Plants, soil microbes, and environments: Taking a phytobiome approach with big data to explore biodiversity across ecosystems

Laura Super, Josh Yang, Jerry Zhang and Robert D. Guy, University of British Columbia, Vancouver, BC, Canada, Alexander R. Young, Forest and Natural Resources Management, SUNY College of Environmental Science and Forestry, Syracuse, NY

Background/Question/Methods
A phytobiome is a plant, its associated organisms (or viruses), and the environment. Soil microbe and plant communities interact in complex ways. Relationships in taxa diversity across landscapes and abiotic environments are actively explored to fill gaps in our knowledge and understanding. We utilized data from the National Ecological Observatory Network (NEON), a large initiative covering a range of North American ecosystems. To explore a manageable dataset, criteria were used to select 11 sites with three plots per site and triplicate soil sampling per plot for years 2016-2018. We compare relationships between herbaceous plant richness, woody plant richness, prokaryote richness (16S amplicon), fungi richness (ITS amplicon), and soil pH in mineral and organic soil horizons using Pearson correlation tests. We ask the following research questions: i) Is soil microbe taxa richness (number of taxa) higher in organic than mineral soils? ii) Does soil microbe taxa richness correlate with pH and differ with soil type (organic versus mineral)? iii) Will soil microbiome taxa richness be positively correlated with plant taxa richness?

Results/Conclusions
There were positive correlations in samples associated with organic layers. For example, herbaceous plant richness was positively correlated with soil fungi richness (r = 0.36, P = 0.008), prokaryotic richness (r = 0.51, P < 0.001), and pH (r = 0.63, P < 0.001). Prokaryotic richness varied positively with fungi richness (r = 0.63, P < 0.001), and pH (r = 0.48, P < 0.001). Lastly, fungi richness was positively correlated with pH (r = 0.67, P < 0.001). However, there were negative correlations for woody plant versus herbaceous plant richness (r = -0.36, P = 0.009), and pH (r = -0.31, P = 0.024). Predominately, samples associated with mineral layers had insignificant or even negative correlations: for example, pH versus prokaryotic richness (r = -0.28, P = 0.022), herbaceous plant richness (r = -0.35, P = 0.004), and woody plant richness (r = -0.37, P = 0.003). However, mineral samples had positive correlations for prokaryotic and herbaceous plant richness (r = 0.31, P = 0.013). In conclusion, microbe taxa richness was higher in organic than mineral soil, microbe taxa richness was correlated with pH, and there was covariance in plant and microbiome communities with pH and soil layer. Big data from NEON provides valuable insight for understanding broad relationships between soil microbe and plant communities at a continental scale.