Does Climate Warming Favour Early Season Species?
Bibliographic record
Abstract
Plant species that start early in spring are generally more responsive to rising temperatures, raising concerns that climate warming may favour early season species and result in altered interspecific interactions and community structure and composition. This hypothesis is based on changes in spring phenology and therefore active growing season length, which would not be indicative of possible changes in growth as would changes in cumulative forcing temperatures (growing degree days/hours) in the Northern Hemisphere. In this study we analysed the effects of a moderate climate warming (2°C warmer than the 1981-2010 baseline) on the leaf-out of hypothetical species without chilling restriction and actual plant species with different chilling and forcing requirements in different parts of the globe. In both cases, early season species had larger phenological shifts due to low leaf-out temperatures, but accumulated fewer forcing gains (changes in cumulative forcing temperatures by warming) from those shifts because of their early spring phenology. Leaf-out time was closely associated with leaf-out temperatures and therefore plant phenological responses to climate warming. All plant species would be equally affected by climate warming in terms of total forcing gains added from higher temperatures when forcing gains occurring between early and late season species are included. Our findings will improve the understanding of possible mechanisms and consequences of differential responses in plant phenology to climate warming.
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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 | 0.001 |
| 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) | 0.003 | 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".