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Published in

American Society for Microbiology, Applied and Environmental Microbiology, 14(81), p. 4801-4808, 2015

DOI: 10.1128/aem.00705-15

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Depth-Dependent Survival of Escherichia coli and Enterococci in Soil after Manure Application and Simulated Rainfall

Journal article published in 2015 by M. D. Stocker, Y. A. Pachepsky ORCID, R. L. Hill, D. R. Shelton
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

ABSTRACT Once released, manure-borne bacteria can enter runoff via interaction with the thin mixing layer near the soil surface. The objectives of this work were to document temporal changes in profile distributions of manure-borne Escherichia coli and enterococci in the near-surface soil layers after simulated rainfalls and to examine differences in survival of the two fecal indicator bacteria. Rainfall simulations were performed in triplicate on soil-filled boxes with grass cover and solid manure application for 1 h with rainfall depths of 30, 60, and 90 mm. Soil samples were collected weekly from depth ranges of 0 to 1, 1 to 2, 2 to 5, and 5 to 10 cm for 1 month. Rainfall intensity was found to have a significant impact on the initial concentrations of fecal indicator bacteria in the soil. While total numbers of enterococci rapidly declined over time, E. coli populations experienced initial growth with concentration increases of 4, 10, and 25 times the initial levels at rainfall treatment depths of 30, 60, and 90 mm, respectively. E. coli populations grew to the approximately the same level in all treatments. The 0- to 1-cm layer contained more indicator bacteria than the layers beneath it, and survival of indicator bacteria was better in this layer, with decimation times between 12 and 18 days after the first week of growth. The proportion of bacteria in the 0- to 1-cm layer grew with time as the total number of bacteria in the 0- to 10-cm layer declined. The results of this work indicate the need to revisit the bacterial survival patterns that are assumed in water quality models.