Natal experience and conspecifics influence the settling behaviour of the juvenile terrestrial isopod <i>Armadillidium vulgare</i>
Bibliographic record
Abstract
Cues used by dispersing juveniles to assess habitat quality can be based on public information available to all individuals or on private information obtained from experience in the natal habitat. The presence of conspecifics (public information) and natal habitat quality (private information) have been shown to influence habitat preferences in many species, but the relative importance of these two cue types is seldom investigated. We examined whether habitat quality relative to the natal habitat had a stronger influence on the settling decisions of the juvenile terrestrial isopod Armadillidium vulgare (Latreille, 1804), than sign of conspecifics. We raised juvenile A. vulgare in either high- or low-quality habitats and then observed how the presence of conspecific sign influenced their preference for each of these habitats. When conspecific sign was absent, juveniles preferred high-quality habitat, regardless of their natal habitat. When the low-quality habitat was treated with conspecific sign, juveniles born on low-quality habitat continued to prefer the high-quality habitat, but juveniles raised on high-quality habitat displayed no preference. This suggests juvenile isopods respond to these cues hierarchically: they first search for habitats higher in quality than their natal habitat and then cue into conspecific sign when the preferred habitat is unavailable.
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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) | 0.001 | 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".