PhD: A metabolic theory of deep-sea ecology

A metabolic theory of deep-sea ecology

Dr Brian BettDr Daniel JonesDr Adrian MartinDr Sven ThatjeDr Henry Ruhl.



University of Southampton

National Oceanography Centre Southampton

United Kingdom



The Metabolic Theory of Ecology (MTE, Brown et al., 2004) provides a mechanism for linking the biology of individual organisms to the ecology of populations, communities and ecosystems (Sibly et al., 2012). The MTE appears to have practical application in benthic ecology (Bett, 2013) and deep-sea biology. It is an approach that may prove to be particularly valuable in the biogeochemical modelling of seafloor systems and it may be important in assessing the potential impacts of climate change and other human interventions in deep-sea ecosystems. Interestingly, however, it cannot explain the full range of variation observed, and mechanisms like those that relate to niche-theory also have clear importance. The MTE may be used to a number of ends: (i) to form testable hypotheses, (ii) to assist in the interpretation of existing field data, and (iii) to make various forms of prediction to test the limits of MTE as a theoretical framework.

The successful candidate will explore hypotheses surrounding the premise that explicit temperature- and mass-scaling of biological processes can significantly improve our current understanding of the macroecology of marine benthic systems.



This project will initially focus on the improved interpretation of field data, and as such will not be limited by ship-time availability or successful field campaigns (although it is expected that sea-going experience and field data generation will be offered as a component part of the training within this project). For example, existing large datasets could be significantly reinterpreted by application of MTE concepts.

A key second component of the project will be to further develop the MTE, and related approaches, to consider temporal variation, particularly in resource supply (e.g. particulate organic carbon flux). As presently implemented, the MTE typically deals with the ‘steady state’ condition of ‘climax communities’. The addition of temporal variation in resource supply and other environmental factors will substantially broaden and improve the practical application of this approach. For example, the steady state benthic body-size model developed at NOC could be importantly expanded to incorporate temporal variation in organic matter supply.

The project will involve substantial data manipulation, analysis, and modelling components. The successful candidate will, therefore, require good basic mathematical skills and the ability to apply them efficiently (i.e. coding in appropriate software environments).



All doctoral candidates will enrol in the Graduate School of NOCS (GSNOCS), where they will receive specialist training in oral and written presentation skills, have the opportunity to participate in teaching activities, and have access to a full range of research and generic training opportunities. GSNOCS attracts students from all over the world and from all science and engineering backgrounds. There are currently around 200 full- and part-time PhD students enrolled (~60% UK and 40% EU & overseas).

The studentship is eligible for inclusion within the NERC SPITFIRE Doctoral Training Partnership (DTP). The SPITFIRE DTP programme provides comprehensive personal and professional development training alongside extensive opportunities for students to expand their multi-disciplinary outlook through interactions with a wide network of academic, research and industrial/policy partners. The student will be registered within the Graduate School of NOCS (GSNOCS). Specific training will include: quantitative benthic biology / ecology (in temporal and spatial domains); ecological theory and model development; practical deep-sea sampling and observation. The student will participate in ocean-going cruises to collect material, and will be trained in the collection of deep-sea samples. The student will learn sampling design methods that will allow quantitative analysis to identify possible temporal and / or spatial patterns and ultimately test hypotheses. The training will also include statistical analysis of research results. Research results obtained will be presented at international conferences, and ultimately be written up for publication in peer-reviewed journals.


Wider Implications: 

Metabolism is a strong factor in explaining how communities are assembled, but has yet to be fully examined in a dynamic benthic framework. Consideration of the MTE and niche theory from a more dynamic time- and space-perspective is expected to help reconcile aspects of each theory and it will be used to help understand observations, where steady state theories are too often tested within systems undergoing change. Since this project will inform us on the links between these theories for deep-sea benthic communities, the results will serve the interests of scientists, marine policy makers and conservation groups. The proposed research will help us understand anthropogenic impacts on benthic ecosystems and will allow us to focus future research on the consequences of change in the ocean.


Eligibility & Funding Details: 

This SPITFIRE project is open to applicants who meet the SPITFIRE eligibility criteria, alongside other exceptional applicants. 

Check your eligibility and find information on how to apply please click here.

UK applicants and EU students who meet the RCUK eligibility criteria please apply to SPITFIRE

Non SPITFIRE eligible applicants please apply to GSNOCS

Please make sure you apply to the correct programme as applications to SPITFIRE from non-eligible applicants will be rejected automatically.


Background Reading: 

1. Bett BJ (2013) Characteristic benthic size spectra: potential sampling artefacts. Marine Ecology Progress Series 487, 1-6.

2. Brown JH, Gillooly JF, Allen AP, Savage VM, West GB (2004) Toward a metabolic theory of ecology. Ecology 85, 1771-1789.

3. Peters RH (1983) The ecological implications of body size. Cambridge, Cambridge University Press.

4. Sibly, RM, Brown, JH, Kodric-Brown, A (2012) Metabolic ecology: a scaling approach. Chichester, Wiley-Blackwell.