Combined effects of disease and competition on plant fitness
Bibliographic record
Abstract
Wheat genotypes susceptible to different races of a pathogen, Puccinia striiformis, were planted in pure stands and in three different 1:1 mixtures, in both the presence and absence of disease, in two sites, and over 3 years. Using analyses of variance, we tested whether disease and intergenotypic competition influenced a genotype's fitness and whether significant interactions existed between the effects of disease and competition on genotype fitness. Seed weight, number of inflorescences per seed planted, seeds per inflorescence, and absolute fitness were estimated for each genotype in each treatment. Absolute fitness was determined as the number of seeds collected per seed planted. Disease reduced seed weight. The other fitness measures were influenced by either disease or competition, and the impact of each factor often varied among site-year combinations. In general, interactions between the effects of disease and competition on genotype fitness were not significant. The few significant interactions indicated a less than additive effect of competition and disease on genotype fitness. The overall lack of interaction may be, in part, due to lesser disease levels in mixed as compared with pure stands, or reduced level of competition under diseased conditions.Key words: pathogens, competition, plant fitness, stripe rust, wheat.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".