Dissolved Nitrogen Cycling in The Eastern Canadian Arctic Archipelago and Baffin Bay from Stable Isotopic Data
Bibliographic record
Abstract
Climate change is expected to alter the input of nitrogen (N) sources in the Eastern Canadian Arctic Archipelago (ECAA) and Baffin Bay due to increased discharge from glacial meltwater and permafrost thaw. Since dissolved inorganic N is generally depleted in surface waters, dissolved organic N (DON) could represent a significant N source fueling phytoplankton activity in Arctic ecosystems. Yet, few DON data for this region exist. We measured concentrations and stable isotope ratios (δ15N and δ18O) of DON and nitrate (NO3−) to investigate the sources and cycling of dissolved nitrogen in regional rivers and at the sea surface from samples collected in the ECAA and Baffin Bay during the summer of 2019. The isotopic signatures of NO3- in rivers could be reproduced in a steady state isotopic model by invoking mixing between atmospheric NO3- and nitrified ammonium as well as NO3- assimilation by phytoplankton. DON concentrations were low in most rivers (≤4.9 µmol L−1), whereas the concentrations (0.54–12 µmol L−1) and δ15N of DON (−0.71–9.6 ‰) at the sea surface were variable among stations, suggesting dynamic cycling and/or distinctive sources. In two regions with high chl-a, DON concentrations were inversely correlated with chlorophyll‐an and the d15N of DON, suggesting net DON consumption in localized phytoplankton blooms. We derived an isotope effect of −6.9‰ for DON consumption. Our data helps establish a baseline to assess future change in nutrient regime for this climate sensitive region.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".