Seasonal and temporal variation in scaled mass index of Black-capped Chickadees (<i>Poecile atricapillus</i>)
Bibliographic record
Abstract
Avian body mass reflects a trade-off between risk of starvation and predation, and may vary with ambient temperature, age, and time of day. Seasonal variability in body mass is a common occurrence in northern temperate regions, including adaptive fattening. Previous evidence suggests that seasonal variability is less pronounced in tree-feeding bird species, as their food sources during winter are less limited and variable compared to ground-foraging species. We determined fat scores of tree-feeding Black-capped Chickadees (Poecile atricapillus) captured year-round between 2004 and 2015 (n = 4248) in southern Quebec, to test the relative strength of possible drivers of variability in chickadee body mass, including time, date, and year of capture, age, and temperature. First, we demonstrated that scaled mass index (SMI) was the body condition index, out of four possible indices tested, which most strongly correlated with fat scores measured in the field. We used SMI subsequently as our estimator of body condition to avoid observer effects associated with fat scores. Similar to other studies, time of capture significantly affected SMI, in which birds captured later were heavier, indicating that chickadees experience overnight weight loss and subsequent weight gain from foraging throughout the day. SMI was constant from April to November, then peaked in late winter, but was not influenced by daily temperature after accounting for month and year. SMI was not significantly affected by age. We concluded that adaptive fattening is an evolutionary response to risk of starvation in winter, rather than a proximal response to immediate ambient temperature.
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.
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) | 0.006 | 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".