Individual Mechanical Energy Expenditure Regimens Vary Seasonally with Weather, Sex, Age and Body Condition in a Generalist Carnivore Population: Support for Inter-Individual Tactical Diversity
Bibliographic record
Abstract
Diverse individual energy-budgeting tactics within wild populations provide resilience to natural fluctuations in food availability and expenditure costs. Although substantial heterogeneity in activity-related energy expenditure has been documented, few studies differentiate between responses to the environment and inter-individual differences stemming from life history, allometry, or somatic stores. Using tri-axial accelerometry, complemented by diet analysis, we investigated inter-individual within-season variation in overall dynamic body acceleration (ODBA; activity intensity measure) and “Activity” (above an ODBA threshold) in a high-density population of European badgers (Meles meles). Weather (including wind speed) affected ODBA and activity according to predictors of earthworm (food) availability and cooling potential. In spring, maximal ODBA expenditure at intermediate rainfall and temperature values suggested that badgers traded foraging success against thermoregulatory losses, where lower-condition badgers maintained higher spring ODBA irrespective of temperature while badgers in better body condition reduced ODBA at colder temperatures. Conversely, in summer, lower-condition badgers modulated ODBA according to temperature, likely in response to super-abundant food supply. Between 35% (spring, summer) and 57% (autumn) of residual total daily ODBA variance related to inter-individual differences unexplained by seasonal predictors, suggesting within-season tactical activity typologies. We propose that this heterogeneity among individual energy-expenditure profiles may contribute to population resilience under rapid environmental change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".