The temporal structures of gross primary production (GPP) and ecosystem respiration (ER) vary across time scales in response to complex interactions among dynamic drivers (e.g., flow, light, temperature, organic matter supply). To explore emergent patterns of river metabolic variation, we applied frequency‐domain analysis to multiyear records of metabolism across 87 US rivers. We observed a dominant annual periodicity in metabolic variation and universal fractal scaling (i.e., power spectral density inversely correlated with frequency) at subannual frequencies, suggesting these are foundational temporal structures of river metabolic regimes. Frequency‐domain patterns of river metabolism aligned best with drivers related to energy inputs: benthic light for GPP and GPP for ER. Simple river metabolism models captured frequency‐domain patterns when parameterized with appropriate energy inputs but neglecting temperature controls. These results imply that temporal variation of energy supply imprints directly on metabolic signals and that frequency‐domain patterns provide benchmark properties to predict river metabolic regimes.

中文翻译：

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能量输入对河流代谢状况产生季节性和分形结构影响


总初级生产（GPP）和生态系统呼吸（ER）的时间结构随着时间尺度的变化而变化，以响应动态驱动因素（例如流量、光照、温度、有机物供应）之间复杂的相互作用。为了探索河流代谢变化的新模式，我们对美国 87 条河流的多年代谢记录应用了频域分析。我们观察到亚年频率的代谢变化和通用分形标度（即功率谱密度与频率成反比）具有显着的年度周期性，表明这些是河流代谢状况的基本时间结构。河流代谢的频域模式与能量输入相关的驱动因素最一致：GPP 的底栖光和 ER 的 GPP。当用适当的能量输入进行参数化但忽略温度控制时，简单的河流代谢模型捕获了频域模式。这些结果意味着能量供应的时间变化直接影响代谢信号，并且频域模式提供了预测河流代谢状况的基准特性。