iForest - Biogeosciences and Forestry


Diameter growth prediction for individual Pinus occidentalis Sw. trees

S Bueno-López (1)   , E Bevilacqua (2)

iForest - Biogeosciences and Forestry, Volume 6, Issue 4, Pages 209-216 (2013)
doi: https://doi.org/10.3832/ifor0843-006
Published: May 27, 2013 - Copyright © 2013 SISEF

Research Articles

Predictive equations calibrated with remeasurement data from 25 permanent plots having individually identified trees were used to project stem diameter of Pinus occidentalis Sw. in Dominican Republic. The general form of the models used to fit the growth and yield functions included fixed effect covariates related to three subsets of explanatory variables: initial tree size, stand attributes, and competition indexes. The subsets were incrementally added in a stepwise fashion for each of the three response variables and the intercept of the model was allowed to vary randomly between plots. The models evaluated included a yield function that predicted future diameter at year t (dt), a periodic annual increment model using five-year diameter increment (id5) and its natural log transformation [ln(id5+0.01)]. For trees that were not remeasured exactly 5 years after the first measurement, id5 was computed by averaging the mean annual increment nearest the 5 year point and multiplying by five. Each approach was evaluated using an independent validation data set based on seven goodness-of-fit statistics, graphical display of residuals and the variance components of each model combination. LMM, including fixed and random parameters, provided a better fit among the models tested. For estimating future diameter, accuracy of predictions is within one centimeter for a five-year projection interval, and bias is negligible. All the models had moderately improved fit statistics when random effects were included in the evaluation. The degree of improvement behaved in a similar manner for most fit statistics, with differences in the range of values for MSE, RMSE and RMSE% of 0.53, 0.23 and 1.05, respectively. The absolute difference between the extreme values for Bias and relative Bias (%) in all the models was 0.20 and 0.92. The differences in values for MAD were only 0.15 and R2 values were practically equivalent.


Repeated Measurements, Mixed Models, Stepwise Regression, Site Quality, Individual Tree Competition Indexes

Authors’ address

S Bueno-López
Vicerrectoria de Investigaciones e Innovación, Pontificia Universidad Catolica Madre y Maestra, Santiago de los Caballeros (Dominican Republic)
E Bevilacqua
College of Environmental Science and Forestry, State University of New York, 1 Forestry Drive, 13210 Syracuse, NY (USA)

Corresponding author

S Bueno-López


Bueno-López S, Bevilacqua E (2013). Diameter growth prediction for individual Pinus occidentalis Sw. trees. iForest 6: 209-216. - doi: 10.3832/ifor0843-006

Academic Editor

Marco Borghetti

Paper history

Received: Oct 26, 2012
Accepted: Mar 06, 2013

First online: May 27, 2013
Publication Date: Aug 01, 2013
Publication Time: 2.73 months

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Adame P, Hynynen J, Cañellas I, Del Rio M (2007)
Individual-tree diameter growth model for rebollo oak (Quercus pyrenaica Willd.) coppices. Forest Ecology and Management 255: 1011-1022.
CrossRef | Gscholar
Baskerville GL (1972)
Use of logarithmic regression in the estimation of plant biomass. Canadian Journal of Forest Research 2 (1): 49-53.
CrossRef | Gscholar
Bevilacqua E (1999)
Growth responses in individual eastern white pine (Pinus strobus L) trees following partial cutting treatments. PhD Dissertation, University of Toronto, Ontario, Canada, pp. 137.
Bueno-López SW (2009)
Understanding growth and yield of Pinus occidentalis Sw. in La Sierra, Dominican Republic. PhD Dissertation, College of Environmental Science and Forestry, State University of New York, Syracuse, NY, USA, pp. 266.
Bueno-López SW, Bevilacqua E (2011)
Developing a diameter-distribution prediction system for Pinus occidentalis Sw. in La Sierra, Dominican Republic. Revista Chapingo, Serie Ciencias Forestales y del Ambiente 17 (1): 115-132. [in Spanish]
CrossRef | Gscholar
Bueno-López SW, Bevilacqua E (2012)
Nonlinear mixed model approaches to estimating merchantable bole volume for Pinus occidentalis. iForest 5 (5): 274-254.
CrossRef | Gscholar
Calama R, Montero G (2005)
Multilevel linear mixed model for tree diameter increment in Stone pine (Pinus pinea): a calibrating approach. Silva Fennica 39: 37-54.
CrossRef | Gscholar
Davis LS, Johnson KN (1987)
Forest management. McGraw-Hill Company, New York, USA, pp. 790.
Dobler G, Peralta LE, Debord LT, Torres JG (1995)
Investigación y manejo de especies maderables de uso comun en La Sierra: guía técnica. San José de las Matas, Plan Sierra Inc., Republica Dominicana, pp. 269. [in Spanish]
Farjon A, Perez-De la Rosa JA, Styles BT (1997)
A field guide to the pines of Mexico and Central America. The Royal Botanic Gardens, Kew, UK.
Garrett MF, Laird NM, Ware JH (2004)
Applied longitudinal analysis. Wiley-Interscience, John Wiley & Sons, Inc., New Jersey, USA, pp. 536.
Gregoire TG, Schabenberger O (1995)
A nonlinear mixed-effects model to predict cumulative bole volume of standing trees. Journal of Applied Statistics 23: 257-271.
CrossRef | Gscholar
Gutzwiller KJ, Riffell SK (2007)
Using statistical models to study temporal dynamics of animal-landscape relations. In: “Temporal Dimensions of Landscape Ecology: Wildlife Responses to Variable Resources” (Bissonette JA, Storch I eds). Spinger-Verlag, New York, USA.
Holdridge L (1987)
Ecología basada en zonas de vida. Instituto Interamericano de Cooperación para la Agricultura, San José, Costa Rica.
Kiernan DH, Bevilacqua E, Nyland RD (2008)
Individual-tree diameter growth model for sugar maple trees in uneven-aged northern hardwood stands under selection system. Forest Ecology and Management 256: 1579-1586.
CrossRef | Gscholar
Littell RC, Milliken GA, Stroup WW, Wolfinger RD (1996)
SAS system for mixed models. SAS Institute Inc., Cary, NC, USA, pp. 633.
Monleon VJ (2004)
A hierarchical model for tree height prediction. In: Proceedings of the “2003 Meeting of the American Statistical Association, Section on Statistics and the Environment”. San Francisco (CA - USA) 3-7 August 2003. The American Statistical Association, Alexandria, VA, USA, pp. 2865-2869.
Palahí M, Pukkala T, Miina J, Montero G (2003)
Individual tree-growth and mortality models for Scots pine (Pinus sylvestrys L.) in north-east Spain. Annals of Forest Science 60: 1-10.
CrossRef | Gscholar
Perry DA (1985)
The competition process in forest stands. In: “Attributes of trees as crop plants”. Titus Wilson & Son Ltd, Kendal, Cumbria, UK, pp. 592.
Popper KR (1963)
Conjectures and refutations. Routledge and Kegan Paul, London, UK.
Pukkala T (1989)
Predicting diameter growth in evenaged Scots pine stands with a spatial and non-spatial model. Silva Fennica 23: 101-116.
Online | Gscholar
Reineke LH (1933)
Perfecting a stand-density index for even aged forest. Journal of Agricultural Research 46: 627-638.
Sanchez-Gonzalez M, Del Rio M, Canellas I, Montero G (2006)
Distance independent tree diameter growth model for cork oak stands. Forest Ecology and Management 225: 262-270.
CrossRef | Gscholar
SAS Institute Inc. (1996)
SAS/STAT User’s guide. SAS Institute Inc., Cary, North Carolina. pp. 213.
Swedforest Consulting AB (1992)
Plan maestro sector forestal. Informe principal. Plan Sierra Inc., San José de las Matas, Santiago, Dominican Republic, pp. 82.
Uzoh FC, Oliver WW (2008)
Individual tree diameter increment model for managed even-aged stands of ponderosa pine throughout the western United States using multilevel linear mixed effects models. Forest Ecology and Management 256: 438-445.
CrossRef | Gscholar
Vanclay JK (1994)
Modeling forest growth and yield: Applications to Mixed Tropical Forests, CAB International, Wallingford, CT, USA, pp. 312.
West PW (1981)
Simulation of diameter growth and mortality in regrowth eucalypt forest of Southern Tasmania. Forest Science 27: 603-616.
Westfall JA (2006)
Predicting past and future diameter growth for trees in the northeastern United States. Canadian Journal of Forest Research 36: 1551-1562.
CrossRef | Gscholar
Wycoff W (1990)
A basal area increment model for individual conifers in the northern Rocky Mountains. Forest Science 36: 1077-1104.
Zhang L, Gove JH (2005)
Spatial assessment of model errors from four regression techniques. Forest Science 51 (4): 334-346.
Zhang L, Peng C, Dang Q (2004)
Individual-tree basal area growth models for jack pine and black spruce in northern Ontario. Forestry Chronic 80 (3): 366-374.
CrossRef | Gscholar
Zhao D, Borders B, Wilson M (2004)
Individual-tree diameter growth and mortality models for bottomland mixed-species hardwood stands in the lower Mississippi alluvial valley. Forest Ecology and Management 199: 307-322.
CrossRef | Gscholar

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