Boundary Chain Model
Informed by social science research and tested through GLISA’s applied practice, the boundary chain model relies on existing knowledge networks to pass pertinent climate information to stakeholders and information end-users. Through the boundary chain model GLISA is able to multiply its reach across numerous sectors and communities. In addition to the boundary chain model increasing the reach of GLISA information, the model also ensure that knowledge from partner boundary organizations flows back to GLISA and informs the social and physical science needs of the region.
To learn more about the GLISA approach for fostering networks around climate adaptation knowledge, read the publication by former GLISA Program Manager David Bidwell and GLISA Co-Investigators Don Scavia and Tom Dietz: Fostering knowledge networks for climate adaptation in Nature Climate Change.
For more on the boundary chain model see GLISA Co-Director Maria Carmen Lemos’ 2014 paper:
Moving climate information off the shelf: Boundary Chains and the role of RISAs as adaptive organizations.
Integrating Local and Historical Climate Data
Local climate information forms the backbone of the resources that GLISA provides to its boundary organization partners and stakeholders throughout the region. GLISA provides local historical climate data at two resolutions: the regional scale and at the local weather station specific scale. By leading with historical climate information and demonstrating climate changes over the past several decades (typically over the past 60 years, comparing 1951 – 1981 and 1981 – 2010) GLISA is able to build confidence and trust by adding quantitative data to the subjective feelings people hold about the changing climate in their community or region.
Uncertainty and Downscaling
As the Great Lakes drive our regional economy and culture, they also are a driving force on our climate. Given the presence of this unique element acting on the climate of the region, GLISA strives to inform stakeholders on how to leverage existing downscaled climate information and how to understand the benefits and risks from using available global and regional models. GLISA staff and researchers also work to illustrate the differences between uncertainty and climate variability and how to cope with each of these challenges in decision making processes.
Understanding how knowledge moves across networks is critical to GLISA’s work and essential when employing the boundary chain model. GLISA social scientists have studied how knowledge moves across the region via climate-related documents, events, and individuals, in order to better understand where we can intersect these networks to inform broader audiences. Recent findings point to GLISA playing a crucial role in the scaling information across scales of government and ensuring that federal agencies and local actors are able to learn from one another and share experiences and knowledge to continue building climate ready sectors and communities across our region.
For more on the evolution of knowledge networks across the Great Lakes region and how GLISA is playing a role in scaling across scales see:
Frank, K., I. Chen, Y. Lee, S. Kalafatis, T. Chen, Y. Lo, and M. Lemos., 2012. Network Location and Policy-Oriented Behavior: An Analysis of Two-Mode Networks of Co-Authored Documents Concerning Climate Change in the Great Lakes Region. Policy Studies Journal. 3, 492-515.