Sustainable use of common-pool resources like groundwater, fisheries, or forests is often challenging as it requires cooperation from all users. While evidence has shown that communities prevent over-exploitation and avoid the tragedy of the commons by developing self-governing institutions, the collaboration they enable—and its long-term benefits—remains poorly understood.
A new paper published today in Nature Sustainability offers insight into the emergence of cooperation by common-pool resource users. Co-authored by Paolo D'Odorico, a professor in the Department of Environmental Science, Policy, and Management, and postdoctoral researcher Chengyi Tu (UC Berkeley and Zhejiang Sci-Tech University), the study found that cooperation may emerge when information on changes in resource level is made available to users.
Prior studies on the emergence of collective action and cooperation among users of common-pool resources have historically overlooked both the feedback between user decisions and resource dynamics, and the emergence of cooperation from shared goals. Tu said the study uses both experimental approaches and theoretical models to help fill that knowledge gap.
The researchers developed an online platform to run experiments where participants representing users of a common-pool resource choose (and update over time) their individual extraction rates based on knowledge of resource level and neighbor’s behavior. The authors found that users tend to cooperate when they share common goals, allowing for long-term resource sustainability.
While the study suggests individuals tend to adjust their harvest rate accordingly as resources are depleted, cooperation only emerges when individuals are rewarded for their shared goals. “We observed that players tend to adopt greedy strategies and maximize short-term payoffs over short durations, while with longer durations they cooperate in hopes of attaining greater rewards in the long term,” D’Odorico said.
These findings are consistent with the results from a resource-decision model developed by the authors to explain the emergence of cooperation as a trade-off between individual and collective payoffs.
“What’s really exciting about this research is that we were able to link the dynamics of users’ decisions to those of the common-pool resource and account for the feedback between the two, both experimentally and in a theoretical model,” added co-author Samir Suweis, a professor at the University of Padova in Italy.
Zhe Li of the University of South China and Yunnan University was also a co-author of the study. The research was supported by UC Berkeley’s Experimental Social Science Laboratory, Microsoft AI for Earth, and Zhejiang Sci-Tech University.