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Determining the impacts of non-native species on global ecological network structure


   School of Biological and Behavioural Sciences

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  Dr Tom Fayle, Dr Pavel Kratina  No more applications being accepted  Awaiting Funding Decision/Possible External Funding

About the Project

  • Supervisors: Dr Tom Fayle, Dr Pavel Kratina and Dr Shuang Xing
  • Funding: China Scholarship Council (CSC)
  • Deadline: 31st January 2023

Research environment

The School of Biological and Behavioural Sciences at Queen Mary is one of the UK’s elite research centres, according to the 2021 Research Excellence Framework (REF). We offer a multi-disciplinary research environment and have approximately 180 PhD students working on projects in the biological and psychological sciences. Our students have access to a variety of research facilities supported by experienced staff, as well as a range of student support services.

The Network and Community Ecology lab led by Dr Tom M. Fayle explores how network structure is affected environmental gradients, with a particular focus the impacts of anthropogenic global changes, and consequences for ecosystem processes. The research group of Dr Pavel Kratina evaluates the roles of multiple environmental changes (including invasive species and climate warming), foraging behavior, and other organismal traits on the complexity, structure, and dynamics of communities and ecosystems. Dr Shuang Xing is an Assistant Professor at Sun Yat-sen University (China), with interests in network ecology and species responses to environmental gradients, and collaborated with TMF to set up the LifeWebs database.

Training and development

Our PhD students become part of Queen Mary’s Doctoral College which provides training and development opportunities, advice on funding, and financial support for research. Our students also have access to a Researcher Development Programme designed to help recognise and develop key skills and attributes needed to effectively manage research, and to prepare and plan for the next stages of their career.

The student will have opportunities to develop their skills in statistical programming, scientific writing, and database management, and for a collaborative visit to work with Czech-based members of the LifeWebs team.

Project description

Humans are rapidly driving homogenisation of the world’s biological diversity through transportation of species from one place to another. These non-native species frequently have detrimental effects on the local native communities, and alter ecosystem functioning, often with loss of ecosystem services vital for human wellbeing. Although there are many case studies demonstrating the impacts of individual non-native species, we are only now starting to understand impacts at the level of entire ecological networks. A recent pioneering meta-analysis of plant-frugivore networks showed that non-native species greatly reduced compartmentalisation of global meta-networks (Fricke and Svenning Nature 2020, https://doi.org/10.1038/s41586-020-2640-y). However, it remains unclear whether other kinds of mutualistic networks are affected by invasions in the same way. Furthermore, mutualistic networks might be more likely to show changes in structure due to invasions, since they are more compartmentalised than antagonistic networks.

The PhD student will quantify differences in global scale impacts of non-native species on mutualistic and antagonistic ecological networks using the LifeWebs database (www.lifewebs.net, the world’s largest ecological network database), of which TMF is the PI, which comprises >1200 networks, documenting interactions between > 1 million organisms. They will compare compartmentalisation of mutualistic and antagonistic networks, for global meta-networks, and at the scale of individual datasets. We predict that non-native plant species in mutualistic networks are more likely to be phylogenetically closely related to native plant species, since they are able to share mutualistic partners. Conversely for antagonistic networks, we predict that non-native species that are phylogenetically distinct are more likely to persist (enemy release hypothesis). The project can also be expanded in a direction of the student's own choosing. This work will potentially help prediction of novel invasive species, and to identify native communities that will be vulnerable to invasion in the future. These issues are of particular concern with rapid ranges of species shifting under climate change.

Funding

This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

Eligibility and applying

Applicants must be:

- Chinese students with a strong academic background.

- Students holding a PR Chinese passport.

- Either be resident in China at the time of application or studying overseas.

- Students with prior experience of studying overseas (including in the UK) are eligible to apply. Chinese QMUL graduates/Masters’ students are therefore eligible for the scheme.

Please refer to the CSC website for full details on eligibility and conditions on the scholarship. 

Applications are invited from outstanding candidates with or expecting to receive a first or upper-second class honours degree in an area relevant to the project, such as Biology, Mathematics or Physics. A masters degree in a similar topic is desirable, but not essential.

Good programming skills in the language R are desireable for applicants, along with a passion for ecology. Some experience of network ecology, particularly from a theoretical persespective, would be an advantage.

Applicants from outside of the UK are required to provide evidence of their English language ability. Please see our English language requirements page for details: https://www.qmul.ac.uk/international-students/englishlanguagerequirements/postgraduateresearch/

Informal enquiries about the project can be sent to Dr Tom M. Fayle at [Email Address Removed]. Formal applications must be submitted through our online form by 31st January 2023 for consideration, including a CV, personal statement and qualifications.

Shortlisted applicants will be invited for a formal interview by the project supervisor. Those who are successful in their application for our PhD programme will be issued with an offer letter which is conditional on securing a CSC scholarship along with academic conditions still required to meet our entry requirements.

Once applicants have obtained their offer letter from Queen Mary they should then apply to CSC for the scholarship by the advertised deadline with the support of the project supervisor.

For September 2023 entry, applicants must complete the CSC application on the CSC website between 10th March - 31st March 2023.

Only applicants who are successful in their application to CSC can be issued an unconditional offer and enrol on our PhD programme. For further information, please go to: https://www.qmul.ac.uk/scholarships/items/china-scholarship-council-scholarships.html

Apply Online


Funding Notes

This studentship is open to students applying for China Scholarship Council funding. Queen Mary University of London has partnered with the China Scholarship Council (CSC) to offer a joint scholarship programme to enable Chinese students to study for a PhD programme at Queen Mary. Under the scheme, Queen Mary will provide scholarships to cover all tuition fees, whilst the CSC will provide living expenses for 4 years and one return flight ticket to successful applicants.

References

Fricke, E.C. and Svenning, J.C., 2020. Accelerating homogenization of the global plant–frugivore meta-network. Nature, 585(7823), pp.74-78.
Xing S. & Fayle T.M. (2021) The rise of ecological network meta-analyses: problems and prospects. Global Ecology and Conservation 30: e01805.
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