Tree basal area models and density for selected plantation species in swamp forest zone of Rivers State, Nigeria

Individual-tree models of basal area growth and density were developed for seven plantation species in swamp forest zone of Rivers State, Nigeria. Tree growth data were collected from pure permanent sample plots of seven plantation species within the study area with measurements of diameter at breast height (cm), diameter at the base (cm), total height of tree (m), and also the number of tree per plot was taken and obtained from plantation records. The Quantitative data collected from these selected plantation species were subjected to descriptive analysis, correlation and regression analyses. Linearized models for description of relationship between BA and other growth attributes were developed. The results of the major growth variables by species in the study area showed that Treculia africana has the highest dbh mean value 30.804 ±2.031 (cm) with density 0.0022 and basal area per hectare 1.79×10–4 (m2). Similarly, the results also showed that Nauclea dedirrichii has the lowest dbh mean value 08.484 ±0.339 (cm) with basal area 3.92×10–5 (m2) and density 0.0063 per hectare. The results of correlation analyses showed general associations between basal area and the growth attributes by species with coefficients of correlation ranging from –0.023 to 0.999. The results similarly revealed distinct variations by species in density, basal area and tree number in the study area. The results of relationship between basal area and other growth variables showed significant model fit (best fit) with diameter attributes with model order: LNBA = b0 + b1lnDb + b2Dbh2 in Enthandrophragma angolense (R2 - 0.964, RSME – 0.837). The results of the study revealed that there were significant variations in the growth attributes by species in the study area; with significant associations between the basal area and major growth variables evaluated in the study, while the selected best adjudged fit model in the study area could be reasonably used for predicting basal area which is critical in cubical volume estimation and sustainable management of the study area.