Dynamic system strategies for climate social tipping points

Society is currently struggling to manage a complex set of socio-ecological challenges related to climate change. Solutions

range from reducing our consumption to novel technology used to decouple the economy from its impacts. Regardless of the

strategy, materialising the green transition into a low carbon society means crossing a social tipping point (STP).

An STP occurs when the collective action of a population reaches leads to wide-ranging systemic change. STPs can be

triggered by bottom-up approaches like consumer boycotts, or top-down interventions like policies, tax disincentives, and

trade agreements. The problem is that, so far, STP have only been described qualitatively and the mechanisms beyond their

emergence remain poorly understood.

The overall project goal is to provide a deeper understanding of which types of change allow society to move towards a more

sustainable status, specifically by unveiling the role of social tipping points in reaching sustainability.

I intend to use system dynamics (SD) to study social tipping points quantitatively. SD is a modelling approach to simulate

feedback loops between variables in a system. SD is a perfect fit to the quantitative study of STPs for two reasons. First, it is

a flexible tool to model coupled human and natural systems (CHANS), whereby ecological processes exhibit changes over

time under the influence of human drivers. Second, it allows one to determine when changes in elements of the system lead

to the crossing of a tipping point and to a different system configuration.

My combined expertise in CHANS and SD, supported by my supervisor’s background in sustainability assessment make us

an ideal team to conduct this research. Not only that, this fellowship will improve my research profile providing a steppingstone

towards my career goals.