Ecological Interactions, biodiversity and stability


   School of Biological Sciences

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  Prof V Jansen, Dr Axel Rossberg  No more applications being accepted  Competition Funded PhD Project (UK Students Only)

About the Project

Natural ecosystems exist in a continuously changing environments, often in highly unpredictable and disorderly ways. How species interact, what governs ecosystems’ functioning and how ecosystems maintain a balance and persist in a changeable world are among key questions of ecology. These questions have only gained in importance with the loss of biodiversity through the increased impact of anthropogenic changes on our environment. How much diversity an ecosystem has, and whether or not this diversity can be maintained depends ultimately on the interactions that species have. One of the fundamental questions in biology is how ecosystem stability and diversity depends on the interactions between species.

Mathematical models have played a key role in answering this question. The seminal work of May showed how ecosystems would typically become less stable as they become more complex (May, 1972). But what May’s approach can not answer is how many species we can expect to persist in an ecosystem. This question has been described as one of the big open questions in theoretical ecology (Rohr et al. 2014, Stone 2016). Recently, significant advances have been booked in solving this question for simple, competitive ecosystems (Rossberg 2013, Stone 2016, Stone 2018).

This project aims to investigate that the probability that ecosystems are feasible and/or stable in a variety of ecosystems models that have more complicated interactions. Other results have shown that if the mean, or the variance, of the strength of the competition is increased, an random ecosystems have fewer species. Presumably, it will also have an effect on the capacity of such models to support biodiversity at different trophic levels of diversity. In this project we aim to solve a fundamental question of what biodivertsity we can theoretically expect in predator-prey and other trophic interactions.

By studying such models using recent advances for random ecosystems we can increase our theoretical predictions of how ecosystems function. There have been several studies which have generated empirical insights in how natural communities are structured by interactions. One such studies claimed that microbiological communities either characterised by either mutualistic or competitive interactions. We do not know what causes this dichotomy. In this project we aim to generate answers to fundamental questions like these.

This project is suitable for applicants with first degree in biology or environmental sciences and some experience in and affinity to modelling, or applicants with a quantitative background in, for instance, mathematics, physics or computer science and an interest in biology and ecology. Candidates are strongly advised to contact main supervisor in advance of applying. 

To apply follow link and instructions at https://www.royalholloway.ac.uk/research-and-teaching/departments-and-schools/geography/news/london-nerc-dtp-competition-funded-studentship/


Funding Notes

The studentship is fully funded with a 4 years stipend at UKRI level and funding for research and training purposes as set by the London NERC DTP.

References

• Kokkoris, Jansen, Loreau, M. and Troumbis (2002), Variability in interaction strength and implications for biodiversity. Journal of Animal Ecology, 71: 362-371 https://doi.org/10.1046/j.1365-2656.2002.00604.x
• Machado et al. (2021) Polarization of microbial communities between competitive and cooperative metabolism. Nat Ecol Evol 5, 195–203. https://doi.org/10.1038/s41559-020-01353-4
• May (1972) Will a Large Complex System be Stable?. Nature 238, 413–414 (1972) https://doi.org/10.1038/238413a0
• Rohr, Saavedra and Bascompte (2014) On the structural stability of mutualistic systems.Science345,1253497 https://doi.org/10.1126/science.1253497
• Rossberg, A.G., (2013) Food Webs and Biodiversity: Foundations, Models, Data. Wiley.
• Stone (2016) The Google matrix controls the stability of structured ecological and biological networks. Nat Commun 7, 12857 (2016). https://doi.org/10.1038/ncomms12857
• Stone (2018) The feasibility and stability of large complex biological networks: a random matrix approach. Sci Rep 8, 8246 https://doi.org/10.1038/s41598-018-26486-2

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