Composition, Spatial Distribution, and Trophic Structure of the Zooplankton Community in San Jorge Gulf, Southwestern Atlantic Ocean
Bibliographic record
Abstract
The goal of this study was to understand the zooplankton community composition and food web structure in San Jorge Gulf (45°–47°S, 65°30'W), a highly productive marine ecosystem in southern Argentina. A spatial grid of 14 stations was sampled in 2014. The sampled zooplankton community was composed of 30 taxa, with copepods accounting for 83% of the total abundance. Community composition was strongly related to surface temperature and water column stratification. Two distinct zooplankton assemblages were present. The zones designated North and Center were dominated by Ctenocalanus vanus; copepodite stages of C. vanus, Clausocalanus brevipes, and Paracalanus parvus; appendicularians; and Oithona helgolandica. The South zone was dominated by P. parvus, copepodites, Acartia tonsa, and Drepanopus forcipatus. The plankton food webs were increasingly enriched in carbon and nitrogen stable isotopes from the North to the South. Depleted δ 13 C signatures in the North may be explained by terrigenous inputs derived from strong westerly winds. The zooplankton taxa displayed a wide feeding range in the North, whereas the narrow trophic space of the South food web suggested similar feeding strategies among the taxa. Appendicularians were positioned at the base of the food webs, copepods were in the middle, and chaetognaths occupied high trophic positions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".