Ruth G. Shaw
University of Minnesota
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Primary Section: 27, Evolutionary Biology Membership Type:
Member
(elected 2021)
Photo Credit: Frank H. Shaw |
Biosketch
Ruth Shaw’s research focuses on evolutionary processes in wild plant populations using approaches of quantitative genetics and population biology. With collaborators, she has addressed questions concerning effects of new mutations on plant fitness, the pace of evolutionary adaptation in response to changing climate, and evolutionary consequences of severe, abrupt fragmentation of prairie. More recently, the group has implemented an approach to directly evaluate a population’s capacity for ongoing adaptation. Current research is assessing the rate of adaptation of populations to ascertain whether adaptation will suffice, over the near term, to maintain the size and hence persistence of these populations. Shaw was born and raised with five siblings near Philadelphia PA. She graduated from Oberlin College, earning her B.A. in Biology, and then earned her Ph.D. in Botany and Genetics at Duke University. After a postdoc at University of Washington, she joined the faculty of Botany and Plant Sciences at University of California, Riverside and moved to her current position at the University of Minnesota in 1993. She has served as Editor in Chief of Evolution and President of the Society for the Study of Evolution.
Research Interests
Ruth Shaw and her collaborators work toward elucidating ongoing evolution in wild plant populations. To do so, they carry out quantitative genetic experiments in the wild, focusing on prairie plant populations, especially the annual plant Chamaecrista fasciculata (partridgepea) and the long-lived perennials, Echinacea angustifolia (narrow-leaved purple coneflower) and Schizachyrium scoparium (little bluestem). These studies are designed to reveal the severity of inbreeding depression, as well as genetic variance underlying variation in numerous traits, including individual fitness, an individual’s contribution of offspring to its population. Collectively, these studies yield insight into populations’ current growth rates and likelihood of persistence. They also shed light on populations’ capacity for ongoing adaptation as environments change. To enable the work to predict evolutionary change, the group has implemented software for estimating genetic variance of traits. To address the particularly challenging goal of making statistical inferences about lifetime fitness, which is a composite of survival and reproduction, she collaborated with statistician Charles Geyer, her brother, in developing a new approach, called aster.
