Our knowledge of ecological stability is built on assumptions of scale. These assumptions limit our ability to reach a generalizable and mechanistic understanding of stability under global environmental change. Moving towards a multiscale approach—across space, time and environment—will allow us to better understand the intrinsic (e.g., demographic) and extrinsic (environmental) drivers of ecological stability. In this perspective, we review multiple sources of variation responsible for shaping ecological dynamics, and how scale affects our observation of these dynamics through its confounding effect on drivers of variation in ecosystems. We discuss the effect of temporal scale when combining empirical dynamic modeling with high‐resolution population time series to consider the time‐varying nature of multispecies interaction networks, highlighting interspecific interactions as an intrinsic driver of community dynamics. Next, we examine energy landscape analysis as a method for inferring stability and transience during community assembly and its interaction with spatial scale, emphasizing the intrinsic role of compositional variability in assembly dynamics. We then examine population dynamics at species' range margins and show how considering the interaction between spatial and temporal environmental heterogeneity, an extrinsic driver of population dynamics, can facilitate a nuanced understanding of population expansions, range shifts, and species invasions. Finally, we discuss broadly how the sources of intrinsic and extrinsic variation interact with each other and with spatiotemporal scale to shape ecological dynamics. Better recognition of the scale‐dependent nature of the relationship between drivers of variation and ecological dynamics will be invaluable to illuminate the dynamics influencing ecological stability across scales.

中文翻译：

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阐明各个尺度上生态稳定的内在和外在驱动力

我们对生态稳定性的了解是建立在规模假设的基础上的。这些假设限制了我们对全球环境变化下对稳定性的普遍理解和机械理解的能力。向跨空间，时间和环境的多尺度方法迈进，将使我们能够更好地了解生态稳定性的内在（例如人口）和外在（环境）驱动因素。从这个角度出发，我们回顾了造成生态动态变化的多种变化来源，以及尺度如何通过其对生态系统变化驱动力的混杂影响来影响我们对这些动态的观察。我们讨论了将经验动态模型与高分辨率种群时间序列结合起来以考虑多物种相互作用网络的时变性质时的时间尺度效应，强调种间互动是社区动态的内在驱动力。接下来，我们将能源景观分析作为一种推断社区组装过程中的稳定性和瞬态及其与空间尺度的相互作用的方法，强调组成变异性在组装动力学中的内在作用。然后，我们研究了物种范围边缘处的种群动态，并展示了如何考虑时空环境异质性（种群动态的外在驱动因素）之间的相互作用，可以促进对种群扩展，范围变化和物种入侵的细微了解。最后，我们广泛地讨论了内在和外在变化的来源如何相互影响以及如何以时空尺度相互作用以塑造生态动力学。