Towards an energetic landscape: broad‐scale accelerometry in woodland caribou
Bibliographic record
Abstract
Energetic balance is a central driver of individual survival and population change, yet estimating energetic costs in free- and wide-ranging animals presents a significant challenge. Animal-borne activity monitors (using accelerometer technology) present a promising method of meeting this challenge and open new avenues for exploring energetics in natural settings. To determine the behaviours and estimated energetic costs associated with a given activity level, three captive reindeer (Rangifer tarandus tarandus) at the Toronto Zoo were fitted with collars and observed for 53 h. Activity patterns were then measured over 13 months for 131 free-ranging woodland caribou (R. t. caribou) spanning 450,000 km(2) in northern Ontario. The captive study revealed a positive but decelerating relationship between activity level and energetic costs inferred from previous behavioural studies. Field-based measures of activity were modelled against individual displacement, vegetation abundance (Normalized Difference Vegetation Index), snow depth and temperature, and the best fit model included all parameters and explained over half of the variation in the data. Individual displacement was positively related to activity levels, suggesting that broad differences in energetic demands are influenced by variation in movement rates. After accounting for displacement, activity was highest at intermediate levels of vegetation abundance, presumably due to foraging behaviour. Snow depth, probably associated with digging for winter forage, moderately increased activity. Activity levels increased significantly at the coldest winter temperatures, suggesting the use of behavioural thermoregulation by caribou. These interpretations of proximate causal factors should be regarded as hypotheses subject to validation under normal field conditions. These results illustrate the landscape characteristics that increase energetic demands for caribou and confirm the great potential for the use of accelerometry in studies of animal energetics.
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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) | 0.001 | 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) | 0.002 | 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".