Evaluating how plant community composition influences natural enemy biodiversity and pest regulation services in temperate agroforestry systems
Project Description
"The overarching aim of this studentship is to work with the Woodland Trust to provide them with sufficient evidence to encourage and optimise integrated tree use on agricultural land. This is known as agroforestry, i.e. farming systems that incorporate the cultivation of trees into agricultural production. These systems often benefit from increased pollination services and biodiversity, and can achieve higher production efficiency, relative to conventional mono-cropping. Modifications to the design of these systems could enable further increases in productivity by enhancing the quality of habitats for biodiversity, enabling further integration of biodiversity derived ecosystem services into production.
During this project the student will be trained in a variety of fieldwork techniques and will generate new data sets to:
1) investigate the links between plant community composition and natural pest regulation services provided by agroforestry; and
2) develop and test novel management practices to provide more eco-functional agroforestry systems with enhanced pest regulation services
Using the data generated in these studies in combination with our pre-existing data sets on carbon, biodiversity, pollination and yield (crop and tree) in agroforestry systems, the student will gain training in quantitative methods to:
3) model the economic value of both pest regulation and pollination services provided by agroforestry systems; and
4) investigate the trade-offs between the different ecosystem services provided by agroforestry."
PLEASE NOTE THE DEADLINE FOR APPLICATIONS IS NOW THE 30TH JULY 2017
Funding Notes
Interested candidates can apply directly to the supervisor ([Email Address Removed]) by sending their CV, a covering letter explaining why they are interested in the project and CDT, and the names and e-mail addresses of two academic referees. At least one should have supervised the applicant on a previous research project.
Applicants will have, or be about to obtain, a Masters qualification (MSc, MRes or MSci/MMath) in a relevant discipline. Exceptional students at Bachelors level without a Masters will be considered. Relevant post-graduate experience will also be taken into account.
