Case study: South West Water

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Project Partner

South West Water is part of Pennon Group plc. South West Water provides reliable, efficient and high quality drinking water and waste water services throughout Cornwal and Devon and in smal areas of Dorset and Somerset.

Project Rationale

In recent years, therapid advancements in DNA sampling and sequencing have led to a set of new molecular screening and monitoring tools that can be integrated into environmental water quality analysis and river management plans. Most commonly, a monitoring initiative involves the sampling of river water and/or naturally grown riverine biofilms, often termed eDNA, and subsequent analysis of the whole DNA or specific genes therein. Organisms of all six biotic kingdoms can be identified from eDNA. The sampling of eDNA lends itself well to the detection of organisms that are present in low numbers, and also to the analysis of communities, which are too small to be reliably detected by other means, i.e. bacteria, fungi, zooplankton and phytoplankton. The monitoring of these communities combined with the routine monitoring of chemical water data allows for an early detection of changes in the normal functioning of the river as a consequence to e.g. changes in run-off or sewage effluent composition, and can therefore inform river management.

Project Methodology

Tellus SW sampled 20 sites within the Tamar catchment. Sites were chosen to represent a range of possible ecological conditions and influences, including sites above and below Roadford Reservoir, sites before and after the confluence of major tributaries, and sites on major tributaries (Broadwood Brook, the River Thrushel, the River Lyd) before their confluence with the larger stream. Stone scrapes were taken at each site following a protocol similar to DARES. One filtered and one unfiltered water chemistry sample were taken at each site.

Taxonomic Grouping Per Sample

The phyla Proteobacteria, Bacteroidetes and Actinobacteria, which form the most dominant groups here, are often the most abundant in rivers. Taxonomic groups per sample at the phylum level shows a high level of variability not only between sites but also at the same site. The Proteobacteria show a number of different subgroups at the genus level. The considerable variability of taxonomic groups between sampling locations gives the impression that the sites are very different from each other, however, a breakdown of the predicted functional traits is a reminder that many of the microbial organisms found at each site do very similar things. Site 15 contains a relatively high prevalence of Deinococcus thermus ([Thermi]). This phylum of extremophiles can withstand unfavourable environmental conditions from high temperatures to radiation or metal pollution and is able e.g. to metabolize arsenic. Species from this phylum might therefore serve as indicators, pointing towards unusual environmental conditions, and the need for a site specific investigation.

Diversity

Microbial diversity can be an indicator for particular environmental conditions or management practices at specific sites. On the other hand, diversity changes in a catchment can also be the function of biogeographical patterns. It's obvious that the average diversity differs between rivers, with Tamar and Thrushel showing greater diversity than the others. Diversity scores are between 3.0 and 5.4, which is within an expected range for microbial communities. Diversity does not appear to be directly influenced by nutrient and organic matter loading in the rivers, as there are no discernible trends.

Functional Traits

MaAsLin analysis of the predicted functional traits showed associations between sites and functions. Sites 4, 8 and 9 are associated with pinene degradation, a monoterpene found in pine needles, suggesting that there are significant numbers of pines near the sampling site. The analysis also yielded information on specific pollutants, such as at Site 20, which is associated with fluorobenzoate and streptomycin degradation, amongst others. Fluorbenzoate is a residue from herbicide and fungicide applications and streptomycin is often used in veterinary medicine. This could mark out Site 20 as one that gets contaminated with agricultural effluents or rural sewage effluent. This shows that functional associations can be valuable indicators for a number of other stressors and pollutants, especially when samples are taken over time.

Chemistry

All rivers had different levels of Dissolved Organic Matter (DOC), Total Dissolved Phosphorus (TDP) and Ammonium (NH4), which are linked to habitat deterioration. Particularly notable are the differences in DOC and NH4 levels in the Wolf above the reservoir and in the Wolf below the reservoir, where levels are higher. Although the chemistry parameters between the different rivers varied, there is no significant differences between the bacterial communities in the different rivers. Associations between specific chemical parameters and the relative abundance of particular OTUs showed that Total Dissolved Phosphorus (TDP), NO2, Soluble Reactive Phosphorus (SRP), Ammonium (NH4), Sulphate (SO4), Aluminium (Al), Manganese (Mn), Iron (Fe), Bromide (Br), Zinc (Zn) and changes in conductivity and oxidation-reduction potential (ORP) are all associated with changes to the relative abundance of particular bacterial species in the samples.

Catchment Management
Catchments have often been subjected to anthropogenic modifications such as water abstraction points, channel widening or straightening or in the case of the Tamar catchment, a reservoir. The invertebrate data collected during the same sampling campaign observed differences between sites above and below the reservoir. The bacterial communities, however, appear not to follow that pattern. Bacterial communities, functional traits and diversity are similar above and below the reservoir.

Conclusions
The basic study design was appropriate for general data exploration and provides a number of catchment descriptors that add additional information to already existing invertebrate and chemical data. This information serves as a microbial snapshot of the catchment and can be used to derive habitat classification and site characteristics, or to look for the effect of known pollutants such as Aluminium or pesticide residues. The data highlight catchment characteristics and shows the scope of microbial sampling to inform catchment management practice however additional work is required.