An imprecise probability approach-based determination of over-represented southern African plant genera and families used in ethnopharmacology.
The analyses of patterns of over-representation of southern African traditional medicinal plants at the genus and family level provide information about the differences in plant use among southern African countries and disease categories. 'Over-representation' refers to the phenomenon whereby the pr...
| Publicado en: | Journal of Ethnopharmacology Vol. 324 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Elsevier B.V.
Apr2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175297075&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175297075 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03788741 3MS jtl: Journal of Ethnopharmacology issn: 03788741 maglogo: N pubinfo: dt: Apr2024 vid: 324 pid: 1004 pub: Elsevier B.V. artinfo: ui: 175297075 10.1016/j.jep.2024.117757 175297075 ppct: 1 formats: tig: atl: An imprecise probability approach-based determination of over-represented southern African plant genera and families used in ethnopharmacology. aug: au: Moyo, Prince N. van Heerden, Fanie R. affil: School of Chemistry and Physics, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, Pietermaritzburg, South Africa sug: subj: Medicine, African Traditional Utilization Disease Vectors Prevention and Control South Africa Surveys Pearson's Correlation Coefficient ab: The analyses of patterns of over-representation of southern African traditional medicinal plants at the genus and family level provide information about the differences in plant use among southern African countries and disease categories. 'Over-representation' refers to the phenomenon whereby the proportion of plants belonging to a taxonomic group is higher in ethnobotanical pharmacopoeia than in the total flora. This study aimed to use the Imprecise Dirichlet Model (IDM) to analyse data from ten southern African countries to establish how over-represented medicinal plant families compare with over-represented genera, how over-represented medicinal taxa differ among countries in this region of Africa, and how over-represented taxa differ among six major disease categories. Floral data for the total species composition of each country were obtained from online databases. Medicinal plant species lists were generated from published surveys, inventories, and books. IDM calculations were executed using the inverse of the cumulative beta probability density function in Microsoft Excel™. Python programming language source code was used to calculate Pearson correlation (r) values and Jaccard coefficients (J). Nine of forty-two over-represented medicinal plant families in southern Africa (group 1) do not have over-represented genera. Seven of the forty genera with the highest margins of over-representation belong to under-represented families. Nineteen of the forty-two over-represented families have margins of over-representation smaller than the cumulative margins of their over-represented genera. Groups of countries with similar overall flora (J ≥ 0.333) are Botswana and Namibia (group 2), Malawi, Mozambique, Zambia and Zimbabwe (group 3). The families and genera with the highest margins of over-representation are Loganiaceae and Albizia in group 1, Combretaceae and Vachellia in group 2, Dioscoreaceae and Senna in group 3, and Sapotaceae and Solanum in group 4 (South Africa). The families and genera with the highest margins of over-representation across disease categories are Ebenaceae and Albizia , Canellaceae and Dicoma , Combretaceae and Pterocelastrus , Ebenaceae and Bersama , Francoaceae and Erythrina , and Aristolochiaceae and Strychnos for plants used in the treatment of STIs, febrile and mosquito-vector diseases, microbial infections, pain, skin conditions, and female sexual/reproductive problems, respectively. Genus-level calculations are more efficient in generating taxonomic lists that can be used for ethnopharmacological investigations due to the exclusion of under-represented genera. Limiting the size of geographical areas from which medicinal plant lists are sampled and targeting plants used to treat specific types of disease prevents the underestimation of niche over-represented taxa. [Display omitted] pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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