Trends in Lake Erie zooplankton biomass and community structure during a 25-year period of rapid environmental change
Bibliographic record
Abstract
Zooplankton play a key role in aquatic ecosystems, providing potential top-down control on phytoplankton and linking primary production to higher trophic levels. Thus, knowledge of zooplankton dynamics is fundamental to any assessment of the impacts of human driven rapid environmental change on lakes. Lake Erie has undergone eutrophication since the 1990s, resulting in summer harmful cyanobacterial blooms, dominated by Microcystis aeruginosa, since approximately 2003 in the western basin (WB) and 2008 in the central basin (CB). The effect of eutrophication on zooplankton in Lake Erie is unclear; few studies have characterized trends in zooplankton biomass and community structure during this period of rapid change. We used the Lake Erie Plankton Abundance Study (LEPAS) zooplankton dataset to analyze interannual trends in the dynamics of eight major zooplankton groups in the WB and CB during 1995–2020. In both basins, we found directional change in zooplankton biomass and community structure. These directional trends in zooplankton biomass overlaid approximate five-year cycles in nearly all taxa, potentially linked to the El Niño Southern Oscillation. Eutrophication was associated with an increase in the summer biomass of total zooplankton, calanoids, and large cladocerans but surprisingly, not cyclopoids, rotifers or small cladocerans. The surprisingly positive or neutral effect of eutrophication and M. aeruginosa on zooplankton biomass may be due to a combination of bottom-up (e.g. concurrent increases in more edible algae) and top-down (e.g. changes in planktivory) forces.
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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 | 0.001 |
| 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) | 0.000 | 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".