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

Forest Ecology and Management. · 1 Jan 2019 · 10.1016/j.foreco.2018.08.043

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.

Plant phenotyping relevance

植物の地下部バイオマスという明示的な形質を推定する汎用アロメトリーモデルを開発し、複数の機能型・林分で予測性能を検証しており、形質測定法が研究の中心です。

abstractWe 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.
abstractWe further assessed the generality of the plant functional type models across 11 contrasting stands where data from whole-plot excavation of BGB were available.
abstractThe efficiency of model prediction of stand-based BGB was 93%, with a mean absolute prediction error of only 6.5%

Code and data availability

The paper's below-ground biomass allometry is built from the authors' Australian Individual Tree Biomass Library (Paul et al. 2017b), a public dataset deposited with a DOI and ÆKOS portal URL, which qualifies as a paper-specific public phenotype dataset. The ecoregions map and Dryad wood density database are generic/cd

Datasetpublic

H, England JR, Davies MJ, Luck H (2017a) Measurements of stem diameter: 786 implications for individual- and stand-level errors. Environmental Monitoring and Assessment, 189, 416, 1- 787 14. 788 Paul KI, Larmour, J., Zerihun, A., et al. (2017b) Australian Individual Tree Biomass Library, Version 3. 789 10.4227/05/566629ADA95DA. http://www.aekos.org.au/dataset/223706. Obtained from Australian 790 Ecological Knowledge and Observation System Data Portal (ÆKOS, http://www.portal. aekos.org.au/), , Generic allometrics 38

Open resource ↗aekos.org.au · 10.4227/05/566629ADA95DA · pdf-layout-page:38 lines:1-43

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