Quantifying uncertainty of marine ecosystem responses to climate change

Supervisors: Dr Julia Blanchard, Professor Mat Collins (University of Exeter), Kieran Hyder (Cefas) & Dr Tom Webb

Predicting the consequences of changes in the physical environment and potential food availability for fish and fisheries, when many detailed aspects of species’ ecological and physiological constraints are not known, is challenging. Different food web modeling approaches of ecosystems have been developed to link physical and biogeochemical processes to ecological processes. These range in complexity from simple species bioclimate envelope modeling (Cheung et al. 2010, Global Change Biology 16:24-35) and size-based food web models (e.g. Blanchard et al. 2012, Phil Trans Roy Soc 367:2979-2989) to multi-species and complex ‘whole of ecosystem’ models (Fulton et al. 2011 Fish Fish 12: 171–188). The latter are limited in their capacity to resolve global-scale questions, due to high data demands and do not yet account for invasions or spatial re-distributions of new species from adjacent regions, whereas the former do not resolve the detailed species-level interactions that will be important for regional fisheries management.

Relatively little work has been done to put these different models and their predictions into a framework to quantify uncertainty or assess if additional complexity actually leads to a better prediction, as is commonly done in other fields (e.g. climate predictions). Multi-model ensembles also enable a range of plausible projections to be considered alongside each other (Collins et al. 2012 Nature Climate Change 2:403–409).

Using an ensemble approach this PhD will develop techniques to:

1. Quantify uncertainties in projections by combining information from models, understanding and records of past change
2. Establish the skill of alternative (species- and size-based) models for predicting changes in the ecological properties of marine communities and fisheries across different temporal and spatial scales
3. Determine whether alternative processes nested within models helps to improve uncertainty

The project will help to improve knowledge of uncertainty for future projections of climate change on large marine ecosystems and global fisheries. It will use global oceanographic and fisheries datasets as well as detailed long-term historic time series available from the North Sea. This project offers a unique opportunity to work with quantitative marine ecologists, climate scientists and fisheries scientists. The PhD student will ideally have strong quantitative skills with computer programming experience. The student will be based in the Dept. of Animal & Plant Sciences, Sheffield but with opportunity to spend significant time at University of Exeter and Cefas. Funding is available for 3.5 years beginning from March 2013.

To apply, please complete an online application form which can be found at www.shef.ac.uk/postgraduate/research/apply/applying
The closing date is 15 January 2013