The relevance of quantitative ethnobotanical indices for ethnopharmacology and ethnobotany

As an interdisciplinary field of research ethnopharmacology draws on methodologies and methods from a variety of disciplines. A range of ethnobotanical indices are frequently used to transform primary data obtained through field studies into statistical measures. These indices are claimed to serve as a proxy for efficacy or drug discovery (Fidelity Level 'FL') and to show the importance of botanical drugs and plants used as medicines (Relative Importance 'RI', Use Value 'UV' or Cultural Importance Index 'CI', Cultural Value Index 'CV', Relative Frequency of Citation 'RFC'). This is, however, doubtful, as these indices have not been developed by statisticians, nor by pharmacologists while a proof of concept is lacking. Moreover, the question whether a simple number can summarize the cultural value or importance of plants is not only mathematical but also epistemological.

The FL, RI, UV/CI, CV and the RFC are shortly reviewed. Their statistical rigour is explained and the relevance for ethnobotany, ethnopharmacology and drug discovery discussed.

The effect of the sample size on the dispersal of data and the differential probability of botanical drugs being used for the different categories of use are not being considered by these indices. They lack statistical rigour and are simple percentage calculations. Moreover, important factors influencing plant use, such as the availability of pharmaceutical drugs, or the severity of diseases covered by the use-categories, are not accounted for.

Especially unexperienced and young researchers may be ensnared by using ethnobotanical indices to describe their field data. However, the cultural value and importance of plants in general, and more specifically, of medicinal plants and botanical drugs cannot be summed up by numbers. The discussed indices encrypt parts of the primary data but fail to show the value or importance of plant use because the reasons for which plants are valued or important to people are far more complex than what the formulations of these indices suggest. The indices also lack the power to pinpoint plant species or botanical drugs for drug discovery that contextualized primary data has. Botanical drugs may be useful for a range of disorders or only for specific indications, according to their pharmacologic properties. Therefore, the exclusiveness of therapeutical applications (FL) does not serve as a proxy for effectiveness. The solution is to use and understand the contextualized primary data.