Some like it hot? How do Antarctic species and ecosystems respond to global warming?
Supervisors: Professor Bill Amos (Department of Zoology); Dr Pietro Lio’, UCam (Computer Lab, firstname.lastname@example.org); Dr Melody Clark (BAS, email@example.com) Prof Lloyd Peck, (BAS, firstname.lastname@example.org)
Understanding species’ responses to environmental change underpins our abilities to predict future biodiversity and the state of ecosystems under any range of scenarios. This is particularly important in global regions undergoing rapid warming, with fragile ecosystems, such as the poles. Detailed evaluations are best achieved at the molecular level, by understanding which biochemical pathways are most affected by changing conditions and then evaluating impacts on whole animal resilience or sensitivity (Clark et al. (2016) Global Change Biology DOI: 10.1111/gcb.13357). This proposal, using a multiple species approach with extensive ecological metadata on the chosen species (Peck et al. (2009) Functional Ecology, 23, 248) will enable predictive, mechanistic evaluations of responses to climate change from cellular to macroscopic scales, including ecosystems' and global scales. The aim is for the analyses to take recent the contributions of theoretical computer science to life sciences, drawing on biophysics and biomathematics to develop predictive scenarios for Antarctic ecosystems under threat (cf. Angione et al. (2016) BMC Bioinformatics, 17, 257).
This project will characterise underlying cellular mechanisms of responses to warming in Antarctic marine species and use these as proxies for predicting ecosystem resilience using modelling approaches. We will use transcriptomic data to test the hypothesis that the current overarching paradigms on sensitivity to changing conditions (e.g. oxygen limitation, conserved stress response, accumulation of toxic oxidised proteins etc.) do not universally apply across species and stressors. We propose that responses to change are species and context-specific, that this approach allows us to identify biochemical pinch-points in each species, and population level variability of these genes impacts levels of phenotypic plasticity.