A Review of Apparent 20th Century Changes in the Presence of Mussels (<i>Mytilus trossulus</i>) and Macroalgae in Arctic Alaska, and of Historical and Paleontological Evidence Used to Relate Mollusc Distributions to Climate Change
Bibliographic record
Abstract
Live mussels attached to fresh laminarioid brown algae, all fastened to clusters of pebbles and small cobbles, were repeatedly cast ashore by autumn storms at Barrow, Alaska, in the 1990s. Specimens of Laminaria saccharina and L. solidungula shorten by 100 km a 500 km gap (Peard Bay to Stefansson Sound) between previously known concentrations of these kelp species. For the genus Mytilus, a 1600 km gap in fully documented locations existed between Kivalina in the southern Chukchi Sea and the Mackenzie River delta. Barrow specimens were identified using a mitochondrial DNA marker as M. trossulus, an identity consistent with dispersal from the Pacific-Bering side of the Arctic. Live mussels and macroalgae were neither washed up by storms nor collected by active biological sampling during extensive benthic surveys at Barrow in 1948-50. We cannot interpret the current presence of these bivalves and macrophytes as Arctic range extensions due to warming, similar to those manifested by the tree line in terrestrial systems and by Pacific salmon in marine environments. Supplemental information and critical evaluation of survey strategies and rationales indicate that changes in sea temperatures are an unlikely cause. Alternative explanations focus on past seafloor disturbances, dispersal from marine or estuarine refugia, and effects of predators on colonists. This review suggests refining some interpretations of environmental change that are based on the extensive resource of Cenozoic fossils of Arctic molluscs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".