**ABSTRACT**

Forests have several pools that acts as carbon sink to atmospheric carbon which is released by anthropogenic causes. Leaf litter is one of those very important pools whose role in nutrient cycling and carbon sequestration cannot be overemphasized. This study was conducted to develop equations for carbon stored in leaf litter of *Tectona grandis* using tree growth characteristics as explanatory variables. Data was collected from four 20 m × 20 m sample plots which were randomly selected. Within each plots, four litter traps were set to collect leaf litter on a weekly basis. The collected litter was further taken to the laboratory for carbon analysis. The tree growth variables measured in the plots were processed into suitable form for statistical analyses using descriptive statistics in form of tables, charts and graphs and inferential statistics using correlation and regression analysis. Different equation were developed and tried with different tree growth characteristics with a view to select the best equation among the simulated ones. The equation with a highest coefficient of determination (R^{2}) and lowest standard error of estimate (SEE) was selected as the best fit. The average leaf litters produced per day ranged from 2.26g/m^{2} to 7.67g/m^{2}, the maximum and minimum values of carbon stored in the studied species was 63%, 59% respectively. All the tried equations were significant and fit the data set well. The result showed that the logarithm equation has the highest R^{2} and lowest SEE values and was therefore selected as the best model. Result from the validated models showed that all tried equations except the exponential equation were good for prediction. Conclusively, the ability of the forest to sequester carbon is a function of the biomass production which is linked to the litter fall produced by the system. Since litter fall represent a major flux for the transfer of carbon and other nutrients between the vegetation and soil, it should therefore not be altered in order not to have an effect on below ground processes. Even though the scope of this study only covers a very small area and sample of the Nigeria forest, it is still very important for prediction of leaf litter carbon and hence, served as a tool for sustainable forest management.

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