Contrasting effects of freezing-stress memory on biomass production among herbaceous plant species
Bibliographic record
Abstract
Prior exposure to freezing can increase the subsequent freezing tolerance of plants and reduce the severity of injury. However, it is unknown how freezing memory influences plant productivity. We investigated the effects of repeated freezing events over multiple seasons on the biomass of Bromus inermis, Lolium perenne, Festuca rubra, Plantago lanceolata, and Poa pratensis. The plants were exposed to different combinations of freezing in the early spring, late spring, or fall (2017), as well as the following spring (2018); control plants were frozen only once, along with all of the other treatments, during the spring of 2018. Bromus inermis that experienced every freeze, and the plants frozen in both the early and late spring, had higher biomass than the controls. Similarly, Poa pratensis plants frozen in both the early and late spring had higher biomass than the controls. In contrast, Festuca rubra plants frozen in early spring and fall had lower root biomass than the control plants, and Lolium perenne plants that experienced every freeze had lower root biomass than the controls. Variation among species in repeated freezing responses could have important consequences for the relative abundances of herbaceous species in northern temperate regions.
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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 | 0.000 |
| 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) | 0.001 | 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".