Estimating the capacity of Chamaecrista fasciculata for adaptation to change in precipitation

Anna Riba Peschel, Emma Lauren Boehm, Ruth Geyer Shaw

Research output: Contribution to journalArticlepeer-review

Abstract

Adaptation through natural selection may be the only means by which small and fragmented plant populations will persist through present day environmental change. A population's additive genetic variance for fitness (VA(W)) represents its immediate capacity to adapt to the environment in which it exists. We evaluated this property for a population of the annual legume Chamaecrista fasciculata through a quantitative genetic experiment in the tallgrass prairie region of the Midwestern United States, where changing climate is predicted to include more variability in rainfall. To reduce incident rainfall, relative to controls receiving ambient rain, we deployed rain exclusion shelters. We found significant VA(W) in both treatments. We also detected a significant genotype-by-treatment interaction for fitness, which suggests that the genetic basis of the response to natural selection will differ depending on precipitation. For the trait-specific leaf area, we detected maladaptive phenotypic plasticity and an interaction between genotype and environment. Selection for thicker leaves was detected with increased precipitation. These results indicate capacity of this population of C. fasciculata to adapt in situ to environmental change.

Original languageEnglish (US)
Pages (from-to)73-85
Number of pages13
JournalEvolution
Volume75
Issue number1
DOIs
StatePublished - Jan 2021

Bibliographical note

Funding Information:
We thank T. Warnke for site preparation and A. Gorton and J. Benning for the insights into experimental design, and construction and deployment of rain exclusion shelters. J. Benning, E. Peschel, N. Gayford, and N. Hakanson helped with data collection in the field. A. Holz, I. Laurus, A. Olson, B. Choudhury, J. Bertram, S. Jordan, B. Peterson, L. Brynes, and K. Hakanson helped with leaf sample processing and seed counting. We are grateful to F. Shaw for guidance with Quercus, and to C. Geyer and M. Kulbaba for help with aster modeling. We thank two anonymous reviewers for their helpful comments. This work was supported with funding from the Dayton Bell Museum Fund Fellowship through the University of Minnesota Twin Cities.

Publisher Copyright:
© 2020 The Authors. Evolution © 2020 The Society for the Study of Evolution.

Keywords

  • Adaptation
  • additive genetic variance
  • heritability
  • natural selection
  • precipitation
  • quantitative genetics

PubMed: MeSH publication types

  • Journal Article

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