The behaviour–performance continuum: how does individual variation in locomotor abilities relate to behaviour?
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Notice bibliographique
Résumé
A series of terminological, technical, conceptual, and statistical challenges present themselves when trying to study correlations between measures of performance abilities (what an animal can do) and behavioural traits (what an animal chooses to do). We attempt to synthesise literature on this topic, with a specific focus on locomotor performance and behavioural traits measured with standardised tests. We argue that measures of forced performance (e.g. endurance on a motorised treadmill) and voluntary behaviour (e.g. wheel running) often fall along a continuum, sometimes grading into each other. On the performance end of the continuum, tests should measure what an animal can do when motivation is maximal and/or it is given no choice but to exert itself maximally. On the behavioural end of the continuum, tests should capture what animals choose to do of their own free volition, with no experimental attempt to affect motivation. Hence, performance tests attempt to eliminate variation in motivation by forcing all individuals to be maximally motivated, whereas variation in motivation is an inherent component of all behavioural tests. In some cases, however, differentiating between measures of performance versus behaviour can seem almost arbitrary. Moreover, individuals may consistently differ in how willing they are to 'perform' even when 'forced' to do so. We compiled studies reporting any association (covariation, correlation or linear regression) between putative measures of locomotor performance and behaviour in various taxa. The vast majority of those studies report phenotypic correlations, and only a handful have reported genetic correlations or explored potential correlated responses to selection on performance or behaviour. To our knowledge, this is the first global overview of how locomotor performance and behaviour covary in animals, and we believe that our synthesis will be useful to guide future research on locomotor performance and its relationship with other ecologically relevant traits. For example, we argue that a multi-level (co)variance partitioning approach is necessary to gain insights into the importance of how motivation differs across levels (e.g. among- versus within-individual variation, genetic versus environmental variation). Finally, we outline a multitude of compensation and co-specialisation mechanisms that may occur between performance and behaviour, and propose future avenues for research that include selection and manipulative studies to help identify the role of correlational selection, individual experience, and predation detectability on the relationships between behaviour and performance.
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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 | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 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 découle