Current research projects

Chamaecrista Project: Potential for adaptation, and its realization, in natural plant populations

Kellogg&BeeTheory underlying the process of adaptive evolution is well established, yet few empirical studies have assessed how well the potential rate of adaptation predicts realized adaptation in natural populations. Using Chamaecrista fasciculata (partridge pea) populations from Minnesota and Iowa (in collaboration with Dr. Vince Eckhart at Grinnell College), we are performing quantitative genetic experiments in nature to characterize how a population’s genetic variability affects the rate of adaptation over several generations. In addition to increasing our understanding of the capacity for adaptation in natural populations, this research will facilitate assessments of whether populations can adapt rapidly enough to keep up with the pace of climate change. The specific objectives of this research are to:

1)     characterize the immediate capacity for ongoing adaptation to current conditions in nature

2)     evaluate the extent to which that adaptive potential is realized, and

3)     elucidate causes of discrepancies.

 The Echinacea Project

EAatHLThis project investigates consequences of habitat fragmentation in tallgrass prairie. The aim is to conduct research for a better understanding of the biology, conservation, and restoration of plants and insects. The primary model system is a common native prairie plant, Echinacea angustifolia (a purple coneflower), growing in remnant populations within an agricultural landscape in western Minnesota.

The Echinacea Project website

The Echinacea Project blog

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Healthy Prairies Project: Prairie Sustainability through Seed Storage, Beneficial Microbes, and Adaptation

Photo by John Benning

Photo by John Benning

Minnesota’s prairies once covered approximately 18 million acres; now, less than 1% remains. As prairie plant populations have decreased and become fragmented, genetic diversity has declined. This may impact the capacity of prairie plant species to adapt to rapid environmental change. Increasingly, society recognizes that prairies provide valuable ecosystem services; consequently, there is growing demand for prairie restoration. However, restorations require large amounts of seed, as well as research on the local adaptation and genetic variation in prairie plant species.

The Healthy Prairies project involves large-scale seed collection from native prairies in Minnesota, as efforts to collect and preserve the genetic diversity of native plants are essential both to avert their loss altogether and to support prairie restoration. In addition, the Project experimentally addresses the following questions:

  • Which microbes are present in native prairie plants and do those microbes help plants to become locally adapted?
  • What is the geographic scale of local adaptation in prairie plant species and do “home” populations perform better than “away” populations when grown in a common environment?
  • What is the extent of genetic variation in target prairie plant species? This variation determines adaptive capacity and must be determined experimentally.

The full project workplan is available here. The Healthy Prairies Project is actively recruiting undergraduate researchers, through the Undergraduate Research Opportunities Program and the University Honors Program.

Funded by: Minnesota Environment and Natural Resources Trust Fund as recommended by the Legislative‐Citizen Commissionon Minnesota Resources (LCCMR)

Principal investigators: Ruth Shaw, Georgiana May, and Don Wyse

Aster modeling

aster_modelIndividual fitness, an individual’s lifetime contribution of offspring to the next generation, is a key metric for evolutionary adaptation and for population growth.  It is straightforward, if time-consuming, to record the components of fitness, survival and the stages of reproduction. Statistical analysis of such data, however, has been problematic because of the compound nature of the distribution of fitness in a population.  To enable rigorous statistical analysis of fitness, aster modeling has been developed through close collaboration with Dr. Charles Geyer, School of Statistics, University of Minnesota. Aster capabilities now include estimation and comparison of the mean fitness of study populations, phenotypic selection analysis, random effects models for estimating genetic components of variance, and estimation of  population growth rate.  Geyer maintains a website that displays all matters aster, including technical reports and tutorials, as well as all our papers about aster and applying it to address evolutionary questions.