Houghton KM, Santamaria Cerrutti ME. 2022. Groundwater Ecosystem Monitoring: Microbial diversity and function, report 1. Lower Hutt (NZ): GNS Science. 51 p. (GNS Science report; 2022/54). doi:10.21420/E0ZE-N191.
Abstract
GNS Science’s Groundwater Ecosystem Monitoring workstream (Strategic Science Infrastructure Fund) aims to investigate groundwater ecosystem health and identify relationships between microbial diversity and groundwater chemistry. This programme complements the National Groundwater Monitoring Programme (NGMP) and was initiated in 2020. This report is the first of a series of annual reports summarising the results of this monitoring. Conclusions are preliminary and may be adjusted following further sampling and analysis of Aotearoa New Zealand groundwaters. The accompanying dataset (xlsx format) includes taxonomy, DNA sequencing data, groundwater chemistry and sample details (GNS_Science_SR2022_54_Appendix_1.xlsx). This information can be used by regional authorities to inform groundwater ecosystem management and protection.
Groundwater samples (n = 40) from 27 aquifers across the country were collected at monitoring wells or private wells either by council or GNS Science staff. These samples were analysed for a chemical suite including major ions and heavy metals. Samples were also collected for DNA extraction and sequencing. Taxonomic classification was obtained using metagenomic analysis, where sufficient DNA quantities were retrieved (n = 20), and 16S rRNA gene sequencing for the remainder of the samples (n = 17). DNA extraction was unsuccessful with three samples.
Chemical composition varied across the groundwaters, e.g. electrical conductivity
78–1325 µS/cm and redox -241.9–192.9 mV. Calcium concentrations ranged between 2.7 and 157 mg/L, while bicarbonate (as HCO3) was measured between 14.8 and 723.6 mg/L. Many of the maximal concentrations were measured in one sample, which differed significantly from the median concentration of 14/22 measured parameters. Variations within chemistry have been previously shown to drive microbial diversity. In all samples, microbial communities comprised a wide range of taxa, with several genera dominating one or a few samples but absent from the majority. 581 genera were identified with 8 genera ubiquitous in the metagenomic dataset, while 520 genera were identified with 6 genera ubiquitous in the 16S rRNA marker gene dataset. Only one genus (Pseudomonas) was identified as ubiquitous across both datasets.
Sequencing of functional genes identified potential metabolic capabilities within the microbial communities. The following metabolic functions were investigated: nitrogen cycling; methane cycling; organic acid metabolism and degradation of toxic substances. All 37 samples showed the presence of genes involved in nitrate or nitrite reduction, but predictions of complete denitrification ability were rare. The potential for removing contaminants such as arsenate and mercury was prevalent across all groundwater samples. Several samples had microbial communities with the ability to convert methane into methanol (methanotrophy), with one methanotrophic genus, Methylobacter, identified. All groundwater microorganisms detected in the samples were capable of using acetate, lactate, and pyruvate, as well as producing ethanol through fermentation of these substrates, although the relative abundance varied between the samples.
On-going sampling and monitoring, increasing regional coverage, and more consistency in which hydrochemical parameters are measured are necessary to further develop the database. In particular, a larger sample size will enable testing of statistical correlations between hydrochemistry, microbial diversity, locations, and aquifer lithology. This will form the basis of the next Groundwater Ecosystem Monitoring report. (The authors)
