Population structure in Arctic marine forests is shaped by diverse recolonisation pathways and far northern glacial refugia
Bibliographic record
Abstract
Abstract The Arctic is experiencing a rapid shift towards warmer regimes, calling for a need to understand levels of biodiversity and ecosystem responses to climate cycles. This study examines marine refugial locations during the Last Glacial Maximum in order to link recolonization pathways to patterns of genetic diversity in Arctic marine forests. We present genetic data for 109 species of seaweed to infer community-level patterns, and hindcast species distributions during the Last Glacial Maximum to further pinpoint likely refugial locations. Sequence data 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. Hindcasted species distributions highlighted refugia in the Bering Sea, Northwest Atlantic, South Greenland, and Europe. 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. Moreover, we hypothesize these northerly refugia likely played a key role in promoting polar endemic diversity, as reflected by abundant unique population haplotypes and endemic species in the East Arctic. Significance Statement Our work challenges the existing paradigm that marine Arctic ecosystems are depauperate extensions of southerly (temperate) communities established in the wake of recent glaciation, fundamentally changing how these systems should be viewed and interpreted. We forward novel hypotheses regarding the recent history of Arctic marine systems, particularly with regards to endemism being an integral feature of Arctic biomes, and present a firm framework for future evolutionary research in this system typically viewed as “ecologically immature.”
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".