Project highlights

  • Addresses fundamental knowledge gaps in the relationship between soil communities and ecosystem multifunctionality.
  • Gains new insights from tightly controlled mesocosm experiments under disturbance events related to climate change.
  • Employs a coupled empirical-modelling approach to develop a novel modelling framework for predicting the stability of soil communities and functions under climate change.

Overview

Soil communities play important roles in multiple ecosystem functions, including carbon and nitrogen cycling. Divergent shifts in soil community composition under climate changes could therefore have dramatic consequences for ecosystem service provision. Yet, we know little about the functional role of different soil community groups, their varying abilities to resist and recover from disturbances, and how shifts in community composition influences ecosystem functions.

This project will use experiments to develop a novel framework for predicting the stability of soil communities and functions under climate change. The framework accounts for high functional redundancy in soil systems, by characterising soil communities according to broad functional traits, and will elucidate the functional role of each group under control, soil warming, drought, and flood treatments. The central hypothesis tested is that the functional traits of soil community groups strongly influence both soil community and ecosystem function responses to climate change related stressors.

This new process-based understanding of the links between soil communities and functions will be translated according to fundamental principles from ecological theory and integrated in a mechanistic agent-based model (ABM). The ABM then allows us to determine how functional group responses shape ecosystem multifunctionality, and the interactive effects of disturbance events related to climate change on the stability of soil communities and functions (Figure 1). Importantly, the ABM forms a basis for better anticipating how the interplay between soil communities and functions drive ecosystem resilience under climate change in the future.

 

Host

Cranfield University

Theme

  • Climate and Environmental Sustainability
  • Organisms and Ecosystems

Supervisors

Project investigator

  • Alice Johnston, Cranfield University

 

Co-investigators

  • Nick Girkin, Cranfield University
  • Jacqueline Hannam, Cranfield University

How to apply

Methodology

The PhD project will follow a structured methodology, outlined below.

1) Review the literature on soil community and ecosystem multifunctionality metrics to identify up to six functional groups (e.g. bacteria, fungi, micro-predators, litter transformers, ecosystem engineers).

2) Conduct mesocosm experiments in control and soil warming, flood, and drought conditions, removing functional groups from the soil community one at a time. Ecosystem function metrics will be recorded over time, and the control mesocosms used to infer trait-function relationships for the soil community groups.

3) Test the applicability of fundamental principles from ecological theory to develop functional responses for the soil community groups.

4) Integrate the functional responses within an ABM and set up the ABM to replicate the mesocosm experiments.

5) Use the ABM to test and determine the mechanisms linking climate-induced shifts in soil community composition to ecosystem multifunctionality over time.

6) Communicate research in journals with the widest readership.

Training and skills

Specific opportunities available to the student include training in conducting laboratory-based mesocosm experiments, individual-based modelling, Netlogo programming, and R statistical software at Cranfield University. Training will be provided both by the supervisory team and using CENTA training courses. The student will also be encouraged to gain broader skills, for instance in project management and knowledge transfer, which will benefit the students career development.

Partners and collaboration

Project collaborations will be sought from the Bomford Trust and other relevant partners.

Further details

We encourage applications from environmental and/or quantitative disciplines, with a minimum 2:1 or equivalent post-graduate work experience. We particularly welcome applications from diverse and under-represented backgrounds and can offer flexible working arrangements.


Dr Alice Johnston, Lecturer in Environmental Data Science

Centre for Environmental & Agricultural Informatics

Blg 53, School of Water, Energy and Environment

Cranfield University, Bedfordshire MK43 0AL

E: a.s.johnston@cranfield.ac.uk

 

To apply, the Cranfield web address is:

https://www.cranfield.ac.uk/research/phd/predicting-the-stability-of-soil

Possible timeline

Year 1

Conduct a systematic literature review of soil community and ecosystem multifunctionality observations to classify soil communities according to key functional groups. The review will form the basis of the student’s thesis and will be written up as a meta-analysis study. For the paper, training in R statistical software will be required and training in paper writing will be encouraged. Plan the field collection and mesocosm experimental setup, and ensure all equipment is available/has been acquired.

Year 2

Conduct all mesocosm experiments: in control, soil warming, drought, and flood conditions. Each experimental treatment should take around 12 weeks to complete, resulting in around 48 weeks of experimental work. The control treatment will be conducted first, and preliminary work on translating the trait-function relationships according to fundamental principles of ecological theory will begin. All experimental data should have been compiled by the end of the year.

Year 3

The first 6 months will be dedicated to developing the functional responses for each soil community group, learning Netlogo programming and writing the R-Netlogo code to develop the ABM. The remaining 6 months will use the ABM to test and determine the mechanisms linking climate-induced shifts in soil community composition to ecosystem multifunctionality over time. This process will be streamlined by using an Approximate Bayesian Computation (ABC) approach and Cranfield University’s high-performance computer. By the end of the year all model simulations should be complete.

Further reading

Wagg, C. et al. (2014) ‘Soil biodiversity and soil community composition determine ecosystem multifunctionality’, Proceedings of the National Academy of Sciences of the United States of America, 111(14), pp. 5266–5270. doi: 10.1073/pnas.1320054111.

Yang, G. et al. (2018) ‘How Soil Biota Drive Ecosystem Stability’, Trends in Plant Science, 23(12), pp. 1057–1067. doi: 10.1016/j.tplants.2018.09.007.

Guerra, C. A. et al. (2020) ‘Blind spots in global soil biodiversity and ecosystem function research’, Nature Communications, 11(1), p. 3870. doi: 10.1038/s41467-020-17688-2.

COVID-19

The research in this project would be impacted by the ongoing Covid-19 pandemic at the initial stage where the field collection of soils and mesocosm experiments are proposed. For instance, if access to field sites and laboratory space is not permitted. Current restrictions represent a minor risk but if tighter restrictions are imposed then samples spanning a range of ecosystems can be provided through our collaborative networks as a contingency.