Phloem phytochemistry and aphid responses to elevated <scp> CO <sub>2</sub> </scp> , nitrogen fertilization and endophyte infection
Bibliographic record
Abstract
Abstract Rising atmospheric CO 2 has been shown to alter plant nitrogen metabolism, growth and secondary chemistry. We hypothesized that altered aphid performance under elevated CO 2 is linked to phloem nitrogen chemistry. Rhopalosiphum padi performance on endophyte‐infected or uninfected tall fescue was examined under three levels of CO 2 (ambient, 800 and 1000 p.p.m.) and high and low nitrogen fertilization. Ethylenediaminetetracetic acid‐facilitated exudation was used to sample phloem sap, followed by quantification of relative amino acid concentrations using reverse‐phase high‐performance liquid chromatography. Aphid abundance was reduced at 800 p.p.m. relative to ambient CO 2 but returned to baseline at 1000 p.p.m. The density of aphids was reduced in both the elevated CO 2 treatments. Aphids were unsuccessful at colonizing endophyte‐infected plants, possibly as a result of the presence of loline alkaloids. Multivariate analysis showed that certain groups of phloem amino acids were altered by nitrogen fertilization and CO 2 . We found that four amino acids (valine, arginine, glutamine and aspartate) were correlated with aphid performance. These findings partially explained the effect of plant nitrogen fertilization and elevated CO 2 on aphids. The present study represents a first step toward providing a mechanistic explanation of the aphid performance changes that may result from rising atmospheric CO 2 .
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 | 0.000 | 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 | 0.001 |
| 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".