Progress towards sustainability is hampered by differing perceptions of how to advance goals in systems characterized by massive interdependency. Systems thinking has been advocated as a model for improving understanding and management of complex systems, but theory and methods to analyse systems thinking are not well developed. We propose and apply a new way of assessing systems thinking using social network tools to analyse mental models. We examine the cognitive maps of 148 thought leaders in sustainable agriculture in California and measure the extent to which each map captures six fundamental causal patterns. We find that the more complex forms of causal structure that are associated with systems thinking are relatively under-represented in the experts’ maps. Our findings have important implications for individual and collective decision making about sustainable agriculture and other science and policy debates involving complex systems. Cognitive mapping reveals how people think about complex systems and enables hypothesis tests on understanding interdependency. This study finds that education and experience are associated with more nuanced form of complex-systems thinking in sustainable agriculture, such as feedback loops and indirect effects.
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