Category: Ecology of Games

by Tara Pozzi, Mark Lubell, Tanya Heikkila, Andrea K. Gerlak, & Pamela Rittelmeyer

Science enterprises play an increasingly important role in shaping the policy process. While existing literature explores the nexus of science and decision-making, research is limited by a lack of empirical institutional analysis—specifically how science is shaped by and a feature of governance institutions. To address this gap, we integrate the ecology of games framework (EGF) and collective learning framework (CLF) to examine how polycentric systems of science actors and forums influence policy-relevant learning. This exploration is guided by three types of hypotheses to account for diverse actors:

1.  Individual-level hypotheses consider how organizational affiliation, professional involvement, forum participation, and expertise on diverse issues of individual actors participating in a science enterprise may shape perceived learning.
2. Forum-level hypotheses consider how variance in forum social dynamics, institutional structure, and functional domain characteristics may shape perceived learning.
3. The learning stage hypothesis suggests that the perceived level of learning will be lower at later stages of the adaptive management cycle.

In 2021, we conducted a survey of science actors involved in managing and governing the California Delta. The survey participants were individuals who produce, interpret, or use science for Delta policymaking, including academics, government agency officials, and nonprofit and community representatives. Respondents were identified through a purposive sampling, using the Delta Science Program to disseminate the survey electronically to numerous listservs. The survey measured core perceptions of the regional science forums, such as extent of professional involvement and participation, expertise of diverse issues, leadership effectiveness, representative engagement, coordination, resources, and forum purpose.

To analyze the data, we estimated four generalized linear multi-level models using Bayesian methods. The models analyze the effect of individual- and forum-level variables on perceived learning across different science forums, with a separate model for a composite scale and each stage of the adaptive management cycle.

As illustrated in Figure 5, the social and institutional attributes of science forums are the most important drivers of learning, relative to the human and financial capital attributes of the forums or the level of individual actor engagement. For example, the variables of leadership, trust, and coordination consistently have the largest positive influence on all learning stages of adaptive management, whereas the resources variable is consistently less positive. This finding suggests that administrative and financial resource limitations are less important for learning than social drivers.

Figure 5. Bayesian plot for learning models associated with “plan,” “do,” and “evaluate and respond” stages of adaptive management, and combined stages.

Through integrating two policy process frameworks, we have created a new theoretical basis for analyzing policy-related learning within polycentric governance systems. Our Bayesian approach allowed us to visualize the changing importance of social dynamics versus administrative resources across developmental stages of scientific forums. As polycentric systems grow over time, resources pose less limitations on their effectiveness. Our forum-level results also reaffirm findings in a comparative case study that social capital plays an important role in policy-related learning. The findings shed light on how science shapes and is shaped by the policy process, providing valuable insights into how policy-relevant learning occurs in polycentric governance systems.

You can read the original article in Policy Studies Journal at

Lubell, Mark, Tara Pozzi, Tanya Heikkila, Andrea K. Gerlak and Pamela Rittelmeyer. 2025. “ Learning in Polycentric Governance: Insights From the California Delta Science Enterprise.” Policy Studies Journal 53(1): 7–28. https://doi.org/10.1111/psj.12581.

About the Authors

Tara Pozzi is a PhD candidate in the Graduate Group in Ecology at the University of California, Davis. Her research focuses on how governance networks influence climate adaptation policy and planning.

Mark Lubell is a Professor in the Department of Environmental Science and Policy at University of California Davis. His research focuses on human behavior and the role of governance institutions in solving collective action problems and facilitating cooperation.

Tanya Heikkila is a Professor in the School of Public Affairs at University of Colorado Denver. Her work investigates how conflict and collaboration arise in policy processes, and what types of institutions support collaboration, learning, and conflict resolution.

Andrea K. Gerlak is a Professor in the School of Geography and Development and Director of the Udall Center for Studies in Public Policy at the University of Arizona. Her work addresses institutions, learning,  and governance of environmental challenges.

Pamela Rittelmeyer is a Senior Regulatory Analyst of energy efficiency programs at the California Public Utilities Commission.  Her work centers around better understanding various perspectives of environmental problems and supporting policy development.