title: A new theoretical discrete growth distribution with verification for microbial counts in water.
abstract: Living microbes are discrete, not homogeneously distributed in environmental media, and the form of the distribution of their counts in drinking water has not been well established. However, this count may "scale" or range over orders of magnitude over time, in which case data representing the tail of the distribution, and governing the mean, would be represented only in impractically long data records. In the absence of such data, knowledge of the general form of the full distribution could be used to estimate the true mean accounting for low-probability, high-consequence count events and provide a basis for a general environmental dose-response function. In this article, a new theoretical discrete growth distribution (DGD) is proposed for discrete counts in environmental media and other discrete growth systems. The term growth refers not to microbial growth but to a general abiotic first-order growth/decay of outcome sizes in many complex systems. The emergence and stability of the DGD in such systems, defined in simultaneous work, are also described. The DGD is then initially verified versus 12 of 12 simulated long-term drinking water and short-term treated and untreated water microbial count data sets. The alternative Poisson lognormal (PLN) distribution was rejected for 2 (17%) of the 12 data sets with 95% confidence and, like other competitive distributions, was not found stable (in simultaneous work). Sample averages are compared with means assessed from the fitted DGD, with varying results. Broader validation of the DGD for discrete counts arising as outcomes of mathematical growth systems is suggested.
authors.affiliation: jenglehardt@miami.edu
authors.forename: James
authors.initials: J
authors.lastname: Englehardt
authors.forename: Jeff
authors.initials: J
authors.lastname: Swartout
authors.forename: Chad
authors.initials: C
authors.lastname: Loewenstine
mesh_terms: D015169:Colony Count, Microbial; D036262:Empirical Research; D016012:Poisson Distribution; D014481:United States; D014484:United States Environmental Protection Agency; D014871:Water Microbiology; D014881:Water Supply