Accurately predicting how species, ecological communities and ecosystems will respond to climate change remains one of the biggest challenges in ecology and conservation. While some ecosystems have shown strong responses to climate change, with rapid turnover in species, others have shown relative stability1,2. The unpredictability of this variation in different levels of responses to climate change presents a significant challenge for conservation. Without adequate understanding about how species and ecosystems will respond to climate change, effective targeting of conservation efforts towards high-risk areas becomes difficult. Here, the successful candidate will develop and test a generalisable framework for predicting how species, ecological communities and ecosystems respond to climate change. This information can help predict climate change impacts on biological systems and inform conservation decision making.
Within this framework, we predict that the strength of species responses to climate change will depend on relative positions within the species range: populations at the edge of a species range are expected to show strong responses, whereas populations central to the species range are expected to show weak responses. These drivers of climate change responses are expected to be applicable to a wide range of taxa, thus giving a generalisable framework for forecasting and mitigate biodiversity-wide effects of climate change.
Within this PhD project, the successful candidate will:
1. Use individual based modelling (IBM), using the modelling platform, “Rangeshifter”, to gain a greater understanding of the behaviour of populations at differing positions of a species range under climate change. Within this component, the student will explore the role of range size, rate of climate change, local adaptation, and species interactions in influencing the rate of population changes to climate change.
2. Estimate rates of population change for multiple species across a wide range of taxa, including plants, invertebrates, and mammals, using survey data from partner organisations and publicly available records data. Such datasets can allow the testing of how applicable the theoretical framework is at predicting across all of biodiversity.
3. Using two plant community model systems, calcareous grasslands, which are known to exhibit relative stability in the face of climate change2, and oceanic montane ecosystems, know to rapidly respond to climate change1, the student will generate temperature-response curves for a suite of 15 species, from each ecosystem (30 species total). These response curves will allow the student to understand why each system has differing susceptibility to climate change and forecast how each study species is expected to respond to climate change.
4. Establish two mesocosm experiments, which will be transplanted across thermal gradients to test the accuracy of the predictions from objective two. By growing plants in both monoculture and mixed species mesocosms, the student will test ecological responses to climate change at different hierarchical levels of biological organisation, gaining insight into how individual responses to climate change scale to ecosystem wide responses.
The PhD student will join our flourishing School of Biological & Environmental Sciences, at Liverpool John Moores University and work under the supervisory team of Dr Rob Fitt, Dr Sarah Dalrymple & Dr Danni Hinchcliffe.
1. Grime, J.P., Fridley, J.D., Askew, A.P., & Bennett, C.R. (2008) Long-term resistance to simulated climate change in an infertile grassland. PNAS. 105 (29) 10028-10032. doi.org/10.1073/pnas.0711567105
2. Hodd, R.L., Bourke, D., , Sheehy Skeffington, M. (2014) Projected Range Contractions of European Protected Oceanic Montane Plant Communities: Focus on Climate Change Impacts Is Essential for Their Future Conservation. PLOS ONE, doi.org/10.1371/journal.pone.0095147