Plant-soil microbe feedbacks depend on distance and ploidy in a mixed cytotype population of Larrea tridentata.

PREMISE: Theory predicts that mixed ploidy populations should be short-lived due to strong fitness disadvantages for the rare ploidy. However, mixed ploidy populations are common, suggesting that the fitness costs for rare ploidies are counterbalanced by ecological benefits that emerge when rare. We investigated whether differences in ecological interactions with soil microbes help to maintain a tetraploid-hexaploid population of Larrea tridentata (creosote bush) in the Sonoran Desert, California, United States, where prior work documented ploidy-specific root-associated microbes. METHODS: We used a plant-soil feedback (PSF) experiment to test whether host-specific soil microbes can alter the outcomes of intraploidy vs. interploidy competition. Host-specific soil microbes can build up over time; thus, distance from a host plant can affect the fitness of nearby plants. RESULTS: Seedlings grown in soils from near plants of a different ploidy produced greater biomass relative to seedlings grown in soils from near plants of the same ploidy. Moreover, seedlings grown in soils from near plants of a different ploidy produced more biomass than those grown in soils that were farther from plants of a different ploidy. These results suggest that the ecological consequences of PSF may facilitate the persistence of mixed ploidy populations. CONCLUSIONS: This is the first evidence, to our knowledge, that is consistent with plant-soil microbe feedback as a viable mechanism to maintain the coexistence of multiple ploidy levels in a single population.

Why so many polyploids? Accounting for environmental stochasticity in unreduced gamete formation lowers the perceived barriers to polyploid establishment.

While polyploids are common in nature, existing models suggest that polyploid establishment should be difficult and rare. We explore this apparent paradox by focussing on the role of unreduced gametes, as their union is the main route for the formation of neopolyploids. Production of such gametes is affected by genetic and environmental factors, resulting in variation in the formation rate of unreduced gametes (u). Once formed, neopolyploids face minority cytotype exclusion (MCE) due to a lack of viable mating opportunities. More than a dozen theoretical models have explored factors that could permit neopolyploids to overcome MCE and become established. Until now, however, none have explored variability in u and its consequences for the rate of polyploid establishment. Here, we determine the distribution that best fits the available empirical data on u. We perform a global sensitivity analysis exploring the consequences of using empirical distributions of u to investigate effects on polyploid establishment. We determined that in many cases, u is best fit by a log-normal distribution. We found environmental stochasticity in u dramatically impacts model predictions when compared to a static u. Our results help reconcile previous modelling results suggesting high barriers to the polyploid establishment with the observation that polyploids are common in nature.

Exploring the impact of trait number and type on functional diversity metrics in real-world ecosystems.

The use of trait-based approaches to understand ecological communities has increased in the past two decades because of their promise to preserve more information about community structure than taxonomic methods and their potential to connect community responses to subsequent effects of ecosystem functioning. Though trait-based approaches are a powerful tool for describing ecological communities, many important properties of commonly-used trait metrics remain unexamined. Previous work in studies that simulate communities and trait distributions show consistent sensitivity of functional richness and evenness measures to the number of traits used to calculate them, but these relationships have yet to be studied in actual plant communities with a realistic distribution of trait values, ecologically meaningful covariation of traits, and a realistic number of traits available for analysis. Therefore, we propose to test how the number of traits used and the correlation between traits used in the calculation of functional diversity indices impacts the magnitude of eight functional diversity metrics in real plant communities. We will use trait data from three grassland plant communities in the US to assess the generality of our findings across ecosystems and experiments. We will determine how eight functional diversity metrics (functional richness, functional evenness, functional divergence, functional dispersion, kernel density estimation (KDE) richness, KDE evenness, KDE dispersion, Rao's Q) differ based on the number of traits used in the metric calculation and on the correlation of traits when holding the number of traits constant. Without a firm understanding of how a scientist's choices impact these metric, it will be difficult to compare results among studies with different metric parametrization and thus, limit robust conclusions about functional composition of communities across systems.