Are Current Rates of Atmospheric Nitrogen Deposition Influencing Lakes in the Eastern Canadian Arctic?
Bibliographic record
Abstract
Although arctic lakes rank among the most pristine ecosystems remaining on Earth, widespread paleoecological analyses have revealed rapid recent changes in lake ecology that largely surpass Holocene natural variability and that are generally attributed to climate warming since the end of the Little Ice Age. However, the possibility that climate is only one dimension of these unprecedented ecological shifts remains an untested possibility, especially given that current warming may not yet exceed maximum, naturally mediated, postglacial warmth. In this paper, we assess whether increased anthropogenic nitrogen (N) deposition from distant sources is contributing to directional changes in the biogeochemistry and ecology of two remote lakes on Baffin Island in the eastern Canadian Arctic. Paleolimnological analyses, including diatom assemblages and a suite of biogeochemical proxies (total organic matter, biogenic silica, organic N and C contents, and stable isotopic ratios) reveal a complex suite of progressive changes that are coherently expressed in both lakes. Diatom assemblages began to change as early as the mid-19th century, but major inflections in the biogeochemical proxies occurred significantly later, being most pronounced after 1950. Among these changes are increases in sediment organic matter, depletions of 2‰ in sediment δ15N, and decoupling of δ13C and δ15N signatures. It seems likely that climate warming, subsequently coupled to anthropogenic N deposition, is synergistically driving these ecosystems towards states for which no prior natural analogs exist.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".