Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass
Abstract
The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. To address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate ( A MASS ) and leaf nitrogen ( N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (8)
Robert W. Heckman
Department of Biology, University of North Carolina
Grace P. John
Department of Biology, University of Florida
Jason E. Bonnette
Department of Integrative Biology, University of Texas at Austin
Brandon E. Campitelli
Department of Integrative Biology, University of Texas at Austin
Felix B. Fritschi
Division of Plant Science and Technology, University of Missouri
David B. Lowry
Department of Plant Biology, Michigan State University
Philip A. Fay
United States Department of Agriculture, Agricultural Research Service, Grassland, Soil, and Water Lab
Thomas E. Juenger
Department of Integrative Biology, University of Texas at Austin