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University of Reading Featured PhD Programmes

Masters by Research: Understanding the drivers of biodiversity potential in urban ponds

School of Applied Sciences

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Dr R Briers , Dr J Dodd No more applications being accepted Self-Funded PhD Students Only

About the Project

Urban freshwater ecosystems are often characterised as impacted with limited biological life. Throughout the last century however, urban water quality has been improving, with concomitant changes in biological diversity. Approaches to the management of water within urban areas have changed radically, with the widespread use of artificial waterbodies that are built-in to developments, so-called sustainable urban drainage systems or SUDS. These systems, which are mainly in the form of small ponds, present an opportunity to diversify and enhance urban freshwater biodiversity, if managed correctly which is one of the stated aims of SUDS design. This MRes project aims to examine the local- and catchment-scale drivers behind variation in biodiversity in urban pond sites. The proposed work would involve a combination of field research to collect data on invertebrate communities and physico-chemical conditions from urban ponds in Scotland and analysis of existing UK-wide data to develop understanding of the processes driving variation in species richness and composition.

Academic qualifications
A first degree (at least a 2.1) ideally in (aquatic) ecology, environmental science or a related subject with a good fundamental knowledge of freshwater taxonomy and sampling methods along with strong statistical and data management skills.

English language requirement
IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:
• Skilled in identification of freshwater invertebrates and physico-chemical analysis of water samples.
• Experience of collation and management of heterogeneous datasets and undertaking statistical analysis using R, multivariate analysis.
• Good written and oral communication skills
• Strong motivation, with evidence of independent research skills relevant to the project
• Good time management

Desirable attributes:
• Knowledge of GIS and spatial analysis techniques

Funding Notes

This is an unfunded MRes position


Briers, R. A. (2014) Clean: Soil Air Water, 42: 193-200.
Hill, M.J., Biggs, J., Thornhill, I. et al. Landscape Ecol (2018) 33: 389.

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