Calcium Availability and the Interaction of Arabidopsis thaliana and Myzus persicae
Bibliographic record
Abstract
The reciprocity inherent to plant-animal interactions allows these ecological systems to be influenced by a variety of external factors. Nutrient availability in soil is an important and extremely sensitive variable in the determination of successful plant performance. In particular, calcium is a macromineral that plays a role in both plant growth and facultative defence. Increased cytosolic calcium concentrations are correlated with an increase in callose deposition, a defence mechanism against piercing-sucking herbivores. In this experiment, we moderated the amount of calcium available to Arabidopsis thaliana samples, and assessed both direct effects on plant performance and indirect effects on the Myzus persicae populations that resided on the plants. Half of the plants in this study were inoculated with viviparous aphids, and all plants were treated with varying amounts of dolomitic limestone throughout the experimental timeline. Plant performance and aphid fecundity was evaluated through measures of aphid count, new leaf growth, old leaf growth, and plant height. A two-way analysis of variance was used to analyze the interactive effect of calcium treatment and time on the total number of aphids and the interactive effect of day and block on new leaf growth. In general, calcium treatment was shown to negatively affect aphid population growth. Plants inoculated with aphids performed more poorly over time than plants that were not inoculated. The results of this experiment indicate a relationship between aphid population growth and soil calcium levels. This overall negative trend could be explained by resource availability theory. Further studies of this interdependence would indicate the ways in which human manipulation of the environment can have effects that propagate across many trophic levels.
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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".