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Growth and yield models for teak in Shangev-Tiev Plantation, Konshisha Local Government Area Benue State, Nigeria

V.D. Popoola
N.G. Ude


Growth and yield models can estimate future yields and explore silvicultural options. Models enable an effective process to prepare resource forecasts, the most significant aspect is its potentials to explore management options and silvicultural alternatives. Growth and yield models give a mathematical and statistical way to quantifying the quantity of wood in a tree without felling the tree in order to manage wood resources, take economic choices and promote sustainable forest management. The increasing wave of errant and unmanaged exploitation of forests causes high rate of deforestation therefore the reservation of forest estates has to be created. The aim of this study was to assess the growth and yield models of Shangev-tiev teak plantation in Konshisha Local Government Area of Benue State. Twenty-five sample plot size of 20m x 20m were randomly selected. Growth variable measured were total height, diameter at breast height and diameter at the base. A total of twelve volume models was selected to estimate tree volume. Tree volume had a mean of 1.27m3 with 2.68m3 as the maximum volume. All the models generated have positive intercepts. Models 3, 7, 11 and 12 had a R2 value of 0.99 and standard error estimate of 0.01. lnV= 0.30 + 0.01 ln (D) had the highest F-Ratio value of 4385 with a R2 value of 0.90 and standard error estimate of 0.25. Model 5 is recommended for use in the study area because it is simpler and practical because it needs only one explanatory variable (diameter at breast height) to be measured and by pass the height measurements that is time-consuming and costlier. It also by passes the errors inherent in height measurements of standing trees. It is recommended that beating up should be carried out because of the shortage of trees as a result of deforestation, expansion and associated erection of buildings to avoid extinction of trees in the study area.

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print ISSN: 2141-1778