Global variation in zooplankton niche divergence: Evidence of environmental and trait signals for calanoid copepods
Bibliographic record
Abstract
Ocean warming has led to significant changes for marine zooplankton. Modelling responses to climate change assume that zooplankton respond uniformly with little adaptation (niche conservatism). Oceanic barriers, local adaptation and genetic variation in cosmopolitan species could drive niche divergence between same species populations. We assess niche divergence among 325 globally distributed species across the five main ocean basins. There were 487 diverged niches out of 1124 ocean basin comparisons. The proportion of diverged niches varied both across and within phyla. Calanoida (133 of 325 species) were used to test the likelihood of niche divergence between same species population across environmental gradients. Niche divergence was more likely to occur in species that occupy colder waters and in shallower depths. Niche divergence was more likely for larger ominivore-herbivores than smaller sized carnivores. This study demonstrates adaptive potential across environmental-niche gradients, which must be considered when modelling population responses to climate change.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".