Streams are important emitters of CO₂ but extreme spatial variability in their physical properties can make upscaling very uncertain. Here, we determined critical drivers of stream CO₂ evasion at scales from 30 to 400 m across a 52.5 km² catchment in northern Sweden. We found that turbulent reaches never have elevated CO₂ concentrations, while less turbulent locations can potentially support a broad range of CO₂ concentrations, consistent with global observations. The predictability of stream pCO₂ is greatly improved when we include a proxy for soil‐stream connectivity. Catchment topography shapes network patterns of evasion by creating hydrologically linked “domains” characterized by high water‐atmosphere exchange and/or strong soil‐stream connection. This template generates spatial variability in the drivers of CO₂ evasion that can strongly bias regional and global estimates. To overcome this complexity, we provide the foundations of a mechanistic framework of CO₂ evasion by considering how landscape process domains regulate transfer and supply.

中文翻译：

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景观过程域驱动了从河网排放二氧化碳的模式

溪流是CO _2的重要排放源，但其物理性质的极度空间变异性可能使升尺度非常不确定。在这里，我们确定了在瑞典北部52.5 km ^2的集水区中，从30到400 m范围内流CO ₂逃逸的关键驱动因素。我们发现，湍流到达的CO ₂浓度从未升高，而较少的湍流位置可以潜在地支持广泛的CO ₂浓度，这与全球观测一致。流p CO ₂的可预测性当我们包含用于土壤流连通性的代理时，将大大改善。集水区地形通过形成水文联系紧密的“域”，从而形成规避网络的格局，这些域以高水-大气交换和/或牢固的土壤-河流连接为特征。该模板在CO ₂逃逸的驱动因素中产生了空间变异性，该变异性可能会严重影响区域和全球估算。为了克服这种复杂性，我们通过考虑景观过程域如何调节转移和供应来提供CO ₂逃逸机制框架的基础。