Claim · model-written summary
The authors recommend obtaining more extensive training data, including mature forests, to reduce payback-period uncertainty.
- Taxon
- forestse0
- Outcome
- obtaining more extensive training datae0
- Qualifier
- including mature forests of all typese0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionValue
Verbatim
e0“The resulting uncertainty in payback periods could be reduced by either obtaining more extensive training data (including mature forests of all types)”
Title
Quantifying forest growth uncertainty on carbon payback times in a simple biomass carbon model
Will Rolls; Piers M Forster Environmental Research Communications 2020. doi:10.1088/2515-7620/ab7ff3
Other claims from this paper (10)
- Method / resource Changes to model inputs improved fit of the forest site growth function to its training data.
- Method / resource Small parameter changes altered predicted forest site carbon uptake by up to 92 tC.ha −1, or 18% at year 500.
- Method / resource Changed forest site carbon estimates altered calculated payback periods by up to 54 years in a clear-fell scenario.
- Observation The uncertainty was confined to slower growing forests whose training data did not extend to maturity.
- Method / resource The authors provide improved parameterisations for all forest types of the original model.
- Method / resource The revised forest parameterisations provide better fits to the underlying data.
- Method / resource The authors provide margins of error for generated forest growth curves.
- Method / resource The revised model can reproduce the earlier forest biomass model results.
- Association The earlier headline figures depend heavily on how the forest growth curve is fitted to training data.
- Recommendation The authors recommend modifying the forest growth function to reduce payback-period uncertainty.