Climate change predictions are influenced by social learning

June 6 (UPI) — Using a new climate model, scientists have identified the influence of social learning and social norms on climate change.

Climate change is caused by humans. And if climate change is to be slowed or stopped, it will require human action. Climate systems and human systems are intimately linked, and yet, little is known about the interactions between these systems.

To better understand how social phenomena impacts climate change, and vice versa, researchers in Canada developed a mathematical model that approximates key features of social and climate systems.

Their model showed that people adopt climate mitigation strategies through social learning. Over a long enough period of time, social learning patterns can inspire significant changes in human behavior — purchasing an electric or hybrid car, for example.

Unfortunately, social norms have the opposite effect. Social norms reinforce the behavioral patterns of the majority — currently, inaction. Even once mitigation becomes the norm, the new model showed social norms will do little to hasten the transition to a carbon-zero economy.

Researchers also used their model to identify ways to encourage climate-friendly behavior.

“Our socio-climate model indicates that an increase in social media and other campaigns to raise awareness, such as climate marches and international reports, should ideally be followed by governmental and other incentives to reduce carbon emissions,” Thomas Bury, researcher at the University of Waterloo, said in a news release.

Bury and his research partners described their modeling efforts this week in the journal PLOS Computational Biology.

“There are pathways for humans to mitigate climate change, but processes driving behavior and norms at the individual and societal level will be essential to all of them, and our longstanding work on coupled human-environment systems applied here to climate change is providing direction in this regard,” researcher Madhur Anand said.