2016
DOI: 10.1111/gcb.13201
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Testing the generality of above‐ground biomass allometry across plant functional types at the continent scale

Abstract: Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregion… Show more

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Cited by 144 publications
(136 citation statements)
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“…(b) Mean relative errors [Error = (AGB est − AGB obs /AGB obs ) × 100] for the compared models across the observed aboveground biomass values. The compared models correspond to Model 1 proposed here; the global model proposed by Chave et al (), including diameter at breast height (DBH), height ( H ) and wood density (ρ); the model proposed by Jucker et al () for angiosperms including mean crown diameter (CD) and H ; and the shrub models proposed by Paul et al () using stem diameter at 10 cm height (D10) as a main variable (MULTI and SHRUB models). RMSE = root mean square error; Bias = average relative systematic error of model predictions [Colour figure can be viewed at wileyonlinelibrary.com]…”
Section: Resultsmentioning
confidence: 93%
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“…(b) Mean relative errors [Error = (AGB est − AGB obs /AGB obs ) × 100] for the compared models across the observed aboveground biomass values. The compared models correspond to Model 1 proposed here; the global model proposed by Chave et al (), including diameter at breast height (DBH), height ( H ) and wood density (ρ); the model proposed by Jucker et al () for angiosperms including mean crown diameter (CD) and H ; and the shrub models proposed by Paul et al () using stem diameter at 10 cm height (D10) as a main variable (MULTI and SHRUB models). RMSE = root mean square error; Bias = average relative systematic error of model predictions [Colour figure can be viewed at wileyonlinelibrary.com]…”
Section: Resultsmentioning
confidence: 93%
“…with both 3a and 3b developed by Paul et al () based only upon stem diameter at 10 cm height (D10) at the Australian continental scale.…”
Section: Methodsmentioning
confidence: 99%
“…However, building height-diameter allometric models for different species is often challenging as a great number of stems per size-class is required. A recent study form Australia showed that using generic allometric models based on plant functional types rather than species-specific models [80]. Moreover, in montane forests, the same species can have different heights for a given diameter depending on exposure to wind, windward/leeward side of mountain, slope or other factors (soil) (see [81]).…”
Section: Discussionmentioning
confidence: 99%
“…The above-ground biomass was estimated using general allometric relationships for softwood plantations and eucalypt vegetation for the Pinus sp. forest and adjacent vegetation, respectively (Paul et al, 2016). These allometrics were developed based on existing biomass datasets in Australia and were based on 455 individuals of softwoods (mostly Pinus radiata) and 6004 eucalypt individuals (Eucalyptus and closely-related genus of Corymbia and Angophora).…”
mentioning
confidence: 99%