The limnological response of Arctic deltaic lakes to alterations in flood regime
Bibliographic record
Abstract
Arctic freshwaters are being rapidly altered by global climate change with consequences to hydrology, biogeochemistry, and ecology, but in many cases the trajectory of these changes is poorly understood. We collected a unique 5-year time series of major ion, nutrient, and trace metal data from lakes in the Mackenzie Delta (NT, Canada) to examine limnological changes during a period of variable flood conditions, including years of recent historic high and low peak river levels. Previous work in the Mackenzie Delta has established that lake water chemistry is strongly related to connection time with the river during the period of spring ice-jam flooding or via channel connections through the growing season. We show that differences in peak spring water levels explain differences in lake chemistry in lakes isolated from the channel during the summer. Isolated, macrophyte-rich lakes in the Mackenzie Delta have been shown to be CO2 absorbers during summer. We demonstrate a response to alterations in flood regime by variables related to macrophyte productivity in isolated lakes with the greatest connectivity to the river that suggests productivity declines with increasing connection time. The connectivity of low-elevation lakes, which represent a majority of lake number and area in the Mackenzie Delta, has been projected to increase with climate change. Our work suggests that an increase in connection time may decrease the macrophyte productivity of these lakes, with potential consequences to the CO2 balance of individual lakes and the Mackenzie Delta as a whole.
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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 | 0.001 | 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".