The covariance between metabolic rate and behaviour varies across behaviours and thermal types: meta‐analytic insights
Notice bibliographique
Résumé
Energy metabolism has received much attention as a potential driver of repeatable among-individual differences in behaviour (animal personality). Several factors have been hypothesized to mediate this relationship. We performed a systematic review with a meta-analysis of >70 studies comprised of >8000 individuals reporting relationships between measures of maintenance metabolic rates (i.e. basal metabolic rate, resting metabolic rate, and standard metabolic rate) and behaviour. We evaluated support for three hypothesized mediators: (i) type of behaviour, (ii) opportunities for energy re-allocation, and (iii) magnitude of energetic constraints. Relationships between measures of maintenance metabolic rate (MR) and behaviour are predicted to be strongest for behaviours with strong consequences for energy turnover (acquisition or expenditure). Consistent with this, we found that behaviours with known consequences for energy gain (e.g. foraging, dominance, boldness) or expenditure (e.g. maximum sprint speed, sustained running speed, maximum distance travelled, etc.) had strong positive correlations with MR, while behaviours with putatively weak and/or inconsistent associations with net energy gain or loss (e.g. exploration, activity, sociability) were not correlated with MR. Greater opportunities for energy reallocation are predicted to weaken relationships between MR and behaviour by creating alternative pathways to balance energy budgets. We tested this by contrasting relationships between MR and behaviour in ectotherms versus endotherms, as thermoregulation in endotherms creates additional opportunities for energy reallocation compared with ectotherms. As predicted, the relationship between behaviour and MR was stronger in ectotherms compared with endotherms. However, statistical analyses of heterogeneity among effect sizes from different species did not support energy re-allocation as the main driver of these differences. Finally, we tested whether conditions where animals face greater constraints in meeting their energy budgets (e.g. field versus laboratory, breeding versus non-breeding) increased the strength of the relationship between MR and behaviour. We found that the relationship between MR and behaviour was unaffected by either of these modifiers. This meta-analysis provides two key insights. First, we observed positive relationships of similar magnitude between MR and behaviours that bring in net energy, and behaviours that cost net energy. This result is only consistent with a performance energy-management model. Given that the studies included in our meta-analysis represent a wide range of taxa, this suggests that the performance model may be the most common model in general. Second, we found that behaviours with putatively weak or inconsistent consequences for net energy gain or expenditure (exploration, activity, sociability) show no relationship with MR. The lack of relationship between MR and behavioural traits with weak and/or inconsistent consequences for energy turnover provides the first systematic demonstration of the central importance of the ecological function of traits in mediating relationships between MR and behaviour.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,018 | 0,046 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,030 |
| Bibliométrie | 0,004 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».