Phenological responses of <i>Equisetum arvense</i> to experimental air and soil warming in boreal forest of interior Alaska
Bibliographic record
Abstract
Across high-latitude regions, warmer spring and fall conditions are associated with expanded growing seasons. However, almost all work on plant phenological shifts in response to climate change has focused on seed plants. Equisetum species (horsetails) are seedless vascular plants abundant in circumboreal forests. We evaluated phenological responses of Equisetum arvense L. in boreal forest of interior Alaska to earlier ground thaw and warmer air temperatures. We performed a 2 × 2 factorial experiment using modified greenhouses (air warming) and snow removals to advance ground thaw (soil warming), and developed monitoring protocols for the phenology of seedless vascular plants. Warming soil caused vegetative and reproductive stems to emerge sooner, and warming air caused faster vegetative growth and earlier advancement to a photosynthetically active phenophase, but treatments had minimal impacts on time of senescence. Plants that were exposed to both air and soil warming extended the growing season by 6.7 days compared to plants in control conditions, despite the short duration of the treatments and unusually cold spring conditions. We conclude that E. arvense has the potential to substantially increase its growing season as spring conditions continue to advance.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".