Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Australia

Barrett, Damian J., Galbally, Ian E. and Graetz, R. Dean (2001) Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Australia. Global change biology, 7 8: 883-902. doi:10.1046/j.1354-1013.2001.00449.x

Author Barrett, Damian J.
Galbally, Ian E.
Graetz, R. Dean
Title Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Australia
Journal name Global change biology   Check publisher's open access policy
ISSN 1354-1013
Publication date 2001-12-01
Year available 2001
Sub-type Article (original research)
DOI 10.1046/j.1354-1013.2001.00449.x
Volume 7
Issue 8
Start page 883
End page 902
Total pages 20
Place of publication Oxford, UK
Publisher Blackwell
Language eng
Subject 270708 Conservation and Biodiversity
Abstract Quantifying continental scale carbon emissions from the oxidation of aboveground plant biomass following land-use change (LUC) is made difficult by the lack of information on how much biomass was present prior to vegetation clearing and on the timing and location of historical LUC. The considerable spatial variability of vegetation and the uncertainty of this variability leads to difficulties in predicting biomass C density (t(c) ha(-1)) prior to LUC. The issue of quantifying uncertainties in the estimation of land based sources and sinks of CO2, and the feasibility of reducing these uncertainties by further sampling, is critical information required by governments world-wide for public policy development on climate change issues. A quantitative statistical approach is required to calculate confidence intervals (the level of certainty) of estimated cleared above-ground biomass. In this study, a set of high-quality observations of steady state aboveground biomass from relatively undisturbed ecological sites across the Australian continent was combined with vegetation, topographic, climatic and edaphic data sets within a Geographical Information System. A statistical model was developed from the data set of observations to predict potential biomass and the standard error of potential biomass for all 0.05 degrees (approximately 5 x 5 km) land grid cells of the continent. In addition, the spatial autocorrelation of observations and residuals from the statistical model was examined. Finally, total C emissions due to historic LUC to cultivation and cropping were estimated by combining the statistical model with a data set of fractional cropland area per land grid cell, f(Ac) (Ramankutty & Foley 1998). Total C emissions from loss of above-ground biomass due to cropping since European colonization of Australia was estimated to be 757 Mt(C). These estimates are an upper limit because the predicted steady state biomass may be less than the above-ground biomass immediately prior to LUC because of disturbance. The estimated standard error of total C emissions was calculated from the standard error of predicted biomass, the standard error of f(Ac), and the spatial autocorrelation of biomass. However, quantitative estimates of the standard error of f(Ac) were unavailable. Thus, two scenarios were developed to examine the effect of error in f(Ac), on the error in total C emissions. In the first scenario, in which fAc was regarded as accurate (i.e. a coefficient of variation, CV, of f(Ac) = 0.0), the 95% confidence interval of the continental C emissions was 379-1135 Mt(C). In the second scenario, a 50% error in estimated cropland area was assumed (a CV of f(Ac) = 0.50) and the estimated confidence interval increased to between 350 and 1294 Mt(C). The CV of C emissions for these two scenarios was 25% and 29%. Thus, while accurate maps of land-use change contribute to decreasing uncertainty in C emissions from LUC, the major source of this uncertainty arises from the prediction accuracy of biomass C density. It is argued that, even with large sample numbers, the high cost of sampling biomass carbon may limit the uncertainty of above-ground biomass to about a CV of 25%.
Keyword Carbon
greenhouse gas emissions
uncertainty analysis
vegetation clearing
geographical information systems
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Unknown

Document type: Journal Article
Sub-type: Article (original research)
Collection: Sustainable Minerals Institute Publications
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Citation counts: TR Web of Science Citation Count  Cited 28 times in Thomson Reuters Web of Science Article | Citations
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Created: Fri, 13 Nov 2009, 00:39:38 EST by Thelma Whitbourne on behalf of Sustainable Minerals Institute