首页> 外文期刊>Journal of Ethnopharmacology: An Interdisciplinary Journal Devoted to Bioscientific Research on Indigenous Drugs >An imprecise probability approach for the detection of over and underused taxonomic groups with the Campania (Italy) and the Sierra Popoluca (Mexico) medicinal flora
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An imprecise probability approach for the detection of over and underused taxonomic groups with the Campania (Italy) and the Sierra Popoluca (Mexico) medicinal flora

机译:使用坎帕尼亚(意大利)和塞拉波波卢卡(墨西哥)药用菌群检测过量和未充分利用的分类学类别的不精确概率方法

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Aim of the study: We use the IDM model to test for over- and underuse of plant taxa as source for medicine. In contrast to the Bayes approach, which only considers the uncertainty around the data of medicinal plant surveys, the IDM model also takes the uncertainty around the inventory of the flora into account, which is used for the comparison between medicinal and local floras. Materials and methods: Statistical analysis of the medicinal flora of Campania (Italy) and of the medicinal flora used by the Sierra Popoluca (Mexico) was performed with the IDM model and the Bayes approach. For Campania 423 medicinal plants and 2237 vascular plant species and for the Sierra Popoluca 605 medicinal plants and 2317 vascular plant species were considered. Results: The IDM model (s=4) indicates for Campania the Lamiaceae and Rosaceae as overused, and the Caryophyllaceae, Poaceae, and Orchidaceae as underused. Among the Popoluca the Asteraceae and Piperaceae turn out to be overused, while Cyperaceae, Poaceae, and Orchidaceae are underused. In comparison with the Bayes approach, the IDM approach indicates fewer families as over- or underused. Conclusions: The IDM model leads to more conservative results compared to the Bayes approach. Only relatively few taxa are indicated as over- or underused. The larger the families (n j=s) are, the more similar do the results of the two approaches turn out. In contrast to the Bayes approach, small taxa with most or all species used as medicine (e.g., n j=2, x j=2) tend not to be indicated as overused with the IDM model.
机译:研究的目的:我们使用IDM模型测试植物分类单元作为药物来源的过度使用和使用不足。与仅考虑药用植物调查数据不确定性的贝叶斯方法不同,IDM模型还考虑了植物群清单周围的不确定性,该方法用于比较药用植物和本地植物群。材料和方法:使用IDM模型和贝叶斯方法对Campania(意大利)的药用菌群和Sierra Popoluca(墨西哥)使用的药用菌群进行统计分析。对于Campania,考虑了423种药用植物和2237种维管植物,对于Sierra Popoluca 605考虑了药用植物和2317维管植物。结果:IDM模型(s = 4)表明,对于桔梗科,桔梗科和蔷薇科被过度使用,而石竹科,禾本科和兰科未被充分利用。在Popoluca中,菊苣科和胡椒科被过度使用,而莎草科,禾本科和兰科则未得到充分利用。与贝叶斯方法相比,IDM方法表明过度使用或未充分使用的家庭较少。结论:与贝叶斯方法相比,IDM模型得出的结果更为保守。仅相对较少的分类单元被指示为过度使用或未充分使用。族(n j = s)越大,两种方法的结果越相似。与贝叶斯方法相反,大多数或所有物种都被用作药物的小型分类单元(例如,n j = 2,x j = 2)往往不会被IDM模型过度使用。

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