:Tanzania
chemical_list: D012987:Soil; D002244:Carbon