Shifts in Plankton, Nutrient and Light Relationships in Small Tundra Lakes Caused by Localized Permafrost Thaw
Bibliographic record
Abstract
Tundra lakes located in the Mackenzie Delta uplands, NWT, Canada, are increasingly being affected by permafrost thaw in the form of shoreline retrogressive thaw slumping. This form of thaw-induced disturbance is used as a surrogate indicator of landscape-related disturbance linked to regional climate warming. We compared 22 lakes, half affected by thaw slumping and half unaffected, to determine whether water column nutrient concentrations, light availability, and plankton biomass differed between these two lake types. Total phosphorus (TP), total dissolved nitrogen (TDN), dissolved organic carbon (DOC), and chlorophyll a concentrations were higher in unaffected lakes than in slump-affected lakes. Absorbance related to water colour of both UV and photosynthetically active radiation in the water column was also higher in unaffected lakes, but bacterioplankton abundance was not different between lake types. UV light absorbance was found to be the best predictor of pelagic chlorophyll a concentrations in unaffected lakes, whereas TDN (and to a lesser extent TP) were the best predictors of pelagic chlorophyll a in slump-affected lakes. These findings indicate that slumping arising from permafrost thaw produces a shift in tundra lake nutrient, light, and phytoplankton relationships. Given the projections of continued warming, this result has significant implications for the future biogeochemical and ecological states of Arctic tundra lakes.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".