Meso-scale distributions of lake zooplankton reveal spatially and temporally varying trophic cascades
Bibliographic record
Abstract
The horizontal distribution of crustacean zooplankton is known to vary spatially in large lakes. Patterns in smaller dimictic lakes and variation through time (hourly and monthly) are less well established. Currents, chlorophyll and predators are all factors that vary through time, potentially affecting zooplankton distribution in stratified waters. Along an intermediate-length transect extending from the littoral area to the pelagic zone, we measured crustacean zooplankton size and horizontal position, as well as chlorophyll, currents and predators. We also assessed zooplankton vertical distribution patterns near each transect end. Horizontally, zooplankton were highly spatially structured in high summer, especially during daytime, when they preferred pelagic regions. A regular diel vertical migration pattern in early summer was replaced by an inverse one, suggesting a strong role for predation. Chlorophyll and zooplankton were inversely related, indicating a strong grazing interaction. The weakest signal was detected for currents. Results indicate that there can be large spatial fluctuations in zooplankton abundance apparently driven by predation. Furthermore, zooplankton distribution correlates inversely with chlorophyll only in the absence of a higher trophic level. We expect that plankton distribution in many small dimictic lakes will similarly be dominated by biotic factors, indicating that spatial variation should be taken into account when trophic interactions are considered.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".