Claim · model-written summary
Simple power-law models explained 84–95% of biomass variation.
Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Verbatim
e0“Simple power-law models explained 84-95% of the variation in biomass”
Title
Keryn I. Paul; Stephen H. Roxburgh; Jerome Chave; et al. Global Change Biology 2015. doi:10.1111/gcb.13201
Other claims from this paper (8)
- Observation Biomass–stem diameter relationships were generic across ecoregions for five plant functional types.
- Method / resource Adding plant and site variables improved model performance little.
- Method / resource Generalized models lost less than 1% prediction efficiency compared with species-specific models.
- Method / resource Generalized multispecies models showed no significant biomass prediction bias for 92% of 53 species.
- Method / resource Stand-level biomass prediction efficiency was 99%.
- Method / resource Mean absolute prediction error was 13%.
- Recommendation The authors recommend generic plant-functional-type allometric models for cost-effective biomass prediction.
- Recommendation The authors recommend new species-specific models only when stand prediction accuracy gains are high.