NERC E4 Assessing and explaining the per-unit costs of non-native plant species. at University of Edinburgh on FindAPhD.com

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Dr Guillaume Latombe, Dr A Twyford No more applications being accepted Competition Funded PhD Project (Students Worldwide)

Edinburgh United Kingdom Ecology Evolution

About the Project

Interested individuals must follow the "how to apply" link on the Geosciences E4 Doctoral Training Partnership web page: http://www.ed.ac.uk/e4-dtp/how-to-apply

Summary

The aim of this project is to estimate the damage and management costs of non-native plant species per unit of abundance and area, and to explore how the characteristics of the non-native species and of the receiving environment may explain these costs.

Background

Invasive non-native species that have been transported beyond their native range by humans are amongst the main threats to biodiversity and cost billions of dollars each year globally. Yet, predictive tools to anticipate their future impacts are still lacking. Potential impacts for specific regions are currently estimated based on impacts in other regions with similar biotic and abiotic conditions. Not only does this kind of approach provide little information on how impacts are generated, they do not allow us to anticipate the impacts of species that have not yet been introduced outside of their native range. This is a problem, as the global number of non-native species shows a constant increase.

The total impact (I) of a non-native species can be conceptualised as being equal to the product of its range size (R), its local abundance (A), and its per-unit effects (E), i.e. the effects per unit of abundance (e.g. biomass or individual) and per unit of area: I = R × A × E. As a result, knowledge of E, and future values of R and A should enable us to anticipate future impacts I.

Despite the elegance of this formula, which has been proposed over 20 years ago, for capturing the mechanisms of impacts, it has not yet been operationalised. This is because most efforts have focused on forecasting future distributions of non-native species, on estimating total impacts, and on relating total impacts to range size or abundance. By contrast, per-unit effects have been largely neglected. Recently, we proposed a flexible yet simple approach (GIRAE) that generalises this formula beyond linear relationships, and allows for the computation of per-unit effects of non-native species.

This PhD project will combine two global databases to estimate the per-unit effects of plant species in multiple environments: the recent InvaCost database on the global costs of non-native species contains data on 563 plant species in 86 countries; the sPlot and sPlotOpen databases on plant species occurrence and abundance (sPlotOpen contains data on 42681 plant species in 114 countries). Per-unit effects will then be related to species traits and to environmental characteristics, to pave the way towards mechanistic, predictive models of non-native plant species impacts.

This PhD will be based in the Institute of Ecology and Evolution and will involve collaborations with other researchers across international universities.

Research questions

This project will aim at quantifying, comparing and explaining the per-unit costs of non-native plant species in different environments by addressing the following research questions:

How does the per-unit effect of non-native plant species vary across species in similar environments?
How does the per-unit effect of the same non-native species vary across different environments?
Which characteristics of non-native plant species explain their per-unit effects?
Which characteristics of the receiving environment explain the per-unit effects of different non-native plant species?

Methodology

The InvaCost and sPlotOpen databases will be explored in details and combined to generate the dataset used in the analyses. The GIRAE approach presented by Latombe et al. (2022) will then be applied to these data. The main principles of this approach consists of the following steps:

generalising the original impact formula using exponents to account for non-linear relationships: I = R^α × A^β × E
linearising the model through log-transformation: log(I) = α log(R) + β log(A) + log(E)
using a (generalised) linear regression to estimate the coefficients (corresponding to the exponents in the non-log-transformed formula), the intercept and the residuals (whose combinations provide the per-unit effects).

The PhD student will develop a robust workflow to apply GIRAE and quantify per-unit effects across multiple non-native plant species in different environments. The relationship between the characteristics of non-native species (including traits and characteristics of their native range), the characteristics of the receiving environments, and per-unit effects will then be explored using statistical models.

The recruited student will have the opportunity to explore and develop their own research questions, to tailor the research to their interests. These could include (but not limited to): considering additional or other databases and datasets on other taxonomic groups or different types of impacts (e.g. ecological), developing statistical approaches for different types of impacts, ordeveloping some field work.

Training

The recruited student will gain skills in invasion science, ecology, data analysis, statistical modelling, programming, and training in science best practice including FAIR data principles and science communication. The PhD programme will include some international collaboration and the recruited student will have the opportunity to develop their own targeted research questions. A comprehensive training programme will be provided comprising both specialist scientific training and generic transferable and professional skills.

Requirements

We seek an enthusiastic and motivated student with a background in ecology and quantitative analyses. Applicants should have good quantitative and mathematical abilities. Good programming skills are essential, particularly in R, but other programming languages would also be appropriate. And knowledge of or a willingness to learn version control in GitHub and open science best practice is encouraged.

Twyford.bio.ed.ac.uk

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Funding Notes

This project is eligible for the E4 Doctoral Training Partnership. The E4 projects are currently available for full NERC studentship funding which is competitive by interview to UK, EU and International applicants (The fee difference will be covered by the University of Edinburgh for successful international applicants.).
For application details see http://www.ed.ac.uk/e4-dtp/how-to-apply
Further details here - https://www.ed.ac.uk/e4-dtp/how-to-apply/e4-dtp-projects

References

Most of the following articles can be found online using the DOI provided. If you cannot access some of them through your university, feel free to contact glatombe@ed.ac.uk.
- Parker et al. (1999) introduces and discusses the original impact formula:
Parker, I.M., Simberloff, D., Lonsdale, W.M., Goodell, K., Wonham, M., Kareiva, P.M., Williamson, M.H., Von Holle, B.M.P.B., Moyle, P.B., Byers, J.E. & Goldwasser, L. (1999). Impact: toward a framework for understanding the ecological effects of invaders. Biological invasions, 1(1): 3-19. DOI: 10.1023/A:1010034312781
- Latombe et al. (2022) generalises the original formula and presents an approach to quantify per-unit effects:
Latombe, G., Catford, J. A., Essl, F., Lenzner, B., Richardson, D. M., Wilson, J. R., & McGeoch, M. A. (2022). GIRAE: a generalised approach for linking the total impact of invasion to species' range, abundance and per-unit effects. Biological Invasions, 1-21. DOI: 10.1007/s10530-022-02836-0
- This paper present the main findings from the InvaCost database:
Diagne, C., Leroy, B., Vaissière, A.C., Gozlan, R.E., Roiz, D., Jarić, I., Salles, J.M., Bradshaw, C.J. & Courchamp, F. (2021). High and rising economic costs of biological invasions worldwide. Nature, 592(7855): 571-576. DOI: 10.1038/s41586-021-03405-6

- These papers present the sPlotOpen database:

Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B. & Aubin, I. (2019). sPlot–A new tool for global vegetation analyses. Journal of Vegetation Science, 30(2): 161-186. DOI: 10.1111/jvs.12710
Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F. & Jiménez‐Alfaro, B. (2021). sPlotOpen–An environmentally balanced, open‐access, global dataset of vegetation plots. Global Ecology and Biogeography, 30(9): 1740-1764. DOI: 10.1111/geb.13346

- This paper presents a framework to explain impacts from species and environmental characteristics:

Thomsen, M. S., Olden, J. D., Wernberg, T., Griffin, J. N., & Silliman, B. R. (2011). A broad framework to organize and compare ecological invasion impacts. Environmental research, 111(7), 899-908. DOI: 10.1016/j.envres.2011.05.024

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