Drivers of compliance monitoring in forest commons

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"To be effective, institutional arrangements need to be well-matched to the defining features of the problems they address. This makes it essential to recognize from the outset that environmental problems differ from one another in ways that have fundamental implications for the nature of the arrangements required to solve or at least ameliorate them"

(Oran Young, 2008)

In pre-COVID times, when face to face meetings were possible, we formed the Testing and Extending Ostrom's Frameworks Pursuit at the National Socio-Environmental Synthesis (SESYNC) Centre in Annapolis, Maryland, USA. This group included political scientists, ecologists, and institutional economists from across the globe with diverse expertise, knowledge and field experience. Our meetings focused on identifying and addressing theoretical gaps in the literature on the commons and social-ecological systems using novel empirical and computational methods. With three weeks of extensive brainstorming, spread over a period of two years, and several virtual follow ups in between, we collectively put forth an agenda aiming to address gaps in our understanding of the structure, function and performance of natural resource governance across diverse problems and contexts.  

Photo: The SESYNC Team in Annapolis, Maryland, USA.  Top row: Örjan Bodin, Lukas Egli, Cristina Apetrei, Hayley Clements, Hita Unnikrishnan, Georgina Gurney, Graham Epstein, Graeme Cumming.  Middle Row: Sivee Chawla, Maja Schlüter, Tiffany Morrison, Sergio Villamayor Tomas.  Bottom Row: Nick Magliocca, Birgit Müller, Mark Lubell, Jacopo Baggio, Marty Anderies.  Other team members include Michael Cox, Steve Lade, Ralf Seppelt, Chris Weible

One key insight that underpinned our research agenda is the fact that there are no panaceas for addressing global sustainability challenges. The need to tailor solutions to the specific problem and context in which it is found is greater than ever. However, there remains a troubling lack of knowledge concerning the contexts in which different environmental policies or governance systems are more or less likely to contribute to successful outcomes. A second important dimension of our research agenda was to utilize the growing toolbox of computational methods to overcome longstanding problems of method in this literature.  Collective action and sustainable environmental governance is influenced by a wide range of social, ecological and institutional factors, often times involving non-linear responses and complex interactions among them. The research we present here aims to respond to this theoretical challenge by drawing upon data collected as part of the International Forest Resources and Institutions (IFRI) program and using boosted decision trees to examine factors influencing compliance monitoring by user groups in forest commons. Thus, based on previous studies, we identified a large number of potentially influential variables, developed estimates of their relative importance to understanding outcomes, and visualized the relationship between these variables and outcomes.   

We found three factors that were strongly related to the likelihood of local monitoring of compliance: local rulemaking, markets, and group size.  Local forest user groups are more likely to self-organize to monitor compliance with forest rules when rules are developed by local stakeholders, the user groups are located either close to or far from markets for forest products, and the group is larger in size.  Leadership also plays an important role in certain contexts, for example, in situations where the group size is small and located in close proximity to markets. While these are interesting and important observations that allude to underlying drivers of collective action in forest commons, these insights would benefit greatly from further empirical testing and a careful examination of underlying mechanisms that link the explanatory variables with compliance monitoring.

Predicted probability of compliance monitoring as a function of (A) local rulemaking, (B) distance to market and (C) group size.  

Our work also highlights the effectiveness of machine learning approaches as a tool for generating insights in complex social-ecological systems. At the same time, it is important to note that these insights, while providing an important additional dimension for planners to consider, cannot replace the role of place based and contextually situated knowledge in environmental planning exercises and critical social sciences.  

Graham Epstein

Postdoctoral Researcher, School of Politics, Security and International Affairs, University of Central Florida