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Global commodity flows between distally connected social-ecological systems pose important challenges to sustainability governance. These challenges are partly due to difficulties in designing and implementing governance institutions that fit or match the scale of the environmental and social problems generated in such telecoupled systems. We focus on the spatial dimension of governance fit in relation to global commodity flows and telecoupled systems. Specifically, we draw on examples from land use and global agricultural commodity governance to examine two overarching types of governance mismatches: boundary mismatches and resolution mismatches. We argue that one way to address mismatches is through governance rescaling and illustrate this approach with reference to examples of three broad types of governance approaches: trade agreements, due diligence laws, and landscape approaches to supply chain governance. No single governance approach is likely to address all mismatches, highlighting the need to align multiple governance approaches to govern telecoupled systems effectively.

Blockchain and distributed ledger technology (BC/DLT) provides distributed databases with decentralized governance, tamper-proof recording, high availability and non-copyable digital assets, which have made it a natural technological basis for supply chain management. In this paper, we introduce REALISTIC, a novel event-based modeling framework for supply chain networks (SCNs) that includes production processes. It extends McCarty's Resources-Events-Agents (REA) accounting model with secure transformations, which, across the entire SCN, guarantee that certified output resources cannot be digitally produced ex nihilo, but require certified input resources of at least the same amount as what is produced. This generalizes the no-double-spend guarantee of current BC/DLT to (digital twins of) physical resources and their production. Authenticated human or robotic Internet of Things (IoT) actors digitally sign and cryptographically commit to the veracity of real-world events on an immutable database, without having to take responsibility for their aggregate consequences. User-specifiable interpretations, corresponding to queries and analytical functions in database systems, provide auditable aggregate information computed from recorded events across the entire SCN. This includes fine-grained and trustworthy tracing of final products through multiple stages of production processes, semi-finished products, quality certifications and transportation all the way back to their raw materials. We present a case study for an end-to-end coffee supply chain that tracks fine-grained and detailed information from a farmer's coffee cherries to retail coffee bags, involving all its actors. Our model handles product provenance; auditable sustainability, quality and trade information; production processes from parchment via green to roasted coffee; product quality tests; farmer certifications; and transportation across the entire coffee supply chain. It is based on field work involving