Multiple tracers demonstrate distinct sources of dissolved organic matter to lakes of the Mackenzie Delta, western Canadian Arctic
Bibliographic record
Abstract
Lakes of the Mackenzie Delta occur across a gradient that contains three clear end members: those that remain connected to river‐water channels throughout the summer; those that receive only brief inputs of river water during an annual spring flood but contain dense macrophyte stands; and those that experience significant permafrost thaw along their margins. We measured dissolved organic carbon (DOC) concentration, dissolved organic matter (DOM) absorption and fluorescence, and stable isotopes of DOM, DOM precursor materials, and bacteria to elucidate the importance of river water, macrophytes, and thermokarst as DOM sources to Mackenzie Delta lakes. Despite standing stocks of macrophyte C that are sevenfold to 12‐fold greater than those of total DOC, stable isotopes indicated that autochthonous sources contributed less than 15% to overall DOM in macrophyte‐rich lakes. Instead, fluorescence and absorption indicated that the moderate summertime increase in DOC concentration in macrophyte‐rich lakes was the result of infrequent flushing, while bacterial δ13C indicated rapid bacterial removal of autochthonous DOC from the water column. In thermokarst lakes, summertime increases in DOC concentration were substantial, and stable isotopes indicated that much of this increase came from C released as a result of thermokarst‐related processes. Our results indicate that these distinct sources of DOM to neighboring arctic Delta lakes may drive between‐lake differences in C cycling and energy flow. Rapidly assimilated macrophyte DOM should be an important contributor to microbial food webs in our study lakes. In contrast, the accumulation of thermokarst‐origin DOM allows for a significant role in physico‐chemistry but indicates a lesser contribution of this DOM to higher trophic levels.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".