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Crown ratio models for tropical rainforests species in Oban division of the cross river national park, Nigeria


AA Adeyemi
SO Jimoh
PO Adesoye

Abstract

Crown ratio (CR) is a characteristic used to describe the crown size, which is an important element of forest growth and yield. It is often used as an important predictor variable for tree-level growth equations. It indicates tree vigour and is an important habitat variable. It is often estimated using allometry. Modified versions of Logistics, Richards, Weibull and Exponential functions were used to predict CR for tree species in the Oban Division of the Cross River National Park. Systematic sampling technique was adopted in the three study sites (Aking; Ekang and Old-Netim) for plot locations. Two transects of 2km long with a distance of 600m apart were cut in each of the study sites. Four sample plots of 50m×50m were then laid alternately along each transect at 500m intervals. This procedure was repeated in the close-canopy and secondary forests in the three study sites. Forty-eight sample plots were used for the study. Tree variables (Dbh; diameter at the middle and merchantable top; crown diameter; total height; merchantable height; stem quality and crown length were measured on all the trees with Dbh>10cm. The canopy layer to which each tree belongs was noted. All the measured trees were identified. The Weibull and Exponential functions gave consistent and accurate results in almost all the canopy layers in the two forest types with R2; SEE values of 0.72; 0.068 and 0.72; 0.067 respectively for the dominant canopy, 0.75; 0.075 and 0.75; 0.074 respectively for the co-dominant canopy. Exponential function produced the best fit models in the study except under intermediate canopy layer, where it was not found suitable for crown ratio predictions. However, the difference in results produced by the two functions is negligible. They are therefore recommended for crown ratio prediction studies in Oban Division of the Cross River National.

Keywords: Tree-crown, predictions, functions, tree variables, canopy-layers


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eISSN: 1595-7470