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Predicting the Unpredictable: the role of eco-evolutionary experience in species interactions across taxa and habitats

Project Description

This project will be supervised by Professor Jaimie Dick of Queen’s University School of Biological Sciences and by Professor Xavier Lambin of the University of Aberdeen’s Institute of Biological and Environmental Sciences. The start date will be 1 October 2019.

Invasive alien species, range shifts, re-invasions by recovering native species and rewilding are among the major drivers of the current and future redistribution of the world’s biota (e.g. Seebens et al. 2017). We thus face unprecedented challenges in our ability to predict the outcomes of new species interactions and their impacts on biodiversity. This project will develop recent advances in predictions of species interaction outcomes in ecological and evolutionary contexts across a range of species and habitats.

The degree of eco-evolutionary experience (EEE) among interacting species is emerging as a major predictor of outcomes, such as species replacements after invasion (e.g. Penk et al. 2017). Indeed, recent advances in metrics that predict the ecological impacts of invasive alien species are consistent with the hypothesis that EEE drives outcomes, such as dramatic decreases in native fauna due to invasive predators (Dick et al. 2017) and the impact of recovering native predators on modified ecosystems.

Here, we propose to develop a predictive framework that allows forecasting of the outcomes of species interactions under scenarios ranging from recolonisations by natives to completely novel pairs of interacting species. This will be based on combinations of metrics that show great promise in predicting outcomes of competitive and predatory interactions across taxa and trophic groups (Dick et al. 2017). In particular, combining the classic “functional response” (resource uptake rate) and numerical response (e.g. abundance, reproduction) into the Relative Impact Potential (RIP) metric has led to prediction of the degree of invasive species impacts and has promise for wider species interactions across the spectrum of species’ eco-evolutionary experience (Dick et al. 2017).

Further, by incorporating key factors such as climate change and parasitism/disease, the RIP metric can incorporate these context-dependencies into prediction, a hitherto elusive goal in ecology (Dick et al. 2017). We thus propose to utilise study systems in Northern Ireland i.e. Queen’s University Belfast (e.g. invasive trout) and Scotland i.e. University of Aberdeen (e.g. recovering pine marten, goshawk and buzzard, invasive mink) to address this overall challenge by: (1) testing our metrics for predictive power in individual study systems, incorporating context-dependencies and reconciling small scale data with ecosystem wide impacts, and (2) collating existing/new study systems data to test generality with meta-analyses. For example, recent invasions in N. Ireland by Ponto-Caspian species have resulted in novel interactions among taxa with little eco-evolutionary history, while range shifts of e.g. pine marten, goshawk and buzzard in Scotland are resulting in the re-establishment of species interactions. This range of EEE provides a rich source of systems to test specific outcomes and generality of the methodology across habitats, taxonomic groups, trophic levels and predicted environmental change that provides context-dependencies.

Training will be provided in the following (not exhaustive) list: experimental design and analyses, with R in general and bespoke packages (e.g. FRAIR developed at QUB for functional response analyses); field survey, sampling and analytical tools (e.g. tracking and Bayesian analyses at Aberdeen). The student will also benefit from choice of an extensive range of training provided by the QUADRAT NERC DTP.

Dick, J.T.A. et al. (2017). Invader Relative Impact Potential: a new metric to understand and predict the ecological impacts of existing, emerging and future invasive alien species. Journal of Applied Ecology, 54: 1259-1267.
Penk, M., Saul, W.-C., Dick, J.T.A., Donohue, I., Alexander, M.E., Linzmaier, S. & Jeschke, J.M. (2017). A trophic interaction framework for identifying the invasive capacity of novel organisms. Methods in Ecology and Evolution, 8: 1786–1794.
Seebens, H. et al. (2018). Global rise in emerging alien species results from increased accessibility of new source pools. Proceedings of the National Academy of Sciences, 115, 2264–2273.

Funding Notes

This studentship is available to UK and other EU nationals and provides funding for tuition fees and stipend, subject to eligibility.

Candidates should have (or expect to achieve) a minimum of a 2.1 Honours degree in a relevant subject.


Application Procedure:

(1) Apply for Degree of Doctor of Philosophy in Biological Sciences;
(2) State name of the lead supervisor as the name of proposed supervisor;
(3) State QUADRAT DTP as intended source of funding;
(4) State the exact project title on the application form.

How good is research at Queen’s University Belfast in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 24.40

Research output data provided by the Research Excellence Framework (REF)

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