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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #379593

Research Project: Resilient Management Systems and Decision Support Tools to Optimize Agricultural Production and Watershed Responses from Field to National Scale

Location: Grassland Soil and Water Research Laboratory

Title: The effects of plant-soil feedback on switchgrass productivity depend on microbial origin

Author
item Kiniry, James
item ARTHUR, CAROLINE - University Of Texas
item BANICK, KATHERINE - University Of Texas
item FRITSCHI, FELIX - University Of Missouri
item WU, YANQI - Oklahoma State University
item HAWKES, CHRISTINE - North Carolina State University

Submitted to: Agronomy
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/24/2020
Publication Date: 11/26/2020
Citation: Kiniry, J.R., Arthur, C.E., Banick, K.M., Fritschi, F.B., Wu, Y., Hawkes, C.V. 2020. The effects of plant-soil feedback on switchgrass productivity depend on microbial origin. Agronomy. 10. Article 1860. https://doi.org/10.3390/agronomy10121860.
DOI: https://doi.org/10.3390/agronomy10121860

Interpretive Summary: Much effort has gone into maximizing bioenergy from switchgrass, using local adaptation to climate and nutrient management in this perennial grass. However, the biotic component of soils can also affect plant production and long-term suitability at a site. In this study, we tested how productivity values of four switchgrass cultivars were affected by four microbial sources from the Great Plains. All inoculum soil sources were previously conditioned by a mixture of switchgrass cultivars, allowing us to explicitly address plant-soil feedback effects. Microbial soil inocula were added to one soil to avoid soil chemistry and soil textural variation across the sources. We found that the soil microbial inoculum source mattered more than cultivar in determining switchgrass biomass. The addition of microbes resulted in smaller plants, with largest plants found on control soils with no inoculum, but some inocula were less negative than others. There was no geographic matching between cultivars and soil microbial inoculum, suggesting little local adaptation to the biotic component of soils. In addition, measurements of fungal root colonization suggest that fungi are not responsible for the observed patterns. Based on these results, we suggest that switchgrass cultivation could benefit from considering effects of the soil biota. Additional work is needed to generalize these patterns over time, to a wider geographic area, and to a broader range of cultivars.

Technical Abstract: A great deal of effort has gone into maximizing switchgrass (Panicum virgatum L.) production for bioenergy by leveraging existing local adaptation to climate and via nutrient management in this perennial grass crop. However, the biotic component of soils can also affect plant production and long-term suitability at a given site. Here, we tested how productivity of four switchgrass cultivars were affected by four microbial sources from the Great Plains. All inoculum soil sources were previously conditioned by a mixture of switchgrass cultivars, allowing us to explicitly address plant-soil feedback effects. Microbial soil inocula were added to a consistent background soil to avoid physicochemical variation across the sources. We found that the soil microbial inoculum source mattered more than cultivar in determining switchgrass biomass. The addition of microbes resulted in smaller plants, with largest plants found on control soils with no inoculum, but some inocula were less negative than others. There was no geographic matching between cultivars and soil microbial inoculum, suggesting little local adaptation to the biotic component of soils. In addition, measurements of fungal root colonization suggest that fungi are not responsible for the observed patterns. Based on these results, we suggest that switchgrass cultivation could benefit from considering effects of the soil biota. Additional work is needed to generalize these patterns over time, to a wider geographic area, and to a broader range of cultivars.