Data from: Genotypic diversity and trait variance interact to affect marsh plant performance
Cite this dataset
Hughes, A. Randall (2015). Data from: Genotypic diversity and trait variance interact to affect marsh plant performance [Dataset]. Dryad. https://doi.org/10.5061/dryad.7ng3j
1. Intraspecific diversity can have important effects on population, community and ecosystem processes, yet we have little understanding of the relative importance of genetic- vs. trait-based measures of intraspecific diversity. 2. I conducted a manipulative field experiment of plant (Spartina alterniflora) genotypic diversity and trait diversity to examine their independent and interactive effects on plant performance and community structure. I focused on variation within and among genotypes in plant stem height, a trait that varies substantially across environmental gradients and can be an important predictor of plant competition intensity. 3. Trait and genotypic diversity interactively affected multiple metrics of plant performance. Both stem density and spatial spread increased with genotypic diversity in the low trait diversity combinations, yet there were negligible to weak negative effects in the high trait diversity treatments. S. alterniflora percent cover also varied with genotypic and trait diversity, but not in a clear linear pattern. 4. There were no effects of trait or genotypic diversity on associated macrofauna above-ground, yet they interactively affected below-ground measures. Infaunal abundance and sediment oxygen availability mirrored the idiosyncratic response of plant percent cover. 5. Despite the interactive effects of genotypic and trait diversity, high trait diversity consistently increased plant performance in genotypic monoculture. 6. Synthesis: The effects of intraspecific plant trait diversity on a range of plant and community responses in this study reinforce the premise that functional differences underlie ecological effects of genetic diversity and suggest that readily measured trait variance may serve as a valuable predictor of plant performance.
Gulf of Mexico