Anny's dissertation research focused on how plant-soil microbial feedbacks drive long term coexistence dynamics between two desert grass species. Plants are known to cultivate species-specific rhizosphere microbial communities which then feedback to affect the fitness of their plant associates. Previous work have shown that these plant-soil feedbacks (PSF) are a potential mechanism that promotes self-limitation in associated plants, leading to increased opportunities for coexistence. In my dissertation work, I conducted a greenhouse experiment that demonstrated for the first time that soil microbes increased the potential for plant species coexistence. Specifically, soil microbes caused negative feedback and negative frequency dependence in two asymmetrically competing grass species that dominate grasslands of the southwestern US. To explore the role of PSFs in plant community dynamics at realistic temporal and spatial scales, I then combined long-term (26-year) field observations with a field experiment to test PSFs as a driver of spatial variation in plant species coexistence. My multi-year field experiment demonstrated that coexistence stability could not be explained by spatial variation in abiotic drivers, but instead correlated with different plant-soil microbial feedbacks. The results also helped to explain 20+ years of plant abundance dynamics at the landscape scale. Finally, with support from an NSF DDIG award, I used next-generation (Illumina MiSeq) and Sanger sequencing to couple microbial dynamics with plant responses in the greenhouse and field experiments. I found disparate microbial dynamics drove similar plant responses to PSF in the field and greenhouse despite shared “core” fungal taxa. I also developed a data analysis pipeline to combine results from direct inoculations, sequence prevalence in the next-generation dataset, and plant responses to determine how co-variation between specific microbe taxa and plant growth drove observed PSFs. Using this method, I linked PSFs to 5 microbe taxa (from >1000 candidates), providing a tractable framework to reduce the dimensionality of sequence datasets for future natural history and ecology characterization. Anny recently gave a virtual seminar at Tyson Reseach Center on this topic: https://www.youtube.com/watch?v=t5lMjpVEjJQ
