Abstract:
This study was carried out to examine the relationship among tree species diversity, growth variables and soil properties of natural forest ecosystem (rainforest) in Southwest Nigeria. Data collection took place in undisturbed Forest Reserves and an adjoining disturbed free area forest. The undisturbed natural forest is represented by three forest reserves namely Akure Forest Reserve (Queens Plot Aponmu), Oluwa Natural Forest, Permanent Sample Plot (PSP 29) in Akure Forest Reserve while the disturbed forest is represented by an adjoining free area to PSP. The Systematic Line Transect method was employed in laying of plots where tree growth data and soil samples were collected. In each of the study site, two parallel transects of 200m apart were laid and four equal sized sample plots (25x25 m) were laid in alternate direction on each transect. So, a total sum of 16 sample plots was accessed in all the selected forest reserves. On each sample plot, all trees with DBH ≥ 10 cm were tagged, measured, identified and classified into families and their frequency of occurrence were also obtained to ascertain tree species diversity and abundance. The diameters at the base, middle and top and the total height of all the trees in each of the plots were also measured for volume estimation. Soil samples were collected at a depth of 0-30cm from each plot to form composite samples which were analyzed for microbial (Fungi and Bacteria) population using the standard procedure. The chemical properties of the soil samples were also determined in the laboratory with standard procedures for each element. Biological indices were used for tree species diversity assessment and comparison. All the variables obtained were grouped into Microbial and Chemical properties, Microbial and Growth variables, Microbial and Biodiversity indices, Chemical properties and Biodiversity indices, and Growth variables and Biodiversity indices. Five model forms (Simple linear regression, power, exponential, logarithm transformed and Binomial) were generated to assess
