Late Quaternary variations in tree cover at the northern forest-tundra ecotone
Bibliographic record
Abstract
[1] Accurate land cover reconstructions are essential to understanding the past and present biogeochemical and biogeophysical interactions between the land surface and atmosphere and the impacts of these interactions on climate. Here we quantitatively reconstruct late Quaternary shifts in woody cover across the Northern Hemisphere forest-tundra ecotone, based on a synthesis of Northern Hemisphere pollen records and contemporary observations of woody cover from the advanced very high resolution radiometer sensor. Our reconstructions document the expansion of Northern Hemisphere forests following deglaciation and reveal significant hemispheric asymmetries in the Holocene position, steepness, and history of the forest-tundra ecotone. In western Canada, for example, forest expansion and infilling continued through the Holocene, while in much of northern Asia, forests reached their maximal expansion during the early Holocene, then retreated. The woody cover reconstructions are generally consistent with macrofossil-based reconstructions of northern tree line dynamics and complement them by extending study of the northern forest-tundra ecotone from the tree line limit (well mapped by macrofossils) to the entire ecotone. Using the Lund-Potsdam-Jena dynamic vegetation model, we estimate that changes in northern forest density resulted in at least a 47.7 Gt C increase in aboveground carbon sequestration between 21 and 9 ka, a 13.9 Gt C increase between 9 and 6 ka, and a 3.5 Gt C loss of aboveground carbon from northern forests after 6 ka. This trajectory is consistent with atmospheric carbon isotopic measurements for the Holocene, which suggest carbon uptake by the terrestrial biosphere until 6 ka and small carbon releases from the terrestrial biosphere afterward.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".