Arctic shrub colonization lagged peak postglacial warmth: Molecular evidence in lake sediment from Arctic Canada
Bibliographic record
Abstract
Abstract Arctic shrubification is an observable consequence of climate change, already resulting in ecological shifts and global‐scale climate feedbacks including changes in land surface albedo and enhanced evapotranspiration. However, the rate at which shrubs can colonize previously glaciated terrain in a warming world is largely unknown. Reconstructions of past vegetation dynamics in conjunction with climate records can provide critical insights into shrubification rates and controls on plant migration, but paleoenvironmental reconstructions based on pollen may be biased by the influx of exotic pollen to tundra settings. Here, we reconstruct past plant communities using sedimentary ancient DNA (sedaDNA), which has a more local source area than pollen. We additionally reconstruct past temperature variability using bacterial cell membrane lipids (branched glycerol dialkyl glycerol tetraethers) and an aquatic productivity indicator (biogenic silica) to evaluate the relative timing of postglacial ecological and climate changes at a lake on southern Baffin Island, Arctic Canada. The sedaDNA record tightly constrains the colonization of dwarf birch (Betula, a thermophilous shrub) to 5.9 ± 0.1 ka, ~3 ka after local deglaciation as determined by cosmogenic 10Be moraine dating and >2 ka later than Betula pollen is recorded in nearby lake sediment. We then assess the paleovegetation history within the context of summer temperature and find that paleotemperatures were highest prior to 6.3 ka, followed by cooling in the centuries preceding Betula establishment. Together, these molecular proxies reveal that Betula colonization lagged peak summer temperatures, suggesting that inefficient dispersal, rather than climate, may have limited Arctic shrub migration in this region. In addition, these data suggest that pollen‐based climate reconstructions from high latitudes, which rely heavily on the presence and abundance of pollen from thermophilous taxa like Betula, can be compromised by both exotic pollen fluxes and vegetation migration lags.
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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| 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".