Host plant preference and offspring performance of a leaf‐mining moth, <i><scp>C</scp>aloptilia fraxinella</i>, on two <i><scp>F</scp>raxinus</i> species
Bibliographic record
Abstract
Abstract The preference‐performance or ‘mother‐knows‐best’ hypothesis states that female insects choose to oviposit on a host plant that increases the performance of their offspring. This positive link between host plant choice and larval performance is especially important for leaf miners with non‐motile larvae that are entirely dependent upon the oviposition choice of the female for host plant location. Preference and performance of the ash leaf coneroller, Caloptilia fraxinella (Ely) (Lepidoptera: Gracillariidae), a specialist on ash trees, Fraxinus spp. (Oleaceae), were tested in a series of laboratory and field experiments. Female C. fraxinella were exposed to two closely related hosts, black ash, Fraxinus nigra Marshall, and green ash, Fraxinus pennsylvanica Marshall var. subintegerrima (Vahl), in oviposition choice and wind tunnel flight experiments to determine which host is most attractive for oviposition. Caloptilia fraxinella females were inconsistent in host choice, yet performance of larvae was greater on green than black ash. In preference studies, C. fraxinella preferred to oviposit on black ash when leaflets were removed from the tree, but preferred intact green ash over black ash seedlings for oviposition and host location in a wind tunnel. In the field, however, more C. fraxinella visited black ash var. ‘Fallgold’ at leaf flush than green ash at the same sites. Age of the ash leaflet also influences oviposition in this leaf miner and females preferred new over old leaflets for oviposition. Performance of C. fraxinella larvae was evaluated in field and laboratory experiments and was greater on green ash than on black ash in both experiments based on larval survival and development time parameters. The stronger oviposition and host location preference in the field for black ash were not linked to enhanced performance of offspring, as green ash was the superior host, supporting higher larval survival and faster development. A stronger host location preference in the wind tunnel for green ash over black ash, however, suggests that under certain circumstances with this moth species, ‘mother (may) know best’.
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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".