The Holocene thermal maximum in the North American Arctic
Bibliographic record
Abstract
Global databases of Holocene paleoclimates have been assembled, but these contain few data from the north American Arctic, especially from the High- and Mid-Arctic zones. A series of lake sediment cores from across the North American Arctic as well as data on treeline variations have been analyzed for several different proxy-climate data. The results show longitudinal differences in the timing of the maximum temperatures, with transitions synchronous across the North American Arctic, although not necessarily in the same direction. For example, at 8.2ka, the western and central Arctic cooled, but eastern Arctic and northern Greenland warmed. This space-time pattern of the Holocene Thermal Maximum (HTM) can be attributed to changes in the atmospheric circulation in response to the melting ice sheet, changes in the local energy balance in response to orbital insolation changes and other forcing.The impacts of these changes on Arctic ecosystems are subtle but noticeable. Multiple proxies from the same core or from nearby lakes sometimes show coherent changes but at other times differences. For terrestrial ecosystems, biodiversity seems less affected by warmer conditions than biological production, which increased during local HTM. Periods of warm conditions and high terrestrial plant production were associated with a decrease in diatom production (as measured by accumulation rates) in some sites, and in some cases, with an absence of diatoms in the sediments (diatom-free zones), for reasons not yet clear. Secondary production of chironomid communities living in the lake sediments was sometimes coherent with diatom production, but not at other times.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".