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

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-layer

Assessment of Tree Diversities in Oban Division of the Cross River National Park (CRNP), Nigeria

Many tropical forests are under great anthropogenic pressure and require management intervention to maintain the overall biodiversity, productivity and sustainability. This cannot be possible without proper understanding of their structure and species diversities. Tree diversity in Oban Division of the CRNP was assessed. Systematic sampling technique was adopted for plot locations. Two transects, 2km long with a distance of 600m apart were cut in each of the three study sites. Four plots of 50m×50m were laid alternately along each transect at 500m intervals in the closed canopy and secondary forests. Forty-eight plots were used for the study. Tree growth parameters were measured on all the trees with Dbh>10cm within each plot. All the measured trees were identified and classified into their respective families. Species diversity indices were computed for the trees in the two forest types. The canopy layer to which each tree belongs was noted. Data were analyzed using descriptive statistics, Diversity Indices, t-test as well as analysis of variance. A total of 118 species (107 genera and 37 families) of trees were recorded, with 72 and 69 species in the closed canopy and secondary forests respectively. The Strombosia spp. was the most abundant species in the forests. The family, Olacaceae accounted for 11.94% of the total individuals recorded in the area. This was followed by Mimosoideae (8.4%). The average tree stems/ha was 158 and 130 in the closed canopy and secondary forest respectively. The Simpson’ Indices were 0.99 and 0.98 for the two forest types respectively, which implied high floristic richness. The Shannon-Wiener’s Indices (4.36 and 4.14) and the equitability ratios (0.9513 and 0.9506) were high for the two forest types, which indicated moderate representation of most of the species in the area. The tree growth parameters significantly differ under different canopy layers (P<0.05). However, most of the parameters were not significantly different in the two forest types (P>0.05).Key words: forest-types, species, families, diversity indices, growth parameter