Project Description

About the Project

Environmental regulators rely on biological monitoring to assess the condition of rivers and detect ecological change, but high-quality professional monitoring is expensive and consequently limited in its spatial and temporal coverage. Citizen-science programmes could greatly increase the quantity of biological information available to regulators, but these data cannot simply be combined with professional observations. Differences in sampling, identification expertise and quality control can be confounded with genuine biological variation.

This PhD will address this problem through methodological development in data-driven biology. The student will develop new statistical approaches for integrating heterogeneous biological observations while explicitly representing their different error structures. Freshwater macroinvertebrate communities provide an unusually powerful test system because WildFish’s SmartRivers programme collects full-community biological data directly comparable with professional regulatory monitoring.

SmartRivers contains several complementary observation pathways: samples collected and analysed professionally; samples collected by trained volunteers and analysed professionally; and samples both collected and analysed by trained volunteers. These are supplemented by quality-control samples and can be combined with open-access professional monitoring data from environmental regulators. This structure provides a rare opportunity to learn how errors enter biological observations and how information from data sources of differing quality can be integrated without treating them as equivalent.

The student will: (1) quantify sampling, detection and identification error across observation pathways; (2) develop hierarchical Bayesian models that estimate underlying biological communities from professional, hybrid, volunteer and regulatory observations; (3) exploit spatial, temporal and taxonomic structure to improve inference across partially overlapping datasets; and (4) determine when citizen-science observations provide sufficient additional information to strengthen regulatory assessment, and where professional sampling and quality-control effort are most valuable.

The project will therefore deliver both new methodology and an applied framework through which environmental regulators and other monitoring organisations can make statistically defensible use of citizen-science biological data. Methods and open-source software will be designed to generalise beyond freshwater monitoring to other areas of bioscience where multiple observation technologies, protocols or expertise levels provide imperfect measurements of an underlying biological system.

Training will include Bayesian hierarchical modelling, computational statistics, data integration, community ecology and reproducible research, in addition to exposure to freshwater fieldwork techniques. Through the CASE partnership with WildFish, the student will also gain practical experience of biological monitoring, citizen-science programme design and translating quantitative evidence for environmental decision makers.

Funding Information

Funding Notes

This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership.

This opportunity is open to UK and International students and provides funding to cover stipend at UKRI standard rate and UK level tuition fees. The University of St Andrews will cover the Home-International fee difference.

Eligibility Requirements

UKRI eligibility guidance: Terms and Conditions: View Website International/EU: View Website

Application Process

How to apply

Application instructions can be found on the EASTBIO website- How to Apply | EastBio Doctoral Training Partnership | Biology

1) Download and complete the Equality, Diversity and Inclusion survey.

2) Download and complete the EASTBIO Application Form.

3) Please complete an application on our online portal: How to apply – Study at St Andrews – University of St Andrews

4) Select the course ‘PhD with internship’

5) Your online application must include the following documents:

• Completed EASTBIO application form
• Academic Qualifications
• English Language Qualification (if applicable)
• 2 References: this must be completed on the EASTBIO Reference Form, also found on the EASTBIO website.

Please download the EASTBIO reference form and send it to your referees. They can either upload it directly to the portal using the automated email they will receive, or they can email it to Rachel at [email protected]

Contact

Queries on the project can be directed to the project supervisor at [email protected]

Queries on the application process can be directed to Rachel Horn at [email protected]

Application enquires: [email protected]