Interaction effects of zooplankton and<scp>CO</scp><sub>2</sub>on phytoplankton communities and the deep chlorophyll maximum
Bibliographic record
Abstract
Abstract Studies examining the consequences of increased partial pressure of carbon dioxide ( p CO 2 ) in freshwater ecosystems associated with climate change have focused on direct effects for phytoplankton, showing increases in primary productivity, biomass or altered composition. However, in lakes, phytoplankton dynamics are also regulated by zooplankton predation and thermal stratification which can lead to a concentration of phytoplankton biomass in a deep chlorophyll maximum ( DCM ) layer, making the response to CO 2 increase important to understand here. Mesocosm experiments were conducted in a meso‐oligotrophic north temperate lake with a strong summer phytoplankton DCM , to estimate the independent and interaction effects of zooplankton grazing and elevated p CO 2 on water column phytoplankton communities and on DCM characteristics. Interaction of CO 2 effects with zooplankton grazing occurred for three of four phytoplankton spectral groups, influencing water column phytoplankton biomass. Zooplankton selective grazing appeared as important as CO 2 concentration in controlling phytoplankton population and biomass. Unexpectedly, CO 2 had an overall negative effect on phytoplankton total biomass despite positive productivity responses. Elevated CO 2 led to more peaked (stronger vertical gradient) mid‐water column chlorophyll distribution, but to smaller DCM peaks overall. Zooplankton had unexpected effects, inducing clustering of more edible phytoplankton and greater temporal variation in the DCM . Our experiment points to interactions in the microbial food web and stoichiometric considerations with nutrient addition that should be explored further in future work with realistic lake food webs to better understand these complex responses to CO 2 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".