Testing the generality of above-ground biomass allometry across plant functional types at the continent scale

Paul, Keryn I., Roxburgh, Stephen H., Chave, Jerome, England, Jacqueline R., Zerihun, Ayalsew, Specht, Alison, Lewis, Tom, Bennett, Laurent T., Baker, Thomas G., Adams, Mark A., Huxtable, Dan, Montagu, Kelvin D., Falster, Daniel S., Feller, Mike, Sochacki, Stan, Ritson, Peter, Bastin, Gary, Bartle, John, Wildy, Dan, Hobbs, Trevor, Larmour, John, Waterworth, Rob, Stewart, Hugh T. L., Jonson, Justin, Forrester, David I., Applegate, Grahame, Mendham, Daniel, Bradford, Matt, O'Grady, Anthony, Green, Daryl, Sudmeyer, Rob, Ranc, Stan J., Turner, John, Barton, Craig, Wenk, Elizabeth H., Grove, Tim, Attiwill, Peter M., Pinkard, Elizabeth, Butler, Don, Brooksbank, Kim, Spencer, Beren, Snowdon, Peter, O'Brien, Nick, Battaglia, Michael, Cameron, David M., Hamilton, Steve, Mcauthur, Geoff and Sinclair, Jenny (2016) Testing the generality of above-ground biomass allometry across plant functional types at the continent scale. Global Change Biology, 22 6: 2106-2124. doi:10.1111/gcb.13201

Author Paul, Keryn I.
Roxburgh, Stephen H.
Chave, Jerome
England, Jacqueline R.
Zerihun, Ayalsew
Specht, Alison
Lewis, Tom
Bennett, Laurent T.
Baker, Thomas G.
Adams, Mark A.
Huxtable, Dan
Montagu, Kelvin D.
Falster, Daniel S.
Feller, Mike
Sochacki, Stan
Ritson, Peter
Bastin, Gary
Bartle, John
Wildy, Dan
Hobbs, Trevor
Larmour, John
Waterworth, Rob
Stewart, Hugh T. L.
Jonson, Justin
Forrester, David I.
Applegate, Grahame
Mendham, Daniel
Bradford, Matt
O'Grady, Anthony
Green, Daryl
Sudmeyer, Rob
Ranc, Stan J.
Turner, John
Barton, Craig
Wenk, Elizabeth H.
Grove, Tim
Attiwill, Peter M.
Pinkard, Elizabeth
Butler, Don
Brooksbank, Kim
Spencer, Beren
Snowdon, Peter
O'Brien, Nick
Battaglia, Michael
Cameron, David M.
Hamilton, Steve
Mcauthur, Geoff
Sinclair, Jenny
Title Testing the generality of above-ground biomass allometry across plant functional types at the continent scale
Journal name Global Change Biology   Check publisher's open access policy
ISSN 1365-2486
Publication date 2016-06
Year available 2016
Sub-type Article (original research)
DOI 10.1111/gcb.13201
Open Access Status Not yet assessed
Volume 22
Issue 6
Start page 2106
End page 2124
Total pages 19
Place of publication Chichester, West Sussex, United Kingdom
Publisher Wiley-Blackwell Publishing
Collection year 2017
Language eng
Formatted 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 ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha-1). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures).
Keyword Eucalyptus
Above ground
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
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