Project Description
Endemic and emerging diseases transmitted from wildlife have significant impacts on human and livestock health across the globe, especially in Lower Middle-Income Countries. Understanding how anthropogenic stressors such as climate change and habitat fragmentation influence the distribution and prevalence of parasites and pathogens in wildlife populations will be crucial for future efforts to predict and mitigate risk. As the impact of such stressors on parasite dynamics is mediated through effects on key determinants of transmission rates (e.g. host and/or vector abundance, host contact patterns, survival of free-living stages), consequences will vary between parasites with different life histories. To help generate predictions, we need to determine how different parasites respond to abiotic and biotic factors and explore how life-history modulates the responses.
Rodent populations are ideal model study systems for disease ecology, as they are easy to survey and sample, and play host to a wide range of macroparasites (e.g. ectoparasites, helminths) and microparasites (e.g. bacteria, viruses), including zoonotic pathogens. This project will build on a long-term study of water vole metapopulations, using new and archived data and samples to examine the relative importance of environmental factors and host population dynamics for infection patterns of a range of parasites and pathogens. Studies over the last 20 years provide unparalleled knowledge of host metapopulation dynamics (e.g. extinction-recolonisation), as well as the distribution and prevalence of different parasites and pathogens. These include ectoparasites, helminths and microparasites. Whilst some parasites and pathogens are distributed widely across the metapopulations others are more spatially restricted.
The project will:
- determine how the spatial-temporal dynamics of different parasites and pathogens are influenced by both environmental and host associated factors (e.g. climate, local soil conditions, host and vector abundance, population connectivity, distribution of alternative hosts and coinfection).
- compare key drivers of dynamics between parasites with different life cycles and epidemiology.
- develop mechanistic models to explore how variation in microclimate can drive spatial and seasonal differences in parasite infection pressure.
- explore implications for disease emergence under global change.
The project will involve fieldwork to collect new data and samples, including new data on microclimatic conditions across the metapopulations; lab-work to extend the data on the distribution and prevalence of different parasites; and statistical analyses using hierarchical spatial models to account for uncertainty in detection at all stages of the sampling process. Analyses will determine the relative importance of climate and host dynamics to parasite persistence and prevalence in fragmented populations. Conclusions are likely to differ between parasites because life histories will be affected in contrasting ways by temperature, moisture and other environmental variables.
The project would suit a student with a background in ecology or epidemiology and numerical skills. The student will receive multidisciplinary training in field and laboratory skills and advanced statistical modelling. There is considerable scope for the student’s interest to drive the evolution of the project.
Essential & desirable candidate skills
Essential: Background in ecology or parasitology, willingness to contribute to fieldwork and lab-work; desire to develop statistical and/or mathematical modelling skills
Desirable: Lab-work experience. Some experience of statistical analysis of ecological data.
Supervisors
Sandra TelferPrimary Supervisor: | Profile: Sandra Telfer Email: s.telfer@abdn.ac.uk Institution: University of Aberdeen Department/School: School of Biological Sciences |
Eric MorganSecondary Supervisor: | Profile: Eric Morgan Email: eric.morgan@qub.ac.uk Institution: Queen's University, Belfast Department/School: School of Biological Sciences |
Xavier LambinAdditional Supervisor: | Profile: Xavier Lambin Email: x.lambin@abdn.ac.uk Institution: University of Aberdeen Department/School: School of Biological Sciences |
Additional Supervisor: | Dr Chris Sutherland, University of St Andrews. Chris is a long-term collaborator on the water vole metapopulation study and will provide advice on the use of hierarchical models to account for uncertainty in detection across the sampling process. |
References
Cable et al. (2017) Global change, parasite transmission and disease control: lessons from ecology. Phil. Trans. R. Soc. B 372: 20160088 http://doi.org/10.1098/rstb.2016.0088
Manlove et al. (2022) Defining an epidemiological landscape that connects movement ecology to pathogen transmission and pace of life. Ecology Letters 25: 1760-1782 https://doi.org/10.1111/ele.14032
Miller et al. (2012). Estimating patterns and drivers of infection prevalence and intensity when detection is imperfect and sampling error occurs. Methods Ecol. Evol. 3:850–859 https://doi.org/10.1111/j.2041-210X.2012.00216.x
Impact
Endemic and emerging diseases transmitted from wildlife have significant impacts on human and livestock health across the globe, especially in Lower Middle-Income Countries. Understanding how anthropogenic stressors such as climate change and habitat fragmentation influence the distribution and prevalence of parasites and pathogens in wildlife populations, and therefore disease risk, will be crucial for future efforts to predict and mitigate risk. Studying parasites and pathogens of concern is often difficult, leading to a lack of information on their ecology and the impacts of environmental change. The water vole metapopulations in north-west Scotland represent an ideal model study system to explore how biotic and abiotic factors interact to influence parasite prevalence. The populations are naturally fragmented, and there is an archive of data and samples extending up to 20 years for some parasites. By studying a range of parasites with different life histories, the project will explore to what extent the key factors are common across parasites with similar life histories and differ between parasites with contrasting life histories. The project will therefore make a significant contribution to our general ability to predict responses of parasites to some key elements of global change, specifically population fragmentation and climate change.
In terms of scientific publications, it is anticipated this project will produce three to four articles.
Proposed Supervision
Sandra Telfer is a Wellcome Trust Senior Research Fellow at the University of Aberdeen, with research focussing on population ecology, disease ecology, the epidemiology of zoonoses (especially rodent-borne zoonoses) and strategies to mitigate zoonotic risk. Her research includes studies in Scotland, Tanzania and Madagascar. ST will provide training in field techniques for population ecology, lab diagnostic tests and statistical analyses of ecological and epidemiological data.
Eric Morgan is a Professor at Queen’s University Belfast, with an interest in how climate influences the epidemiology of parasitic infections. His research combines field research, experiments on parasite biology and predictive computer modelling. EM will provide advice on climate impacts on parasites and training in the development of microclimate linked mechanistic models of parasite infection.
Xavier Lambin is a Professor in ecology at the University of Aberdeen. He is an expert in understanding the contributions of dispersal to population dynamics. XL will provide additional support in the analysis and interpretation of data.
Chris Sutherland is a Reader in Statistics at the University of St Andrews. He is a long-term collaborator on the water vole metapopulation study and will provide advice on the use of hierarchical models to account for uncertainty in detection across the sampling process.
Proposed Timetable
Year 1 (2023-2024)
Months 1-3: Literature review, initial exploration of existing data to facilitate project development (rodent-parasite data from Assynt; open-source data for climate, soil variables).
Months 4-8: Training in relevant lab methodologies and development of project plan. Start screening archived samples as necessary depending on project plan. Development of protocols for microclimate measurements in field.
Months 9-11: Fieldwork and sample collection.
Month 12: Lab-work
Year 2
Months 13-19: Further lab-work and development of statistical analysis pipeline to determine relative importance of climate and host dynamics on prevalence. Drafting of first article.
Months 18-20: Start to develop mechanistic models for selected parasite(s)
Months 20-23: Plan and conduct second year of field work.
Month 24: Lab-work
Year 3
Months 25-27: Completion of any lab work. Implementation of statistical analysis pipeline for additional parasites.
Months 28-36: Drafting of a second article, comparing relative importance of climate and host dynamics for parasites with different life histories. Further development of mechanistic model.
Year 4 (6 months)
Month 37 onwards: Thesis write-up and additional articles.
QUADRAT Themes
- biodiversity
- environmental-management
Partners
Not applicable at this time.
