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  How do recreational activities alter spatiotemporal species interactions networks, and can this knowledge assist in promoting pro-environmental behaviour?


   School of Mathematics and Statistics

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  Dr Chris Sutherland  No more applications being accepted  Funded PhD Project (Students Worldwide)

About the Project

Supervisors

The student will be based primarily at the University of St Andrews within Centre for Research into Ecological and Environmental Modelling (CREEM) in the School of Mathematics and Statistics. The supervisory team is made up of experts and project partners relevant to each aspect of the project:

·      Chris Sutherland (Primary supervisor, University of St Andrews)

·      Xavier Lambin (Partner, University of Aberdeen)

·      Kenny Kortland (Partner, Forestry and Land Scotland)

·      Darragh Hare (Partner, Oxford University)

Project details

In this project, you will examine how recreational disturbance influences species interaction networks and whether providing this information to park visitors can promote pro-environmental behaviour. You will do this using state-of-the-art statistical methods from ecology to quantify ecological networks and animal movement patterns, and methods from social psychology to quantify people’s beliefs, attitudes, intentions, and behaviours.

Contemporary conservation and management strategies prioritise addressing biodiversity loss. We propose a network approach to address two important and ubiquitous challenges associated with meeting biodiversity targets. First, the management and enhancement of large expanses of habitat (e.g., national parks) often requires trade-offs between potentially competing ecological, societal, and economic objectives. In Scotland for example, the remit of Forestry and Land Scotland (FLS), the largest land manager in the country, is to manage landscapes to “support and enable economically sustainable forestry; conserve and enhance the environment; and deliver benefits for people and nature.” Second, addressing the underlying causes of biodiversity loss assumes that the causal mechanisms that result in the loss of species are known, which is difficult to determine, especially in coupled human-natural systems subject to change via an ever-increasing human influence.

The focal community in this project is a predator-prey network consisting of a suite of mobile mammalian and avian generalist predators and a rich prey community that includes deer, passerines, ground nesting birds, and several vole species. Each of these have specific habitat requirements and vary in their vulnerability to recreational disturbance; for example, many of the predators (fox, badger, marten), have a high tolerance to human disturbance, whereas, some prey species, (e.g., locally endangered capercaillie, low density goshawk), are highly sensitive to disturbance. This interspecific disturbance sensitivity and spatial variation in predator-prey network structure presents an opportunity to quantify variation in community size and structure along anthropogenic disturbance gradients.

The management conundrum that emerges is that human behaviour is, to a large degree, beyond the control of resource managers. So, while effective management would benefit from the ability to predict ecological responses to recreational disturbance, it will also rely heavily on being able to understand the motivations for pro-environmental behaviour. Adopting a coupled socio-ecological approach to understanding the human-wildlife interface is likely to provide evidence for informing effective spatial planning for the benefit of the wildlife of the CNP and those who use it for recreation.

Training and Academic Environment

Being based within CREEM, a world-leading interdisciplinary research group at the intersection of ecology and statistics, the student will develop highly sought-after skills in ecological statistics that are transferable to a wide variety of topics. The supervisory team have extensive expertise in applied population ecology, quantitative ecology, and quantitative social science. The student will have the opportunity to participate in training schemes such as the Academy for Postgraduate Training in Statistics. There will also be additional support available for the attendance of conferences and other professional development activities. The student may be able to choose to matriculate in either Biology or Statistics.

Application process

Prior to submitting an application, prospective applicants are welcome to contact the Chris Sutherland ([Email Address Removed]) to discuss the project and to seek guidance or clarification on preparing application materials. Any pre-application conversations will not form part of the assessment of candidates and will not affect decision making.

For full consideration, applications should be received before 14th February 2022. Instructions on how to apply can be found here. Please note that it can take a few days for the required paperwork (including submission of references) to be completed and so you are strongly advised to apply well ahead of this deadline.


Biological Sciences (4) Mathematics (25)

Funding Notes

This is a fully funded PhD through the SUPER Doctoral Training Program, a Natural Environment Research Council (NERC) funded Doctoral training partnership (DTP) that provides excellent postgraduate research opportunities and training in a variety of professional and technical skills and personal development. SUPER offers PhD studentships for 3.5 years (42 months) including stipend and fees at the RCUK rate (rates announced when provided by NERC). Part-time study is also available.

References

Curveira-Santos, G., Sutherland, C., Tenan, S., Fernández-Chacón, A., Mann, G.K., Pitman, R.T. and Swanepoel, L.H., 2021. Mesocarnivore community structuring in the presence of Africa's apex predator. Proceedings of the Royal Society B, 288(1946), p.20202379.
Pollock, L.J., Tingley, R., Morris, W.K., Golding, N., O'Hara, R.B., Parris, K.M., Vesk, P.A. and McCarthy, M.A., 2014. Understanding co‐occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). Methods in Ecology and Evolution, 5(5), pp.397-406.
Sheehy, E., Sutherland, C., O'Reilly, C. and Lambin, X., 2018. The enemy of my enemy is my friend: native pine marten recovery reverses the decline of the red squirrel by suppressing grey squirrel populations. Proceedings of the Royal Society B: Biological Sciences, 285(1874), p.20172603.
Twining, J.P., Sutherland, C., Reid, N. and Tosh, D, G., 2022. Habitat mediates coevolved but not novel species interactions. Proceedings of the Royal Society B, 289(1966).

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