iForest - Biogeosciences and Forestry


A comparison of models for quantifying growth and standing carbon in UK Scots pine forests

Jack Lonsdale (1)   , Georgios Xenakis (2), Maurizio Mencuccini (3), Mike Perks (2)

iForest - Biogeosciences and Forestry, Volume 8, Issue 5, Pages 596-605 (2015)
doi: https://doi.org/10.3832/ifor1403-008
Published: Feb 02, 2015 - Copyright © 2015 SISEF

Research Articles

Scots pine is the most abundant native conifer in the UK. A stand level dynamic growth (SLeDG) model is parametrised for British Scots pine stands for the first time. This model predicts stands annually based on their current state, and allows for changes in forest management. Stand growth and carbon storage predictions using this model were compared with those of the yield look-up package ForestYield, and a process-based model (3PGN). Predictions were compared graphically over an 100 year rotation, and strengths and weaknesses of each were considered. The SLeDG parametrisation provided forecasts of Scots pine growth with percentage mean absolute difference < 12% for all state variables. The model comparison showed that similar outputs were predicted by all three models, with the greatest variation in the yield table based prediction of volume and biomass. Future advances in data availability and computing power should allow for greater use of process-based models, but in the interim more flexible dynamic based growth models may be more useful than static yield tables for providing predictions which extend to non-standard management prescriptions and estimates of early growth and yield.


Growth, Yield, Carbon, Modelling, Dynamical-systems, 3PG, ForestYield

Authors’ address

Jack Lonsdale
School of Geosciences, University of Edinburgh, Edinburgh EH9 3JN (UK)
Georgios Xenakis
Mike Perks
Forest Research, NRS, Roslin, Midlothian EH25 9SY (UK)
Maurizio Mencuccini
ICREA at CREAF, Cerdanyola del Valles, Barcelona (Spain)

Corresponding author

Jack Lonsdale


Lonsdale J, Xenakis G, Mencuccini M, Perks M (2015). A comparison of models for quantifying growth and standing carbon in UK Scots pine forests. iForest 8: 596-605. - doi: 10.3832/ifor1403-008

Academic Editor

Emanuele Lingua

Paper history

Received: Jul 21, 2014
Accepted: Jan 09, 2015

First online: Feb 02, 2015
Publication Date: Oct 01, 2015
Publication Time: 0.80 months

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