The D-A-(C) index: A practical approach towards the microbiological-ecological monitoring of groundwater ecosystems.

Abstract

Groundwater is not only a vital resource, but also one of the largest terrestrial aquatic ecosystems on Earth. However, to date, ecological criteria are often not considered in routine groundwater monitoring, mainly because of the lack of suitable ecological assessment tools. Prokaryotic microorganisms are ubiquitous in groundwater ecosystems even under the harshest conditions, making them ideal bioindicators for ecological monitoring. We have developed a simple, inexpensive approach that enables ecological groundwater monitoring based on three microbiological parameters that can be easily integrated into existing routine monitoring practices: prokaryotic cell density (D) measured by flow cytometry; activity (A) measured as prokaryotic intracellular ATP concentrations using a simple cell-lysis-luminescence assay; and, as an optional parameter, the bioavailable carbon (C) measured as the concentration of assimilable organic carbon in a simple batch growth assay. We analyzed data for three case studies of different disturbances representing some of the main threats to groundwater ecosystems, i.e. organic contamination with hydrocarbons, surface water intrusion, and agricultural land use. For all three disturbances, disturbed samples could be reliably distinguished from undisturbed samples based on a single index value obtained from multivariate outlier analyses of the microbial variables. We could show that this multivariate approach allowed for a significantly more sensitive and reliable detection of disturbed samples compared to separate univariate outlier analyses of the measured variables. Furthermore, a comparison of non-contaminated aquifers from nine different regions across Germany revealed distinct multivariate signatures along the three microbial variables, which should be considered when applying our approach in practice. In essence, our approach offers a practical tool for the detection of disturbances of groundwater ecosystems based on microbial parameters which can be seamlessly extended in the future by additional parameters for higher sensitivity as well as flexibility.