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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Claims 9
Claim · model-written summary
Biomass–stem diameter relationships were generic across ecoregions for five plant functional types.
Verbatim
e0“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.”
Claim · model-written summary
Simple power-law models explained 84–95% of biomass variation.
Not reportedTaxon
Verbatim
e0“Simple power-law models explained 84-95% of the variation in biomass”
Claim · model-written summary
Adding plant and site variables improved model performance little.
Verbatim
e0“with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included”
Claim · model-written summary
Generalized models lost less than 1% prediction efficiency compared with species-specific models.
Verbatim
e0“Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models.”
Claim · model-written summary
Generalized multispecies models showed no significant biomass prediction bias for 92% of 53 species.
Not reportedComparatorDirection
Verbatim
e0“application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested”
Claim · model-written summary
Stand-level biomass prediction efficiency was 99%.
Verbatim
e0“overall efficiency of stand-level biomass prediction was 99%”
Claim · model-written summary
Mean absolute prediction error was 13%.
Verbatim
e0“with a mean absolute prediction error of only 13%”
Claim · model-written summary
The authors recommend generic plant-functional-type allometric models for cost-effective biomass prediction.
- Outcome
- use of generic allometric models based on plant functional typese0
Not reportedTaxon
Verbatim
e0“we recommend use of generic allometric models based on plant functional types”
t0“plant functional types”
Claim · model-written summary
The authors recommend new species-specific models only when stand prediction accuracy gains are high.
- Outcome
- Development of new species-specific modelse0
- Qualifier
- gains in accuracy of stand-based predictions are relatively highe0
Not reportedTaxon
Verbatim
e0“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).”