No abstract

No abstract

The triggers of forest area loss in Cameroon have not been properly understood. The measures used to curb forest area loss have been simplistic, generalized with no clear cut knowledge of the specific role of different potential factors. This study aims at investigating the hypothesis that population growth is the main cause of loss in forest area. This study will be able to identify what factors are of more significance in the causal equation. The open R programming software has been used to produce multiple linear regression models. The correlation between the dependent variable and the independent variables was established by a correlation matrix and the strength of the models tested by power analysis. The results supports the hypothesis that population growth is the most dominant cause of deforestation in Cameroon while arable production and permanent crop land and arable production per capita index are second and third respectively.

No abstract

Aims: This paper evaluates the interactions between forest area, CO 2 emissions, rainfall and arable production at a national scale in Cameroon. Methodology:The data used for this analysis was essentially time series data for all the variables spanning the period 1961-2000. It uses regression analysis to determine the most important of these variables that affects CO 2 emissions and uses correlation analysis and coefficient of determination to verify the nature of the interactions between the variables. Results: The results show that as forest area reduces there is an increase in CO 2 emissions concentration in the air in Cameroon. On the other hand, as forest area and rainfall reduce arable production also reduces but forest area is seen to be more responsible for changes in arable production than rainfall. Conclusion:The study concludes that the interactions between CO 2 and forest area, arable production and forest area seem to be the most significant while rainfall is denoted as very variable from year to year.