Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature

[12–14]. Climate models couple Earth system components like ocean and terrestrial systems with atmospheric dynamics, in order to project future temperature, precipitation, and other variables [15–20]. These model dynamics respond to atmospheric GHG concentration, the roots of which are human activities like fossil fuel usage and deforestation. These models typi- cally assume a fixed trajectory for future GHG emissions as a model input, based on assump- tions about socio-economic development. However, GHG emissions are not fixed but rather they increasingly respond to climate change, as a result of the response from human popula- tions and institutions [21–23]. Human perceptions of climate change, variation in individual behavior driving climate change, and human responses and adaptation strategies are recognized as the three key aspects of human behavioral changes in response to climate change [23]. Human beings recognize and adapt to climate change based on personal experience [24, 25], for instance, individuals living in places with increased temperatures are more likely to perceive climate change than others [22]. This observation suggests that human behavior and climate change are connected into a single coupled human-environment system [26, 27]. Changes in individual behaviors could also contribute to climate change mitigation strategies [27, 28]. Behavioral change alone can lead to significant reduction in emissions [29]. With monetary incentives and feedback, around 0.35 GTCO2 per year reduction in emission levels can be observed from the residential

sector alone [30, 31]. A study regarding potential behavioral changes on climate change in the European Union further establishes the importance of including human behavior: changes to dietary habits, mobility, and household can reduce the emission levels by 6% to 16% leading to a decrease of 13.5% to 30% reduction mitigation costs [32]. These findings underscore the importance of population behavioral transitions in climate change mitigation, which leads to substantial reduction in emissions. Coupled socio-climate models have been gaining importance due to the growing recogni- tion of the role of social processes. Such models have demonstrated the enormous influence of social norms and social learning on temperature projections [27, 33]. These models act as tools to understand the feedback loops between climate and human systems. Several behavioral the- ories could be potentially used in the coupled model [34–36]. Models involving frameworks for representing processing, spreading, and behavioral responses considering the heteroge- neous nature of society have also been developed recently. Qualitative insights on socio-cli- mate models portray the importance of social learning, and the associated cost for mitigation [27]. By combining an Earth System Model with a social dynamics model, Bury et al. [27] observed that increasing social learning and reducing mitigation costs is the most efficient way to reduce global temperature anomalies. These models also help to analyze how different groups in a heterogeneous population respond and evolve [37].

Several models have coupled climate dynamics and economic processes. For instance, inte- grated assessment models (IAMs) couple climate dynamics and economic processes by incor- porating economic feedback in agriculture and energy expenditures [38, 39]. Dynamic Integrated Climate Economy (DICE) models couple climate change and economies with a focus on mitigation costs [40, 41]. However, human attitudes towards climate change could be influenced by the social, religious, or political views in the population [42, 43]. Therefore, models that also include other relevant human processes–like social dynamics–are required for a more comprehensive picture. Machine learning models are also gaining popularity in studying climate systems to predict temperature and precipitation [44]. Various rumor propagation models have been developed and analyzed in different domains. Rumor propagation models inspired by compartmental models are not new [45–47]. Due to the similarities between disease spread and rumor propagation in a population, rumor propagation models are sometimes constructed using mathematical epidemiology [48]. They PLOS ONE Climate-denying rumor propagation in a coupled socio-climate model: Impact on average global temperature PLOS ONE | https://doi.org/10.1371/journal.pone.0317338 January 16, 2025 2 / 18 decision to publish, or preparation of the manuscript. Competing interests: On behalf of all authors, the corresponding author states that there is no conflict of interest.