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Adaptive management of stochastic parasite challenge in animals under climate change

This project is no longer listed on and may not be available.

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  • Full or part time
    Prof E Morgan
    Dr M Robinson
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Project details:

Climate change is causing greater variation in conditions for parasite transmission, and increased unpredictability in disease outbreaks in farmed and other animals. Simultaneously, spreading anthelmintic resistance calls for more discriminate drug use. This can lead to high-risk situations, where unprotected animals face dangerous peaks in infection pressure. This project will consider how to manage these unexpected events using a combination of climate-based prediction of infection pressure, monitoring infection levels, and targeted intervention in groups and individuals. Systems will be selected as exemplars of this approach, e.g. helminths (gastro-intestinal nematodes, lungworm and fluke) in grazing livestock, and the special cases of spring scour worm Nematodirus battus in lambs and the tropical blood-feeding nematode Haemonchus contortus in sheep and goats. Current studies provide access to data sets and field sites, and the approach will be extended to new climates through active projects with partners in southern Africa and North America. Methods will include pen-side diagnostics to track parasite infection levels over time, and risk prediction models, culminating in new field-accessible systems for monitoring and decision support. Training will be provided in diagnostic parasitology and quantitative methods; outcomes will support sustainable parasite control under global change.

This project will be supervised by Professor Eric Morgan and Dr Mark Robinson.

All applications MUST be submitted through

Specific skills/experience required by applicants:

Experience of quantitative methods applied to population dynamics or climate change predictions would be an advantage but training will be provided.

All applicants must meet the academic entry requirements:

Funding Notes

Only UK and EU students are eligible to apply. Before applying, it is strongly recommended that you read the full information on eligibility criteria available from DfE:

Please note in particular that not all successful applicants may be eligible to receive a full studentship (i.e. fees and stipend) - please read in detail the Residency and Citizenship requirements in the document linked to above.

How good is research at Queen’s University Belfast in Agriculture, Veterinary and Food Science?

FTE Category A staff submitted: 33.40

Research output data provided by the Research Excellence Framework (REF)

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