Important Medicinal Plant Families in Thailand

This paper compares the medicinal and food floras of the native peoples of North America. There is a surprising overlap of these floras by both family and taxon. Yet there are also substantial differences-food and medicine tend to involve different plant parts, plant habit, and plant character. The similarities and differences are considered in an evolutionary context and a theoretical perspective is suggested to account for these facts.

Plants have provided medicine to humans for thousands of years, and in most parts of the world people still use traditional plant-derived medicine. Knowledge related to traditional use provides an important alternative to unavailable or expensive western medicine in many rural communities. At the same time, ethnomedicinal discoveries are valuable for the development of modern medicine. Unfortunately, globalization and urbanization causes the disappearance of much traditional medicinal plant knowledge.

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.