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Spatial patterns of soil microbial communities and implications for precision soil management at the field scale

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Abstract

Understanding the spatial patterns of soil microbial communities and influencing factors is a prerequisite for soil health assessments and site-specific management to improve crop production. However, soil microbial community structure at the field scale is complicated by the interactions among topography and soil properties. The objectives of this study were to (1) characterize the spatial variability patterns of soil microbial communities at the field scale; (2) assess the influence of soil physico-chemical properties, topography and management on soil microbial biomass spatial variability. This study was conducted in a 194-ha commercially-managed field in Hale County, Texas, in 2017. A total of 212 composite soil samples were collected at 0–0.15 m depth and analyzed via the ester-linked fatty acid methyl ester (EL-FAME) method to characterize the microbial community structure and biomass. Soil electrical conductivity (EC), pH, soil texture, soil water content (SWC), soil organic carbon (SOC) and total nitrogen (TN) were determined for each soil sample. Topographic attributes, including elevation and slope, were derived from real-time kinematic (RTK) point elevation data. Interpolated microbial community maps at this scale revealed a spatially structured distribution of microbial biomass and diversity with patches of several hundred meters in different directions corresponding to the distribution of soil types and topography. Most of the microbial communities were autocorrelated at greater ranges within the same soil types than across different soils. The distribution of total soil microbial biomass was mainly affected by SOC and SWC. Soil pH and C:N ratio had a negative impact on the biomass of bacterial communities. Biomass of fungal communities was negatively influenced by slope and elevation. The results of this study have the potential to provide a basis for designing soil sampling plans in characterizing microbial community distribution and site-specific soil health management.

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Notes

  1. (Basemap source: Esri, DigitalGlobe, GeoEye, i-cubed, USDA FSA, USGS, AEX, Getmapping, Aerogrid, IGN, IGP, swisstopoand the GIS User Community) [EsB: Estacado loam, 1–3% slopes (Fine-loamy, mixed, superactive, thermic Aridic Paleustolls); MkB: Mansker loam, 0–3% slopes (Coarse-loamy, carbonatic, thermic Calcidic Paleustolls); Lo: Lofton clay loam: 0.5% slopes (Fine, mixed, superactive, thermic Vertic Argiustolls); OtA: Olton loam, 0–1% slopes (Fine, mixed, superactive, thermic Aridic Paleustolls); OtB: Olton loam, 1–2% slopes (Fine, mixed, superactive, thermic Aridic Paleustolls); PuA: Pullman clay loam, 0–1% slopes (Fine, mixed, superactive, thermic Torrertic Paleustolls); Ra: Randall clay (Fine, smectitic, thermic Ustic Epiaquerts) (Soil Survey Staff, 1974)]

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Acknowledgements

The authors gratefully acknowledge the help of Dr. Veronica Acosta-Martinez for conducting the soil microbial analysis in her soil microbiology lab at USDA-ARS, Lubbock, Texas. We thank Mr. Jerry Brightbill and South Plains Precision Ag for assisting the data collection and providing the relevant agronomic data. This research was supported by Cotton Incorporated and Texas Tech University.

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Authors and Affiliations

  1. Department of Plant and Soil Science, Texas Tech University, 79409, Lubbock, TX, United States

    Jasmine Neupane, Wenxuan Guo, Lindsey Slaughter & Sanjit Deb

  2. Department of Soil and Crop Sciences, Texas A&M AgriLife Research, 79403, Lubbock, TX, United States

    Wenxuan Guo

  3. Department of Geography, University of Colorado Boulder, 80309, Boulder, CO, United States

    Guofeng Cao

  4. Department of Mathematics and Statistics, Texas Tech University, 79409, Lubbock, TX, United States

    Fangyuan Zhang

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  1. Jasmine Neupane
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Appendix

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Table 5 Correlation between soil physico-chemical properties (0–0.15 m depth) and topography for a 194-ha field in Hale County, Texas, in 2017
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Neupane, J., Guo, W., Cao, G. et al. Spatial patterns of soil microbial communities and implications for precision soil management at the field scale. Precision Agric 23, 1008–1026 (2022). https://doi.org/10.1007/s11119-021-09872-1

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