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Studies have shown that information on landscape transformation is an important benchmark data set because of its value as an environmental change indicator. Therefore, dynamism of landscape transformation over a 34-year period are analysed for a case study in Ibiono-Ibom, Akwa-Ibom State, Nigeria. The study adopted a mixed method consisting of remote sensing and GIS-based analysis, and semi-structured interviews covering 400 households while factors contributing to landscape structures and changes are studied. The results point out three main driving factors responsible for the landscape transformation in the study area: agricultural practices which lead to intensification of forest resources, riparian vegetation, vegetated wetlands and non-vegetated wetlands; urbanization which modifies the structure and morphology of the landscape, and finally, population growth directly related to massive infrastructural development which encroached on all other land spaces. GIS-based analysis of remotely-sensed data showed that built-up area had increased by 7535.2 ha between 1986 and 2020; shrub and arable land by 1343.9 ha and light forest decreased by 4998.3 ha. While bare-land reduced by 1522.1 ha; vegetated wetland reduced by 1092 ha; water body coverage reduced by 168 ha and non-vegetated wetland size also reduced by 2029.4 ha. Analysis of household survey results revealed that the perceptions of respondents validate the observed patterns during the remotely-sensed data analysis phase of the research, with 54 % (n=400) of respondents reporting a decline in agricultural land use, and 19.3 % (n=400) observing a decline in forest areas in the study area. Furthermore, agricultural intensification, urban development, timber exploitation, firewood collection and increase in settlements were identified as the proximate drivers of these observed landscape transformation dynamics in the study area. The study concluded that the variation in landscape transformation of the study area are clear indication of the extent of biodiversity loss and ecosystem degradation in the study area.

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Cocoa is known as one of the notable cultivated cash crops of the tropical rainforest of the world that is rain dependent. The study examines the effect of rainfall variation on the yield of cocoa plantation in Ondo State, Nigeria. Data used for the study includes the rainfall data of 15 years from 2000 to 2014 collected from Ondo state agro climatological office as well as cocoa yield data for the same period of time from Ondo State ministry of agriculture and forest resources. Descriptive statistical method was employed to determine the relationship between both variables in which the result shows direct relationship between rainfall and cocoa yield. Results were presented using bar charts and line graph for the time series analysis of the variables. Linear regression statistical analysis was used to predict cocoa yield with certain amount of rainfall with the correlation coefficient ‘r’ value of 0.97 which implies that rainfall changes go a long way to determine the same variation trend in the cocoa yield. Though, not only the quantity of rainfall within the range of rainfall required for the growth of this crop affect the yield but its distribution. A little millimeter of rainfall above or below the required range of rain for cocoa plantation greatly affects cocoa yield.