气候变化领域集成服务门户(CCPortal): A revised above-ground maximum biomass layer for the Australian continent

CCPortal

DOI	10.1016/j.foreco.2018.09.011
	A revised above-ground maximum biomass layer for the Australian continent
	Roxburgh S.H.; Karunaratne S.B.; Paul K.I.; Lucas R.M.; Armston J.D.; Sun J.
发表日期	2019
ISSN	0378-1127
起始页码	264
结束页码	275
卷号	432
英文摘要	The carbon accounting model FullCAM is used in Australia's National Greenhous Gas Inventory to provide estimates of carbon stock changes and emissions in response to deforestation and afforestation/reforestation. FullCAM-predicted above-ground woody biomass is heavily influenced by the parameter M, which defines the maximum upper limit to biomass accumulation for any location within the Australian continent. In this study we update FullCAM's M spatial input layer through combining an extensive database of 5739 site-based records of above-ground biomass (AGB) with the Random Forest ensemble machine learning algorithm, with model predictions of AGB based on 23 environmental predictor covariates. A Monte-Carlo approach was used, allowing estimates of uncertainty to be calculated. Overall, the new biomass predictions for woodlands, with 20–50% canopy cover, were on average 49.5 ± 1.3 (s.d.) t DM ha−1, and very similar to existing model predictions of 48.5 t DM ha−1. This validates the original FullCAM model calibrations, which had a particular focus on accounting for greenhouse gas emissions in Australian woodlands. In contrast, the prediction of biomass of forests with a canopy cover >50% increased significantly, from 172.1 t DM ha−1, to 234.4 ± 5.1 t DM ha−1. The change in forest biomass was most pronounced at sub-continental scales, with the largest increases in the states of Tasmania (166 to 351 ± 22 t DM ha−1), Victoria (201 to 333 ± 14 t DM ha−1), New South Wales (210 to 287 ± 9 t DM ha−1), and Western Australia (103 to 264 ± 14 s.d. t DM ha−1). Testing of model predictions against independent data from the savanna woodlands of northern Australia, and from the high biomass Eucalyptus regnans forests of Victoria, provided confidence in the predictions across a wide range of forest types and standing biomass. When applied to the Australian Government's National Inventory land clearing accounts there was an overall increase of 6% in continental emissions over the period 1970–2016. Greater changes were seen at sub-continental scales calculated within 6° × 4° analysis tiles, with differences in emissions varying from −21% to +35%. Further testing is required to assess the impacts on other land management activities covered by the National Inventory, such as reforestation; and at more local scales for sequestration projects that utilise FullCAM for determining abatement credits. © 2018 Elsevier B.V.
英文关键词	Carbon accounting; Forest biomass; National greenhouse gas inventory; Random forest
语种	英语
scopus关键词	Carbon; Decision trees; Deforestation; Forecasting; Gas emissions; Greenhouse gases; Learning algorithms; Learning systems; Reforestation; Uncertainty analysis; Above ground biomass; Above-ground woody biomass; Australian continents; Carbon accounting; Carbon accounting model; Forest biomass; Greenhouse gas inventory; Random forests; Biomass; aboveground biomass; accountability; afforestation; algorithm; biomass; canopy architecture; carbon; carbon emission; carbon sequestration; database; deforestation; forest inventory; greenhouse gas; machine learning; model validation; Monte Carlo analysis; reforestation; savanna; woodland; Biomass; Carbon; Deforestation; Forecasts; Greenhouse Gases; Reforestation; Australia; New South Wales; Tasmania; Victoria [Australia]; Western Australia; Eucalyptus regnans
来源期刊	Forest Ecology and Management
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156394
作者单位	CSIRO Land and Water, GPO Box 1700, Canberra, ACT 2601, Australia; Department of the Environment and Energy, Parkes, ACT, Australia; Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth, Ceredigion SY23 3DB, United Kingdom; Department of Environment and Science Remote Sensing Centre, Ecosciences Precinct, Brisbane, Queensland 4001, Australia; Joint Remote Sensing Research Program, School of Earth and Environmental Sciences, University of Queensland, St. Lucia, Brisbane, Queensland 4067, Australia; Department of Geographical Sciences, University of Maryland, College Park, MD 20742, United States; School of Biological, Earth and Environmental Sciences, The University of New South Wales, Sydney, NSW 2052, Australia
推荐引用方式 GB/T 7714	Roxburgh S.H.,Karunaratne S.B.,Paul K.I.,et al. A revised above-ground maximum biomass layer for the Australian continent[J],2019,432.
APA	Roxburgh S.H.,Karunaratne S.B.,Paul K.I.,Lucas R.M.,Armston J.D.,&Sun J..(2019).A revised above-ground maximum biomass layer for the Australian continent.Forest Ecology and Management,432.
MLA	Roxburgh S.H.,et al."A revised above-ground maximum biomass layer for the Australian continent".Forest Ecology and Management 432(2019).