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Soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria were studied using principal component analysis (PCA) and canonical correlation analysis (CCA). The grid system of vegetation sampling was employed to randomly collect vegetation and soil data from fifteen quadrats of 10 m × 10 m. PCA result showed that exchangeable sodium, organic matter, cation exchange capacity, exchangeable calcium, and sand content were the major soil properties sustaining the regenerative capacity and luxuriant characteristics of the secondary forest, while tree size and tree density constituted the main vegetation parameters protecting and enriching the soil for its continuous support to the vegetation after decades of anthropogenic disturbance (food crop cultivation and illegal logging activities) before its acquisition and subsequent preservation by the Cross River State government in 2003. In addition, canonical correlation analysis showed result similar to PCA, as it indicated a pattern of relationship between soil and vegetation. The only retained canonical variate revealed a positive interrelationship between organic matter and tree size as well as an inverse relationship between organic matter and tree density. These extracted soil and vegetation variables are indeed significantly important in explaining soil-vegetation interrelationships in the highly regenerative secondary forest.

The effects of three different ages of natural fallow vegetation on runoff and sediment loss were investigated in a part of the rainforest zone of Nigeria. Measurements of runoff amount and sediment loss were made for the months of March to November in 2012 rainy season using runoff plots of 40 m 2 . The average runoff amount for the 5-year-old, 3-year-old, and farmland plots were 0.47, 0.26, and 0.41 mm respectively. The average sediment loss on the 5-year-old, 3-year-old, and farmland plots were 209.24, 50.54, and 124.68 kg/ha, respectively. The lowest losses for both runoff and sediment were recorded on the 3-year-old plot, while the 5-year-old plot experienced the highest losses. The variations in runoff and sediment loss among the treatments were significant at P < 0.001. The results evidently showed that rainfall was principally responsible for the erosional losses on all the fallow treatments, and that ground cover (density of herbs) and girth helped to reduce sediment loss on the 3-year-old and farmland surfaces, respectively. The high amount of erosional losses experienced on the 5-yearold fallow than on the 3-year-old fallow and farmland plots imply that fallow that is not adequately protected by ground cover experiences accelerated soil erosion. The continuous loss in topsoil rich in plant nutrients may prolong the optimal capacity of the soil to regain its loss nutrient for subsequent food crop cultivation.

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Multivariate statistical techniques were employed to study soil-vegetation interrelationships in a secondary forest of South-Southern Nigeria. The grid system of vegetation sampling was used to randomly collect vegetation and soil data from fifteen quadrats of 10m x 10m. The result of principal components analysis identified seven basic sets of soil-vegetation variables that enhanced the interrelationships. Canonical correlation result indicated a positive association between organic matter and tree size, while the linear association between organic matter and tree density revealed an inverse relationship. The result of redundancy coefficient indicated that 18 percent of the variance in vegetation characteristics was accounted for by the variability in soil properties whereas, 81 percent of the variance in soil properties was accounted for by the variability in vegetation characteristics. The regression analyses on the other hand indicated that exchangeable sodium positively influenced tree species composition and richness; and that tree size as well as tree density exerted substantial influence on the contents of organic matter and total nitrogen of the soil. However, drawing inference from results of canonical correlation analysis and those of multiple regression analysis, it was concluded that soil and vegetation components of the secondary forest vegetation were mutually dependent and therefore exerted joint influences on each another.