Holocene climate dynamics in Latvia, eastern Baltic region: a pollen‐based summer temperature reconstruction and regional comparison
Bibliographic record
Abstract
Heikkilä, M. & Seppä, H. 2010: Holocene climate dynamics in Latvia, eastern Baltic region: a pollen‐based summer temperature reconstruction and regional comparison. Boreas, Vol. 39, pp. 705–719. 10.1111/j.1502‐3885.2010.00164.x. ISSN 0300‐9483. A pollen‐based summer temperature (Tsummer) reconstruction reveals the Holocene climate history in southeastern Latvia and contributes to the limited understanding of past climate behaviour in the eastern sector of northern Europe. Notably, steady climate warming of the early Holocene was interrupted c. 8350–8150 cal. yr BP by the well‐known 8.2 ka cold event, recorded as a decrease of 0.9 to 1.8 °C in Tsummer. During the Holocene Thermal Maximum, c. 8000–4000 cal. yr BP, the reconstructed summer temperature was ∼2.5–3.5 °C higher than the modern reconstructed value, and subsequently declined towards present‐day values. Comparison of the current reconstruction with other pollen‐based reconstructions in northern Europe shows that the 8.2 ka event is particularly clearly reflected in the Baltic region, possibly as a result of distinct climatic and ecological gradients and the sensitivity of the vegetation growth pattern to seasonal temperature change. The new reconstruction also reveals that the Holocene Thermal Maximum was warmer in Latvia than in central Europe and Fennoscandia. In fact, a gradient of increasing positive temperature anomalies is detected from northernmost Fennoscandia towards the south and from the Atlantic coast in Norway towards the continental East European Plain. The dynamics of the temperate broadleaved tree species Tilia and Quercus in Latvia and adjacent northern Europe during the mid‐Holocene give complementary information on the multifaceted climatic and environmental changes in the region.
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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 | 0.002 |
| 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".