Evaluation of Tree Volume Equations for Gmelina arborea Roxb. Stand in Southwestern, Nigeria
Y. I. Egonmwan
*
Department of Forest Resources and Wildlife Management, University of Benin, Benin City, Nigeria.
W. O. Orukpe
Department of Forest Resources and Wildlife Management, University of Benin, Benin City, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
Effective and sustainable forest management is dependent on volume and yield models. This study was carried out to evaluate ten (10) different tree volume equations for the sustainable management of the Gmelina arborea stand in Oluwa forest reserve. A total of 590 trees were used in this study. The observed volume of the sample trees were calculated by the application Newton‘s formula. The performance of each model were evaluated using five fit statistics such as root mean squared error (RMSE), r-squared (R2), Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and relative rank sum were used. All the models in this study performed significantly well in volume estimation as the R2 were above 75% for all the models. Four models (model 10, 8, 6 and 7) performed best for the data set based on their evaluation statistics and as such they were selected for volume estimation of Gmelina arborea stand in Oluwa forest reserve. The evaluation test revealed that model 10 had the least RMSE of 0.2986, hence it was ranked the best model for the study. Scatter plots showed positive correlation between DBH, total height, BA and total volume. The regression residuals were normally distributed, with constant variance and a zero mean.
Keywords: Gmelina arborea, evaluation, residuals, total volume
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References
Bi H. Hamilton F. Stem volume equations for native tree species in Southern New South Wales and Victoria. Australian Forestry. 1998;61:275-286.
Avery TE, Burkhart HE. Forest measurements, 5th ed. McGraw-Hill Higher Education, New York, USA. 2002;456.
Edward TD. Introduction to mathematical economics. McGraw Hill Book Company New York 2nd Edition. 1992:486.
Akindele SO, LeMay VM. Development of tree volume equations for common timber species in the Tropical Rainforest Area of Nigeria. Forest Ecology and Management. 2006;226:41−48.
Roshetko JM, Mulawarman, Purnomosidhi P. Gmelina arborea - A viable species for small holder tree farming in Indonesia; 2005.
Albrecht J. ed. Tree seed hand book of Kenya. GTZ Forestry Seed Center Muguga, Nairobi, Kenya; 1993.
Katende AB, et al. Useful trees and shrubs for Uganda. Identification, Propagation and Management for Agricultural and Pastoral Communities. Regional Soil Conservation Unit (RSCU), Swedish International Development Authority (SIDA); 1995.
Ogana FN, Ekpa NE. Modeling the non-spatial structure of Gmelina arborea Roxb Stands in the Oluwa Forest Reserve, Nigeria. Forestist. 2020;70(2):133–140.
Onyekwelu JC, Mosandl R, Stimm B. Productivity, site evaluation and state of nutrition of Gmelina arborea plantation in tropical rainforest zone in South-Western Nigeria. Forest Ecology and Management. 2006;229:214–227.
Egonmwan IY, Ogana FN. Application of diameter distribution model for volume estimation in Tectona grandis Lf stands in the Oluwa Forest Reserve, Nigeria. Tropical Plant Research. 2020;7(3):573-80.
Hofstad O. Review of biomass and volume functions for individual trees and shrubs in southeast Africa. Journal of Tropical Forest Sciences. 2005;17:151–62.
Henry M, Picard N, Trotta C, Manlay RJ, Valentini R, Bernoux M, Saint-André L. Estimating tree biomass of sub-Saharan African forests: A review of available allometric equations. Silva Fennica. 2011;45: 477–569.
Philip MS. Measuring trees and forests: A textbook written for students in Africa. Dares Salaam: University of Dares Salaam; 1983.
Cao QV, Burkhart HE. Max TA. Evaluation of two methods for cubic volume prediction for loblolly pine to any merchantable limit. Forest Science. 1980;26:71-80.
Spurr SH. Forest inventory. Ronald Press, New York. 1952:476.
Schumacher FX, Hall FDS. "Logarithmic expression of timber tree volume". Journal of Agricultural Research. 1933;47:719- 734.
Sönmez T, Ercanli I, Kele S. A Distance-independent basal area growth model for oriental spruce (Picea orientalis (L.) Link), growing in mixture with oriental beech (Fagus orientalis, Lipsky) in the Artvin region. North-East, Turkey. African Journal of Agricultural Research. 2009;4: 740–751.
Adam HE, Csalovics E. Integration of remote sensing, GIS, and terrestrial forest inventory in estimation of Acacia senegal tree parameters. In: Rainer Reuter (Ed), Remote Sensing for Science, Education, and Natural and Cultural Heritage, EARSeL. 2010:6.
Andreassen K, Tomter SM. Basal area growth models for individual trees of Norway spruce; Scots Pine; Birch and other broad leaves in Norway. Forest Ecology & Management. 2003;180:11− 24.
Mabvurira D, Miina J. Individual-tree growth and mortality models for Eucalyptus grandis (Hill) maiden plantations in Zimbabwe. Forest Ecology & Management. 2002;161:231–245.
Zhao D, Borders B, Wilson M. Individual-tree diameter growth and mortality models for bottomland mixed-species hardwood stands in the Lower Mississippi Alluvial Valley. Forest Ecology and Management. 2004;199:307–322.
Trasobares T, Pukkala T. Using past growth to improve individual tree diameter growth models for uneven-aged mixtures of Pinus sylvestris L. and Pinus nigra Arn in Catalonia, North-East Spain. Annals For Sci. 2004;61:409–417.