Differences in resource acquisition, not allocation, mediate the relationship between behaviour and fitness: a systematic review and meta‐analysis
Notice bibliographique
Résumé
Within populations, individuals often show repeatable variation in behaviour, called 'animal personality'. In the last few decades, numerous empirical studies have attempted to elucidate the mechanisms maintaining this variation, such as life-history trade-offs. Theory predicts that among-individual variation in behavioural traits could be maintained if traits that are positively associated with reproduction are simultaneously associated with decreased survival, such that different levels of behavioural expression lead to the same net fitness outcome. However, variation in resource acquisition may also be important in mediating the relationship between individual behaviour and fitness components (survival and reproduction). For example, if certain phenotypes (e.g. dominance or aggressiveness) are associated with higher resource acquisition, those individuals may have both higher reproduction and higher survival, relative to others in the population. When individuals differ in their ability to acquire resources, trade-offs are only expected to be observed at the within-individual level (i.e. for a given amount of resource, if an individual increases its allocation to reproduction, it comes at the cost of allocation to survival, and vice versa), while among individuals traits that are associated with increased survival may also be associated with increased reproduction. We performed a systematic review and meta-analysis, asking: (i) do among-individual differences in behaviour reflect among-individual differences in resource acquisition and/or allocation, and (ii) is the relationship between behaviour and fitness affected by the type of behaviour and the testing environment? Our meta-analysis consisted of 759 estimates from 193 studies. Our meta-analysis revealed a positive correlation between pairs of estimates using both survival and reproduction as fitness proxies. That is, for a given study, behaviours that were associated with increased reproduction were also associated with increased survival, suggesting that variation in behaviour at the among-individual level largely reflects differences among individuals in resource acquisition. Furthermore, we found the same positive correlation between pairs of estimates using both survival and reproduction as fitness proxies at the phenotypic level. This is significant because we also demonstrated that these phenotypic correlations primarily reflect within-individual correlations. Thus, even when accounting for among-individual differences in resource acquisition, we did not find evidence of trade-offs at the within-individual level. Overall, the relationship between behaviour and fitness proxies was not statistically different from zero at the among-individual, phenotypic, and within-individual levels; this relationship was not affected by behavioural category nor by the testing condition. Our meta-analysis highlights that variation in resource acquisition may be more important in driving the relationship between behaviour and fitness than previously thought, including at the within-individual level. We suggest that this may come about via heterogeneity in resource availability or age-related effects, with higher resource availability and/or age leading to state-dependent shifts in behaviour that simultaneously increase both survival and reproduction. We emphasize that future studies examining the mechanisms maintaining behavioural variation in populations should test the link between behavioural expression and resource acquisition - both within and among individuals. Such work will allow the field of animal personality to develop specific predictions regarding the mediating effect of resource acquisition on the fitness consequences of individual 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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,008 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,012 | 0,006 |
| Bibliométrie | 0,000 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».