Data from: Polyploid plants obtain greater fitness benefits from a nutrient acquisition mutualism
Forrester, Nicole (2020), Data from: Polyploid plants obtain greater fitness benefits from a nutrient acquisition mutualism, Dryad, Dataset, https://doi.org/10.5061/dryad.5tb2rbp1r
Polyploidy is a key driver of ecological and evolutionary processes in plants, yet little is known about its effects on biotic interactions. This gap in knowledge is especially profound for nutrient acquisition mutualisms, despite the fact that they regulate global nutrient cycles and structure ecosystems. Generalism in mutualistic interactions depends on the range of potential partners (niche breadth), the benefits obtained, and ability to maintain benefits across a variety of partners (fitness plasticity). Here, we determine how each of these is influenced by polyploidy in the legume-rhizobium mutualism. We inoculated a broad geographic sample of natural diploid and autotetraploid alfalfa (Medicago sativa) lineages with a diverse panel of Sinorhizobium bacterial symbionts. To analyze the extent and mechanism of generalism, we measured host growth benefits and functional traits. Autotetraploid plants obtained greater fitness enhancement from mutualistic interactions and were better able to maintain this across diverse rhizobial partners (i.e., low plasticity in fitness) relative to diploids. These benefits were not attributed to increases in niche breadth, but instead reflect increased rewards from investment in the mutualism. Polyploid plants displayed greater generalization in bacterial mutualisms relative to diploids illustrating another axis of advantage for polyploids over diploids.
Data was collected from a controlled, single-strain inoculation experiment in a growth chamber at the University of Pittsburgh.
National Science Foundation, Award: 1247842
Society for the Study of Evolution
National Science Foundation, Award: DEB 1241006
National Science Foundation, Award: 1452386
National Science Foundation, Award: DEB 1150278
National Science Foundation, Award: 1738009