The effect of patch distance, matrix type and experience on habitat perception and flight speed of two species of <i>Heliconius</i> butterflies
Bibliographic record
Abstract
Abstract The perceptual range of an organism is the distance at which landscape elements are recognised by it. Estimates of this sensory trait are relevant to understand how organisms recognise suitable habitat within fragmented landscapes. We investigated how the nature of inhospitable environments (matrix) neighbouring a forest patch and adult experience (lab‐raised naïve vs. free‐flying experienced adults) affect the perceptual range and flight speed of the forest butterfly species Heliconius erato and Heliconius melpomene . In field experiments, butterflies were released at various distances from the edge of the habitat patch. Flight orientation and speed were evaluated. In one experiment, wild‐caught individuals of H. erato and H. melpomene were released in two matrix types, a coconut plantation and an open field. In a subsequent experiment, lab‐raised naïve H. erato was released at the same site. Release distance was the best predictor of butterfly behaviour for the two species. Individuals released up to 60 m successfully oriented towards the habitat patch, indicating a perceptual range below 100 m. Flight speed was higher the closer a butterfly was released to the edge. Matrix type did not affect butterfly orientation within its perceptual range distance. We did not find a significant effect of experience on butterfly orientation. Our study shows that the perceptual distance of Heliconius is within the range of known estimates from other butterfly species. Within this range, and irrespective of matrix type and experience, individuals were capable of orienting towards their preferred habitat and at flight speeds that were related to the distance of release.
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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 | 0.001 |
| 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) | 0.002 | 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".