Permafrost thaw lakes and ponds as habitats for abundant rotifer populations
Bibliographic record
Abstract
Thermokarst lakes and ponds were sampled across a range of permafrost landscapes in subarctic Québec (Nunavik, Canada) to compare their rotifer and other zooplankton characteristics with a set of rock-basin lakes and ponds in the region. A total of 24 rotifer species were identified, with an average of seven taxa per waterbody. Rotifer abundance was an order of magnitude higher in the thaw ponds than in rock-basin waters. In some thaw ponds, rotifers accounted for >50% of the total zooplankton biomass, but for <10% in all of the rock-basin waters. Neither α- nor β-diversity was significantly different between the two waterbody types. Grazing experiments with microspheres (0.5–6 µm diameter) showed that medium-sized particles (2–3 µm) were preferred to smaller and larger particles; clearance rates were <0.05% of the water column per day, implying that the rotifer populations were unlikely to be bottom-up limited by food availability. Rotifer abundance was negatively correlated with cladoceran densities, suggesting possible interference effects. Chaoborus larvae were also present and may exert a top-down control. Thermokarst ponds are currently favorable environments for rotifers, but the rapid change they have begun to experience brings uncertainty about their ongoing capacity to sustain these prolific communities.
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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 | 0.001 | 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) | 0.002 | 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".