Effects of genomic and functional diversity on stand-level productivity and performance of non-native Arabidopsis

Abstract

Biodiversity can affect the properties of groups of organisms, such as ecosystem function and the persistence of colonizing populations. Genomic data offer a newly available window to diversity, complementary to other measures like taxonomic or phenotypic diversity. We tested whether native genetic diversity in field experimental stands of Arabidopsis thaliana affected their aboveground biomass and fecundity in their colonized range. We constructed some stands of genotypes that we a priori predicted would differ in performance or show overyielding. We found no relationship between genetic diversity and stand total biomass. However, increasing stand genetic diversity increased fecundity in high-resource conditions. Polyculture (multiple genotype) stands consistently yielded less biomass than expected based on the yields of component genotypes in monoculture. This under-yielding was strongest in stands with late-flowering and high biomass genotypes, potentially due to interference competition by these genotypes. Using a new implementation of association mapping, we identified genetic loci whose diversity was associated with stand-level yield, revealing a major flowering time locus associated with under-yielding of polycultures. Our field experiment supports community ecology studies that find a range of diversity-function relationships. Nevertheless, our results suggest diversity in colonizing propagule pools can enhance population fitness. Furthermore, interference competition among genotypes differing in flowering time might limit the advantages of polyculture.

From cultivar mixtures to allelic mixtures: opposite effects of allelic richness between genotypes and genotype richness in wheat

“…Analysing diversity effects at the allelic level can help the understanding of the ecological basis of mixing effects. For example, Turner et al (2020) showed that the gene associated with community-level biomass in A. thaliana was a major flowering time locus, and they could therefore attribute mixture underyielding to differences in flowering time between accessions. In our case, we did not find direct associations between allelic variation at the identified locus and any of the phenotypic traits measured in the experiment.…”

Vegetative Phase Change Causes Age-Dependent Changes in Phenotypic Plasticity

“…(Mason et al , 2013; Garbowski et al , 2021). Intraspecific variation can play an important role in community- and ecosystem-level processes (Bolnick et al , 2011; Madritch et al , 2014; Turner et al , 2020; Westerband et al , 2021), though the functional basis of this variation is usually not understood. To better understand the implications of VPC on these large scale processes, further characterization of the timing of VPC across plant species (of which there is currently few; Maize, (Poethig, 1988; Bongard-Pierce et al , 1996); Arabidopsis thaliana , (Telfer et al , 1997); Eucalyptus globulus, (Jordan et al , 1999); Nicotiana tabacum , (Feng et al , 2016); Sorghum, (Hashimoto et al , 2019); Acacia, (Leichty & Poethig, 2019); Passiflora edulis , (Silva et al , 2019); Poplar, (Lawrence et al , 2021a) and Rice, (Asai et al , 2002)) and variation among genotypes within species (even fewer; Eucalyptus globulus , (Jordan et al , 1999); Maize, (Poethig, 1988; Foerster et al , 2015); and A. thaliana , (Doody et al , 2021)) is necessary.…”

Shift in beneficial interactions during crop evolution

“…Trait‐blind approaches have also been developed at the genomic level to investigate how allelic and genotypic diversity affects crop performance under different environmental conditions (Subrahmaniam et al, 2018 ). For instance, allelic diversity at specific DNA regions in experimental stands of Arabidopsis thaliana has been shown to promote stand‐level productivity, through an effect on plant‐soil interactions (Wuest & Niklaus, 2018 ) and flowering time (Turner et al, 2020 ). Although very promising in the context of mixtures, such genomic approaches have only been recently applied in crops (Montazeaud et al, 2022 ).…”