How species affect one another is often influenced by the order and timing in which they arrive in a community. Deconstructing species’ niches into components (overlap, impact, and requirement) may provide a mechanistic framework for assessing the strength of priority effects operating between competitors. Such a framework may be especially important for linking priority effects to the provisioning of ecosystem services, such as disease resistance, in both natural and agricultural ecosystems. Here we revisit a classic pathosystem to empirically test the role of species’ niche components in dictating the strength of priority effects between nectar-inhabiting microbes and the success of a competing plant pathogen, Erwinia amylovora. As the causal agent of fire blight, Erwinia is a destructive pathogen of pome trees. Primary infection of hosts occurs via colonization of floral tissues and invasion through the nectaries. We used a sequential-inoculation experiment involving 50+ bacteria and fungi known to colonize flowers of pome- and other plant hosts. By measuring population growth, and changes imposed by these early-arriving species on the environment, we quantified niche components and linked these metrics to the measured strength of priority effects operating against the late-arriving pathogen.
Results/Conclusions
Preliminary results indicate that the strength of priority effects, and the ability to suppress Erwinia growth, varied widely among nectar microbes. Taxa such as Aspergillus sp. completely suppressed Erwinia growth, while others such as Micrococcus sp. had little or no impact. However, the magnitude of suppressive effects varied as a function of the nectar background (total sugar concentration) in which species competed, suggesting an important role for environmental harshness (osmotic stress) in shaping priority effects. Work is ongoing to characterize species’ niche components and the relative contribution of these vs. phylogenetic relatedness in mediating competitive outcomes. Taken together, our research will test a predictive framework in which to evaluate the magnitude of historical contingency operating between microbial taxa, and inform selection of appropriate biocontrol for a devastating plant pathogen.