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

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Paul, Keryn I., Roxburgh, Stephen H., Chave, Jerome, England, Jacqueline R., Zerihun, Ayalsew, Specht, Alison, Lewis, Tom, Bennett, Lauren T. +40 more·2016·Global Change Biology

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).

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  • For permanent revegetation above-ground, live biomass for each plot was estimated from stem diameter measurements using allometric models for each species group.

    “For permanent revegetation above-ground, live biomass for each plot was estimated from stem diameter measurements using allometric models for each species group (Paul et al. 2016).”

    From Can soil and tree carbon sequestration maintain zero net emissions grazing? (2025) · cites this paper as Paul et al. 2016

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  40. Paul, K. I., Roxburgh, S. H., Chave, J., England, J. R., Zerihun, A., Specht, A., Lewis, T., Bennett, L. T., Baker, T. G., Adams, M. A., Huxtable, D., Montagu, K. D., Falster, D. S., Feller, M., Sochacki, S., Ritson, P., Bastin, G., Bartle, J., Inildy, D. ,... Sinclair, A. (2016). Testing the generality of above-ground biomass allometry across plant functional types at the continent scale. GLOBAL CHANGE BIOLOGY, 22 (6), pp.2106-2124. https://doi.org/10.1111/ gcb.13201. Persistent Link: http://hdl.handle.net/11343/291106

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Authors
Paul, K. I., Roxburgh, S. H., Chave, J., England, J. R., Zerihun, A., Specht, A., Lewis, T., Bennett, L. T., Baker, T. G., Adams, M. A., Huxtable, D., Montagu, K. D., Falster, D. S., Feller, M., Sochacki, S., Ritson, P., Bastin, G., Bartle, J., Wildy, D., Hobbs, T., Larmour, J., Waterworth, R., Stewart, H. T. L., Jonson, J., Forrester, D. I., Applegate, G., Mendham, D., Bradford, M., O'Grady, A., Green, D., Sudmeyer, R., Rance, S. J., Turner, J., Barton, C., Wenk, E. H., Grove, T., Attiwill, P. M., Pinkard, E., Butler, D., Brooksbank, K., Spencer, B., Snowdon, P., O'Brien, N., Battaglia, M., Cameron, D. M., Hamilton, S., McAuthur, G., & Sinclair, J.
Affiliations
  • Commonwealth Scientific and Industrial Research Organisation (AU)
  • UMR 5174 Laboratoire Evolution et Diversité Biologique CNRS &amp; Université Paul Sabatier Toulouse 31062 France
  • Curtin University (AU)
  • The University of Queensland (AU)
  • University of the Sunshine Coast (AU)
  • The University of Melbourne (AU)
  • The University of Sydney (AU)
  • Equinox Environmental Pty Ltd. 6 Craigie Cres Manning WA 6152 Australia
  • Colo Consulting, Winmalee Parramatta NSW 2777 Australia
  • Macquarie University (AU)
  • University of British Columbia (CA)
  • Murdoch University (AU)
  • FarmWoods 3/104 South Street Fremantle WA 6160 Australia
  • Department of Land Resource Management (AU)
  • Government of Western Australia (AU)
  • Fares Rural Pty Ltd PO Box 526 Wembley WA 6913 Australia
  • Department for Environment and Water (AU)
  • Mullion Group 2a Fitzroy Rd Forrest ACT 2603 Australia
  • Hugh Stewart Consulting 8 Upland Road Strathmore Vic. 3041 Australia
  • The University of Western Australia (AU)
  • University of Freiburg (DE)
  • CSIRO Agriculture CSIRO Land and Water Private Bag 12 Hobart Tas 7001 Australia
  • PO Box 1683 Dubbo NSW 2830 Australia
  • Department of Agriculture and Food Western Australia (AU)
  • CSIRO Land and Water (AU)
  • Forsci Pty Ltd. Ste 4.05/ 32 Delhi Rd North Ryde NSW 2113 Australia
  • Western Sydney University (AU)
  • Queensland Herbarium Mt Coot‐tha Road Toowong Qld 4066 Australia
  • New Forests Asset Management Pty Ltd. PO Box 434 North Sydney NSW 2059 Australia
  • Southern Cross University (AU)
  • Hamilton Environmental Services 2345 Benalla‐Tatong Road Tatong Vic. 3673 Australia
  • AusCarbon Pty Ltd. PO Box 395 Nedlands WA 6909 Australia
  • Green Collar Group Level 1 37 George St Sydney NSW 2000 Australia
Corresponding author
Paul, Keryn I.
Venue
Global Change Biology
Publisher
Wiley
Published
2016-03-29
Volume
22
Issue
6
Pages
2106-2124
ISSN
  • 1354-1013 (ISSN-L)
  • 1365-2486
OpenAlex
W2201465434
Cited by
206
References
1
Citations by year
2026: 19 · 2025: 24 · 2024: 19 · 2023: 18 · 2022: 23 · 2021: 31 · 2020: 28 · 2019: 14 · 2018: 12 · 2017: 15 · 2016: 3
FWCI
10.38
Type
journal article
Language
en
Open access
Locations
  • Global Change Biology (publishedVersion)
  • PubMed (publishedVersion)
  • eCite Digital Repository (University of Tasmania) (submittedVersion)
  • Cross Connect (Southern Cross University) (submittedVersion)
  • UWA Profiles and Research Repository (UWA) (submittedVersion)
  • Murdoch University Research Portal (submittedVersion)
  • Queensland Department of Agriculture and Fisheries archive of scientific and research publications (Queensland Department of Agriculture and Fisheries) (submittedVersion)
  • eSpace (Curtin University) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Minerva Access (University of Melbourne) (submittedVersion)
  • Griffith Research Online (submittedVersion, other-oa)
  • Swinburne figshare (Swinburne University of Technology) (submittedVersion)
Funders
Department of the Environment, Australian Government
Topics
  • Physical Sciences › Environmental Science › Nature and Landscape Conservation › Forest ecology and management
  • Physical Sciences › Environmental Science › Environmental Engineering › Remote Sensing and LiDAR Applications
  • Physical Sciences › Environmental Science › Global and Planetary Change › Forest Management and Policy
Keywords
aboveground biomass, allometric equations, plant functional types, stem diameter, Eucalyptus, wood density, ecoregional variation, Australian forests, carbon balance, forest plantations
MeSH terms
Australia, Carbon, Eucalyptus, Models, Biological, Trees, Wood, Ecosystem, Biomass, Plant Stems, Carbon Sequestration, Forests

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