Perceptual Range, Targeting Ability, and Visual Habitat Detection by Greater Fritillary Butterflies Speyeria cybele (Lepidoptera: Nymphalidae) and Speyeria atlantis
Bibliographic record
Abstract
Butterflies are widely invoked as model organisms in studies of metapopulation and dispersal processes. Integral to such investigations are understandings of perceptual range; the maximum distance at which organisms are able to detect patches of suitable habitat. To infer perceptual range, researchers have released butterflies at varying distances from habitat patches and observed their subsequent flight behaviors. It is often assumed that butterflies rely on visual senses for habitat detection; however, this assumption has not been explicitly investigated. Here, we assess the extent and sensory determinants of perceptual range for the great spangled fritillary (Speyeria cybele (Fabricius, 1775)) and Atlantis fritillary (Speyeria atlantis (W.H. Edwards, 1862)). This was achieved by experimentally releasing butterflies over open water at various distances from a lake island, representing an isolated habitat patch in a dichotomous habitat-matrix landscape. To infer whether butterflies rely on vision for habitat detection, we exposed a subset of butterflies to a series of intense light flashes before release to induce flash blindness (bleaching of photoreceptive rhodopsins) without affecting olfaction. Flashed individuals were 30.1 times less likely to successfully navigate to the target island after release, suggesting butterflies rely primarily on visual senses to navigate fragmented landscapes. For unflashed butterflies, the likelihood of successful navigation decreased by a factor of 2.1 for every 10 m increase in release distance. However, no specific distance threshold for perceptual range was observed. We therefore suggest that perceptual range is best viewed as a continuum of probabilities (targeting ability), reflecting the likelihood of habitat detection across a range of distances.
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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".