Regional ecosystem variability drives the relative importance of bottom-up and top-down factors for zooplankton size spectra
Bibliographic record
Abstract
The relative effects of top-down and bottom-up drivers of zooplankton size structure were examined in three limnologically diverse regions of Quebec, Canada. Lake productivity drove biomass of small-sized zooplankton (300–1000 µm) in the Eastern Townships and Laurentian regions, which have high total phosphorus gradients, but was not significant in the low-productivity region, Gouin. Fish species composition was found to affect biomass of large-sized (>1000 µm) zooplankton and was the primary factor affecting zooplankton size structure in the low productivity region. When size structure of the zooplankton communities were described as normalized biomass size spectra, only bottom-up factors were significant, as increasing productivity resulted in higher curve peaks and increased parabola curvature. No factors were significantly related to any parameter of the Pareto distribution to describe size spectra. Overall, bottom-up forces were stronger drivers of zooplankton size structure, particularly in regions with wide ranges in lake trophy, while fish predation was more important in regions with low productivity variability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".