Extreme Levels of Ocean Acidification Restructure the Plankton Community and Biogeochemistry of a Temperate Coastal Ecosystem: A Mesocosm Study
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Bibliographic record
Abstract
The oceans’ uptake of anthropogenic carbon dioxide (CO 2 ) decreases seawater pH and alters the inorganic carbon speciation – summarized in the term ocean acidification (OA). Already today, coastal regions experience episodic pH events during which surface layer pH drops below values projected for the surface ocean at the end of the century. Future OA is expected to further enhance the intensity of these coastal extreme pH events. To evaluate the influence of such episodic OA events in coastal regions, we deployed eight pelagic mesocosms for 53 days in Raunefjord, Norway, and enclosed 56–61 m 3 of local seawater containing a natural plankton community under nutrient limited post-bloom conditions. Four mesocosms were enriched with CO 2 to simulate extreme p CO 2 levels of 1978 – 2069 μatm while the other four served as untreated controls. Here, we present results from multivariate analyses on OA-induced changes in the phyto-, micro-, and mesozooplankton community structure. Pronounced differences in the plankton community emerged early in the experiment, and were amplified by enhanced top-down control throughout the study period. The plankton groups responding most profoundly to high CO 2 conditions were cyanobacteria (negative), chlorophyceae (negative), auto- and heterotrophic microzooplankton (negative), and a variety of mesozooplanktonic taxa, including copepoda (mixed), appendicularia (positive), hydrozoa (positive), fish larvae (positive), and gastropoda (negative). The restructuring of the community coincided with significant changes in the concentration and elemental stoichiometry of particulate organic matter. Results imply that extreme CO 2 events can lead to a substantial reorganization of the planktonic food web, affecting multiple trophic levels from phytoplankton to primary and secondary consumers.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it