Assistant Curator
High Elevation Ethnobotany
and GLORIA
William L. Brown Center
Research Interests
• Ethnobotany / Ethnobiology
• Plant Ecology
• Climate Change
Biases in the use of importance measures in ethnobotanical studies. Dr. Hart is a research specialist in the William L. Brown Center (WLBC) who studies ethnobotany and the effects of climate change on plant communities. Ethnobotanical studies, like other biological inventories, comprise huge data sets: at the most fundamental level, lists of species used. After fieldwork is concluded, analyzing, interpreting and reporting data offers significant challenges. Ecologists use various importance metrics, such as abundance and dominance. Ethnobotanists are faced with a similar challenge – in a large survey, which plants are most important? Ethnobotanical metrics such as “Cultural Importance” and “Use Value” attempt to highlight the vital parts of these large datasets, which document human uses of plants. But these metrics may bias data in unexpected ways. Ethnobotanists at the Garden's WLBC have recently shown in a large study of useful plants of the Caucasus that as the Use Value of a given species increases, so does its chance of being collected from a home-garden, rather than from the wild. The inverse is true of Cultural Importance, which tends to favor wild plants. Working with researchers in the WLBC, the REU student would find and analyze a larger body of published ethnobotanical datasets against a number of commonly used importance metrics, assess bias in these metrics, review how these biases may have affected the ethnobotanical literature more broadly, and offer suggestions for more nuanced use of these metrics in the future. Students comfortable working independently for periods of time, with some familiarity with primary literature, and with ethnobotanical interests would be ideal for this project. During the project the student will learn basics of analysis in the R statistical framework, so experience or interest in quantitative methods and/or coding would be very helpful.