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Testing the generality of below-ground biomass allometry across plant functional types
Journal article   Open access   Peer reviewed

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

Keryn I Paul, John Larmour, Alison Specht, Ayalsew Zerihun, Peter Ritson, Stephen H Roxburgh, Stan Sochacki, Tom Lewis, Craig V M Barton, Jacqueline R England, …
Forest Ecology and Management, Vol.432, pp.102-114
2019
DOI: https://doi.org/10.1016/j.foreco.2018.08.043
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Accepted VersionCC BY-NC-ND V4.0,  Open Access
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https://doi.org/10.1016/j.foreco.2018.08.043View
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Abstract

acacia carbon stem diameter eucalyptus multi-stemmed roots shrubs plant functional types
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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