Anthropogenic climate change drives shift and shuffle in North Atlantic phytoplankton communities
Bibliographic record
Abstract
Anthropogenic climate change has shifted the biogeography and phenology of many terrestrial and marine species. Marine phytoplankton communities appear sensitive to climate change, yet understanding of how individual species may respond to anthropogenic climate change remains limited. Here, using historical environmental and phytoplankton observations, we characterize the realized ecological niches for 87 North Atlantic diatom and dinoflagellate taxa and project changes in species biogeography between mean historical (1951-2000) and future (2051-2100) ocean conditions. We find that the central positions of the core range of 74% of taxa shift poleward at a median rate of 12.9 km per decade (km⋅dec(-1)), and 90% of taxa shift eastward at a median rate of 42.7 km⋅dec(-1) The poleward shift is faster than previously reported for marine taxa, and the predominance of longitudinal shifts is driven by dynamic changes in multiple environmental drivers, rather than a strictly poleward, temperature-driven redistribution of ocean habitats. A century of climate change significantly shuffles community composition by a basin-wide median value of 16%, compared with seasonal variations of 46%. The North Atlantic phytoplankton community appears poised for marked shift and shuffle, which may have broad effects on food webs and biogeochemical cycles.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".