Arctic North American seasonal temperatures from the latest Miocene to the Early Pleistocene, based on mutual climatic range analysis of fossil beetle assemblages
Bibliographic record
Abstract
Late Tertiary and early Quaternary fossil beds in the arctic regions of North America have yielded abundant, well-preserved remains of plants and arthropods, documenting the existence of coniferous forests in the high arctic latitudes. Nearly all of the beetle (Coleoptera) specimens in these fossil assemblages represent extant species. We have applied the mutual climatic range (MCR) method of paleotemperature analysis to fossil beetle assemblages from 11 sites to estimate mean summer (Tmax) and winter (Tmin) temperatures. We found that arctic Tmin values during the latest Miocene and Pliocene were substantially warmer than they are today. The MCR estimates therefore support the scenario derived from the paleobotanical data, namely that arctic Pliocene climates were far less continental. Several Pliocene-age assemblages from the high Arctic yielded Tmax estimates 9-10°C warmer than modern values at the sites. This is the same degree of warming required to allow coniferous forests to grow in the high Arctic. By 3 million years BP, a cooling trend is marked in the paleobotanical and fossil beetle evidence from Alaska. All assemblages dating between 5.7 and 2 million years BP yielded calibrated Tmax values between 12.4 and 13.8°C, regardless of location. Thus the insect fossil data support the theory that there was far less latitudinal gradation in temperatures during the Late Pliocene than there is today. Our reconstructions suggest regional climatic cooling (especially winter temperatures) began by at least 2 million years BP.
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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 | 0.000 |
| Scholarly communication | 0.000 | 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".