Examining shifts in zooplankton community variability following biological invasion
Bibliographic record
Abstract
We examined 20 yr of zooplankton samples from Harp Lake for shifts in zooplankton variability following invasion by zooplankton predator Bythotrephes longimanus, using organism body size—as measured at high resolution by Laser Optical Plankton Counter (LOPC)—as the primary metric of investigation. A period of transitory high variability in the 2 yr post‐invasion was observed for both body size compositional variability and aggregate variability metrics, with both measures of variability shifting from low or intermediate to high variability immediately following invasion, before shifting again to intermediate variability ∼ 2 yr post‐invasion. Aggregate and compositional variability dynamics were also considered in combination over the study period, revealing that the period of transitory high variability coincided with a shift from a community‐wide stasis variability pattern to one of asynchrony, before a shift back to stasis 2 yr post‐invasion. These dynamics were related to changes in the significant zooplankton species within the Harp Lake community over the pre‐ and post‐invasion periods, and are likely to be indicative of changes in the stability in the zooplankton community following invasion by Bythotrephes. The dual consideration of aggregate and compositional variability as measured by LOPC was found to provide a valuable means to assess the ecological effects of biological invasion on zooplankton communities as a whole, extending our knowledge of the effects of invasion beyond that already revealed through more traditional taxonomic investigation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".