Variable extrafloral nectary expression and its consequences in quaking aspen
Bibliographic record
Abstract
Extrafloral nectaries (EFNs) are secretory glands most commonly linked to defensive mutualisms. Both a plant’s need for defense and the strength of defense provided by mutualists will vary with plant condition and local insect community. Thus, the benefit of EFNs may vary spatially and temporally. However, little attention has been paid to natural variation in the presence and abundance of EFNs within and among individuals of the same species. Quaking aspen, Populus tremuloides Michx., bear EFNs on a subset of their leaves. Here, we describe patterns of EFN expression on shoots within ramets, among ramets, and among putative clones in interior Alaska. We also examine the relationship between EFN presence and herbivory by both the very abundant aspen leaf miner, Phyllocnistis populiella Chambers, and less common chewing herbivores. The proportion of leaves bearing EFNs varied from 33% to 87% among distinct aspen stands. Within stands, short (1–2 m height) ramets had higher EFN frequency than their taller (>4 m) neighbors. Patterns of herbivory also differed between short and tall ramets. Compared with leaves without EFNs, those with EFNs suffered less mining damage on short ramets but slightly higher damage on tall ramets. Tall ramets suffered more chewing damage than short ramets, but this damage was unrelated to the presence of EFNs. Our results suggest that variable EFN expression may be explained by variation in the benefits of EFNs. Leaves with EFNs on short ramets benefit through reduction in leaf mining, but this benefit does not extend to tall ramets or other forms of herbivory.
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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 | 0.001 | 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".