|Title||The effects of genotype richness and genomic dissimilarity of Andropogon gerardii on invasion resistance and productivity|
|Publication Type||Journal Article|
|Year of Publication||2015|
|Authors||Avolio, ML, Chang, CC, Weis, JJ, Smith, MD|
|Journal||Plant Ecology and Diversity|
|Keywords||Andropogon bladhii, biodiversity ecosystem function, complementarity, dominant species, genomic dissimilarity, genotypic richness, invasion resistance, productivity, tallgrass prairie|
Background: The genetic diversity within populations has been shown to affect ecosystem functions, including productivity and invasion resistance. To date most experiments have focused on manipulation of genotypic richness and have ignored other measures of genetic diversity. Aims: In the present study we aimed to establish whether manipulated genotypic richness and genomic dissimilarity of Andropogon gerardii affect productivity and invasion resistance. Methods: We created experimental mesocosms with three levels of genotypic richness: one-, three-, and nine-genotypes. In the three-genotype treatment, we manipulated a range of genomic dissimilarity values (genetic relatedness among individuals). At the end of one growing season we measured above-ground, below-ground and total biomass of the mesocosms, and invasion resistance to Andropogon bladhii. Results: Overall, we found no significant effect of genotypic richness on any measure of ecosystem function, although there tended to be more root biomass (due to complementarity) and invasive seedling biomass with higher levels of genotypic richness. Within the three-genotype treatment we found a significant positive relationship between genomic dissimilarity and above-ground biomass, which was caused by a selection effect. We also found a positive relationship between genomic dissimilarity and biomass of A. bladhii. Conclusions: Using these two measures of genetic diversity we detected differences in the strength and mechanism of positive diversity effects within the same experiment, demonstrating the value of manipulating multiple measures of diversity when performing biodiversity–ecosystem function experiments.