Enhancing Autonomy for Climate Change Adaptation Using Participatory Modeling

Abstract

AbstractParticipatory modeling is commonly applied in climate change adaptation research to integrate stakeholder knowledge, beliefs, values, and norms into modeling processes. However, participation is not neutral, and current climate change adaptation research is tailored toward those with sufficient resources to adapt, as opposed to those most in need of adaptation. These are commonly marginalized stakeholder groups who remain on the social, economic, and political periphery, driving their vulnerability to climate change impacts. This paper presents the concept of autonomy in the context of multilevel governance for climate change adaptation before examining past participatory modeling approaches, illustrating the lack of application as an emancipatory tool for increasing the autonomy of marginalized stakeholder groups. Therefore, a list of 10 necessary conditions is presented for conducting participatory modeling for increasing the autonomy of marginalized stakeholder groups, strengthening multilevel governance for climate change adaptation. These theoretical foundations are intended to guide public policy and increase the societal impact of participatory modeling.Significance StatementResponding to climate change impacts requires the strengthening of multilevel governance. An important aspect is that multilevel governance is dependent on local actors having sufficient autonomy to carry out climate change adaptation actions. Participatory climate change adaptation research can contribute to enhancing autonomy for climate change adaptation in applying participatory modeling. This paper explains why this is important, how participatory modelers need to design their research, and in what way this could contribute to strengthening multilevel governance and the wider societal response to climate change impacts.If you’re a scholar who studies the social impacts of climate change and you aren’t somehow an activist what are you really?—Professor Kian Goh, University of California, Los Angeles