Chapter 2. Exploring Data


I arrived at the UBC Botany Dept. and jumped through some of the hoops set out for new grad students, including a first committee meeting where I met Jack Maze. My graduate research centered on comparing two sunflower genera – Balsamorhiza (balsamroot) and Wyethia (mule’s ears), to quantify their differences.

I worked in Bruce B’s lab learning how to extract and identify flavonoids for use as taxonomic characters with the help of post-docs Wilf N. and Susan M. Wilf helped me organize fieldwork and joined me for the first few weeks of my spring and summer collecting trip as we hunted balsamroots and mule’s ears in the western states.

I learned about different approaches to statistical analysis when Jack and his colleague, plant ecologist Gary Bradfield, offered a course in multivariate statistics. In addition to classical statistical approaches, such as finding the optimal fertilizer rate for a cornfield, students were introduced to multivariate approaches where one can compare wetland and upland vegetation in a wild place, or explore variation and development in individual plants. I was always pretty awful at math, but principal components analysis, one multivariate method, helps us humans to discover patterns, especially correlations among variables, in a set of data. Jack and his student, Rob S., were using exploratory data analysis to study how organization among plant structures changes during development. They were both skeptical of neo-Darwinian theory.

Before I headed out for some serious plant collecting with Wilf, I went on a day trip with Jack to visit hybrid populations of balsamroots and the two, very different parent species. Ernst Mayr’s well-worn Biological Species Concept, based mainly on sex, doesn’t seem very accurate – hybrids are common in nature, especially in plants. We still don’t have a very good idea of what species are.

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