About the project
This project will use a multidisciplinary approach combining ecological surveying, high performance liquid chromatography (HPLC) analysis, and network analysis, to capture the impacts of loss of nutrition, including quality and quantity of nectar and pollen nutrients, on wild pollinator trophic, competitive, and parasitic interactions, in fragmented and agriculturally dominated landscapes.
UK wild bee species are essential in the pollination of crops and securing food but are also critical for the pollination, structure, and functioning of wild plant communities. Living in diverse ecosystems, wild pollinators have interactions with many other organisms, ranging from microbes to parasites and predators. There is strong evidence of wild pollinator decline in the UK, largely linked to habitat loss. When habitat is lost, so are pollinators sources of nutrition. However, to date, we do not understand the wider impacts of nutrient loss on the community structure of other pollinator-organism interactions. This is a very topical environmental issue and links to the global challenges of food security and biodiversity loss.
The aim of this project is to understand how the available nutrients in a community influence the composition and functionality of a pollinator-dependent ecosystem.
The project will provide the candidate opportunities to develop skills in ecological surveying to capture the interacting organisms in different landscapes. They will also develop analytical techniques, including HPLC, to quantify macronutrients found in nectar and pollen. They will then apply their findings to map the interactions of communities and model predictions of changes in interactions for different habitat types.
This work will help us understand how changes in the nutrition available in an environment impact community structure and allow us to predict how management of land use can benefit wild pollinators and their broader ecological interactions.
This project would be ideal for a candidate who wishes to develop diverse skills in field work, lab work and data analysis.
