CO2 Elevation and Photoperiods North of Seed Origin Change Autumn and Spring Phenology as Well as Cold Hardiness in Boreal White Birch
Bibliographic record
Abstract
Climate change is expected to shift tree species distribution further polewards in the future. These shifts will expose trees to new photoperiod regimes and higher atmospheric carbon dioxide concentration ([CO2]). These factors will likely have interactive effects on the ecophysiological traits of plants, particularly in the boreal region where the climate change will be the most prominent. This study investigated how CO2 elevation and photoperiod regimes interactively influence the timing of bud development, leaf senescence, cold hardiness, and bud break in white birch (Betula papyrifera Marsh.). Seedlings were exposed to ambient ([CO2]) (AC= 400 μmol mol−1) or elevated (EC= 1000 μmol mol−1) and photoperiod regimes (at 48 (seed origin), 52, 55, and 58º N latitude) under controlled environment for two growing seasons. We found that EC advanced the initiation of leaf color change in the fall by 23 days, but delayed the completion date. Leaf senescence started earlier at photoperiods of 55 and 58° N latitude than at those of 48 and 52o N latitudes under EC, but no differences occurred under AC. Additionally, the temperature causing 50% electrolyte leakage (a measure of susceptibility to freezing damage) was more negative at two longest photoperiods under EC (-46 ºC at 55º, -60 ºC at 58º N) than other conditions (>-40 ºC). Budburst occurred earlier at the two longest photoperiods under EC, but the trend was opposite under AC. Our study highlights the complex interaction between photoperiod and CO2 conditions to alter autumnal and spring phenology of birch that is required to ensure successful seedling recruitment in new habitats and thus should be considered in predicting the future distribution and productivity of boreal trees.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".