Unique biodiversity in Arctic marine forests is shaped by diverse recolonization pathways and far northern glacial refugia
Bibliographic record
Abstract
The Arctic is experiencing a rapid shift toward warmer regimes, calling for a need to understand levels of biodiversity and ecosystem responses to climate cycles. This study presents genetic data for 109 Arctic marine forest species (seaweeds), which revealed contiguous populations extending from the Bering Sea to the northwest Atlantic, with high levels of genetic diversity in the east Canadian Arctic. One-fifth of the species sampled appeared restricted to Arctic waters. Further supported by hindcasted species distributions during the Last Glacial Maximum, we hypothesize that Arctic coastal systems were recolonized from many geographically disparate refugia leading to enriched diversity levels in the east Canadian Arctic, with important contributions stemming from northerly refugia likely centered along southern Greenland. Our results suggest Arctic marine biomes persisted through cycles of glaciation, leading to unique assemblages in polar waters, rather than being entirely derived from southerly (temperate) areas following glaciation. As such, Arctic marine species are potentially born from selective pressures during Cenozoic global cooling and eventual ice conditions beginning in the Pleistocene. Arctic endemic diversity was likely additionally driven by repeated isolations into globally disparate refugia during glaciation. This study highlights the need to take stock of unique Arctic marine biodiversity. Amplification of warming and loss of perennial ice cover are set to dramatically alter available Arctic coastal habitat, with the potential loss of diversity and decline in ecosystem resilience.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".