The movement responses of three libellulid dragonfly species to open and closed landscape cover
Bibliographic record
Abstract
Abstract The land cover between habitats (i.e. matrix environment) can affect connectivity by impacting organismal movement. Many animals, however, have preferences for specific matrix environments, which can affect their movement through the landscape. We examined how different terrestrial matrix environments impacted the fine‐scale movement of adult dragonflies. Based on previous studies of adult dragonfly dispersal and larval distributions, we hypothesised that dragonflies would prefer to enter fields rather than forests and that forests would be a barrier to dragonfly movement, due to forests’ structural complexity, low understory light availability, and lower air temperatures. To test how adult dragonflies responded to various terrestrial environments, we released 108 Leucorrhinia intacta , a mixture of 108 Sympetrum rubicundulum and obtrusum/rubicundulum hybrids, and 108 Sympetrum vicinum , at field‐forest ecotones and assessed their preferences for fields or forests. Individual behavioural responses were recorded, including their probability of taking flight, their direction of movement with respect to the two matrix types, and flight time. The likelihood of adult dragonflies taking flight was species‐specific in response to release location. Adults moved more frequently towards fields than forests when released at a forest edge. Individuals released within forests had shorter flight times, but again this response was species‐specific. The presence of an open matrix (field or meadow) is likely important for facilitating movement in dragonflies; however, forests are not movement barriers for all dragonfly species. Integrating assays of matrix and habitat preferences can provide insight into how landscape connectivity can be maintained for actively dispersing species.
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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".