Tropical Plant Research
An International Journal by Society for Tropical Plant Research
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2020, VOLUME 7 ISSUE 3Pages: 609-618
Slenderness coefficient models for tree species in Omo biosphere reserve, South-western Nigeria
A. O. Oladoye, P. O. Ige, N. Baurwa, Q. A. Onilude and Z. T. Animashaun
*Federal University of Agriculture, Abeokuta, Nigeria
Abstract:
This study was carried out to aid the prediction of tree slenderness coefficient using non-linear regression models for tree species in Omo Biosphere Reserve, Southwestern Nigeria. Systematic line transect design was adopted for the study. Three transects were laid with four plots on each transect at alternate positions which made a total of 12 sample plots (50 m × 50 m) in the study area. Diameter at breast height (DBH), diameter at the top, diameter at the middle and diameter at the base as well as total height and merchantable height of all trees were measured. Descriptive statistics, Pearson’s correlation and regression analysis were adopted for the study. The study showed that about 23.5% of the trees in the study area are susceptible to wind-throw damage. Correlation analysis revealed that DBH is a better predictor of Slenderness coefficient than other tree growth characteristics. Six non-linear models were adopted for the tree slenderness coefficient prediction. The best models were selected based on the highest Adj.R2, lowest AIC and SEE values. Normal logarithmic equation SLC = 30.72 + (-41.21) In(D) was selected as the candidate model for the pooled data. The same candidate model (Natural logarithm) was selected for both the Desplatsia lutea and Strombosia pustulata species with the equation SLC = -0.04 + (-63.82) In(D) and SLC = 22.12 + (-51.40) In(D) respectively while exponential model with equation SLC = 170.94e(-1.93) was selected for Sterculia rhinopetala. These equations were recommended for predicting slenderness coefficient for each of the tree species in Omo Biosphere with apparently valid potentials for enhancing reasonable quantification of the stands’ stability.
This study was carried out to aid the prediction of tree slenderness coefficient using non-linear regression models for tree species in Omo Biosphere Reserve, Southwestern Nigeria. Systematic line transect design was adopted for the study. Three transects were laid with four plots on each transect at alternate positions which made a total of 12 sample plots (50 m × 50 m) in the study area. Diameter at breast height (DBH), diameter at the top, diameter at the middle and diameter at the base as well as total height and merchantable height of all trees were measured. Descriptive statistics, Pearson’s correlation and regression analysis were adopted for the study. The study showed that about 23.5% of the trees in the study area are susceptible to wind-throw damage. Correlation analysis revealed that DBH is a better predictor of Slenderness coefficient than other tree growth characteristics. Six non-linear models were adopted for the tree slenderness coefficient prediction. The best models were selected based on the highest Adj.R2, lowest AIC and SEE values. Normal logarithmic equation SLC = 30.72 + (-41.21) In(D) was selected as the candidate model for the pooled data. The same candidate model (Natural logarithm) was selected for both the Desplatsia lutea and Strombosia pustulata species with the equation SLC = -0.04 + (-63.82) In(D) and SLC = 22.12 + (-51.40) In(D) respectively while exponential model with equation SLC = 170.94e(-1.93) was selected for Sterculia rhinopetala. These equations were recommended for predicting slenderness coefficient for each of the tree species in Omo Biosphere with apparently valid potentials for enhancing reasonable quantification of the stands’ stability.
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