Good welfare is attractive: Female zebrafish (Danio rerio) prefer males from complex, well-resourced conditions over males from conventional barren laboratory tanks
Bibliographic record
Abstract
Applied ethologists often find that sub-optimal housing (e.g. barren versus 'enriched', well-resourced conditions) impairs animals' interactions with conspecifics. Furthermore, some housing effects on social/sexual interactions persist even in standardised test situations. For example, in mating tests on three mammalian and two insect species, males from sub-optimal housing have been shown to be less successful with females (e.g. less attractive to them) compared to males with better welfare. Here, we assessed whether similar effects occur in fish, using zebrafish ( Danio rerio, Tübingen strain) as models. In a purpose-built maze, 16 groups of ready-to-spawn females were each given choices between two pairs of enclosed males that had been raised and housed differentially (in either conventional laboratory tanks, ‘Barren’, or large, well-resourced ones, ‘WR’). After this ‘Choice Phase’, they were allowed to spawn via free access to one type of male (half WR, half Barren). All trials were run (and videos analysed) blind to housing, to avoid unconscious experimenter biases. Results showed that in the Choice Phase, WR males were significantly preferred over Barren, attracting more proximity from more females; while in the Spawning Phase, WR males also attracted more courtship, and tended to elicit fewer escape attempts. Some of these benefits of being WR were only detectable, however, if male body size was statistically controlled for, because of an independent effect of male size (longer males being more attractive, despite WR males being unexpectedly smaller). Females thus used multiple housing-sensitive cues to select preferred mates: body length, plus unknown attributes of WR males (which could involve improved cognitive abilities, better physical health, greater stress resilience, and/or signs of greater libido: all topics for future study). This suggests many future avenues for fish research, potentially leading to improved welfare and reproductive success for laboratory-housed zebrafish (and even other species in aquaculture and conservation breeding facilities). Furthermore, these results (along with the studies inspiring this experiment) add to applied ethologists' longstanding appreciation of animals' sensitivity to conspecific signals of emotion: they indicate that animals can also detect longer-term welfare states, perhaps even finding poor welfare unattractive. • Female zebrafish were offered males from tanks differing in quality. • Half came from conventional barren tanks, half from large well-resourced ones. • Females preferred the males from well-resourced, 'enriched' conditions. • This adds to growing evidence that housing quality affects social phenotypes. • How females detect males from better housing-conditions is as yet unknown.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".