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Disturbances fundamentally alter ecosystem functions; yet predicting the impacts of disturbances remains a key scientific challenge. The study of disturbances is ubiquitous across almost all ecological disciplines, yet varying terminology and methodologies have led to the lack of an agreed upon, cross-disciplinary foundation for discussing and quantifying the complexity of disturbances. This shortcoming presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can further destabilize ecosystem responses. By harvesting the ‘swarm intelligence’ of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we propose a pathway towards a new conceptual model of ecological disturbances. Together we identify an essential limitation in disturbance ecology––that the word ‘disturbance’ is used interchangeably to refer to both the events that cause and the consequences of ecological change, despite fundamental distinctions between the two meanings. We develop a generalized framework of ecosystem disturbances to reconcile this limitation and enable examination of the drivers and impacts of disturbances simultaneously. Our proposed framework puts forth a well-defined lexicon for understanding disturbance across perspectives and scales, thereby increasing the interoperability of research across scientific domains. We also recommend minimum reporting standards that detail the magnitude, duration, and rate of change of driver and response variables, regardless of scale. Importantly, while we address some challenges of disturbance research here, developments in technology, methodology, and cross-disciplinary approaches are necessary to close knowledge gaps. We therefore propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.