Source and fate of dissolved organic matter in boreal headwater streams
Bibliographic record
Abstract
Understanding the source and fate of dissolved organic matter (DOM), a key water quality variable, in boreal headwaters is of critical importance considering the amount of carbon stored and processed in different ecosystem components within the boreal forest and the sensitivity of these processes to climate change. Using historical streamflow and stream chemistry data in combination with direct measurements of the landscape sources of DOM and more detailed stream DOM quality data from 2021 at the IISD-ELA, I examined how the terrestrial source of DOM influences the quantity and quality of DOM in three boreal headwater streams. Using historical stream data from 1981-2021, I found that concentration-discharge (c-Q) relationships varied based on both catchment characteristics and hydrological conditions. Streams draining upland-dominated catchments were more often transport-limited (i.e., concentration increased with increasing flow), whereas a wetland-dominated stream was more often source-limited (i.e., concentration decreased with increasing flow) in terms of stream DOM concentration. DOM concentration and quality data in soil leachate indicated that streamwater had DOM characteristics suggesting it originated from near-stream organic soils, while after the drought the DOM came proportionally more from distal mineral soils (in addition to near-stream organic soil contributions). I showed that the severe drought in 2021 made streams with varying landscape characteristics respond similarly to the post-drought flush. These findings also illustrate that while c-Q relationships may be different among streams draining upland-dominated and wetland-dominated catchments as a result of the different abilities of these landscape to accumulate and mobilize DOM, DOM quality responded to this drought to post-drought flush synchronously among all three streams. As climate change will alter the frequency, duration, and severity of future hydrological conditions, this has repercussions for the DOM dynamics in headwater streams and the resulting water quality downstream.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".