ABSTRACT
Demand for medicinal plant remedies is rising globally, while indigenous knowledge about medicinal plants is declining rapidly. The preservation of indigenous knowledge is critical in discovering and developing innovative drugs. The ongoing discussions on providing nature-based solutions to contemporary issues make it urgent to document indigenous knowledge about medicinal trees, especially in areas with limited or no studies such as our study area. Our study aimed to understand the use of medicinal trees among the communities fringing the Asukese and Amama Shelterbelt Forest Reserves. We administered structured questionnaires and interviewed 88 respondents who were selected using snowball and simple random techniques. The ethnobotanical survey data were processed and evaluated using parameters such as Indigenous Knowledge Index (IKI), Relative Citation Frequency (RCF), Species Use Value (SUV), Family Use Value (FUV), and Plant Part Value (PPV). We found that ethnobotanical knowledge about medicinal trees was higher in respondents who were widowed or had larger number of dependants. We found that the local communities used diverse medicinal trees (70 species belonging to 33 families) to treat 83 ailments. Azadirachta indica had the highest RCF (8.9) and SUV (23.4). The other top four species according to the SUV were Alstonia boonei (SUV = 11.1), Khaya senegalensis (SUV = 10.7), Moringa oleifera (SUV = 10.3) and Cocos nucifera (SUV = 10.2). The most-well represented and valuable families were Fabaceae, Anacardiaceae, Meliaceae, Arecaceae, Rubiaceae and Malvaceae. Medicinal trees had alternative uses such as food, fodder, fuelwood, and construction material. Indigenous knowledge about medicinal trees was transmitted to younger generations predominantly by parents. The results show that the most known botanical families and species with the most useful parts were the most useful plant families and species. Thus, the selection of medicinal trees was driven by their traits. Furthermore, results indicate that species diversity is critical to the healthcare needs of local communities and that their conservation and sustainable use and the preservation of indigenous knowledge are crucial to ensuring good health and the general well-being of local communities of all ages.
ABSTRACT
Allometric models which are used to describe the structure of trees in agroforestry systems are usually extrapolated from models developed for trees in forest ecosystems. This makes quantitative assessment of the functions of shade trees in agroforestry systems challenging since increased availability of light and space in these systems may induce structural differences from those growing under forest conditions. We addressed this issue by providing species-specific allometric information on the structural characteristics of associated shade trees on cocoa agroforestry systems and assessed if allometries conformed to theoretical predictions. At the plot level, stand and soil characteristics affecting tree structural characteristics were assessed. The study was conducted in cocoa agroforestry systems at Suhum, Ghana. The height-diameter at breast height (H-DBH) allometry had the best fits (R2 = 53-89%), followed by the crown area (CA)-DBH allometry (R2 = 27-87%) and then the CA-H allometry (R2 = 22-73%). In general, the scaling exponents of the CA-DBH, H-CA and H-DBH allometries conformed to the metabolic scaling theory (MST). However, both the CA-DBH and H-DBH allometries diverged from the geometric similarity model. Though forest tree species had similar crown areas as fruit trees, they were slenderer than fruit trees. Tree slenderness coefficients were positively correlated with soil P, Ca, Cu and the ratios (Ca + Mg):K, (Ca + Mg):(K + Na) and Ca:Mg, but not C:N while DBH and H were correlated with soil P and C:N ratio. Our results show that critical soil nutrients and their ratios affects shade tree structural attributes (e.g. slenderness and CA), which possibly restrict variations in species-specific allometries to a narrow range on cocoa systems. Furthermore, shade tree species richness and density are better predictors of relative canopy projection area (a proxy for shade intensity) than tree species diversity. In conclusion, the results have implications for shade tree species selection, monitoring of woody biomass and maintenance of biodiversity.
