Quantifying the relative influence of factors and processes controlling riverine ecosystem function is essential to predicting future conditions under global change. Dissolved organic matter (DOM) is a fundamental component of riverine ecosystems that fuels microbial food webs, influences nutrient and light availability, and represents a significant carbon flux globally. The heterogeneous nature of DOM molecular composition and its propensity for interaction (i.e., functional diversity) can characterize riverine ecosystem function across spatiotemporal scales. To investigate fundamental drivers of DOM diversity, we collected seasonal water samples from 42 nested locations within five watersheds spanning multiple watershed sizes (~ 5 to 30,000 km²) across the United States. Patterns in DOM molecular richness, aromaticity, relative abundance of N-containing formulas, and putative biochemical transformations derived from high-resolution mass spectrometry were assessed across gradients of explanatory variables associated with watershed characteristics (e.g., watershed area, water residence time, land cover). We found that putative biochemical transformations were more strongly related to explanatory variables across watersheds than common bulk DOM parameters and that watershed area, surface water residence time and derived Damköhler numbers representing DOM reactivity timescales were strong predictors of DOM diversity. The data also indicate that catchment-specific land cover factors can significantly influence DOM diversity in diverging directions. Overall, the results highlight the importance of considering water residence time and land cover when interpreting longitudinal patterns in DOM chemistry and the continued challenge of identifying generalizable drivers that are transferable across watershed and regional scales for application in Earth system models. This work also introduces a Findable Accessible Interoperable Reusable (FAIR) dataset (> 300 samples) to the community for future syntheses.

量化控制河流生态系统功能的因素和过程的相对影响对于预测全球变化下的未来状况至关重要。溶解有机物 (DOM) 是河流生态系统的基本组成部分，为微生物食物网提供燃料，影响养分和光的可用性，并代表着全球重要的碳通量。 DOM 分子组成的异质性及其相互作用的倾向（即功能多样性）可以表征跨时空尺度的河流生态系统功能。为了调查 DOM 多样性的基本驱动因素，我们从美国跨越多个流域大小（约 5 至 30,000 km ² ）的 5 个流域内的 42 个嵌套位置收集了季节性水样。通过与流域特征（例如，流域面积、水停留时间、土地覆盖）相关的解释变量的梯度，评估了 DOM 分子丰富度、芳香性、含氮分子式的相对丰度以及源自高分辨率质谱的推定生化转化的模式。 ）。我们发现，与常见的散装 DOM 参数相比，假定的生化转化与跨流域的解释变量的相关性更强，并且流域面积、地表水停留时间和代表 DOM 反应时间尺度的衍生 Damköhler 数是 DOM 多样性的强有力的预测因子。数据还表明，流域特定的土地覆盖因素可以在不同方向上显着影响 DOM 多样性。 总体而言，结果强调了在解释 DOM 化学纵向模式时考虑水停留时间和土地覆盖的重要性，以及识别可跨流域和区域尺度转移以应用于地球系统模型的普遍驱动因素的持续挑战。这项工作还向社区引入了一个可查找、可访问、可互操作、可重用 (FAIR) 数据集（> 300 个样本），以供未来综合。