The significance of shared leaf shape in <i>Alseuosmia pusilla</i> and <i>Pseudowintera colorata</i>
Bibliographic record
Abstract
Leaf shape, size, and colour are used by herbivores to identify sources of palatable foliage for food. It is possible, therefore, that an undefended plant might gain protection from herbivores by matching leaf characteristics of a chemically defended species. We demonstrate the use of a geometric morphometric approach to quantify spatial variation in leaf shape and size across populations of Pseudowintera colorata (Raoul) Dandy, and a putative Batesian mimic, Alseuosmia pusilla (Colenso) A. Cunningham. These are unrelated, sympatric species that, to the human eye, bear strikingly similar foliage. Using the Cartesian coordinates of leaf margins as descriptors of leaf shape, we found that in the chemically defended P. colorata, leaves were morphologically distinct from all of the neighbouring species except for the undefended A. pusilla. Alseuosmia pusilla individuals were more similar to neighbouring than to distant P. colorata, and 90% of leaf shape variation in the two species varied similarly across an altitudinal gradient. The data are consistent with Batesian mimicry, wherein the conspicuous characteristic of a defended model is replicated by an undefended mimic across its entire growing range. Our study provides the first detailed and powerful quantitative leaf shape evidence of leaf shape being matched between an undefended plant species to a chemically defended unrelated species across a shared growing range, and highlights the importance of using a spatially explicit morphometric method when investigating leaf shape, especially in relation to plant mimicry.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".