This work represents an interdisciplinary collaboration among Paige Fischer (project leader), with training in sociology and human geography; Seth Guikema, an engineer with expertise in climate-driven hazards and human decision-making regarding risk; Gretchen Keppel-Aleks, a climate scientist at UM Climate and Space Sciences and Engineering, who focuses on modeling climate impacts on vegetation including forests modeling; Matt Hamilton, who has expertise in environmental policy and climate change adaptation; and Bill Currie, a landscape ecologist and ecosystem modeler.
It is well-known that climate change is a pressing global concern that may cause large-scale adaptation or changes in human choices, behaviors, and activities. It is also well-known that Earth System Models are widely used to forecast future climate change, including projections made by the Intergovernmental Panel on Climate Change (IPCC). Typically, these climate modeling activities and projections begin with a set of narrative storylines about plausible future trends in socioeconomic drivers over the next 30 to 100 years. These alternative futures, or scenarios, include plausible trends in economic growth, international relations, and technological development. Once fixed, the scenarios are used to drive Earth System / climate models that include dynamic responses in vegetation, oceans, and the atmosphere. However, these models do not include dynamic adaptation in human choices, actions, and behaviors that could feed back to have significant impacts on the management of terrestrial ecosystems and landscapes — including adaptation to rising temperatures, or changes in ecological disturbance regimes including droughts, patterns of wildfire occurrence or insect outbreaks. These types of disturbances are expected to increase with climate change. Humans will likely adapt to these disturbances by changing their management or agricultural practices, which would then affect the way that vegetation functions in the Earth System over large spatial scales and decadal to century time scales — something not accounted for in climate models.
In 2017 we received a small grant from the Graham Sustainability institute to form this interdisciplinary team to do a pilot study addressing this question: How can information about human behavior improve climate impact models to inform decision-making regarding adaptation?