Light loggers reveal weather-driven changes in the daily activity patterns of arboreal and semifossorial rodents
Bibliographic record
Abstract
Measuring daily and seasonal patterns of activity is useful for understanding the ecological and evolutionary drivers of behavior. We used collar-mounted light loggers to examine how nest attendance in arboreal squirrels and aboveground activity in semifossorial ground squirrels are affected by weather-driven changes in thermoregulatory conditions. Activity of lactating red squirrels (Tamiasciurus hudsonicus) had a diurnal pattern showing 3 daily peaks of activity with time spent outside the nest increasing with increasing ambient temperature, but decreasing with increasing relative humidity and wind. Despite the persistence of daylight during midsummer in the arctic environment, female arctic ground squirrels (Urocitellus parryii) also exhibited diurnal activity patterns with time spent above ground each day decreasing in response to precipitation but increasing with increasing ambient temperature and incident solar radiation. On cooler days, ground squirrels exhibited a unimodal activity pattern. However, on warm days, ground squirrels spent less time above ground when solar radiation and ambient temperature were both at their daily maxima, which resulted in a bimodal activity pattern. Our results highlight the utility of light loggers as a cost-effective means of addressing questions related to foraging behavior, parental care, thermoregulation, energetics, and timing of activity in arboreal and semifossorial small mammals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".