Abstract:
Climate change is predicted to change the distribution of species worldwide. Predictive models are required to help forecast these ecosystem responses. However, to build such models, the mechanisms behind the ecological and evolutionary dynamics of species distributions need to be better understood. One central driver and modulator of eco-evolutionary dynamics is temperature and its changes due to human impacts, for example. Yet, temperature dependence of ecological and evolutionary processes is often modelled in very simplified ways with unrealistic assumptions. To build a more productive theory of the temperature impacts in ecology and evolution, I take a bottom-up approach, integrating molecular mechanisms and large-scale population dynamics: I study how different assumptions of protein level dynamics that constrain thermal evolution may scale up to the macroecological level and change range dynamic predictions. Importantly, this mechanistic approach allows me to include likely targets of selection and model feedback with the evolutionary dynamics of local adaptation of the thermal performance curve (TPC) and dispersal. I build an individual-based metapopulation model of range expansion along a temperature gradient. Using three
different models of thermal adaptation at the protein level, I show the importance of the
mechanism considered under selection in determining range expansion trends. The TPCs described by protein thermal stability are more flexible and lead to accelerated expansion along an increasing temperature gradient. While TPCs described by enzyme-substrate re-action rates are much less flexible and lead to much slower expansion. Overall, my project shows the importance of defining TPCs realistically and its large-scale consequences.
