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Hypsometric equations of selected tree species in university of port Harcourt

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Author Affiliations

  • 1Department of Environmental Forestry and Wildlife Management, Faculty of Agriculture, University of Port Harcourt, Rivers State, Nigeria
  • 2Department of Environmental Forestry and Wildlife Management, Faculty of Agriculture, University of Port Harcourt, Rivers State, Nigeria
  • 3Department of Environmental Forestry and Wildlife Management, Faculty of Agriculture, University of Port Harcourt, Rivers State, Nigeria

Int. Res. J. Environment Sci., Volume 14, Issue (3), Pages 42-49, July,22 (2025)

Abstract

Deeper comprehension of the relationship between hypsometric equations and forest growth and yield models would enhance forest monitoring, management, and volume estimation. Numerous elements, including socioeconomic position, age, density, sivilcultural treatments, species features, and the quality of the forest site, influence this relationship. .Therefore, the aim of this study was to develop suitable hypsometric models for the selected tree species in University of Port Harcourt using purposive sampling technique. Four regression model (linear, parabolic, hyperbolic and weibull) functions were developed and four amenity trees were selected for this study. Growth variables such as: Total height, Clear Bole height, Merchantable height, Crown length, Crown diameter, Diameter outside bark at breast height (DBH, 1.3m above the ground) were measured and processed into suitable form for statistical analysis using descriptive statistic and correlation analysis. Among the selected species, Terminalia mantaly was the most abundant species present accounting for 26.6% (75), followed by Mangifera indica 25.2% (71), Azadirachta indica 24.8% (70) and Terminalia catappa 23.4% (66). The correlation matrix observed a significant difference between height and other growth variables. However, merchantable height has the highest correlation value of 0.780 at p>0.01. Although all models revealed no significant difference between the mean observed and mean predicted values, meaning the model is fit for height diameter prediction. The best hypsometric model observed was Weilbull function with the highest coefficient of determination (R2=0.601) and the lowest standard error of estimate (SEE =2.440). Conclusively, the result of this study has evidently revealed that the weibull function can be used in developing hypsometric equations and recommended due to their suitable height prediction and biological simplicity.

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