Erika C Freeman, Maruti K Mudunuru, Kelli L Feeser, Emily Ann McClure, Ricardo González-Pinzón, Christopher S Ward, Eric M Bottos, Stefan Krause, Jasquelin Peña, Michelle E Newcomer
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Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B-Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R<sup>2</sup> ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from - 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. This research bridges biogeochemistry and ecology, providing tools to anticipate molecular transformations across scales.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"27019"},"PeriodicalIF":3.8000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Molecular diversity of dissolved organic matter reflects macroecological patterns in river networks.\",\"authors\":\"Erika C Freeman, Maruti K Mudunuru, Kelli L Feeser, Emily Ann McClure, Ricardo González-Pinzón, Christopher S Ward, Eric M Bottos, Stefan Krause, Jasquelin Peña, Michelle E Newcomer\",\"doi\":\"10.1038/s41598-025-12835-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Deciphering dissolved organic matter (DOM) molecular complexity is crucial for understanding ecosystem function. Using the continental-scale Worldwide Hydrobiogeochemistry Observation Network for Dynamic Rivers Systems (WHONDRS) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) dataset, we reveal fundamental scaling patterns of DOM chemodiversity with watershed characteristics. Analysis of 54 river sites shows local and regional watershed features significantly influence DOM chemodiversity (2500-8718 unique formulae), exhibiting consistent scaling patterns across compound classes and a novel latitudinal gradient (decreasing diversity with increasing latitude). Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B-Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R<sup>2</sup> ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from - 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. 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Molecular diversity of dissolved organic matter reflects macroecological patterns in river networks.
Deciphering dissolved organic matter (DOM) molecular complexity is crucial for understanding ecosystem function. Using the continental-scale Worldwide Hydrobiogeochemistry Observation Network for Dynamic Rivers Systems (WHONDRS) Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) dataset, we reveal fundamental scaling patterns of DOM chemodiversity with watershed characteristics. Analysis of 54 river sites shows local and regional watershed features significantly influence DOM chemodiversity (2500-8718 unique formulae), exhibiting consistent scaling patterns across compound classes and a novel latitudinal gradient (decreasing diversity with increasing latitude). Scaling relationships for DOM composition vary by compound class. Crucially, the scaling parameters (B, baseline chemodiversity; Z, sensitivity) are linearly interrelated. This B-Z relationship is most robust for potentially bio-labile carbohydrates (coefficient of determination R2 ≈ 0.85), diminishing for recalcitrant, plant-derived molecules (such as lignin), and indicates (potential) biolability-dependent coupling between baseline diversity and environmental responsiveness. These quantitative scaling relationships, with scaling exponents ranging from - 2.1 to 2.2 across compound classes, enable prediction of DOM composition across watersheds, offering a framework to understand ecosystem responses to environmental change. This research bridges biogeochemistry and ecology, providing tools to anticipate molecular transformations across scales.
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