Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (NDP-055)

Brown, S.

doi:10.2172/814661

Cited by 10 publications

(11 citation statements)

References 4 publications

(8 reference statements)

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“…We also overlaid this combined map over two regional maps produced by NASA for Southeast Asia and Tropical Africa (Brown and Gaston, 1996;Brown et al, 2001). The resulting estimates, also corrected for above-below ground biomass ratio (column 4 in Table 2), were averaged with the estimates from Potter's (1999) map to produce our average GIS estimate (column 5 in Table 2).…”

Section: Emissions Per Hectarementioning

confidence: 99%

Reducing emissions from deforestation—The “combined incentives” mechanism and empirical simulations

Strassburg

Turner

Fisher

et al. 2009

Global Environmental Change

163

119

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Section: Emissions Per Hectarementioning

confidence: 99%

Reducing emissions from deforestation—The “combined incentives” mechanism and empirical simulations

Strassburg

Turner

Fisher

et al. 2009

Global Environmental Change

163

119

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“…Apart from savanna, forest is also an important biome in Africa. African forests are among the most pristine on Earth and contain large carbon stocks in biomass, up to 400 tC ha −1 in Equatorial rainforests (Brown et al, 1996). These forest carbon stocks are vulnerable to human impact and to climate change.…”

Section: Introductionmentioning

confidence: 99%

Variability and recent trends in the African terrestrial carbon balance

et al. 2009

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Abstract. We modeled the African terrestrial carbon balance over the past century using a spatially resolved process based vegetation model (ORCHIDEE). The model is forced by changing climate and by human-induced changes in land use. It includes a simple parameterization of natural fires, but the natural vegetation dynamics was ignored. The period analyzed is 1901-2002. Overall, we found that the African net terrestrial carbon balance (Net Biome Productivity, NBP) increased from a net CO 2 source to the atmosphere of 0.14 Pg C yr −1 in the 1980s to a net sink of 0.15 Pg C yr −1 in the 1990s. The land use flux alone is estimated to be a source of 0.13 Pg C yr −1 caused by deforestation. This implies that climatic trends (mainly increasing precipitation) and CO 2 increase (fertilization effect), are causing a sink of 0.28 Pg C yr −1 which offsets the land-use source. We found that the interannual variability of NBP is large, and mostly driven by photosynthesis variability. Over savannas, photosynthesis changes from one year to the next are strongly correlated with rainfall changes (R 2 =0.77 in northern Africa, and R 2 =0.42 in southern African savannas). Over forests, such a control by rainfall is not found. The main spatial pattern of interannual variability in NBP and photosynthesis/ecosystem respiration fluxes is related with ENSO, with dryer conditions prevailing over savannas during El Niño and wetter conditions over forests. Climate induced variations in fire emissions respond to this ENSO forcing, but do not determine strongly the NBP interannual variability. Finally, we model that ecosystem respiration variations (mostly autotrophic respiration) are correlated with those of photosynCorrespondence to: P. Ciais (philippe.ciais@lsce.ipsl.fr) thesis, on interannual as well as on decadal time scales, but this result is uncertain given the potential for acclimation for autotrophic respiration processes.

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“…To improve confidence in estimated emissions, equal emphasis is needed on improving spatially explicit estimates of carbon stored in forests, which remain uncertain in tropical regions (13). The largest proportion of this uncertainty is in estimates of aboveground biomass (14,15), which accounts for 70-90% of forest biomass carbon (16), and its spatial variability that depends on factors such as climate, human and natural disturbance and recovery, soil type, and topographical variations (14,17). Reducing the uncertainty in emissions estimates requires temporally constrained estimates of forest carbon content at a spatial scale that is fine enough to capture the variability over the landscape and is quantified at the scale of disturbance affecting the forest.…”

mentioning

confidence: 99%

“…Reducing the uncertainty in emissions estimates requires temporally constrained estimates of forest carbon content at a spatial scale that is fine enough to capture the variability over the landscape and is quantified at the scale of disturbance affecting the forest. Such information would improve project-and national-level carbon stock estimates as well as assist in the development of baseline information required for reducing emissions from deforestation and degradation (REDD) activities designed to curb greenhouse gas emissions from the land use sector (15,18).…”

mentioning

confidence: 99%

Benchmark map of forest carbon stocks in tropical regions across three continents

Saatchi

Harris

Brown

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

1,910

1,906

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Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above-and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.forest biomass | forest height | microwave and optical imaging | error propagation | carbon cycling

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Tropical Africa: Land Use, Biomass, and Carbon Estimates for 1980 (NDP-055)

Cited by 10 publications

References 4 publications

Reducing emissions from deforestation—The “combined incentives” mechanism and empirical simulations

Reducing emissions from deforestation—The “combined incentives” mechanism and empirical simulations

Variability and recent trends in the African terrestrial carbon balance

Benchmark map of forest carbon stocks in tropical regions across three continents

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