标题： 重新审视生态预测的限制：潜力、实际性和相对系统可预测性 显示英文标题

标题： The ecological forecast limit revisited: Potential, actual and relative system predictability

摘要： 生态预测是关于时间或空间上目前未知的生态系统状态的基于模型的陈述。为了使模型预测对决策者有用，模型验证和确认决定了其充分性。可以转化为预报可接受范围上限的预报优度衡量标准被称为“预报限制”。虽然天气预报中的验证遵循严格的准则，并有既定的指标和预报限制，但对生态预测模型的评估仍然特定于实验，并且很少报告预报限制。因此，生态预测的使用者无法了解预报可以在多大程度上被信任。在这项工作中，我们综合了现有的方法，在一个统一的框架内定义经验预报限制，以评估生态预测性，并提供了计算这些预报限制的方法。我们区分了模型的潜在预报限制和绝对预报限制，并展示了基准模型如何帮助确定其相对预报限制。这些方法通过来自种群、生态系统和地球系统研究的三个案例研究进行了演示。我们发现，预报限制可以通过三个要求来计算：验证参考、评分函数和预测误差容限。在我们的框架内，预报限制被定义为适用于任何生态预报，并支持生态预测性分析的研究。 显示英文摘要

摘要： Ecological forecasts are model-based statements about currently unknown ecosystem states in time or space. For a model forecast to be useful to inform decision makers, model validation and verification determine adequateness. The measure of forecast goodness that can be translated into a limit up to which a forecast is acceptable is known as the 'forecast limit'. While verification in weather forecasting follows strict criteria with established metrics and forecast limits, assessments of ecological forecasting models still remain experiment-specific, and forecast limits are rarely reported. As such, users of ecological forecasts remain uninformed of how far into the future statements can be trusted. In this work, we synthesise existing approaches to define empirical forecast limits in a unified framework for assessing ecological predictability and offer recipes for their computation. We distinguish the model's potential and absolute forecast limit, and show how a benchmark model can help determine its relative forecast limit. The approaches are demonstrated with three case studies from population, ecosystem, and Earth system research. We found that forecast limits can be computed with three requirements: A verification reference, a scoring function, and a predictive error tolerance. Within our framework, forecast limits are defined for practically any ecological forecast and support research on ecological predictability analysis.