Climate Change and Urbanization Decouple Dissolved Organic Carbon Quantity and Composition in Streams
Bibliographic record
Abstract
Abstract Dissolved organic carbon (DOC) is a ubiquitous component of freshwater ecosystems that is sensitive to global change. In turn, DOC controls fundamental biogeochemical processes and functions. These controls depend on both the amount and composition of organic molecules comprising the dissolved organic matter (DOM) pool, which reflects the relative contributions of catchment‐derived terrestrial inputs and in situ production. Stream DOM fluctuates with land use, soil mobility, and hydrology; however, few studies have monitored long‐term changes in DOM composition to investigate links with climate. Here, we characterized 17‐year trends in DOC and DOM in 48 streams across a land use gradient and modeled patterns therein with climatic and hydrological conditions. Across streams, Mann‐Kendall trend analyses showed that DOC decreased through time, while DOM became fresher, more aromatic, and contained an increased proportion of urban‐derived DOM from the terrestrial catchment. Using generalized additive models, we observed significant linear, unimodal, and multimodal patterns in DOM composition with precipitation and soil temperature. Generally, precipitation increased terrestrial DOM, whereas soil temperature increased urban‐derived DOM, particularly in catchments characterized by increasing levels of urbanization. Our study highlights the importance of long‐term monitoring in understanding dynamic interactions between terrestrial—fluvial carbon transfer and biogeochemical effects of global climate change and urbanization. Altogether, our results show that interactions between climate change and urbanization will shape future DOM dynamics in streams.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".