Increases in humic and bioavailable dissolved organic matter in a forested New England headwater stream with increasing discharge
Bibliographic record
Abstract
Understanding the processes controlling the transfer of organic matter from terrestrial to aquatic ecosystems is of fundamental importance for the aquatic sciences. Over the course of a full year, fluorescence, absorbance and bioavailability of dissolved organic matter (DOM) were characterised in Bigelow Brook, a forested headwater stream in Massachusetts, USA. Parallel factor analysis (PARAFAC) identified a four-component model to describe observed DOM fluorescence (C1–C4). Component C2 exhibited the characteristics of a more humic-like fluorophore, with a potentially more reduced redox state and increased with discharge, whereas more fulvic-like (C1) and protein-like (C3, C4) fluorophores decreased. Under both dark and light-exposed conditions, percentage bioavailable dissolved organic carbon (%BDOC) increased with discharge (R2 = 0.37 and R2 = 0.56). C2 and specific absorptivity (SUVA) were reduced following BDOC incubations, whereas C1, C3 and C4 increased. These changes to DOM characteristics with increasing discharge were observed under both baseflow and stormflow conditions, indicating that with rising watertable, loading from a large riparian or hyporheic pool of organic matter is likely occurring. Other headwater streams, where loading is controlled by hillslope processes, are likely to exhibit a similar pattern of increasing export of more humic and bioavailable DOM during hydrologic events.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".