Meta-analysis of cyanobacterial effects on zooplankton population growth rate: species-specific responses
Bibliographic record
Abstract
We analyzed a large data set of laboratory experiments to examine the effects of cyanobacteria containing or lacking intracellular toxic metabolites and of different morphology on zooplankton population growth rates across multiple genera and species of cladocerans, rotifers and cyanobacteria. Twenty-one of the 29 zooplankton species maintained positive growth rates when fed a diet containing cyanobacteria even though cyanobacteria were a poor food source for half of the zooplankton species tested relative to a diet containing only green algae and/or flagellates. Differences among zooplankton species could not be explained by grazer species body lengths, even when experiments were restricted to those that used only filamentous cyanobacteria. Single-celled cyanobacteria were more detrimental to a larger number of zooplankton species compared to filamentous or chroococcoid colonial cyanobacteria. We also found no clear effect of putative cyanobacterial toxins on the growth of seven zooplankton species but we did detect a negative effect for the largest cladoceran species, Daphnia magna. Among the cyanobacterial genera, Microcystis had the largest negative effect on zooplankton population growth and there was no consistent difference between M. aeruginosa strains that produced microcystins and those that did not. Our results highlight the large variation in species-specific responses of zooplankton to cyanobacteria. Although cyanobacterial toxicity and mechanical interference may be important drivers in particular cyanobacteria-zooplankton interactions, we did not find general support for these mechanisms through the use of this meta-analysis.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.017 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".