Energetics of free-ranging large herbivores: when should costs affect foraging behaviour?
Bibliographic record
Abstract
Published relationships were used to build a mathematical model that predicts the daily net energy balance of free-ranging domestic sheep (Ovis aries L.) grazing in the U.K. hills. Net energy balance was predicted for a plausible range of environmental conditions. The behaviour of the model suggested the following predictions. Locomotion will be a relatively unimportant energetic cost. Ambient temperature and rainfall alone will rarely affect energy expenditure, whereas wind will greatly increase energetic costs in winter. These are further increased, but to a relatively small extent, by any concurrent rainfall. Predictions of foraging behaviour based on maximisation of energy intake alone are likely to significantly overestimate dry matter intake from climatically exposed vegetation in winter. Where shelter is available, such models will also overestimate total intake in winter by not taking account of sheltering behaviour. This effect will be most pronounced when forage is of low digestibility or availability, wind speeds are high, or the level of coat insulation is low. Foraging models based instead on maximisation of net energy balance are likely to greatly improve predictions of the impact of large herbivores on vegetation and the mechanisms driving their population dynamics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".