4.7 Article

Quantitative methods in ethnobotany and ethnopharmacology: Considering the overall flora-Hypothesis testing for over- and underused plant families with the Bayesian approach

Journal

JOURNAL OF ETHNOPHARMACOLOGY
Volume 137, Issue 1, Pages 837-843

Publisher

ELSEVIER IRELAND LTD
DOI: 10.1016/j.jep.2011.07.002

Keywords

Meta-analysis; Bayesian approach; Campania; Quantitative ethnobotany; Medicinal plants

Ask authors/readers for more resources

Ethnopharmacological relevance: We introduce and explain the advantages of the Bayesian approach and exemplify the method with an analysis of the medicinal flora of Campania, Italy. The Bayesian approach is a new method, which allows to compare medicinal floras with the overall flora of a given area and to investigate over- and underused plant families. In contrast to previously used methods (regression analysis and binomial method) it considers the inherent uncertainty around the analyzed data. Materials and methods: The medicinal flora with 423 species was compiled based on nine studies on local medicinal plant use in Campania. The total flora comprises 2237 species belonging to 128 families. Statistical analysis was performed with the Bayesian method and the binomial method. An approximated chi(2)-test was used to analyze the relationship between use categories and higher taxonomic groups. Results: Among the larger plant families we find the Lamiaceae. Rosaceae, and Malvaceae, to be overused in the local medicine of Campania and the Orchidaceae, Caryophyllaceae, Poaceae, and Fabaceae to be underused compared to the overall flora. Furthermore, do specific medicinal uses tend to be correlated with taxonomic plant groups. For example, are the Monocots heavily used for urological complaints. Conclusions: Testing for over- and underused taxonomic groups of a flora with the Bayesian method is easy to adopt and can readily be calculated in excel spreadsheets using the excel function Inverse beta (INV.BETA). In contrast to the binomial method the presented method is also suitable for small datasets. With larger datasets the two methods tend to converge. However, results are generally more conservative with the Bayesian method pointing out fewer families as over- or underused. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available