The effect of increasing temperature and p<scp>CO<sub>2</sub></scp> on experimental pelagic freshwater communities
Bibliographic record
Abstract
Abstract As the global climate is changing, average water temperatures and the supply of CO 2 to water bodies are increasing. To determine how the effects of these changes on freshwater communities interact, we ran a month‐long factorial mesocosm experiment, in which we manipulated water temperature (heated, ambient) and pCO 2 (preindustrial, ambient, future). We found that the total phytoplankton biomass responded positively to the pCO 2 and temperature treatments but no interactive effects were detected. Green algae were positively affected by temperature and, over the course of the experiment, responded to pCO 2 first positively, then negatively. Heterokonts, on the other hand, were unaffected by temperature but responded positively to pCO 2 . pCO 2 enrichment also led to increases in seston C : N stoichiometry, although the experiment ended before we could observe any effects of pCO 2 on the zooplankton community composition. Warming caused shifts in zooplankton community composition, primarily through higher abundances of the cladoceran Bosmina longirostris and the rotifer Conochilus unicornis , and lower abundances of the rotifer Polyarthra vulgaris . We found that, in contrast to the effects of temperature, which can be explained by temperature‐dependent plankton growth curves, the responses of algal groups to pCO 2 enrichment were difficult to anticipate, despite the availability of priors from previous pCO 2 enrichment experiments in the same lake mesocosms. We conclude that climate change‐induced increases in aquatic pCO 2 and temperatures are likely to affect pelagic ecosystems, though further research in freshwater systems is needed before generalized claims regarding the simple and interactive effects of pCO 2 can be made.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".