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Understanding the role of animals as predators of disease vectors: An overlooked ecosystem service?

   Department of Biosciences

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  Dr A Welch, Dr H Ferguson  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

A mountain of evidence in the scientific literature suggests that biodiversity provides important ecosystem services for humans. One aspect that has been particularly well studied is agricultural pest control, where animals such as birds and bats are often known to save farmers hundreds of dollars per hectare per year. However, an often overlooked ecosystem service that animals may provide is the consumption of insect disease vectors, which may literally save lives.

Insects that act as vectors, such as mosquitoes, are the deadliest animals on the planet, due to their role in the spread of diseases such as malaria, dengue fever, yellow fever, African sleeping sickness and others. These diseases alone account for more than 600,000 human deaths every year, in addition to suffering by hundreds of millions of people that contract the diseases but subsequently recover, and the economic burden of caring for them and lost productivity. Other diseases spread by insect vectors can be life altering (e.g. Zika virus).

Some progress has been made in controlling vectors like mosquitoes, particularly through the use of insecticides. However, insecticides can have negative outcomes, such as killing key crop pollinators, harming other members of the food webs such as insectivorous birds, and evidence suggests that vectors can and do evolve insecticide resistance. Natural predators of vector insects are poorly understood. For example, bats are known to be voracious consumers of mosquitoes, potentially removing up to 600 from the environment every hour, but it remains unclear which species they may be consuming (disease vectors or those that are relatively benign). Our DNA sequence data from bird and bat faecal samples collected from Cameroon show that at least 15 species of bats and birds consume mosquitoes from five different genera, including Anopheles, Culex, Coquillettidia, Eretmapodites, and Mansonia, which include important human disease vectors. However, our data remain incomplete, because it is very difficult to assign species-level taxonomy to insect vectors using current methods.

Thus, this project aims to:

1) In collaboration with project partners, develop a DNA metabarcoding system that can identify vector insects to species level

2) Employ the newly developed approach to identify animals consuming insect vectors – focusing on birds and bats, but potentially also amphibians, reptiles, and predatory insects

3) Use network and ecological modeling approaches to investigate the food webs that these species participate in, and perform sensitivity analyses to answer questions such as: What would happen if one or more predators were removed (e.g. due to land use or climate change)? What would happen if one or more vector species were removed from the system (e.g. due to vector control strategies)?


The student will leverage our massive collection of more than 2000 bird, bat, and amphibian samples already in hand from our on-going projects in Cameroon, Ghana and Zambia. They will also have the opportunity to join fieldwork in Ghana, if desired, and potentially other new sites in Africa.

In the lab, the student will conduct a literature review and employ public databases to find potential genetic regions with sufficient resolution to identify species-level taxonomy of insect vectors, and design/test candidate metabarcoding PCR primers from these regions. Once a suite of primers has been developed, and using a primer set developed by project partners, the student will conduct DNA metabarcoding of bird, bat, and potentially amphibian, reptile and predatory insect samples (i.e. simultaneous sequencing of all potential insect vector prey) using advanced DNA sequencing technology. These sequences will then be compared to our reference sequence database to assign taxonomy using sophisticated bioinformatics pipelines. Data will be analysed in ecological community networks as well as in a dynamic ecological modelling framework we are currently developing to link species interactions and abundances.

Funding Notes

This project is in competition with others for funding. Success will depend on the quality of applications received, relative to those for competing projects. If you are interested in applying, in the first instance contact the supervisor (Dr Andreanna Welch) with a CV and covering letter, detailing your reasons for applying for the project.


Dainese et al. 2019 A global synthesis reveals biodiversity-mediated benefits for crop production. Science Advances 5: 1–14.
Bimbilé Somda et al. 2022 Adult mosquito predation and potential impact on the sterile insect technique. Scientific Reports 12, 2561
Chandrasegaran et al. 2020 Linking mosquito ecology, traits, behaviour and disease transmission. Trends in Parasitology 36:393-403
Deiner et al. 2016 Environmental DNA metabarcoding: Transforming how we survey animal and plant communities. Molecular Ecology 26:5872-5895
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