Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: 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. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and 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.

干扰从根本上改变了生态系统的功能，但预测其影响仍然是一项关键的科学挑战。尽管对干扰的研究在许多生态学科中无处不在，但没有讨论，量化干扰复杂性的统一，跨学科的基础，也没有一致的术语或方法。由于全球变化的加速以及相互作用的干扰可能破坏生态系统响应的稳定性，这种矛盾提出了越来越紧迫的挑战。通过收集跨15个国家/地区的42个机构的跨学科研究人员的专业知识，我们确定了干扰生态学的一个基本局限性：“干扰”一词可互换使用，既指引起，尽管这两种意义之间有根本区别，但生态变化。作为回应，我们开发了一个可概括的生态系统扰动框架，提供了一个定义明确的词典来理解各种观点和规模的扰动。该框架由在多个科学领域引起共鸣的思想产生，并提供了一个基准标准来比较各个领域的干扰。该框架可以通过特定学科的变量进行补充，以最大程度地促进学科间和学科内研究。为了支持对干扰研究的未来综合和荟萃分析，我们还鼓励研究人员明确定义干扰驱动因素和影响的方式，并建议适用于最小规模的最低报告标准。最后，我们讨论了在制定基线框架时要考虑的主要因素，并提出了四个未来方向，以促进我们对干扰及其社会生态影响的跨学科理解：跨生态尺度的整合，理解干扰的相互作用，建立基线和轨迹以及建立基于过程的方法模型和生态预测计划。我们在这一过程中的经验激励我们鼓励更广泛的科学界继续探索利用开放科学原理来产生创造性和多学科思想的新方法。了解干扰相互作用，建立基线和轨迹，以及开发基于过程的模型和生态预测计划。我们在这一过程中的经验激励我们鼓励更广泛的科学界继续探索利用开放科学原理来产生创造性和多学科思想的新方法。了解干扰相互作用，建立基线和轨迹，以及开发基于过程的模型和生态预测计划。我们在这一过程中的经验激励我们鼓励更广泛的科学界继续探索利用开放科学原理来产生创造性和多学科思想的新方法。