Predicting future climate- and catchment-driven risks to the ‘land-water-shellfish continuum’: towards improved decision-support for Scotland’s shellfish waters
The Scottish shellfish food production industry currently has over 320 active aquaculture sites, is estimated to be worth approximately £9.5m at first sale value and plays a key role in supporting livelihoods in some of Scotland’s more remote rural communities. Good water quality in shellfish production areas (SPAs) and Shellfish Water Protected Areas (SWPAs) is a fundamental requirement for (i) delivering a trusted Scottish food product that is safe for human consumption; and (ii) upholding the reputation of one of Scotland’s best known global export products. Regulatory classifications of SPAs and SWPAs are determined on the basis of shellfish E. coli concentrations, and administered by Food Standards Scotland and the Scottish Environmental Protection Agency, respectively. As part of River Basin Management Planning, 47 out of 85 designated SWPAs were classified as Fair or Insufficient in 2014. Importantly, S(W)PAs and their freshwater contributing catchment areas, with associated land uses, are intricately linked. A critical research need is to therefore identify and manage sources of faecal pollution (e.g. E. coli) in catchments in order to protect the quality and safety of shellfish, and thus the reputation of the product, from being compromised and in turn minimise detrimental economic implications for the shellfish industry.
Climate change is a concern to the Scottish shellfish farming industry because of the coupling of a highly hydrologically-connected landscape with increased risk of rainfall-driven contaminated runoff. In general, climate projections suggest increased risk of extreme rainfall events in Scotland and downstream consequences of reduced microbial water quality on S(W)PAs can threaten the safety and quality of shellfish (primarily mussels and pacific oysters) intended for human consumption. While the severity and scale of future consequences of a changing climate on food safety remain unclear, qualitative evidence suggests that the potential impacts of changing weather patterns and climatic systems on aquatic environments used for food production are complex and varied. These can range from both the immediate effects of pollution from extreme events through to more subtle shifts in the nature of catchment hydrology. Recently, we have developed a novel multi-scale modelling approach for assessing E. coli loading to catchment landscapes (ViPER), which is linked to a hydrological risk mapping tool, now known as SCIMAP-FIO, to enable the identification of critical source areas and ‘at-risk’ tributaries in catchments in terms of high E. coli loading. Resources available to food and environmental regulators are limited, hence models and tools capable of predicting the distribution of pollution risk across large landscape scales offer a means of prioritising effort and targeting scarce resource more efficiently and effectively.
Research objectives: The overarching aim of this studentship is to provide critical data on the impact of climate and land-use change on microbial pollution of S(W)PAs both now and into the future, thus delivering quantitative evidence to help safeguard Scotland’s economically and socially important shellfish industry. The student will forecast future scenarios of risk to Scotland’s shellfish harvesting industry as driven by projected climate change trends, e.g. changing rainfall patterns and intensity, and future shifts in rural and urban land use. Specifically, the research objectives are to:
1. Use the ViPER/SCIMAP-FIO models to generate spatially-distributed and temporally-variable catchment-scale risk outputs for SPAs in Scotland;
2. Identify a subset of three test catchments linked to vulnerable S(W)PAs and undertake a programme of water quality sampling to quantify model fit to observed water quality data through contrasting seasons;
3. Investigate associations between E. coli levels in shellfish at S(W)PAs, modelled outputs of ViPER/SCIMAP-FIO surface water quality in drainage networks and climatic & ‘within-catchment’ environmental datasets;
4. Predict how patterns of risk to S(W)PAs vary in response to different climate and land-use change scenarios;
5. Model catchment ‘what-if’ management and mitigation scenarios to quantify their likely microbial pollution risk-reduction to S(W)PAs from future climate and land-use change.
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Spatial variation in E. coli risk in waters draining a Scottish catchment, as predicted by SCIMAP-FIO (SCIMAP-FIO model output screenshot)
1 – Use the ViPER/SCIMAP-FIO models to generate catchment-scale risk outputs for SPAs in Scotland: The student will derive catchment-scale predictions of in-stream E. coli pollution risk for all catchments that drain into S(W)PAs in Scotland. To determine catchment risk patterns, the student will use the ViPER/SCIMAP-FIO toolset for assessing microbial pollution risk. Phase 1 of this project will familiarise the student with a risk-based modelling approach while also delivering, in unprecedented detail, month-by-month risk model outputs of in-stream E. coli risk distributed across the drainage network of the contributing catchment area. This will provide a spatial and temporal dataset for wider analysis and interpretation.
2 – Identify a subset of test catchments that drain to S(W)PAs and undertake a programme of water quality sampling to quantify model fit to observed values through contrasting seasons: To ground-truth the models developed in Phase 1, a subset of catchments will be identified for investigation via a programme of water quality monitoring. Three rasting contcatchments will be selected, depending on risk model outputs and their catchment size. Water quality within the selected catchments will be monitored across seasons for E. coli, with spatially distributed sampling across different tributaries of varying levels of predicted microbial pollution risk.
3 – Investigate associations between S(W)PA water quality, ViPER/SCIMAP-FIO modelled outputs and climatic & ‘within-catchment’ environmental datasets: The student will analyse historical regulatory & observational monitoring data (E. coli quantified in shellfish flesh) at Scotland’s S(W)PAs together with spatially-distributed catchment data (e.g. land-use, catchment hydrology) and ViPER/SCIMAP-FIO risk outputs to identify any statistical associations between predictor and response variables that can enable quantitative predictions of microbial pollution risk to S(W)PAs based on existing catchment data. This will be complemented with the contemporary water quality sampling undertaken within this studentship to provide a ‘fit-for-purpose’ validation dataset.
4 – Predict how patterns of risk to S(W)PAs vary in response to different climate and land-use change scenarios: The student will use the derived association between ViPER/SCIMAP outputs and S(W)PA microbial water quality to quantitatively predict microbial water quality risk to all of Scotland’s S(W)PAs from 2020 to 2050. Extensive datasets are freely available via a number of stakeholder organisations that report on historical E. coli data, land use, and meteorological data. UKCP18 climate projections will be used to inform future climate scenarios.
5 – Model catchment ‘what-if’ management and mitigation scenarios to quantify their likely risk-reduction to S(W)PAs from future climate and land-use change: A series of catchment management options will be identified that have potential to protect the economic, social and environmental value of Scotland’s S(W)PAs. These will be integrated into model runs through scenario analysis for a subset of the most vulnerable S(W)PAs to predict how microbial risk can be reduced via a range of management approaches that respond to likely environmental and climate change.
As the PhD develops you will also liaise with an external collaborator, Dr Phil Bartie (Computing Science, Heriot-Watt University), to develop novel geospatial skills to complement the studentship.
In the first 4 months of the studentship you will develop a critical review of the literature. After engaging with the literature you will begin to learn key skills for catchment risk mapping and visualisation and participate in key training opportunities.
In year 2 you will begin to develop catchment modelling skills for predicting microbial pollution. This will be complemented with a spatially-targeted catchment-wide sampling campaign. You will be encouraged to begin to draft chapters as you progress.
In addition to writing up aspects of the research undertaken so far you will now investigate and model associations between S(W)PA water quality, ViPER/SCIMAP-FIO modelled outputs and climatic & ‘within-catchment’ environmental datasets. This will also involve a phase of scenario analysis modelling to examine potential impacts of climate and land use change.
The final 6 months will be used to interpret the outputs from the scenario modelling and to finalise the thesis with respect to writing up and refining further the drafts of chapters completed thus far.
This studentship will provide a platform to build an interdisciplinary research career in applied microbiology and hydrology in the context of diffuse pollution with human health impact. The studentship will broaden the scope of the applicant’s skills base by providing specialist training in the safe handling of Hazard Group 2 microorganisms & microbiological methods, and by developing expertise in the use of a wide range of laboratory and modelling techniques. Extensive skill development in fieldwork will include comprehensive training in sampling & monitoring techniques. The student will also be exposed to GIS modelling methodologies including computer code writing and risk & uncertainty analysis, with a focus on Python and the effective use of web based technologies, such as cloud computing and web services, for scientific research.
References & further reading
Clements K, Quilliam RS, Jones DL, Wilson J, Malham SK. (2015). Spatial and temporal heterogeneity of bacteria across an intertidal shellfish bed: implications for regulatory monitoring of faecal indicator organisms. Science of the Total Environment 506-507, 1-9
Oliver DM, Bartie PJ, Heathwaite AL, Reaney SM, Parnell J & Quilliam RS (2018) A catchment-scale model to predict spatial and temporal burden of E. coli on pasture from grazing livestock, Science of the Total Environment, 616, 678-687
Porter KDH, Reaney SM, Quilliam RS, Burgess C & Oliver DM (2017). Predicting diffuse microbial pollution risk across catchments: the performance of SCIMAP and recommendations for future development, Science of the Total Environment, 609, 456-465
For informal enquires: Dr David Oliver (firstname.lastname@example.org tel: 01786 467846)