Dr Ashish Malik - University of Aberdeen, School of Biological Sciences - firstname.lastname@example.org
Dr Eric Paterson - The James Hutton Institute, Ecological Sciences - email@example.com
Dr. Thomas Vogwill - University of Aberdeen, School of Biological Science - firstname.lastname@example.org
Soils harbour an immense diversity of microorganisms that are critical to ecosystem functioning. Microbial communities in soil are significant drivers of soil carbon cycling – they control the fate of recent plant carbon inputs and determine the stability of assimilated carbon. Our work has shown that higher microbial growth yield, with a greater proportion of substrate allocated to biosynthesis, increases the ability of communities to store carbon in soils1. We also know that soil abiotic factors such as moisture levels and resource availability can affect microbial growth yield and hence carbon sequestration. However, the role of biotic interactions within microbial communities in determining carbon cycling rates has not been explored.
Land use has a big impact on microbial diversity and functioning in soil. In lower land use intensity soils, higher water holding capacity and greater availability of resources leads to higher microbial density, higher functional diversity and greater microbial biomass. With the greater connectivity of microbial habitats there is a greater probability of microbial interactions in less intensive soil communities than in those from higher intensity land use. Biotic interactions among individuals can range from defence, antagonism and competition, to cell signalling, co-metabolism and symbiosis. On the contrary, resource limitation and higher turnover in communities in high intensity land use may lead to competition and antagonism between community members. How these interactions influence community dynamics and ecosystem processes has not been understood2.
The project aims to understand the role of different microbial interactions in driving carbon cycling processes in soils using a combination of field assessment and targeted lab experiments. The differences in microbial density and diversity across land use intensity gradients will be used to study co-occurrence of microbial species which is an indication of microbial interactions. These will be further tested using lab mesocosm experiments. Communities with different microbial density and diversity3 will be inoculated into microbe-free model soil. Time-resolved network analysis of species co-occurrence will be performed in the assembled communities and these will be linked to C cycling rates to infer ecosystem implications. Further lab experiments will be performed which will use different combinations of cultured microbes to study interactions on common substrates and rates of organic matter decomposition.
Research methods and training:
Changes in microbial community structure and functions in field and experimental soils will be measured using amplicon and shotgun metagenomic sequencing. Taxonomic and functional classification will be performed using established pipelines. Bioinformatics support will be available to the student through the supervisors. 13C-labelled plant organic matter will be used as a substrate in lab experiments to monitor decomposition rates. Such a combination of genomic sequencing and isotopic approaches in field and lab experiments will allow the student gain a range of unique technical skills.
It may be possible to undertake this project part-time, in discussion with the lead supervisor, however, please note that part-time study is unavailable to students who require a Student Visa to study within the UK.
Please visit this page for full application information: http://www.eastscotbiodtp.ac.uk/how-apply-0
Please send your completed EASTBIO application form, along with academic transcripts to Alison Innes at email@example.com
Two references should be provided by the deadline using the EASTBIO reference form.
Please advise your referees to return the reference form to firstname.lastname@example.org
Unfortunately due to workload constraints, we cannot consider incomplete applications