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Impacts of Sampling Design on Estimates of Microbial Community Diversity and Composition in Agricultural Soils

  • Soil Microbiology
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Abstract

Soil microbiota play important and diverse roles in agricultural crop nutrition and productivity. Yet, despite increasing efforts to characterize soil bacterial and fungal assemblages, it is challenging to disentangle the influences of sampling design on assessments of communities. Here, we sought to determine whether composite samples—often analyzed as a low cost and effort alternative to replicated individual samples—provide representative summary estimates of microbial communities. At three Minnesota agricultural research sites planted with an oat cover crop, we conducted amplicon sequencing for soil bacterial and fungal communities (16SV4 and ITS2) of replicated individual or homogenized composite soil samples. We compared soil microbiota from within and among plots and then among agricultural sites using both sampling strategies. Results indicated that single or multiple replicated individual samples, or a composite sample from each plot, were sufficient for distinguishing broad site-level macroecological differences among bacterial and fungal communities. Analysis of a single sample per plot captured only a small fraction of the distinct OTUs, diversity, and compositional variability detected in the analysis of multiple individual samples or a single composite sample. Likewise, composite samples captured only a fraction of the diversity represented by the six individual samples from which they were formed, and, on average, analysis of two or three individual samples offered greater compositional coverage (i.e., greater number of OTUs) than a single composite sample. We conclude that sampling design significantly impacts estimates of bacterial and fungal communities even in homogeneously managed agricultural soils, and our findings indicate that while either strategy may be sufficient for broad macroecological investigations, composites may be a poor substitute for replicated samples at finer spatial scales.

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Acknowledgements

This research was supported by an internal grant awarded to LK, JG, CR, MS, and DS by the University of Minnesota LTARN and by a USDA-NIFA postdoctoral fellowship awarded to SC. We thank Matt Bickell and Kara Anderson for LTARN plot support, Mindy Dornbusch and Lindsey Otto-Hansen for field assistance, Zewei Song and Trevor Gould for computational assistance, and the University of Minnesota Genomics Center for conducting all molecular sequencing.

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Authors and Affiliations

  1. Department of Plant Pathology, University of Minnesota, Minneapolis, USA

    Sarah C. Castle, Deborah A. Samac & Linda L. Kinkel

  2. USDA-ARS, Plant Science Research Unit, Saint Paul, MN, USA

    Deborah A. Samac

  3. Department of Soil, Water, and Climate, University of Minnesota, Minneapolis, MN, USA

    Michael J. Sadowsky, Carl J. Rosen & Jessica L. M. Gutknecht

  4. Biotechnology Institute, University of Minnesota, Minneapolis, MN, USA

    Michael J. Sadowsky & Linda L. Kinkel

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  1. Sarah C. Castle
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Contributions

JG, LK, CR, MS, and DS conceived of the study. SC oversaw the laboratory work, data analysis, and wrote the manuscript with significant feedback from co-authors.

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Correspondence to Sarah C. Castle.

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Electronic supplementary material

Fig S1

Experimental design and sampling strategy for three Minnesota long-term agricultural research sites. Within a randomized block experimental design, we selected five study plots from each of three agricultural sites (Grand Rapids, Lamberton, Waseca). For each plot, a soil sample was collected at each of the four corners of the plot ~1.5 m from the plot edge and two samples were collected from the plot center six meters from either plot edge. Subsamples of the six individual samples were combined in equal masses to make a physical composite for each plot. Single DNA extractions were done for all individual samples and two additional extractions were done for one randomly selected individual sample. DNA was extracted in triplicate from subsamples of all composite samples. For individual and composite samples, each of the triplicate extractions was sequenced and analyzed individually. (PNG 589 kb)

High Resolution Image (TIF 274 kb)

Fig. S2

Composite samples yielded greater numbers of distinct bacterial and fungal OTUs per sequence than individual samples. Rarefaction curves based on distinct OTUs in individual samples and composite samples created by combining six individual samples from the same plot. Box centerlines represent medians and boxes represent first and third quartiles with 95% confidence intervals. Points represent outliers. Data are based on OTU tables rarefied to 50,300 bacterial and 13,500 fungal sequences per sample. (PNG 264 kb)

High Resolution Image (TIF 937 kb)

Fig. S3

Community variance was significantly greater in individual than composite samples among all sites and within individual sites. Data represent results from a betadispersion analysis of Bray-Curtis distances of total abundance transformed OTUs comparing sampling strategies among samples from ‘all sites’ or within sites. Box centerlines represent medians with 95% confidence interval bars. Points represent outliers and asterisks represent significant differences among sampling strategies. (P < 0.05*; P < 0.01**; P < 0.001***). (PNG 351 kb)

High Resolution Image (TIF 391 kb)

Fig. S4

Microbial richness and diversity were greater in composite than individual samples for bacteria on a per plot basis. Observed OTUs and Shannon H′ Diversity Index for bacterial and fungal communities in individually collected soil samples, or composite samples created by combining six individual samples per plot. Box centerlines represent medians with 95% confidence interval bars. Data are based on OTU tables rarefied to 50,300 bacterial and 13,500 fungal sequences per sample. (PNG 308 kb)

High Resolution Image (TIF 827 kb)

Fig. S5

Regression slopes of individual versus composite sample microbial richness varied by agricultural site for fungal and bacterial samples. Points represent average observed OTUs for bacterial and fungal communities of composite and individually collected soil samples collected from each plot. Statistics are based on Pearson’s correlations for each site. Data are based on OTU tables rarefied to 50,300 bacterial and 13,500 fungal sequences per sample. (PNG 236 kb)

High Resolution Image (TIF 441 kb)

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Castle, S.C., Samac, D.A., Sadowsky, M.J. et al. Impacts of Sampling Design on Estimates of Microbial Community Diversity and Composition in Agricultural Soils. Microb Ecol 78, 753–763 (2019). https://doi.org/10.1007/s00248-019-01318-6

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