Steven M. Ramsey | USGS Science

USGS2022

Local environment and individuals’ beliefs: The dynamics shaping public support for sustainability policy in an agricultural landscape

Agricultural landscapes are the bleeding-edge in the advancement of sustainability and climate change adaptation. Our study focuses on how individual support for sustainability policy is shaped in coupled natural and human systems. We present an agent-based model in which a cultural decision-rule quantifies the probability that a stakeholder decides to support an easement policy for a region in the Central Great Plains, USA. Our model defines a cultural threshold used to assess how culturally meaningful the policy is for each stakeholder. The individual cultural threshold is estimated using the value-belief-norm framework and is modified by perceived changes in the environment. Results demonstrated that few stakeholders support the policy in the average cultural setting (8.9%). However, enough stakeholders would support the policy under a lower cultural threshold (40.7%). Our results indicate that sustainability policies do not need to be cheap if they are culturally meaningful.

Kansas↗

USGS2019

Evaluating environmental change and behavioral decision-making for sustainability policy using an agent-based model: A case study for the Smoky Hill River Watershed, Kansas

Sustainability has been at the forefront of the environmental research agenda of the integrated anthroposphere, hydrosphere, and biosphere since the last century and will continue to be critically important for future environmental science. However, linking humans and the environment through effective policy remains a major challenge for sustainability research and practice. Here we address this gap using an agent-based model (ABM) for a coupled natural and human systems in the Smoky Hill River Watershed (SHRW), Kansas, USA. For this freshwater-dependent agricultural watershed with a highly variable flow regime influenced by human-induced land-use and climate change, we tested the support for an environmental policy designed to conserve and protect fish biodiversity in the SHRW. We develop a proof of concept interdisciplinary ABM that integrates field data on hydrology, ecology (fish richness), social-psychology (value-belief-norm) and economics, to simulate human agents' decisions to support environmental policy. The mechanism to link human behaviors to environmental changes is the social-psychological sequence identified by the value-belief-norm framework and is informed by hydrological and fish ecology models. Our results indicate that (1) cultural factors influence the decision to support the policy; (2) a mechanism modifying social-psychological factors can influence the decision-making process; (3) there is resistance to environmental policy in the SHRW, even under potentially extreme climate conditions; and (4) the best opportunities for policy acceptance were found immediately after extreme environmental events. The modeling approach presented herein explicitly links biophysical and social science has broad generality for sustainability problems.

Kansas↗