PLANT GENOTYPE AND ENVIRONMENT INTERACT TO SHAPE A DIVERSE ARTHROPOD COMMUNITY ON EVENING PRIMROSE (OENOTHERA BIENNIS)
Bibliographic record
Abstract
Both an individual's genotype and environment govern its phenotype, and this phenotype may have extended consequences for species interactions and communities. We examined the importance of plant genotype and environmental factors operating at large (habitat) and small (microhabitat) spatial scales in affecting a multitrophic arthropod community on plants. We planted 926 plants from 14 genotypes of Oenothera biennis into five natural habitats that represent the range of environments in which this plant locally occurs. Genotypic differences among plants accounted for as much as 41% of the variation in arthropod diversity (Simpson's diversity index) and also affected arthropod evenness, richness, abundance, and biomass on individual plants. However, the effects of particular plant genotypes on the arthropod community varied across habitats (i.e., there were significant plant genotype-by-habitat interactions). Plant genotype explained more variation in the arthropod community than did environmental variation among microhabitats, but less variation than habitats, as predicted by the scale-dependent hypothesis. Herbivores and omnivores were more strongly affected by plant genetic variation than predators, consistent with the notion that phytophagous insects undergo stronger reciprocal interactions with plants than do predators. We detected heritable variation in arthropod community variables and the ability for the herbivore community to select on plant traits, suggesting that evolution in O. biennis can lead to changes in the arthropod community. Genetic variation in plant size, architecture, and reproductive phenology were the plant traits most strongly correlated with arthropod community variables. Our results demonstrate that genotype-by-environment interactions are a major determinant of arthropod community structure.
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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) | 0.000 | 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".