Effects of permafrost degradation on water and sediment quality and heterotrophic bacterial production of <scp>A</scp>rctic tundra lakes: An experimental approach
Bibliographic record
Abstract
Abstract To assess the effects of shoreline retrogressive thaw slumping on the chemical, physical, and ecological components of small tundra lakes, an in situ manipulative mesocosm experiment was performed in an upland, unslumped Arctic lake located near Inuvik, Northwest Territories, Canada. Twelve replicate mesocosms were established: three control and three replicates of three treatment levels each dosed with differing amounts of soil sourced from the thaw scar of a nearby lake affected by shoreline retrogressive thaw slumping. The soil was rich in ionic compounds such as calcium, magnesium, and sulfates reflecting the marine origin of the local geology, and also contained nutrients (P and N) and organic carbon. Water column ionic and nutrient concentrations increased with increasing soil input, while pelagic bacterial production decreased. Conversely, benthic bacterial production increased by 44, 112, and 498% in the low, medium, and high soil treatments, respectively. This study shows thermokarst slumping to differentially affect pelagic and benthic heterotrophic microbial production through changes to the physical and chemical properties of the water and sediment. The stimulation of benthic and corresponding inhibition of pelagic heterotrophic productivity relative to the control treatments over the 12‐week experimental period indicate that shoreline retrogressive thaw slumping alters heterotrophic energy pathways during the early successional stages of thermokarst lakes experiencing shoreline slumping.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".