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Background: The West African country of Burkina Faso (BFA) is an example for the enduring importance of traditional plant use today. A large proportion of its 17 million inhabitants lives in rural communities and strongly depends on local plant products for their livelihood. However, literature on traditional plant use is still scarce and a comprehensive analysis for the country is still missing.
Methods: In this study we combine the information of a recently published plant checklist with information from ethnobotanical literature for a comprehensive, national scale analysis of plant use in Burkina Faso. We quantify the application of plant species in 10 different use categories, evaluate plant use on a plant family level and use the relative importance index to rank all species in the country according to their usefulness. We focus on traditional medicine and quantify the use of plants as remedy against 22 classes of health disorders, evaluate plant use in traditional medicine on the level of plant families and rank all species used in traditional medicine according to their respective usefulness.
Results: A total of 1033 species (50%) in Burkina Faso had a documented use. Traditional medicine, human nutrition and animal fodder were the most important use categories. The 12 most common plant families in BFA differed considerably in their usefulness and application. Fabaceae, Poaceae and Malvaceae were the plant families with the most used species. In this study Khaya senegalensis, Adansonia digitata and Diospyros mespiliformis were ranked the top useful plants in BFA. Infections/Infestations, digestive system disorders and genitourinary disorders are the health problems most commonly addressed with medicinal plants. Fabaceae, Poaceae, Asteraceae, Apocynaceae, Malvaceae and Rubiaceae were the most important plant families in traditional medicine. Tamarindus indica, Vitellaria paradoxa and Adansonia digitata were ranked the most important medicinal plants.
Conclusions: The national-scale analysis revealed systematic patterns of traditional plant use throughout BFA. These results are of interest for applied research, as a detailed knowledge of traditional plant use can a) help to communicate conservation needs and b) facilitate future research on drug screening.
BIOfid is a specialized information service currently being developed to mobilize biodiversity data dormant in printed historical and modern literature and to offer a platform for open access journals on the science of biodiversity. Our team of librarians, computer scientists and biologists produce high-quality text digitizations, develop new text-mining tools and generate detailed ontologies enabling semantic text analysis and semantic search by means of user-specific queries. In a pilot project we focus on German publications on the distribution and ecology of vascular plants, birds, moths and butterflies extending back to the Linnaeus period about 250 years ago. The three organism groups have been selected according to current demands of the relevant research community in Germany. The text corpus defined for this purpose comprises over 400 volumes with more than 100,000 pages to be digitized and will be complemented by journals from other digitization projects, copyright-free and project-related literature. With TextImager (Natural Language Processing & Text Visualization) and TextAnnotator (Discourse Semantic Annotation) we have already extended and launched tools that focus on the text-analytical section of our project. Furthermore, taxonomic and anatomical ontologies elaborated by us for the taxa prioritized by the project’s target group - German institutions and scientists active in biodiversity research - are constantly improved and expanded to maximize scientific data output. Our poster describes the general workflow of our project ranging from literature acquisition via software development, to data availability on the BIOfid web portal (http://biofid.de/), and the implementation into existing platforms which serve to promote global accessibility of biodiversity data.