Comparative study of some non-linear models for predicting the yield of Gmelina arborea plantation
Article Main
Abstract
Yield models are important for effective forest management and as such were developed for the University of Benin Gmelina arborea plantation, Nigeria. The objectives of the study were to develop, evaluate and compare predictions from some non-linear models for timber volume estimation. A total of nine non-linear models comprising of three models each for weibull, logistic and log-normal models were developed using the three independent variables combinations (Basal area and merchantable height, diameter at base and merchantable height, diameter at middle and merchantable height). The assessment criteria (correlation coefficient (R), coefficient of determination (R2), standard error of estimate (SE)) with the validation results (using percentage bias and probability plots of residuals) showed that all categories of weibull and logistic models generated in this study discovered to be very adequate for tree volume estimation. The highest R2 (93.80), lowest SE (0.25) and lowest bias% (1.29) in the study were achieved from Weibull model 1a. The log-normal models were the least adequate for tree volume estimation with the highest bias%. The one way analysis of variance revealed that there were no significant differences in the performance of the non-linear models when varying predictor variables were used. The weibull, logistic models were therefore recommended for further use in this ecosystem and in any other forest ecosystem with similar site condition.
Article Details
Article Details
Gmelina arborea, Plantation, Tectona grandis, Yield models
Adekunle, V.A.J., Akindele, S.O. and Fuwape, J.A. (2004). Structure and yield models for tropical lowland rainforest ecosystem of South West Nigeria. Food. Agric. Environ., 2: 395-399.
Akindele, S.O. and Le May, V.M. (2006). Development of tree volume equations for common timber species in the tropical rainforest area of Nigeria. For. Ecol. Manage., 226: 41-48.
Avery, T.E. and Burkhart, H.E. (2002). Forest Measurements. 5th Edn., McGraw Hill, New York, pp: 456.
Glantz, S.A. and Slinker, B.K. (2001). Primer of applied regression and analysis of variance.2nd ed. McGraw-Hill.
Husch, B., Charles, I. M and Thomas, W. B. (2003). Forest Mensuration. New York, U.S.A.: The Ronald Press Company. pp 120-123 International,Wallingford, UK.
Johnson, Norman L.; Kotz, Samuel; Balakrishnan, N. (1994), "14: Lognormal Distributions", Continuous univariate distributions. Vol. 1, Wiley Series in Probability and Mathematical Statistics: Applied Probability and Statistics (2nd ed.), New York: John Wiley & Sons, ISBN 978-0-471-58495-7, MR 1299979
Lindner, M. and Karjalainen, T. (2007). Carbon inventory methods and carbon mitigation potentials of forests in Europe: a short review of recent progress. European Journal of Forestry Research, 126: 149-156.
Marshall, P.L. and Northway (1993). Suggested minimum procedure for validation of growth and yield model: Growth and yield estimation from successive forest inventories. Proceedings of the IUFRO World Congress, 1993, Copenhagen, pp: 281-281.
Myers, R.H. (1986). Classical and modern regression with applications.Duxubury Press, Boston. 359p.
Nelder, J.A. (1961). The fitting of a generalization of the logistic curve. Biometrics 17: 89-110.
Nwoboshi, L.C. (1982).Tropical Silviculture (Principles and techniques) Ibadan University Press Publishing house University of Ibadan,Ibadan,Nigeria 333pp.
Oliver, F.R. (1964). Methods of estimating the logistic function. Applied statistics 13: 57–66.
Onyekwelu, J.C. and Akindele, S.O. (1995). Stand volume equation for Gmelina arborea plantation in Oluwa forest reserve, Nigeria. Nig. J. For., 25:92-95.
Peng, C. (1999). Nonlinear height-diameter models for nine boreal forest tree species in Ontario.Ministry of Natural Resources. Ont. For. Res. Inst., Sault Ste Marie, ON, For. Res. Rep No. 155. 28 pp.
Ratkowsky, D.A. (1983). Nonlinear regression modeling. Marcel Dekker, New York. 276 p.
University of Benin (1993): Master Plan. University of Benin Printing Press. 360 pp.
Vanclay, J. (1994). Modelling Forest Growth and Yield: applications to mixed tropical forests. CAB International. UK. 312 p.
VanderSchaaf C. (2008). Compatible Stem Taper and Total Tree Volume Equations for Loblolly PinePlantations in Southeastern Arkansas. Journal of the Arkansas Academy of Science, 62:103-106.
Yaoxiang L., Lichun J. and Mingyu L. (2011). A Nonlinear Mixed-Effects Model to Predict Stem Cumulative Biomass of Standing Trees. 2011 3rd International Conference on Environmental Science and Information Application Technology ESIAT 2011. Volume 10, Part A, 2011, Pages 215–221.
Yevide A.,Ganglo J., Glelekakai R., Decanniere C., Fonton N.(2014). Growth modeling of short rotation coppice teak ( Tectona grandis L.f) stands in Republic of Bénin. International Journal of Advanced Agricultural Research 2: 58-66.
This work is licensed under Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) © Author (s)
