Ultraviolet-B Radiation and Plant Competition: Experimental Approaches and Underlying Mechanisms
Bibliographic record
Abstract
Under realistic stratospheric ozone depletion scenarios, ultraviolet-B radiation (280-320 nm) (UV-B) influences plant morphology and plant competitive interactions. Influence of UV-B on plant competition can be studied using a variety of experimental and analytical approaches including inverse yield-density models and allometric, neighborhood or size-structure analyses that provide links between plant and ecosystem responses. These approaches differ in their abilities to extract information regarding competitive interactions and their morphological underpinnings. Only a limited number of studies have been carried out to investigate UV-B effects on plant competition, and most of these have used the replacement series approach, which has received much criticism. Nonetheless, results to date indicate that slight differences in UV-B-induced morphological responses of species grown within associations can alter canopy structure thereby influencing photosynthetically active radiation (PAR) interception and relative competitive ability. Because the response of individuals of the same species is expected to be uniform, UV-B may influence intraspecific competition less than interspecific competition. Before we can make clear generalizations and predictions concerning the effects of this radiation on plant competition, an understanding is crucial of the mechanisms underlying UV-B-induced shifts in competitive interactions by assessing competition over time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".