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Record W2907439517 · doi:10.1111/brv.12491

The covariance between metabolic rate and behaviour varies across behaviours and thermal types: meta‐analytic insights

2018· review· en· W2907439517 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiological reviews/Biological reviews of the Cambridge Philosophical Society · 2018
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Alberta
FundersMax-Planck-GesellschaftNatural Sciences and Engineering Research Council of CanadaNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsEctothermBasal metabolic rateForagingBoldnessMetabolic rateEcologyBiologyEnergy balanceAllostasisPsychologyPersonalitySocial psychologyEndocrinology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0000.001
Science and technology studies0.0020.004
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.225
GPT teacher head0.353
Teacher spread0.128 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it