FOREST RESOURCE CONSERVATION AND RURAL LIVELIHOOD IMPROVEMENT IN GHANA : THE PROMISE OF A MODIFIED TAUNGYA SYSTEM

This dissertation addressed four questions: 1) What landcover changes have occurred in Yaya, Nsemre, and Sawsaw forest reserves in Ghana’s Brong Ahafo region before and after Ghana’s MTS program was launched in 2002? 2) What factors influenced the community and household selection into the MTS program? 3) What changes in livelihood assets have occurred among MTS participants and non-participant households since the launching of the program in 2002? And 4) To what extent are the changes in household livelihood assets attributable to the MTS program? An unsupervised landcover classification of January 1990 and 2000 LANSAT images and January 2012 DMC satellite images of the three reserves suggest an initial growth of 0.26 Km2/year in forest cover in Yaya between 1990 and 2000 and then a doubling of growth to about 0.52 Km2/year between 2000 and 2012. Unlike Yaya, forests cover in Nsemre declined by -0.37 Km2/year during the pre-MTS period and then increased sharply at an annual rate of 0.45 Km2 during the post-MTS era. Similar to the trends in Nsemre, Sawsaw likewise experienced an initial decline of -0.73 Km2 in forest cover before increasing annually at a rate of 0.31 Km2 post-MTS. To address research questions two and three, 878 households were surveyed in 19 communities in Yaya, Nsemre, and Sawsaw. Included in the Yaya survey were 406 MTS participants and 240 non-participant households. Also surveyed were another 232 non-participating households in nine communities around Nsemre (4) and Sawsaw (5) where the MTS program did not exist. A Binomial Probit Model (BPM) generated from the survey data, suggests that cash, farm inputs, and labor assistance from local religious organizations, migrant work, type of roof, and proximity to paved roads significantly (p<0.001) increased the expected probability of MTS community selection. Average land ownership exceeding two acres had a significantly (p<0.001) negative influence on MTS community selection. A GIS community mapping exercise conducted in the 19 research communities produced 1,446 household data points used in generating another BPM used to determine the extent to which proximity of households to communal physical assets influenced MTS selection. According to BPM, seven factors significantly increased the predicted probability of MTS community selection, while nine significantly reduced the chance of selection. Also, five factors positively influenced selection while two negatively impacted selection. In order to track changes in livelihood assets post-MTS, five livelihood indexes were constructed and compared for two time periods before and after MTS. The result suggests that the aggregate household physical capital index increased by 17% while social and financial capital both increased by 2% between 1999 and 2009. Also, the human capital index increased by 3% while the natural capital index decreased by 5%. To address question four, a Difference in Difference (DID) model was used to isolate changes in the livelihood indexes between 1999 and 2009 that may be directly attributed to the MTS project or spillover. The DID results indicate that on average, MTS resulted in a 6.8% increase in annual household income and income sufficiency index, a 2.3% increase in the combined household natural capital index, and a 4.8% increase in cropland ownership index. The DID also suggests that MTS participation may be directly responsible for the 2.5% increase in combined household physical capital index and the 1.5% aggregate household social capital index among project participants between 1999 to 2009. Of the DID livelihood indexes, the combined household human capital index (CHCI) was the least impacted by the MTS (0.4%).