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iForest - Biogeosciences and Forestry

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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.

  Keywords


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

Authors’ address

(1)
Jack Lonsdale
School of Geosciences, University of Edinburgh, Edinburgh EH9 3JN (UK)
(2)
Georgios Xenakis
Mike Perks
Forest Research, NRS, Roslin, Midlothian EH25 9SY (UK)
(3)
Maurizio Mencuccini
ICREA at CREAF, Cerdanyola del Valles, Barcelona (Spain)

Corresponding author

 
Jack Lonsdale
jacklonsdale@ed.ac.uk

Citation

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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List of the papers citing this article based on CrossRef Cited-by.

 
(1)
Almeida AC, Siggins A, Batista TR, Beadle C, Fonseca S, Loos R (2010)
Mapping the effect of spatial and temporal variation in climate and soils on Eucalyptus plantation production with 3-PG, a process-based growth model. Forest Ecology and Management 259 (9): 1730-1740.
CrossRef | Gscholar
(2)
Andrén O, Kätterer T (1997)
ICBM: the introductory carbon balance model for exploration of soil carbon balances. Ecological Applications 7 (4): 1226-1236.
CrossRef | Gscholar
(3)
Anfodillo T, Carrer M, Simini F, Popa I, Banavar JR, Maritan A (2013)
An allometry-based approach for understanding forest structure, predicting tree-size distribution and assessing the degree of disturbance. Proceedings of the Royal Society B: Biological Sciences 280: 1751.
CrossRef | Gscholar
(4)
Blanco J, Seely B, Welham C, Scoullar K (2008)
Complexity in modelling forest ecosystems: how much is enough? Forest Ecology and Management 256: 1646-1658.
CrossRef | Gscholar
(5)
Broad LR, Lynch T (2006)
Growth models for Sitka spruce in Ireland. Irish Forestry 63 (1-2): 53-79.
Online | Gscholar
(6)
Coops N, Waring R (2001)
The use of multiscale remote sensing imagery to derive regional estimates of forest growth capacity using 3-PGS. Remote Sensing of Environment 75 (3): 324-334.
CrossRef | Gscholar
(7)
Coops N, Waring R, Landsberg J (1998)
Assessing forest productivity in Australia and New Zealand using a physiologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity. Forest Ecology and Management 104: 113-127.
CrossRef | Gscholar
(8)
Duursma R, Falster D, Valladares F, Sterck F, Pearcy R, Lusk C, Sendall K, Nordenstahl M, Houter N, Atwell B, Kelly N, Kelly J, Liberloo M, Tissue D, Medlyn B, Ellsworth D (2012)
Light interception efficiency explained by two simple variables: a test using a diversity of small-to medium-sized woody plants. New Phytologist 193: 397-408.
CrossRef | Gscholar
(9)
Dyson K, Thomson A, Mobbs D, Milne R, Skiba U, Clark A, Levy P, Jones S, Billett M, Dinsmore K, Oijen M, Ostle N, Foereid B, Smith P, Matthews R, Mackie E, Bellamy P, Rivas-Casado M, Jordan C, Higgins A, Tomlinson R, Grace J, Parrish P, Williams M, Clement R, Moncrieff J, Manning A (2009)
Inventory and projections of UK emissions by sources and removals by sinks due to land use, land use change and forestry. Annual report July 2009, Center for Ecology and Hydrology, Penicuik, UK, pp. 1-80.
Online | Gscholar
(10)
Edwards PN, Christie J (1981)
Yield models for forest management. HMSO, London, UK, pp. 1-32.
Gscholar
(11)
Fonweban J (2012)
Modelled ForestYield yield tables. Forest Research Internal Report, Forest Research, Roslin, UK, pp. 1-14.
Gscholar
(12)
Forest Research (2001)
ForestYield software. Forest Research, Alice Holt Forest, Binsted, East Hampshire District, UK.
Gscholar
(13)
Forestry Commission (2011)
Standing timber volume for coniferous trees in Britain: National Forest Inventory Report. Forestry Commission, Edinburgh, UK, pp. 1-20.
Gscholar
(14)
García O (1979)
Modelling stand development with stochastic differential equations. In: Proceedings of the FRI Symposium “Mensuration for Management Planning of Exotic Forest plantations” (Elliott D eds). New Zealand Forest Service 20: 315-333.
Online | Gscholar
(15)
García O, Ruiz F (2003)
A growth model for eucalypt in Galicia, Spain. Forest Ecology and Management 173: 49-62.
CrossRef | Gscholar
(16)
García O (2009)
A simple and effective forest stand mortality model. Mathematical and Computational Forestry and Natural-Resource Sciences (MCFNS) 1 (1): 1-9.
Online | Gscholar
(17)
García O (2011)
A parsimonious dynamic stand model for interior spruce in British Columbia. Forest Science 57 (4): 265-280.
Online | Gscholar
(18)
García O, Burkhart HE, Amateis RL (2011)
A biologically-consistent stand growth model for loblolly pine in the Piedmont physiographic region, USA. Forest Ecology and Management 262 (11): 2035-2041.
CrossRef | Gscholar
(19)
García O (2013)
Building a dynamic growth model for trembling aspen in western Canada without age data. Canadian Journal of Forest Research 43 (3): 256-265.
CrossRef | Gscholar
(20)
Gardiner B, Suárez J, Achim A, Hale S, Nicoll B (2004)
Forest GALES - A PC-based wind risk model, user’s guide. Forest Research, Roslin, UK, pp. 1-54.
Gscholar
(21)
IPCC (2003)
Good practice guidance for land use, land-use change and forestry. United Nation Framework Convention on Climate Change, IGES for IPCC, Hayama, Japan, pp. 590.
Gscholar
(22)
Jandl R, Lindner M, Vesterdal L, Bauwens B, Baritz R, Hagedorn F, Johnson D, Minkkinen K, Byrne K (2007)
How strongly can forest management influence soil carbon sequestration? Geoderma 137 (3-4): 253-268.
CrossRef | Gscholar
(23)
Kurz WA, Dymond CC, White TM, Stinson G, Shaw CH, Rampley GJ, Apps MJ (2009)
CBM-CFS3: a model of carbon-dynamics in forestry and land-use change implementing IPCC standards. Ecological Modelling 220 (4): 480-504.
CrossRef | Gscholar
(24)
Kutner MH, Nachtsheim C, Neter J (2004)
Applied linear regression models (4th edn). McGraw-Hill/Irwin, New York, USA, pp. 701.
Gscholar
(25)
Landsberg J, Waring R (1997)
A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecology and Management 95 (3): 209-228.
CrossRef | Gscholar
(26)
Landsberg J (2003)
Physiology in forest models: history and the future. Forest Biometry, Modelling and Information Sciences 1: 49-63.
Online | Gscholar
(27)
Landsberg J, Waring R, Coops N (2003)
Performance of the forest productivity model 3-PG applied to a wide range of forest types. Forest Ecology and Management 172 (2-3): 199-214.
CrossRef | Gscholar
(28)
Lehtonen A, Mäkipää R, Heikkinen J (2004)
Biomass expansion factors (BEFs) for Scots pine, Norway spruce and birch according to stand age for boreal forests. Forest Ecology and Management 188 (1-3): 211-224.
CrossRef | Gscholar
(29)
Levy PE, Hale SE, Nicoll BC (2004)
Biomass expansion factors and root: shoot ratios for coniferous tree species in Great Britain. Forestry 77 (5): 421-430.
CrossRef | Gscholar
(30)
Lohmander P (1988)
Continuous extraction under risk. Systems Analysis Modelling Simulation 5: 339-354.
Gscholar
(31)
Mason EG, Methol R, Cochrane H (2011)
Hybrid mensurational and physiological modelling of growth and yield of Pinus radiata D. Don. using potentially useable radiation sums. Forestry 84 (2): 99-108.
CrossRef | Gscholar
(32)
Milne R, Brown T, Murray T (1998)
The effect of geographical variation of planting rate on the uptake of carbon by new forests of Great Britain. Forestry 71 (4): 297-310.
CrossRef | Gscholar
(33)
Minunno F, Xenakis G, Perks MP, Mencuccini M (2010)
Calibration and validation of a simplified process-based model for the prediction of the carbon balance of Scottish Sitka spruce (Picea sitchensis) plantations. Canadian Journal of Forest Research 40 (12): 2411-2426.
CrossRef | Gscholar
(34)
Minunno F, Van Oijen M, Cameron D, Cerasoli S, Pereira J, Tomé M (2012)
Analysing structural error and parameter uncertainty of two Eucalyptus models differing in representation of autotrophic respiration. In: “EGU General Assembly Conference Abstracts, vol. 14” (Abbasi A, Giesen N eds). Vienna (Austria), 22-27 April 2012. EGU General Assembly Conference Abstracts, pp. 1250.
Online | Gscholar
(35)
Monserud RA (2003)
Evaluating forest models in a sustainable forest management context. Forest Biometry, Modelling and Information 1: 35-47.
Online | Gscholar
(36)
Monteith JL (1972)
Solar radiation and productivity in tropical ecosystems. The Journal of Applied Ecology 9 (3): 747.
CrossRef | Gscholar
(37)
Nabuurs GJ, Pussinen A, Karjalainen T, Erhard M, Kramer K (2002)
Stemwood volume increment changes in European forests due to climate change - a simulation study with the EFISCEN model. Global Change Biology 8 (4): 304-316.
CrossRef | Gscholar
(38)
Nijnik M, Mather A (2007)
Analysing institutions and public perspectives to identify the future of British forests. In: “Sustainable Forestry From Monitoring and Modelling to Knowledge Management and Policy Science” (Reynolds KM, Thomson AJ, Köhl M, Shannon MA, Ray Rennolls DK eds). CAB International, Wallingford, UK, pp. 171-188.
Online | Gscholar
(39)
Patenaude G, Milne R, Van Oijen M, Rowland CS, Hill RA (2008)
Integrating remote sensing datasets into ecological modelling: a Bayesian approach. International Journal of Remote Sensing 29 (5): 1295-1315.
CrossRef | Gscholar
(40)
Pinjuv G, Mason EG, Watt M (2006)
Quantitative validation and comparison of a range of forest growth model types. Forest Ecology and Management 236 (1): 37-46.
CrossRef | Gscholar
(41)
Pretzsch H (2010)
Forest dynamics, growth, and yield. Springer, Berlin, Heidelberg, Germany, pp. 664.
CrossRef | Gscholar
(42)
Pyatt G, Ray D, Fletcher J (2001)
An ecological site classification for forestry in Great Britain. Bulletin 124, Forestry Commission, Edinburgh, UK, pp. 75.
Gscholar
(43)
Pérez-Cruzado C, Muñoz Sáez F (2011)
Combining empirical models and the process-based model 3-PG to predict Eucalyptus nitens plantations growth in Spain. Forest Ecology and Management 262: 1067-1077.
CrossRef | Gscholar
(44)
Rennolls K (1995)
Forest height growth modelling. Forest Ecology and Management 71 (3): 217-225.
CrossRef | Gscholar
(45)
Sands P, Landsberg J (2001)
Parameterisation of 3-PG for plantation grown Eucalyptus globulus. Forest Ecology and Management 163 (1-3): 273-292.
CrossRef | Gscholar
(46)
Scottish Executive (2012)
Woodland creation - productive conifer (high cost) woodlands (RP22 301B). Web site.
Online | Gscholar
(47)
Smith J, Heath L (2001)
Identifying influences on model uncertainty: an application using a forest carbon budget model. Environmental Management 27 (2): 253-267.
CrossRef | Gscholar
(48)
Soares P, Tome M, Skovsgaard J, Vanclay J (1995)
Evaluating a growth model for forest management using continuous forest inventory data. Forest Ecology and Management 71 (3): 251-265.
CrossRef | Gscholar
(49)
Swenson J, Waring R, Fan W, Coops N (2005)
Predicting site index with a physiologically based growth model across Oregon, USA. Canadian Journal of Forest Research 35 (7): 1697-1707.
CrossRef | Gscholar
(50)
Valentine HT, Mäkelä A (2005)
Bridging process-based and empirical approaches to modeling tree growth. Tree Physiology 25 (7): 769-79.
CrossRef | Gscholar
(51)
Van Oijen M, Reyer C, Bohn F, Cameron D, Deckmyn G, Flechsig M, Härkönen S, Hartig F, Huth A, Kiviste A, Lasch P, Mäkelä A, Mette T, Minunno F, Rammer W (2013)
Bayesian calibration, comparison and averaging of six forest models, using data from Scots pine stands across Europe. Forest Ecology and Management 289: 255-268.
CrossRef | Gscholar
(52)
Vanclay J, Skovsgaard J (1997)
Evaluating forest growth models. Ecological Modelling 98 (1): 1-12.
CrossRef | Gscholar
(53)
Vanclay JK (1994)
Modelling forest growth and yield. CAB International, Oxon, UK, pp. 330.
Online | Gscholar
(54)
Weiskittel A, Maguire D, Monserud R (2009a)
Development of a hybrid model for intensively managed Douglas-fir in the Pacific Northwest. In: “Forest Growth and Timber Quality: Crown Models and Simulation Methods for Sustainable Forest Management” (Dykstra, DP, Monserud RA). General Technical Report PNW-GTR-791, Pacific Northwest Research Station, USDA Forest Service, Portland, OR, USA, pp. 49-67.
Online | Gscholar
(55)
Weiskittel A, Gould P, Temesgen H (2009b)
Sources of variation in the self-thinning boundary line for three species with varying levels of shade tolerance. Forest Science 55 (1): 84-93.
Online | Gscholar
(56)
Weller DE (1987)
Self-thinning exponent correlated with allometric measures of plant geometry. Ecology 68 (4): 813-821.
CrossRef | Gscholar
(57)
Woodland Expansion Advisory Group (2012)
Report of the woodland expansion advisory group. The Scottish Government, Edinburgh, UK, pp. 92.
Gscholar
(58)
Xenakis G (2007)
Assessment of carbon sequestration and timber production of Scots pine across Scotland using the process-based model 3-PGN. PhD thesis, University of Edinburgh, Edinburgh, UK, pp. 289.
Gscholar
(59)
Xenakis G, Ray D, Mencuccini M (2008)
Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model. Ecological Modelling 219 (1-2): 1-16.
CrossRef | Gscholar
(60)
Xenakis G, Ray D, Mencuccini M (2012)
Effects of climate and site characteristics on Scots pine growth. European Journal of Forest Research 131: 427-439.
CrossRef | Gscholar
(61)
Yoda K (1963)
Self-thinning in over-crowded pure stands under cultivated and natural conditions. XI. Intraspecific competition among higher plants. Journal of Biology Osaka City University 14: 107-129.
Gscholar
(62)
Zeide B (1978)
Standardization of growth curves. Journal of Forestry 76 (5): 289-292.
Online | Gscholar
 

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