Abiotic environmental factors contribute to spatial variation in boldness and exploration in guppies (<scp><i>Poecilia reticulata</i></scp>)
Bibliographic record
Abstract
Research on wild fishes has tended to overlook the role of abiotic factors in shaping behaviours associated with boldness and exploration. This oversight could exist because small-scale variation in the abiotic environment might seem unlikely to influence such behaviours. We challenged this assumption through research in the Trinidadian guppy (Poecilia reticulata) system. We started by quantifying how behaviours associated with boldness (time in a shelter and time frozen in an open field) and a behaviour associated with exploration (number of grid squares crossed in an open field) varied for guppies within and among 15 pools across two streams, where all of the pools within a stream were within 150 m of each other. The measured behaviours differed little between streams, yet they varied dramatically among pools within streams and among individuals within pools, thus illustrating how such behaviours can be structured on very small spatial scales. We next assessed how the observed behavioural variation might be explained by individual-level attributes (sex and body mass) and pool-level abiotic factors (e.g. temperature and dissolved oxygen). Individual-level attributes explained little of the behavioural variation, although smaller guppies did display slightly bolder behaviour. Among-pool abiotic factors, however, were quite informative. As a clear example, guppies from pools with less dissolved oxygen displayed bolder behaviour and (possibly) greater exploration. Our results highlight the importance of abiotic factors in shaping behaviour even on small spatial scales.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".