Testing the generality of below-ground biomass allometry across plant functional types

Authors

Keryn I. Paul, CSIRO Agriculture and CSIRO Land and Water, ACT, Australia
John Larmour, CSIRO Agriculture and CSIRO Land and Water, ACT, Australia
Alison Specht, University of Queensland, Australia
Ayalsew Zerihun, Curtin University, Perth, Western Australia
Peter Ritson, FarmWoods, PO Box 385, Augusta, WA, Australia
Stephen H. Roxburgh, CSIRO Agriculture and CSIRO Land and Water, ACT, Australia
Stan Sochacki, Murdoch University, Murdoch, Western Australia
Tom Lewis, University of Sunshine Coast, Queensland, Australia
Craig V.M Barton, Western Sydney University, NSW, Australia
Jacqueline R. England, CSIRO Agriculture and CSIRO Land and Water, Victoria, Australia
Michael Battaglia, CSIRO Agriculture CSIRO Land and Water, Hobart, Tasmania, Australia
Anthony O'Grady, CSIRO Agriculture CSIRO Land and Water, Hobart, Tasmania, Australia
Elizabeth Pinkard, CSIRO Agriculture CSIRO Land and Water, Hobart, Tasmania, Australia
Grahame Applegate, University of the Sunshine Coast, Queensland, Australia
Justin Jonson, The University of Western Australia, Albany, Australia
Kim Brooksbank, Department of Agriculture and Food, Western Australia, (DAFWA), Albany, AustraliaFollow
Rob Sudmeyer, Department of Agriculture and Food, Western Australia, Esperance, Western AustraliaFollow
Dan Wildy, Fares Rural Pty Ltd,PO Box 57, West Perth, Western Australia
Kelvin D. Montagu, Colo Consulting, Winmalee, Parramatta, NSW, Australia
Matt Bradford, CSIRO Land and Water, Atherton, Queensland, Australia
Trevor Hobbs, Department of Environment, Water and Natural Resources, Adelaide, South Australia

Document Type

Article

Publication Date

1-15-2019

Journal Title

Forest Ecology and Management

ISSN

ISSN 0378-1127 eISSN 1872-7042

Keywords

Acacia, Carbon, Stem diameter, Eucalyptus, Multi-stemmed, Roots, Shrubs, Plant functional types

Disciplines

Agricultural Science | Agronomy and Crop Sciences | Climate | Environmental Indicators and Impact Assessment | Environmental Monitoring | Forest Biology | Forest Management | Natural Resources Management and Policy | Plant Biology | Terrestrial and Aquatic Ecology

Abstract

Accurate quantification of below-ground biomass (BGB) of woody vegetation is critical to understanding ecosystem function and potential for climate change mitigation from sequestration of biomass carbon. We compiled 2054 measurements of planted and natural individual tree and shrub biomass from across different regions of Australia (arid shrublands to tropical rainforests) to develop allometric models for prediction of BGB. We found that the relationship between BGB and stem diameter was generic, with a simple power-law model having a BGB prediction efficiency of 72–93% for four broad plant functional types: (i) shrubs and Acacia trees, (ii) multi-stemmed mallee eucalypts, (iii) other trees of relatively high wood density, and; (iv) a species of relatively low wood density, Pinus radiata D. Don. There was little improvement in accuracy of model prediction by including variables (e.g. climatic characteristics, stand age or management) in addition to stem diameter alone. We further assessed the generality of the plant functional type models across 11 contrasting stands where data from whole-plot excavation of BGB were available. The efficiency of model prediction of stand-based BGB was 93%, with a mean absolute prediction error of only 6.5%, and with no improvements in validation results when species-specific models were applied. Given the high prediction performance of the generalised models, we suggest that additional costs associated with the development of new species-specific models for estimating BGB are only warranted when gains in accuracy of stand-based predictions are justifiable, such as for a high-biomass stand comprising only one or two dominant species. However, generic models based on plant functional type should not be applied where stands are dominated by species that are unusual in their morphology and unlikely to conform to the generalised plant functional group models.

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Digital Object Identifier (DOI)

https://doi.org/10.1016/j.foreco.2018.08.043